M. Yang
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Evaluating LLM-based decision support in safety-critical operational environments
An evaluation framework constructed from expert knowledge, applied to FSRU operations
Floating Storage and Regasification Units (FSRUs) play a critical role in energy security by providing flexible LNG import capacity. Operating these vessels efficiently requires daily decisions that balance multiple competing objectives and rely heavily on tacit expert knowledge that is difficult to articulate or codify. Recent advances in large language models (LLMs) offer opportunities to support this expert-driven decision-making. Before deployment, however, organisations need a structured method to evaluate whether LLM-generated recommendations are adequate. Existing evaluation approaches assess general language quality or assume that domain-specific performance criteria already exist. In expert-knowledge environments, they do not.
This research addresses that gap by developing an evaluation framework for LLM-based decision support in safety-critical operational environments and applying it to EXMAR's FSRU in Eemshaven. The research delivers both the framework and an operationalised evaluation tool for EXMAR, which serves as the framework's test case.
The framework consists of five phases. First, a suitable operational scenario is selected using five requirements: improvement potential, frequent occurrence, safety involvement, sufficient structure, and data availability. Second, tacit operator knowledge is elicited through Cognitive Task Analysis and translated into two assessment components. Decision alignment measures how closely LLM recommendations reproduce expert decisions using the F1-score and Spearman correlation. Decision quality evaluates recommendations against expert-derived criteria, utility functions, and weights that reflect operators' judgments of good decisions. These criteria are elicited from reflective judgment rather than observed decisions, which may be satisficed, enabling a Multi-Criteria Decision Making approach complemented by qualitative reasoning analysis. Third, a benchmark of current operator decision-making is constructed, as no objectively optimal decisions exist in these contexts. Fourth, recommendations are generated by varying prompt design. Fifth, recommendations are evaluated through factual correctness and safety gates before assessing decision quality and alignment, with results interpreted using a 2×2 matrix distinguishing adoptable, investigable, and rejectable recommendations.
The framework is applied to EXMAR's FSRU in Eemshaven using the regasification configuration decision. Interviews with three operators identified four criteria: energy efficiency, operational robustness, operational effort, and safety as a non-negotiable gate. These were operationalised into indicators, utility functions, and weights. Benchmark scores of 0.83 and 0.90 indicate high-quality operator decisions consistent with satisficing behaviour predicted by Naturalistic Decision Making research. Evaluation of sixteen prompt configurations shows that prompt design strongly influences recommendation quality, with structured prompts using explicit performance criteria achieving results comparable to or exceeding the benchmark. Qualitative reasoning identified six failure modes, particularly stopping at the first feasible option, over-fitting to criteria at the expense of safety, and overly conservative equipment loading. Addressing these informed a second prompt iteration, eliminating safety violations across all configurations. Validation across four additional scenarios demonstrated consistent results, and in one case an operator revised their decision after reviewing an LLM recommendation.
This research demonstrates that evaluating LLM-based decision support in safety-critical expert environments is feasible while highlighting its limitations. Some tacit knowledge cannot be fully captured, limiting any evaluation framework. Nevertheless, several prompt configurations matched or exceeded expert performance, suggesting that LLMs and operators are better viewed as complementary. Rather than replacing experts, these systems are most valuable in supporting operational decision-making while leaving the final decision to the operator. ...
This research addresses that gap by developing an evaluation framework for LLM-based decision support in safety-critical operational environments and applying it to EXMAR's FSRU in Eemshaven. The research delivers both the framework and an operationalised evaluation tool for EXMAR, which serves as the framework's test case.
The framework consists of five phases. First, a suitable operational scenario is selected using five requirements: improvement potential, frequent occurrence, safety involvement, sufficient structure, and data availability. Second, tacit operator knowledge is elicited through Cognitive Task Analysis and translated into two assessment components. Decision alignment measures how closely LLM recommendations reproduce expert decisions using the F1-score and Spearman correlation. Decision quality evaluates recommendations against expert-derived criteria, utility functions, and weights that reflect operators' judgments of good decisions. These criteria are elicited from reflective judgment rather than observed decisions, which may be satisficed, enabling a Multi-Criteria Decision Making approach complemented by qualitative reasoning analysis. Third, a benchmark of current operator decision-making is constructed, as no objectively optimal decisions exist in these contexts. Fourth, recommendations are generated by varying prompt design. Fifth, recommendations are evaluated through factual correctness and safety gates before assessing decision quality and alignment, with results interpreted using a 2×2 matrix distinguishing adoptable, investigable, and rejectable recommendations.
The framework is applied to EXMAR's FSRU in Eemshaven using the regasification configuration decision. Interviews with three operators identified four criteria: energy efficiency, operational robustness, operational effort, and safety as a non-negotiable gate. These were operationalised into indicators, utility functions, and weights. Benchmark scores of 0.83 and 0.90 indicate high-quality operator decisions consistent with satisficing behaviour predicted by Naturalistic Decision Making research. Evaluation of sixteen prompt configurations shows that prompt design strongly influences recommendation quality, with structured prompts using explicit performance criteria achieving results comparable to or exceeding the benchmark. Qualitative reasoning identified six failure modes, particularly stopping at the first feasible option, over-fitting to criteria at the expense of safety, and overly conservative equipment loading. Addressing these informed a second prompt iteration, eliminating safety violations across all configurations. Validation across four additional scenarios demonstrated consistent results, and in one case an operator revised their decision after reviewing an LLM recommendation.
This research demonstrates that evaluating LLM-based decision support in safety-critical expert environments is feasible while highlighting its limitations. Some tacit knowledge cannot be fully captured, limiting any evaluation framework. Nevertheless, several prompt configurations matched or exceeded expert performance, suggesting that LLMs and operators are better viewed as complementary. Rather than replacing experts, these systems are most valuable in supporting operational decision-making while leaving the final decision to the operator. ...
Floating Storage and Regasification Units (FSRUs) play a critical role in energy security by providing flexible LNG import capacity. Operating these vessels efficiently requires daily decisions that balance multiple competing objectives and rely heavily on tacit expert knowledge that is difficult to articulate or codify. Recent advances in large language models (LLMs) offer opportunities to support this expert-driven decision-making. Before deployment, however, organisations need a structured method to evaluate whether LLM-generated recommendations are adequate. Existing evaluation approaches assess general language quality or assume that domain-specific performance criteria already exist. In expert-knowledge environments, they do not.
This research addresses that gap by developing an evaluation framework for LLM-based decision support in safety-critical operational environments and applying it to EXMAR's FSRU in Eemshaven. The research delivers both the framework and an operationalised evaluation tool for EXMAR, which serves as the framework's test case.
The framework consists of five phases. First, a suitable operational scenario is selected using five requirements: improvement potential, frequent occurrence, safety involvement, sufficient structure, and data availability. Second, tacit operator knowledge is elicited through Cognitive Task Analysis and translated into two assessment components. Decision alignment measures how closely LLM recommendations reproduce expert decisions using the F1-score and Spearman correlation. Decision quality evaluates recommendations against expert-derived criteria, utility functions, and weights that reflect operators' judgments of good decisions. These criteria are elicited from reflective judgment rather than observed decisions, which may be satisficed, enabling a Multi-Criteria Decision Making approach complemented by qualitative reasoning analysis. Third, a benchmark of current operator decision-making is constructed, as no objectively optimal decisions exist in these contexts. Fourth, recommendations are generated by varying prompt design. Fifth, recommendations are evaluated through factual correctness and safety gates before assessing decision quality and alignment, with results interpreted using a 2×2 matrix distinguishing adoptable, investigable, and rejectable recommendations.
The framework is applied to EXMAR's FSRU in Eemshaven using the regasification configuration decision. Interviews with three operators identified four criteria: energy efficiency, operational robustness, operational effort, and safety as a non-negotiable gate. These were operationalised into indicators, utility functions, and weights. Benchmark scores of 0.83 and 0.90 indicate high-quality operator decisions consistent with satisficing behaviour predicted by Naturalistic Decision Making research. Evaluation of sixteen prompt configurations shows that prompt design strongly influences recommendation quality, with structured prompts using explicit performance criteria achieving results comparable to or exceeding the benchmark. Qualitative reasoning identified six failure modes, particularly stopping at the first feasible option, over-fitting to criteria at the expense of safety, and overly conservative equipment loading. Addressing these informed a second prompt iteration, eliminating safety violations across all configurations. Validation across four additional scenarios demonstrated consistent results, and in one case an operator revised their decision after reviewing an LLM recommendation.
This research demonstrates that evaluating LLM-based decision support in safety-critical expert environments is feasible while highlighting its limitations. Some tacit knowledge cannot be fully captured, limiting any evaluation framework. Nevertheless, several prompt configurations matched or exceeded expert performance, suggesting that LLMs and operators are better viewed as complementary. Rather than replacing experts, these systems are most valuable in supporting operational decision-making while leaving the final decision to the operator.
This research addresses that gap by developing an evaluation framework for LLM-based decision support in safety-critical operational environments and applying it to EXMAR's FSRU in Eemshaven. The research delivers both the framework and an operationalised evaluation tool for EXMAR, which serves as the framework's test case.
The framework consists of five phases. First, a suitable operational scenario is selected using five requirements: improvement potential, frequent occurrence, safety involvement, sufficient structure, and data availability. Second, tacit operator knowledge is elicited through Cognitive Task Analysis and translated into two assessment components. Decision alignment measures how closely LLM recommendations reproduce expert decisions using the F1-score and Spearman correlation. Decision quality evaluates recommendations against expert-derived criteria, utility functions, and weights that reflect operators' judgments of good decisions. These criteria are elicited from reflective judgment rather than observed decisions, which may be satisficed, enabling a Multi-Criteria Decision Making approach complemented by qualitative reasoning analysis. Third, a benchmark of current operator decision-making is constructed, as no objectively optimal decisions exist in these contexts. Fourth, recommendations are generated by varying prompt design. Fifth, recommendations are evaluated through factual correctness and safety gates before assessing decision quality and alignment, with results interpreted using a 2×2 matrix distinguishing adoptable, investigable, and rejectable recommendations.
The framework is applied to EXMAR's FSRU in Eemshaven using the regasification configuration decision. Interviews with three operators identified four criteria: energy efficiency, operational robustness, operational effort, and safety as a non-negotiable gate. These were operationalised into indicators, utility functions, and weights. Benchmark scores of 0.83 and 0.90 indicate high-quality operator decisions consistent with satisficing behaviour predicted by Naturalistic Decision Making research. Evaluation of sixteen prompt configurations shows that prompt design strongly influences recommendation quality, with structured prompts using explicit performance criteria achieving results comparable to or exceeding the benchmark. Qualitative reasoning identified six failure modes, particularly stopping at the first feasible option, over-fitting to criteria at the expense of safety, and overly conservative equipment loading. Addressing these informed a second prompt iteration, eliminating safety violations across all configurations. Validation across four additional scenarios demonstrated consistent results, and in one case an operator revised their decision after reviewing an LLM recommendation.
This research demonstrates that evaluating LLM-based decision support in safety-critical expert environments is feasible while highlighting its limitations. Some tacit knowledge cannot be fully captured, limiting any evaluation framework. Nevertheless, several prompt configurations matched or exceeded expert performance, suggesting that LLMs and operators are better viewed as complementary. Rather than replacing experts, these systems are most valuable in supporting operational decision-making while leaving the final decision to the operator.
Global maritime transportation facilitates more than 80% of world trade; therefore, the reliability of ships is inextricably linked to global supply chains. Inefficient inspection and maintenance practices can trigger failures, which in turn increase operating costs. These failures can account for up to 35% of total expenses and cause downtime that cascades through logistic networks. Consequently, unplanned equipment and machinery failures that occur on a vessel can disrupt the ship’s overall operation and lead to delays, higher transport costs, and wider societal impacts, most notably supply shortages and elevated environmental risks. To avoid these domino effects, ship operators must understand the most common failure mechanisms and their underlying causes. Thus, systematic risk identification is a starting point for any strategy that aims to mitigate operational downtime. Existing literature on risk identification in ship inspection and maintenance operations largely focuses on technical and engineering solutions. In order to address this gap, this research adopts the socio-technical system (STS) approach to identify improvement opportunities for inspection and maintenance activities, ultimately mitigating operational downtime. A two-stage Failure Mode Effects and Criticality Analysis (FMECA) is conducted to determine the fundamental failure mechanism in oil tankers and the most critical system, based on industry inspection reports. The Functional Resonance Analysis Method (FRAM) is used to deep dive into that failure. Semi-structured expert interviews and operational data serve as a means of identifying performance variability scenarios across human, organizational, and environmental contexts, within the ship operational process. Finally, the integration of the FMECA and FRAM assists in evaluating suggested control measures based on their effect on ship availability. Corrosion in the steam supply subsystem arises as the leading operational downtime driver. Personnel competence, equipment availability, inspection areas accessibility, and time constraints are the key factors that create performance variability in the operational process. Hinging upon the FRAM models, which qualitatively visualize the propagation of these variability scenarios, control measures are developed based on a Hierarchy of Controls (HoC) As Low As Reasonably Practicable (ALARP) framework. Next steps should begin with a pilot on a single ship subsystem that is highly critical, and a high-resolution failure and downtime dataset. Virtual tests are advised to be conducted before the actual deployment of the identified control measures.
...
Global maritime transportation facilitates more than 80% of world trade; therefore, the reliability of ships is inextricably linked to global supply chains. Inefficient inspection and maintenance practices can trigger failures, which in turn increase operating costs. These failures can account for up to 35% of total expenses and cause downtime that cascades through logistic networks. Consequently, unplanned equipment and machinery failures that occur on a vessel can disrupt the ship’s overall operation and lead to delays, higher transport costs, and wider societal impacts, most notably supply shortages and elevated environmental risks. To avoid these domino effects, ship operators must understand the most common failure mechanisms and their underlying causes. Thus, systematic risk identification is a starting point for any strategy that aims to mitigate operational downtime. Existing literature on risk identification in ship inspection and maintenance operations largely focuses on technical and engineering solutions. In order to address this gap, this research adopts the socio-technical system (STS) approach to identify improvement opportunities for inspection and maintenance activities, ultimately mitigating operational downtime. A two-stage Failure Mode Effects and Criticality Analysis (FMECA) is conducted to determine the fundamental failure mechanism in oil tankers and the most critical system, based on industry inspection reports. The Functional Resonance Analysis Method (FRAM) is used to deep dive into that failure. Semi-structured expert interviews and operational data serve as a means of identifying performance variability scenarios across human, organizational, and environmental contexts, within the ship operational process. Finally, the integration of the FMECA and FRAM assists in evaluating suggested control measures based on their effect on ship availability. Corrosion in the steam supply subsystem arises as the leading operational downtime driver. Personnel competence, equipment availability, inspection areas accessibility, and time constraints are the key factors that create performance variability in the operational process. Hinging upon the FRAM models, which qualitatively visualize the propagation of these variability scenarios, control measures are developed based on a Hierarchy of Controls (HoC) As Low As Reasonably Practicable (ALARP) framework. Next steps should begin with a pilot on a single ship subsystem that is highly critical, and a high-resolution failure and downtime dataset. Virtual tests are advised to be conducted before the actual deployment of the identified control measures.
This thesis examines how safety and sustainability can be integrated into novel biobased façade panels. In the context of rapid urbanisation, climate change and the construction sector’s significant environmental footprint, biobased materials offer potential but face barriers such as fire safety, durability and long-term performance concerns. The EU’s SSbD framework embeds safety and sustainability from early product development, yet its application to construction, particularly for biobased façades, remains limited.
Using Leafy, a startup producing bamboo-based panels, as a case study, this research operationalises the SSbD framework through a qualitative approach with quantitative elements, drawing on document analysis and stakeholder interviews. Findings indicate that SSbD can be effectively applied to green façade panels through a tiered, multi-criteria assessment that integrates hazard analysis, life cycle thinking and risk mitigation. Responsible design requires meeting minimum safety and sustainability thresholds, guided by precaution and transparency. The study calls for adapting SSbD to address the specific challenges of biobased materials and the evolving needs of the construction sector. ...
Using Leafy, a startup producing bamboo-based panels, as a case study, this research operationalises the SSbD framework through a qualitative approach with quantitative elements, drawing on document analysis and stakeholder interviews. Findings indicate that SSbD can be effectively applied to green façade panels through a tiered, multi-criteria assessment that integrates hazard analysis, life cycle thinking and risk mitigation. Responsible design requires meeting minimum safety and sustainability thresholds, guided by precaution and transparency. The study calls for adapting SSbD to address the specific challenges of biobased materials and the evolving needs of the construction sector. ...
This thesis examines how safety and sustainability can be integrated into novel biobased façade panels. In the context of rapid urbanisation, climate change and the construction sector’s significant environmental footprint, biobased materials offer potential but face barriers such as fire safety, durability and long-term performance concerns. The EU’s SSbD framework embeds safety and sustainability from early product development, yet its application to construction, particularly for biobased façades, remains limited.
Using Leafy, a startup producing bamboo-based panels, as a case study, this research operationalises the SSbD framework through a qualitative approach with quantitative elements, drawing on document analysis and stakeholder interviews. Findings indicate that SSbD can be effectively applied to green façade panels through a tiered, multi-criteria assessment that integrates hazard analysis, life cycle thinking and risk mitigation. Responsible design requires meeting minimum safety and sustainability thresholds, guided by precaution and transparency. The study calls for adapting SSbD to address the specific challenges of biobased materials and the evolving needs of the construction sector.
Using Leafy, a startup producing bamboo-based panels, as a case study, this research operationalises the SSbD framework through a qualitative approach with quantitative elements, drawing on document analysis and stakeholder interviews. Findings indicate that SSbD can be effectively applied to green façade panels through a tiered, multi-criteria assessment that integrates hazard analysis, life cycle thinking and risk mitigation. Responsible design requires meeting minimum safety and sustainability thresholds, guided by precaution and transparency. The study calls for adapting SSbD to address the specific challenges of biobased materials and the evolving needs of the construction sector.
Human-Centric Project Performance in Construction Projects
Integrating Behavioral Team Dynamics into Project Management Frameworks
This thesis investigates the integration of human-centric factors (HCFs) of communication, trust, and flexibility into project management frameworks to enhance performance in civil and offshore constructions. As a reaction against the usual 20-45% cost overrun and 30% schedule delay problems, where 70-80% of failure is caused by human factors, this research presents a new framework to increase schedule compliance, cost-effectiveness, quality, and responsiveness under high-uncertainty situations. Traditional methods like PRINCE2 and PMBOK overlook behavioral team dynamics, but a people-centric approach is needed to mitigate inefficiencies created by disruptions like supply chain disruptions or regulatory changes.
Employing a mixed-methods design, the study integrates systematic literature review, semi-structured interviews with eight field experts, Gioia methodology, A12 highway project case study, and Graphical Evaluation and Review Technique (GERT) modeling. Literature review also identified gaps in empirical data and systematic synthesis of HCFs, whereas thematic synthesis of 50 studies established their impact, e.g., communication of a 10% delay reduction. Gioia analysis and interviews yielded three aggregate dimensions: Integration of Human Factors, Human-Centric Performance Optimization, and Adaptive Team Dynamics. GERT simulations quantified performance improvement with 8% reduced schedule delays using empathetic communication and 10-12% cost and rework avoidance with cooperative workshops. The A12 case study verified the results, wherein stakeholder briefings and trust minimization reduced conflicts by 15%.
The proposed framework offers practical recommendations, including active listening training, joint monthly workshops, and anticipatory planning based on GERT, which supplement mainstream methodologies. It achieves 10-15% reduction in delays and 15-20% increase in team satisfaction. It also advances project management theoretically by creating a qualitative foundation for the merging of HCF and widening the application of GERT in behavior modeling. Despite having a constraint like a small interview sample size, this thesis presents a sound foundation for enhancing construction project performance and resilience through human-centered methods.
Keywords: Human-Centric Factors, Project Management, Project Performance, Communication, Trust, Flexibility, Gioia Analysis, GERT
...
Employing a mixed-methods design, the study integrates systematic literature review, semi-structured interviews with eight field experts, Gioia methodology, A12 highway project case study, and Graphical Evaluation and Review Technique (GERT) modeling. Literature review also identified gaps in empirical data and systematic synthesis of HCFs, whereas thematic synthesis of 50 studies established their impact, e.g., communication of a 10% delay reduction. Gioia analysis and interviews yielded three aggregate dimensions: Integration of Human Factors, Human-Centric Performance Optimization, and Adaptive Team Dynamics. GERT simulations quantified performance improvement with 8% reduced schedule delays using empathetic communication and 10-12% cost and rework avoidance with cooperative workshops. The A12 case study verified the results, wherein stakeholder briefings and trust minimization reduced conflicts by 15%.
The proposed framework offers practical recommendations, including active listening training, joint monthly workshops, and anticipatory planning based on GERT, which supplement mainstream methodologies. It achieves 10-15% reduction in delays and 15-20% increase in team satisfaction. It also advances project management theoretically by creating a qualitative foundation for the merging of HCF and widening the application of GERT in behavior modeling. Despite having a constraint like a small interview sample size, this thesis presents a sound foundation for enhancing construction project performance and resilience through human-centered methods.
Keywords: Human-Centric Factors, Project Management, Project Performance, Communication, Trust, Flexibility, Gioia Analysis, GERT
...
This thesis investigates the integration of human-centric factors (HCFs) of communication, trust, and flexibility into project management frameworks to enhance performance in civil and offshore constructions. As a reaction against the usual 20-45% cost overrun and 30% schedule delay problems, where 70-80% of failure is caused by human factors, this research presents a new framework to increase schedule compliance, cost-effectiveness, quality, and responsiveness under high-uncertainty situations. Traditional methods like PRINCE2 and PMBOK overlook behavioral team dynamics, but a people-centric approach is needed to mitigate inefficiencies created by disruptions like supply chain disruptions or regulatory changes.
Employing a mixed-methods design, the study integrates systematic literature review, semi-structured interviews with eight field experts, Gioia methodology, A12 highway project case study, and Graphical Evaluation and Review Technique (GERT) modeling. Literature review also identified gaps in empirical data and systematic synthesis of HCFs, whereas thematic synthesis of 50 studies established their impact, e.g., communication of a 10% delay reduction. Gioia analysis and interviews yielded three aggregate dimensions: Integration of Human Factors, Human-Centric Performance Optimization, and Adaptive Team Dynamics. GERT simulations quantified performance improvement with 8% reduced schedule delays using empathetic communication and 10-12% cost and rework avoidance with cooperative workshops. The A12 case study verified the results, wherein stakeholder briefings and trust minimization reduced conflicts by 15%.
The proposed framework offers practical recommendations, including active listening training, joint monthly workshops, and anticipatory planning based on GERT, which supplement mainstream methodologies. It achieves 10-15% reduction in delays and 15-20% increase in team satisfaction. It also advances project management theoretically by creating a qualitative foundation for the merging of HCF and widening the application of GERT in behavior modeling. Despite having a constraint like a small interview sample size, this thesis presents a sound foundation for enhancing construction project performance and resilience through human-centered methods.
Keywords: Human-Centric Factors, Project Management, Project Performance, Communication, Trust, Flexibility, Gioia Analysis, GERT
Employing a mixed-methods design, the study integrates systematic literature review, semi-structured interviews with eight field experts, Gioia methodology, A12 highway project case study, and Graphical Evaluation and Review Technique (GERT) modeling. Literature review also identified gaps in empirical data and systematic synthesis of HCFs, whereas thematic synthesis of 50 studies established their impact, e.g., communication of a 10% delay reduction. Gioia analysis and interviews yielded three aggregate dimensions: Integration of Human Factors, Human-Centric Performance Optimization, and Adaptive Team Dynamics. GERT simulations quantified performance improvement with 8% reduced schedule delays using empathetic communication and 10-12% cost and rework avoidance with cooperative workshops. The A12 case study verified the results, wherein stakeholder briefings and trust minimization reduced conflicts by 15%.
The proposed framework offers practical recommendations, including active listening training, joint monthly workshops, and anticipatory planning based on GERT, which supplement mainstream methodologies. It achieves 10-15% reduction in delays and 15-20% increase in team satisfaction. It also advances project management theoretically by creating a qualitative foundation for the merging of HCF and widening the application of GERT in behavior modeling. Despite having a constraint like a small interview sample size, this thesis presents a sound foundation for enhancing construction project performance and resilience through human-centered methods.
Keywords: Human-Centric Factors, Project Management, Project Performance, Communication, Trust, Flexibility, Gioia Analysis, GERT
Learning from the past to enhance the resilience of nuclear power plants against natural disasters
Leveraging digital technologies within the learning process to enhance resilience. A Socio-Technical Systems Theory perspective
Natural disasters pose a significant threat to critical infrastructures, particularly nuclear power plants (NPPs), where the impact of a natural hazard can have far-reaching consequences. That is why enhancing the resilience of NPPs, meaning the ability to prepare for, withstand, adapt to and recover from a disaster, is vital. This thesis aims to enhance resilience by strengthening the learning process from past disasters. And lay the groundwork for a learning process guideline document to be adopted by NPPs as an addition to their existing practices to strengthen their resilience learning. The existing resilience practices within NPPs tend to reactive rather than pro-active. With limited integration of structured learning mechanisms and digital technologies.
This research develops the Enhanced Learning Process (ELP) model. Designed to visualize a structured and digital technology integrated resilience learning approach. Employing a Socio-Technical Systems theory perspective to ensure alignment between technology adoption and organizational dynamics. The systematic literature review (SLR) performed examined the literature of resilience engineering, organizational learning and digital technology utilization. And identified existing gaps in resilience strategies, which included the underutilization of digital tools for historical data processing, simulated scenario-based learning and collaborative decision-making. The synthesized literature, analyzed from a socio-technical systems theory perspective, created the knowledge foundation to structure a theoretical enhanced learning process model proposed in this study. Leveraging digital technology capabilities from a socio-technical perspective to enhance historical disaster data processing, identifying possible underlying vulnerabilities of the plant and cascading effects in the event of a natural disaster. Serving as the foundation of a resilience learning guideline that nuclear power plants can adopt to strengthen their learning from the past capabilities to enhance their resilience practices. The proposed model consists of four stages (Data Collection, Data Analysis, Outcome Evaluation and Strategy Development). Reflecting the resilience learning process within NPPs. Where each stage leverages digital technologies to enhance learning capabilities and support the development of data-driven and sophisticated resilience strategies.
The validity and practical applicability of the model was evaluated through a case-based analysis of the Fukushima Daiichi nuclear disaster. Applying the proposed model to this case, demonstrated its’ applicability in a real-world scenario. And provided insights into points of improvement for their learning processes. Lastly, an expert in the industry was consulted to provide verification of the outcomes of this research and validation of practical application of the proposed model.
The outcomes of this study contribute to the fields of resilience engineering and organizational learning by proposing a transformation of traditional learning processes through a structured, digital technology supported, learning approach to enhance resilience strategies against natural hazards. Furthermore, this study extends the application of STS theory in resilience enhancement learning by structuring the learning process as a socio-technical system. Providing insights for researchers, policy makers and NPP operators seeking to strengthen the resilience and learning capabilities of NPPs. This study suggests further research to focus on further validating and developing the ELP-model in collaboration industry experts and further explore the influence that digital technologies have on learning capabilities.
...
This research develops the Enhanced Learning Process (ELP) model. Designed to visualize a structured and digital technology integrated resilience learning approach. Employing a Socio-Technical Systems theory perspective to ensure alignment between technology adoption and organizational dynamics. The systematic literature review (SLR) performed examined the literature of resilience engineering, organizational learning and digital technology utilization. And identified existing gaps in resilience strategies, which included the underutilization of digital tools for historical data processing, simulated scenario-based learning and collaborative decision-making. The synthesized literature, analyzed from a socio-technical systems theory perspective, created the knowledge foundation to structure a theoretical enhanced learning process model proposed in this study. Leveraging digital technology capabilities from a socio-technical perspective to enhance historical disaster data processing, identifying possible underlying vulnerabilities of the plant and cascading effects in the event of a natural disaster. Serving as the foundation of a resilience learning guideline that nuclear power plants can adopt to strengthen their learning from the past capabilities to enhance their resilience practices. The proposed model consists of four stages (Data Collection, Data Analysis, Outcome Evaluation and Strategy Development). Reflecting the resilience learning process within NPPs. Where each stage leverages digital technologies to enhance learning capabilities and support the development of data-driven and sophisticated resilience strategies.
The validity and practical applicability of the model was evaluated through a case-based analysis of the Fukushima Daiichi nuclear disaster. Applying the proposed model to this case, demonstrated its’ applicability in a real-world scenario. And provided insights into points of improvement for their learning processes. Lastly, an expert in the industry was consulted to provide verification of the outcomes of this research and validation of practical application of the proposed model.
The outcomes of this study contribute to the fields of resilience engineering and organizational learning by proposing a transformation of traditional learning processes through a structured, digital technology supported, learning approach to enhance resilience strategies against natural hazards. Furthermore, this study extends the application of STS theory in resilience enhancement learning by structuring the learning process as a socio-technical system. Providing insights for researchers, policy makers and NPP operators seeking to strengthen the resilience and learning capabilities of NPPs. This study suggests further research to focus on further validating and developing the ELP-model in collaboration industry experts and further explore the influence that digital technologies have on learning capabilities.
...
Natural disasters pose a significant threat to critical infrastructures, particularly nuclear power plants (NPPs), where the impact of a natural hazard can have far-reaching consequences. That is why enhancing the resilience of NPPs, meaning the ability to prepare for, withstand, adapt to and recover from a disaster, is vital. This thesis aims to enhance resilience by strengthening the learning process from past disasters. And lay the groundwork for a learning process guideline document to be adopted by NPPs as an addition to their existing practices to strengthen their resilience learning. The existing resilience practices within NPPs tend to reactive rather than pro-active. With limited integration of structured learning mechanisms and digital technologies.
This research develops the Enhanced Learning Process (ELP) model. Designed to visualize a structured and digital technology integrated resilience learning approach. Employing a Socio-Technical Systems theory perspective to ensure alignment between technology adoption and organizational dynamics. The systematic literature review (SLR) performed examined the literature of resilience engineering, organizational learning and digital technology utilization. And identified existing gaps in resilience strategies, which included the underutilization of digital tools for historical data processing, simulated scenario-based learning and collaborative decision-making. The synthesized literature, analyzed from a socio-technical systems theory perspective, created the knowledge foundation to structure a theoretical enhanced learning process model proposed in this study. Leveraging digital technology capabilities from a socio-technical perspective to enhance historical disaster data processing, identifying possible underlying vulnerabilities of the plant and cascading effects in the event of a natural disaster. Serving as the foundation of a resilience learning guideline that nuclear power plants can adopt to strengthen their learning from the past capabilities to enhance their resilience practices. The proposed model consists of four stages (Data Collection, Data Analysis, Outcome Evaluation and Strategy Development). Reflecting the resilience learning process within NPPs. Where each stage leverages digital technologies to enhance learning capabilities and support the development of data-driven and sophisticated resilience strategies.
The validity and practical applicability of the model was evaluated through a case-based analysis of the Fukushima Daiichi nuclear disaster. Applying the proposed model to this case, demonstrated its’ applicability in a real-world scenario. And provided insights into points of improvement for their learning processes. Lastly, an expert in the industry was consulted to provide verification of the outcomes of this research and validation of practical application of the proposed model.
The outcomes of this study contribute to the fields of resilience engineering and organizational learning by proposing a transformation of traditional learning processes through a structured, digital technology supported, learning approach to enhance resilience strategies against natural hazards. Furthermore, this study extends the application of STS theory in resilience enhancement learning by structuring the learning process as a socio-technical system. Providing insights for researchers, policy makers and NPP operators seeking to strengthen the resilience and learning capabilities of NPPs. This study suggests further research to focus on further validating and developing the ELP-model in collaboration industry experts and further explore the influence that digital technologies have on learning capabilities.
This research develops the Enhanced Learning Process (ELP) model. Designed to visualize a structured and digital technology integrated resilience learning approach. Employing a Socio-Technical Systems theory perspective to ensure alignment between technology adoption and organizational dynamics. The systematic literature review (SLR) performed examined the literature of resilience engineering, organizational learning and digital technology utilization. And identified existing gaps in resilience strategies, which included the underutilization of digital tools for historical data processing, simulated scenario-based learning and collaborative decision-making. The synthesized literature, analyzed from a socio-technical systems theory perspective, created the knowledge foundation to structure a theoretical enhanced learning process model proposed in this study. Leveraging digital technology capabilities from a socio-technical perspective to enhance historical disaster data processing, identifying possible underlying vulnerabilities of the plant and cascading effects in the event of a natural disaster. Serving as the foundation of a resilience learning guideline that nuclear power plants can adopt to strengthen their learning from the past capabilities to enhance their resilience practices. The proposed model consists of four stages (Data Collection, Data Analysis, Outcome Evaluation and Strategy Development). Reflecting the resilience learning process within NPPs. Where each stage leverages digital technologies to enhance learning capabilities and support the development of data-driven and sophisticated resilience strategies.
The validity and practical applicability of the model was evaluated through a case-based analysis of the Fukushima Daiichi nuclear disaster. Applying the proposed model to this case, demonstrated its’ applicability in a real-world scenario. And provided insights into points of improvement for their learning processes. Lastly, an expert in the industry was consulted to provide verification of the outcomes of this research and validation of practical application of the proposed model.
The outcomes of this study contribute to the fields of resilience engineering and organizational learning by proposing a transformation of traditional learning processes through a structured, digital technology supported, learning approach to enhance resilience strategies against natural hazards. Furthermore, this study extends the application of STS theory in resilience enhancement learning by structuring the learning process as a socio-technical system. Providing insights for researchers, policy makers and NPP operators seeking to strengthen the resilience and learning capabilities of NPPs. This study suggests further research to focus on further validating and developing the ELP-model in collaboration industry experts and further explore the influence that digital technologies have on learning capabilities.
This thesis develops and tests a way to read emergency department (ED) performance indicators as direct evidence of resilient performance during disruptions, rather than as disconnected “better or worse” numbers. It focuses on how concrete work adaptations during COVID-19— like new isolation protocols, rapid assessment areas, and point-of-care testing—changed ED performance, and how those changes can be systematically translated into resilient performance profiles and quality trade-off narratives.
Background and problem
Emergency Departments operate under constant pressure to deliver fast, safe, and efficient care with finite resources. These pressures intensified during the COVID-19 pandemic, when EDs had to adjust their operations repeatedly while still maintaining core care functions. Performance indicators (PIs) such as length of stay, waiting times, and left-without-being-seen rates are widely used to monitor quality, but they are usually treated as isolated metrics or crude targets. Resilience Engineering and Safety-II emphasize how systems adapt under stress, yet existing tools typically produce qualitative capability profiles that are weakly linked to day-to-day operational performance.
The thesis identifies a central gap: there is no widely adopted method that uses routinely observed ED performance data to make resilience measurable, interpretable, and comparable, including its implications for the quality of care. As a result, resilience assessments often remain abstract, and they struggle to show concretely how disruptions and work adaptations affect real operations.
Research objective and questions
To address this gap, the thesis develops the Performance Indicator Resilience Assessment (PI–RA) framework, which links work adaptations to observable changes in performance indicators and to their associated quality trade-offs. PI–RA translates heterogeneous case evidence into a transparent read-out of resilient performance. In this thesis, resilient performance is interpreted using the resilience curve in Figure 1: a disruption pushes ED performance away from its usual level, after which the system may stabilize in a degraded state, recover back towards the baseline, or even improve beyond it. PI–RA can not measure the exact depth of the drop, but it uses before–after patterns in performance indicators to classify where the ED ends up on this curve—whether required operations remain degraded, move back onto a recovery trajectory, or improve with limited trade-offs—and what this implies for the quality of care. ...
Background and problem
Emergency Departments operate under constant pressure to deliver fast, safe, and efficient care with finite resources. These pressures intensified during the COVID-19 pandemic, when EDs had to adjust their operations repeatedly while still maintaining core care functions. Performance indicators (PIs) such as length of stay, waiting times, and left-without-being-seen rates are widely used to monitor quality, but they are usually treated as isolated metrics or crude targets. Resilience Engineering and Safety-II emphasize how systems adapt under stress, yet existing tools typically produce qualitative capability profiles that are weakly linked to day-to-day operational performance.
The thesis identifies a central gap: there is no widely adopted method that uses routinely observed ED performance data to make resilience measurable, interpretable, and comparable, including its implications for the quality of care. As a result, resilience assessments often remain abstract, and they struggle to show concretely how disruptions and work adaptations affect real operations.
Research objective and questions
To address this gap, the thesis develops the Performance Indicator Resilience Assessment (PI–RA) framework, which links work adaptations to observable changes in performance indicators and to their associated quality trade-offs. PI–RA translates heterogeneous case evidence into a transparent read-out of resilient performance. In this thesis, resilient performance is interpreted using the resilience curve in Figure 1: a disruption pushes ED performance away from its usual level, after which the system may stabilize in a degraded state, recover back towards the baseline, or even improve beyond it. PI–RA can not measure the exact depth of the drop, but it uses before–after patterns in performance indicators to classify where the ED ends up on this curve—whether required operations remain degraded, move back onto a recovery trajectory, or improve with limited trade-offs—and what this implies for the quality of care. ...
This thesis develops and tests a way to read emergency department (ED) performance indicators as direct evidence of resilient performance during disruptions, rather than as disconnected “better or worse” numbers. It focuses on how concrete work adaptations during COVID-19— like new isolation protocols, rapid assessment areas, and point-of-care testing—changed ED performance, and how those changes can be systematically translated into resilient performance profiles and quality trade-off narratives.
Background and problem
Emergency Departments operate under constant pressure to deliver fast, safe, and efficient care with finite resources. These pressures intensified during the COVID-19 pandemic, when EDs had to adjust their operations repeatedly while still maintaining core care functions. Performance indicators (PIs) such as length of stay, waiting times, and left-without-being-seen rates are widely used to monitor quality, but they are usually treated as isolated metrics or crude targets. Resilience Engineering and Safety-II emphasize how systems adapt under stress, yet existing tools typically produce qualitative capability profiles that are weakly linked to day-to-day operational performance.
The thesis identifies a central gap: there is no widely adopted method that uses routinely observed ED performance data to make resilience measurable, interpretable, and comparable, including its implications for the quality of care. As a result, resilience assessments often remain abstract, and they struggle to show concretely how disruptions and work adaptations affect real operations.
Research objective and questions
To address this gap, the thesis develops the Performance Indicator Resilience Assessment (PI–RA) framework, which links work adaptations to observable changes in performance indicators and to their associated quality trade-offs. PI–RA translates heterogeneous case evidence into a transparent read-out of resilient performance. In this thesis, resilient performance is interpreted using the resilience curve in Figure 1: a disruption pushes ED performance away from its usual level, after which the system may stabilize in a degraded state, recover back towards the baseline, or even improve beyond it. PI–RA can not measure the exact depth of the drop, but it uses before–after patterns in performance indicators to classify where the ED ends up on this curve—whether required operations remain degraded, move back onto a recovery trajectory, or improve with limited trade-offs—and what this implies for the quality of care.
Background and problem
Emergency Departments operate under constant pressure to deliver fast, safe, and efficient care with finite resources. These pressures intensified during the COVID-19 pandemic, when EDs had to adjust their operations repeatedly while still maintaining core care functions. Performance indicators (PIs) such as length of stay, waiting times, and left-without-being-seen rates are widely used to monitor quality, but they are usually treated as isolated metrics or crude targets. Resilience Engineering and Safety-II emphasize how systems adapt under stress, yet existing tools typically produce qualitative capability profiles that are weakly linked to day-to-day operational performance.
The thesis identifies a central gap: there is no widely adopted method that uses routinely observed ED performance data to make resilience measurable, interpretable, and comparable, including its implications for the quality of care. As a result, resilience assessments often remain abstract, and they struggle to show concretely how disruptions and work adaptations affect real operations.
Research objective and questions
To address this gap, the thesis develops the Performance Indicator Resilience Assessment (PI–RA) framework, which links work adaptations to observable changes in performance indicators and to their associated quality trade-offs. PI–RA translates heterogeneous case evidence into a transparent read-out of resilient performance. In this thesis, resilient performance is interpreted using the resilience curve in Figure 1: a disruption pushes ED performance away from its usual level, after which the system may stabilize in a degraded state, recover back towards the baseline, or even improve beyond it. PI–RA can not measure the exact depth of the drop, but it uses before–after patterns in performance indicators to classify where the ED ends up on this curve—whether required operations remain degraded, move back onto a recovery trajectory, or improve with limited trade-offs—and what this implies for the quality of care.
Analyzing and addressing value conflicts in the adoption of hazardous chemicals in the energy transition
A methodological exploration of combining systems thinking and value-driven methods in the design of energy systems
The energy transition requires the adoption of various hazardous chemicals to generate, transport and utilize energy. In this adoption process, value conflicts between stakeholders need to be considered to foster the social acceptance of these chemical molecules. To be able to anticipate on these value conflicts, this study aimed to develop and evaluate a methodological framework for analyzing and addressing value conflicts in the adoption of hazardous chemicals in the energy transition. By integrating principles from systems engineering and value-driven design methods, as well as input from experts in both fields, a framework was developed. The developed methodological framework consisted of three steps being: 1) Applying Systems Thinking to define the socio-technical system the chemical is adopted in and conceptualize stakeholder values (conceptual investigation), 2) Identifying values and value conflicts (empirical investigation) and 3) Classifying and addressing value conflicts (technical investigation). This approach innovates upon the default tripartite value-sensitive design approach by incorporating Systems Thinking in the conceptual investigation phase to suit the broader context of socio-technical systems design rather than just the design of physical technological artifacts like wind turbines and nuclear reactors. Furthermore, it combines parts of existing VSD frameworks in the empirical and technical investigation phase in a novel way.
The methodological framework was evaluated by conducting a case study on the adoption process of ammonia in the Dutch energy transition. To inform the empirical investigation, 11 expert interviews with policy advisors, industry players and research experts provided in-depth information about the values and value conflicts at play. However, it was noted that the broad nature of the interview questions limited the ability to derive specific technical design requirements, suggesting that future studies should adapt the interview questions to focus on particular parts of the socio-technical system if desired. In the empirical investigation phase, value hierarchies were constructed from the value level to the norm level, which provided useful for identifying value conflicts. The results of the empirical investigation revealed seven major values which play a role in the adoption process of ammonia in the Dutch energy transition being: efficiency (of both spatial planning and the energy transition in general), competitiveness, cooperation, safety and health, environmental sustainability, transparency, and (procedural and distributive) justice. The values identified in this study were found to be comparable with those found in related works on the adoption of technologies like nuclear
energy and wind turbines. Seven value conflicts were identified by comparing the norms related to each value and the framework was used to address and classify them. This allowed to derive policy implications.
There is a need for more transparent communication with the public about the energy transition, available technology alternatives to reach net-zero, the associated risks of those alternatives, and the ethical dilemmas that the government is facing. It was established that local communities are willing to bear risks if the government clearly states what the ethical dilemmas are in the energy transition and the choices made in these dilemmas. This vision can build social acceptance from the industry and local communities and address the identified value conflicts between safety and health, justice, and efficiency. In this vision, the government should also address their standpoint on the ethical desirability of adopting certain chemicals in the energy transition. Therefore, it is necessary that the government
has specified the intended use-cases for chemicals like green ammonia. This clarity can help address value conflicts related to competitiveness and environmental sustainability. Furthermore, it is important that the government keeps fostering a strong collaboration between industry and government. This is especially important when adopting chemicals that are new and where the government possesses limited expertise on. As the industry could possess the necessary technical expertise, the government could set regulatory boundaries upon collaboration with industry, enhancing regulatory preparedness. Moreover, to ensure that imported ammonia is produced green, certification standards should be put in place. These interventions could address the identified value conflict between environmental sustainability and competitiveness, fostering the social acceptance of ammonia adoption. ...
The methodological framework was evaluated by conducting a case study on the adoption process of ammonia in the Dutch energy transition. To inform the empirical investigation, 11 expert interviews with policy advisors, industry players and research experts provided in-depth information about the values and value conflicts at play. However, it was noted that the broad nature of the interview questions limited the ability to derive specific technical design requirements, suggesting that future studies should adapt the interview questions to focus on particular parts of the socio-technical system if desired. In the empirical investigation phase, value hierarchies were constructed from the value level to the norm level, which provided useful for identifying value conflicts. The results of the empirical investigation revealed seven major values which play a role in the adoption process of ammonia in the Dutch energy transition being: efficiency (of both spatial planning and the energy transition in general), competitiveness, cooperation, safety and health, environmental sustainability, transparency, and (procedural and distributive) justice. The values identified in this study were found to be comparable with those found in related works on the adoption of technologies like nuclear
energy and wind turbines. Seven value conflicts were identified by comparing the norms related to each value and the framework was used to address and classify them. This allowed to derive policy implications.
There is a need for more transparent communication with the public about the energy transition, available technology alternatives to reach net-zero, the associated risks of those alternatives, and the ethical dilemmas that the government is facing. It was established that local communities are willing to bear risks if the government clearly states what the ethical dilemmas are in the energy transition and the choices made in these dilemmas. This vision can build social acceptance from the industry and local communities and address the identified value conflicts between safety and health, justice, and efficiency. In this vision, the government should also address their standpoint on the ethical desirability of adopting certain chemicals in the energy transition. Therefore, it is necessary that the government
has specified the intended use-cases for chemicals like green ammonia. This clarity can help address value conflicts related to competitiveness and environmental sustainability. Furthermore, it is important that the government keeps fostering a strong collaboration between industry and government. This is especially important when adopting chemicals that are new and where the government possesses limited expertise on. As the industry could possess the necessary technical expertise, the government could set regulatory boundaries upon collaboration with industry, enhancing regulatory preparedness. Moreover, to ensure that imported ammonia is produced green, certification standards should be put in place. These interventions could address the identified value conflict between environmental sustainability and competitiveness, fostering the social acceptance of ammonia adoption. ...
The energy transition requires the adoption of various hazardous chemicals to generate, transport and utilize energy. In this adoption process, value conflicts between stakeholders need to be considered to foster the social acceptance of these chemical molecules. To be able to anticipate on these value conflicts, this study aimed to develop and evaluate a methodological framework for analyzing and addressing value conflicts in the adoption of hazardous chemicals in the energy transition. By integrating principles from systems engineering and value-driven design methods, as well as input from experts in both fields, a framework was developed. The developed methodological framework consisted of three steps being: 1) Applying Systems Thinking to define the socio-technical system the chemical is adopted in and conceptualize stakeholder values (conceptual investigation), 2) Identifying values and value conflicts (empirical investigation) and 3) Classifying and addressing value conflicts (technical investigation). This approach innovates upon the default tripartite value-sensitive design approach by incorporating Systems Thinking in the conceptual investigation phase to suit the broader context of socio-technical systems design rather than just the design of physical technological artifacts like wind turbines and nuclear reactors. Furthermore, it combines parts of existing VSD frameworks in the empirical and technical investigation phase in a novel way.
The methodological framework was evaluated by conducting a case study on the adoption process of ammonia in the Dutch energy transition. To inform the empirical investigation, 11 expert interviews with policy advisors, industry players and research experts provided in-depth information about the values and value conflicts at play. However, it was noted that the broad nature of the interview questions limited the ability to derive specific technical design requirements, suggesting that future studies should adapt the interview questions to focus on particular parts of the socio-technical system if desired. In the empirical investigation phase, value hierarchies were constructed from the value level to the norm level, which provided useful for identifying value conflicts. The results of the empirical investigation revealed seven major values which play a role in the adoption process of ammonia in the Dutch energy transition being: efficiency (of both spatial planning and the energy transition in general), competitiveness, cooperation, safety and health, environmental sustainability, transparency, and (procedural and distributive) justice. The values identified in this study were found to be comparable with those found in related works on the adoption of technologies like nuclear
energy and wind turbines. Seven value conflicts were identified by comparing the norms related to each value and the framework was used to address and classify them. This allowed to derive policy implications.
There is a need for more transparent communication with the public about the energy transition, available technology alternatives to reach net-zero, the associated risks of those alternatives, and the ethical dilemmas that the government is facing. It was established that local communities are willing to bear risks if the government clearly states what the ethical dilemmas are in the energy transition and the choices made in these dilemmas. This vision can build social acceptance from the industry and local communities and address the identified value conflicts between safety and health, justice, and efficiency. In this vision, the government should also address their standpoint on the ethical desirability of adopting certain chemicals in the energy transition. Therefore, it is necessary that the government
has specified the intended use-cases for chemicals like green ammonia. This clarity can help address value conflicts related to competitiveness and environmental sustainability. Furthermore, it is important that the government keeps fostering a strong collaboration between industry and government. This is especially important when adopting chemicals that are new and where the government possesses limited expertise on. As the industry could possess the necessary technical expertise, the government could set regulatory boundaries upon collaboration with industry, enhancing regulatory preparedness. Moreover, to ensure that imported ammonia is produced green, certification standards should be put in place. These interventions could address the identified value conflict between environmental sustainability and competitiveness, fostering the social acceptance of ammonia adoption.
The methodological framework was evaluated by conducting a case study on the adoption process of ammonia in the Dutch energy transition. To inform the empirical investigation, 11 expert interviews with policy advisors, industry players and research experts provided in-depth information about the values and value conflicts at play. However, it was noted that the broad nature of the interview questions limited the ability to derive specific technical design requirements, suggesting that future studies should adapt the interview questions to focus on particular parts of the socio-technical system if desired. In the empirical investigation phase, value hierarchies were constructed from the value level to the norm level, which provided useful for identifying value conflicts. The results of the empirical investigation revealed seven major values which play a role in the adoption process of ammonia in the Dutch energy transition being: efficiency (of both spatial planning and the energy transition in general), competitiveness, cooperation, safety and health, environmental sustainability, transparency, and (procedural and distributive) justice. The values identified in this study were found to be comparable with those found in related works on the adoption of technologies like nuclear
energy and wind turbines. Seven value conflicts were identified by comparing the norms related to each value and the framework was used to address and classify them. This allowed to derive policy implications.
There is a need for more transparent communication with the public about the energy transition, available technology alternatives to reach net-zero, the associated risks of those alternatives, and the ethical dilemmas that the government is facing. It was established that local communities are willing to bear risks if the government clearly states what the ethical dilemmas are in the energy transition and the choices made in these dilemmas. This vision can build social acceptance from the industry and local communities and address the identified value conflicts between safety and health, justice, and efficiency. In this vision, the government should also address their standpoint on the ethical desirability of adopting certain chemicals in the energy transition. Therefore, it is necessary that the government
has specified the intended use-cases for chemicals like green ammonia. This clarity can help address value conflicts related to competitiveness and environmental sustainability. Furthermore, it is important that the government keeps fostering a strong collaboration between industry and government. This is especially important when adopting chemicals that are new and where the government possesses limited expertise on. As the industry could possess the necessary technical expertise, the government could set regulatory boundaries upon collaboration with industry, enhancing regulatory preparedness. Moreover, to ensure that imported ammonia is produced green, certification standards should be put in place. These interventions could address the identified value conflict between environmental sustainability and competitiveness, fostering the social acceptance of ammonia adoption.
Concerning the accidental and intentional major adverse events in chemical process industries, particularly considering the emerging cyber-to-physical (C2P) attack risks affiliated with the automation and digitization process of industrial control systems, this study is dedicated to investigating the dynamic and integrated safety and security barrier management for ensuring the safety and security of chemical plant in the Industry 4.0 era. To achieve the objectives of this study, the following research steps have been made.
A systematic review has been conducted to understand the definitions and classifications of safety and security barriers and get insights into the fundamental aspects of safety and security barriers. Existing methodologies for the performance assessment and management of safety and security barriers have also been reviewed and discussed to identify research gaps, which provide valid foundations for the following steps.
With the identification of multi-dimensional risks (safety risks, physical attack risks, and C2P attack risks) threatening industrial control systems in chemical plants, an integrated approach is developed to construct accident scenarios concerning both safety hazards and security threats and quantitatively assess the risk of chemical facilities considering the interdependency between safety risks and security risks.
Considering the uncertainties associated with the integrated safety and security risks, particularly the uncertainties in attackers' knowledge levels, a vulnerability assessment model is developed to assess C2P attacks, and the combination of Monte Carlo simulations and a Bayesian network model is employed to handle uncertainty propagation in the risk assessment. Furthermore, combining cost-effectiveness analysis with a risk matrix yields the optimal strategy for safety and security barrier enhancements from a cost-effective perspective.
A novel approach for risk-based barrier maintenance is developed to tackle the challenges in solving barrier optimization problems with large-solution spaces.
Accident scenarios regarding safety and physical security are constructed using an extended bow-tie diagram and then modeled based on MATLAB/Simulink simulations.
A combination of cost-effectiveness analysis and genetic algorithms is employed to decide the approximately optimal strategy for barrier maintenance.
Multiple data (periodic proof test data, continuous condition-monitoring data, and accident precursor data) are combined to enable continuous safety barrier improvement by revealing the degradation of safety barriers and performing dynamic risk assessment. Furthermore, multi-source data capable of revealing risk variations are characterized and incorporated with the barrier management framework to empower dynamic and integrated safety and security barrier management. Dynamic and integrated S&S barrier management has the advantage of making timely adaptations according to the new evidence and continuously ensuring the integrated safety and security risks at acceptable levels.
Finally, all methodologies developed in this study are structured into a systematic framework to foster the application of dynamic and integrated management of safety and security barriers in practices. ...
A systematic review has been conducted to understand the definitions and classifications of safety and security barriers and get insights into the fundamental aspects of safety and security barriers. Existing methodologies for the performance assessment and management of safety and security barriers have also been reviewed and discussed to identify research gaps, which provide valid foundations for the following steps.
With the identification of multi-dimensional risks (safety risks, physical attack risks, and C2P attack risks) threatening industrial control systems in chemical plants, an integrated approach is developed to construct accident scenarios concerning both safety hazards and security threats and quantitatively assess the risk of chemical facilities considering the interdependency between safety risks and security risks.
Considering the uncertainties associated with the integrated safety and security risks, particularly the uncertainties in attackers' knowledge levels, a vulnerability assessment model is developed to assess C2P attacks, and the combination of Monte Carlo simulations and a Bayesian network model is employed to handle uncertainty propagation in the risk assessment. Furthermore, combining cost-effectiveness analysis with a risk matrix yields the optimal strategy for safety and security barrier enhancements from a cost-effective perspective.
A novel approach for risk-based barrier maintenance is developed to tackle the challenges in solving barrier optimization problems with large-solution spaces.
Accident scenarios regarding safety and physical security are constructed using an extended bow-tie diagram and then modeled based on MATLAB/Simulink simulations.
A combination of cost-effectiveness analysis and genetic algorithms is employed to decide the approximately optimal strategy for barrier maintenance.
Multiple data (periodic proof test data, continuous condition-monitoring data, and accident precursor data) are combined to enable continuous safety barrier improvement by revealing the degradation of safety barriers and performing dynamic risk assessment. Furthermore, multi-source data capable of revealing risk variations are characterized and incorporated with the barrier management framework to empower dynamic and integrated safety and security barrier management. Dynamic and integrated S&S barrier management has the advantage of making timely adaptations according to the new evidence and continuously ensuring the integrated safety and security risks at acceptable levels.
Finally, all methodologies developed in this study are structured into a systematic framework to foster the application of dynamic and integrated management of safety and security barriers in practices. ...
Concerning the accidental and intentional major adverse events in chemical process industries, particularly considering the emerging cyber-to-physical (C2P) attack risks affiliated with the automation and digitization process of industrial control systems, this study is dedicated to investigating the dynamic and integrated safety and security barrier management for ensuring the safety and security of chemical plant in the Industry 4.0 era. To achieve the objectives of this study, the following research steps have been made.
A systematic review has been conducted to understand the definitions and classifications of safety and security barriers and get insights into the fundamental aspects of safety and security barriers. Existing methodologies for the performance assessment and management of safety and security barriers have also been reviewed and discussed to identify research gaps, which provide valid foundations for the following steps.
With the identification of multi-dimensional risks (safety risks, physical attack risks, and C2P attack risks) threatening industrial control systems in chemical plants, an integrated approach is developed to construct accident scenarios concerning both safety hazards and security threats and quantitatively assess the risk of chemical facilities considering the interdependency between safety risks and security risks.
Considering the uncertainties associated with the integrated safety and security risks, particularly the uncertainties in attackers' knowledge levels, a vulnerability assessment model is developed to assess C2P attacks, and the combination of Monte Carlo simulations and a Bayesian network model is employed to handle uncertainty propagation in the risk assessment. Furthermore, combining cost-effectiveness analysis with a risk matrix yields the optimal strategy for safety and security barrier enhancements from a cost-effective perspective.
A novel approach for risk-based barrier maintenance is developed to tackle the challenges in solving barrier optimization problems with large-solution spaces.
Accident scenarios regarding safety and physical security are constructed using an extended bow-tie diagram and then modeled based on MATLAB/Simulink simulations.
A combination of cost-effectiveness analysis and genetic algorithms is employed to decide the approximately optimal strategy for barrier maintenance.
Multiple data (periodic proof test data, continuous condition-monitoring data, and accident precursor data) are combined to enable continuous safety barrier improvement by revealing the degradation of safety barriers and performing dynamic risk assessment. Furthermore, multi-source data capable of revealing risk variations are characterized and incorporated with the barrier management framework to empower dynamic and integrated safety and security barrier management. Dynamic and integrated S&S barrier management has the advantage of making timely adaptations according to the new evidence and continuously ensuring the integrated safety and security risks at acceptable levels.
Finally, all methodologies developed in this study are structured into a systematic framework to foster the application of dynamic and integrated management of safety and security barriers in practices.
A systematic review has been conducted to understand the definitions and classifications of safety and security barriers and get insights into the fundamental aspects of safety and security barriers. Existing methodologies for the performance assessment and management of safety and security barriers have also been reviewed and discussed to identify research gaps, which provide valid foundations for the following steps.
With the identification of multi-dimensional risks (safety risks, physical attack risks, and C2P attack risks) threatening industrial control systems in chemical plants, an integrated approach is developed to construct accident scenarios concerning both safety hazards and security threats and quantitatively assess the risk of chemical facilities considering the interdependency between safety risks and security risks.
Considering the uncertainties associated with the integrated safety and security risks, particularly the uncertainties in attackers' knowledge levels, a vulnerability assessment model is developed to assess C2P attacks, and the combination of Monte Carlo simulations and a Bayesian network model is employed to handle uncertainty propagation in the risk assessment. Furthermore, combining cost-effectiveness analysis with a risk matrix yields the optimal strategy for safety and security barrier enhancements from a cost-effective perspective.
A novel approach for risk-based barrier maintenance is developed to tackle the challenges in solving barrier optimization problems with large-solution spaces.
Accident scenarios regarding safety and physical security are constructed using an extended bow-tie diagram and then modeled based on MATLAB/Simulink simulations.
A combination of cost-effectiveness analysis and genetic algorithms is employed to decide the approximately optimal strategy for barrier maintenance.
Multiple data (periodic proof test data, continuous condition-monitoring data, and accident precursor data) are combined to enable continuous safety barrier improvement by revealing the degradation of safety barriers and performing dynamic risk assessment. Furthermore, multi-source data capable of revealing risk variations are characterized and incorporated with the barrier management framework to empower dynamic and integrated safety and security barrier management. Dynamic and integrated S&S barrier management has the advantage of making timely adaptations according to the new evidence and continuously ensuring the integrated safety and security risks at acceptable levels.
Finally, all methodologies developed in this study are structured into a systematic framework to foster the application of dynamic and integrated management of safety and security barriers in practices.
Addressing Supply-Side Disruptions
Optimizing Supply Chain Performance through Supplier Selection and Risk Mitigation
In the contemporary global environment, supply chains are increasingly vulnerable to disruptions, with environmental and supplier disturbances posing frequent challenges. This research aimed to understand the influence of a systematic supplier selection approach, combined with an effective risk mitigation strategy, on supply chain performance amidst supply-side disruption risks. We identified a significant gap in current supply chain management: the lack of a structured supplier selection methodology, which can lead to inefficiencies and performance declines. To address this, our study employed the best worst method (BWM) for systematic supplier assessment and ranking. Simultaneously, a discrete-event simulation model on the Simio platform was utilized to emulate supply chain dynamics, factoring in various suppliers and potential disruptions.
Our findings, contextualized within the polymer industry, highlighted Material Quality, Supply Reliability, Price, and Lead Time as the most critical criteria for supplier selection. The BWM rankings correlated strongly with actual supply chain outcomes, emphasizing its effectiveness. In terms of risk mitigation, flexibility-oriented sourcing strategies were superior to redundancy-oriented ones, demonstrating better management of supply-side disruptions and reduced safety stock levels.
These results have both societal and scientific implications. Societally, a methodical supplier selection process ensures resilient supply chains, essential for sectors like healthcare and food, and promotes global collaboration and innovation through diversified supplier sourcing. Scientifically, our research validates the BWM's utility for supplier selection, challenging conventional beliefs linking higher costs to superior risk mitigation. A key insight was the growing importance of flexibility in modern supply chain risk management.
For the polymer sector, we recommend a BWM-based structured supplier selection process. By partnering with top-ranked suppliers and diversifying geographically, businesses can reduce safety stock levels. Our simulation model provides a practical tool for decision-makers, facilitating scenario testing to identify optimal strategies.
However, our study's limitations must be acknowledged. Tailored primarily for the polymer industry, the specific assumptions underpinning our simulation may not be universally relevant. Thus, while our insights are valuable, their applicability might be limited by data constraints and the polymer sector's distinct attributes.
In conclusion, a methodical supplier selection, paired with a flexibility-oriented sourcing approach, optimizes supply chain performance in the face of supply-side disruptions. Enhancing these elements can guide businesses in developing agile supply chains, ensuring cost-effectiveness and improved performance. ...
Our findings, contextualized within the polymer industry, highlighted Material Quality, Supply Reliability, Price, and Lead Time as the most critical criteria for supplier selection. The BWM rankings correlated strongly with actual supply chain outcomes, emphasizing its effectiveness. In terms of risk mitigation, flexibility-oriented sourcing strategies were superior to redundancy-oriented ones, demonstrating better management of supply-side disruptions and reduced safety stock levels.
These results have both societal and scientific implications. Societally, a methodical supplier selection process ensures resilient supply chains, essential for sectors like healthcare and food, and promotes global collaboration and innovation through diversified supplier sourcing. Scientifically, our research validates the BWM's utility for supplier selection, challenging conventional beliefs linking higher costs to superior risk mitigation. A key insight was the growing importance of flexibility in modern supply chain risk management.
For the polymer sector, we recommend a BWM-based structured supplier selection process. By partnering with top-ranked suppliers and diversifying geographically, businesses can reduce safety stock levels. Our simulation model provides a practical tool for decision-makers, facilitating scenario testing to identify optimal strategies.
However, our study's limitations must be acknowledged. Tailored primarily for the polymer industry, the specific assumptions underpinning our simulation may not be universally relevant. Thus, while our insights are valuable, their applicability might be limited by data constraints and the polymer sector's distinct attributes.
In conclusion, a methodical supplier selection, paired with a flexibility-oriented sourcing approach, optimizes supply chain performance in the face of supply-side disruptions. Enhancing these elements can guide businesses in developing agile supply chains, ensuring cost-effectiveness and improved performance. ...
In the contemporary global environment, supply chains are increasingly vulnerable to disruptions, with environmental and supplier disturbances posing frequent challenges. This research aimed to understand the influence of a systematic supplier selection approach, combined with an effective risk mitigation strategy, on supply chain performance amidst supply-side disruption risks. We identified a significant gap in current supply chain management: the lack of a structured supplier selection methodology, which can lead to inefficiencies and performance declines. To address this, our study employed the best worst method (BWM) for systematic supplier assessment and ranking. Simultaneously, a discrete-event simulation model on the Simio platform was utilized to emulate supply chain dynamics, factoring in various suppliers and potential disruptions.
Our findings, contextualized within the polymer industry, highlighted Material Quality, Supply Reliability, Price, and Lead Time as the most critical criteria for supplier selection. The BWM rankings correlated strongly with actual supply chain outcomes, emphasizing its effectiveness. In terms of risk mitigation, flexibility-oriented sourcing strategies were superior to redundancy-oriented ones, demonstrating better management of supply-side disruptions and reduced safety stock levels.
These results have both societal and scientific implications. Societally, a methodical supplier selection process ensures resilient supply chains, essential for sectors like healthcare and food, and promotes global collaboration and innovation through diversified supplier sourcing. Scientifically, our research validates the BWM's utility for supplier selection, challenging conventional beliefs linking higher costs to superior risk mitigation. A key insight was the growing importance of flexibility in modern supply chain risk management.
For the polymer sector, we recommend a BWM-based structured supplier selection process. By partnering with top-ranked suppliers and diversifying geographically, businesses can reduce safety stock levels. Our simulation model provides a practical tool for decision-makers, facilitating scenario testing to identify optimal strategies.
However, our study's limitations must be acknowledged. Tailored primarily for the polymer industry, the specific assumptions underpinning our simulation may not be universally relevant. Thus, while our insights are valuable, their applicability might be limited by data constraints and the polymer sector's distinct attributes.
In conclusion, a methodical supplier selection, paired with a flexibility-oriented sourcing approach, optimizes supply chain performance in the face of supply-side disruptions. Enhancing these elements can guide businesses in developing agile supply chains, ensuring cost-effectiveness and improved performance.
Our findings, contextualized within the polymer industry, highlighted Material Quality, Supply Reliability, Price, and Lead Time as the most critical criteria for supplier selection. The BWM rankings correlated strongly with actual supply chain outcomes, emphasizing its effectiveness. In terms of risk mitigation, flexibility-oriented sourcing strategies were superior to redundancy-oriented ones, demonstrating better management of supply-side disruptions and reduced safety stock levels.
These results have both societal and scientific implications. Societally, a methodical supplier selection process ensures resilient supply chains, essential for sectors like healthcare and food, and promotes global collaboration and innovation through diversified supplier sourcing. Scientifically, our research validates the BWM's utility for supplier selection, challenging conventional beliefs linking higher costs to superior risk mitigation. A key insight was the growing importance of flexibility in modern supply chain risk management.
For the polymer sector, we recommend a BWM-based structured supplier selection process. By partnering with top-ranked suppliers and diversifying geographically, businesses can reduce safety stock levels. Our simulation model provides a practical tool for decision-makers, facilitating scenario testing to identify optimal strategies.
However, our study's limitations must be acknowledged. Tailored primarily for the polymer industry, the specific assumptions underpinning our simulation may not be universally relevant. Thus, while our insights are valuable, their applicability might be limited by data constraints and the polymer sector's distinct attributes.
In conclusion, a methodical supplier selection, paired with a flexibility-oriented sourcing approach, optimizes supply chain performance in the face of supply-side disruptions. Enhancing these elements can guide businesses in developing agile supply chains, ensuring cost-effectiveness and improved performance.
Risk Management Framework for Parachute Mortars on Sounding Rockets
Increasing the safety and functional performance of the parachute mortar
The executive summary offers a concise overview of the thesis research conducted, focusing on enabling risk management for parachute mortars on sounding rockets from a socio-technical perspective. The study aimed to address safety and performance risks associated with these systems and bridge the gap between theoretical risk management methods and practical applications.
The research was initiated with a comprehensive review of the relevant literature, which identified several gaps in the existing knowledge. These included a lack of detailed coverage on risk identification, assessment, and evaluation in case studies, limited information on parachute mortar systems specific to sounding rockets, and a lack of application of socio-technical systems to technical subsystems in spaceflight. The primary objective of this study was to develop a comprehensive risk management guideline specifically tailored for parachute mortar systems, integrating a socio-technical systems approach. The guideline aimed to be grounded in conventional risk management practices while being validated through a practical case study to ensure its feasibility. Throughout the research, various results were obtained. The evaluation of conventional risk management methods, including ISO31010, industry practices and socio-technical views, led to the initial design of the risk management approach. This approach was then applied to a case study involving the DARE mortar, allowing for the reflection on each method’s effectiveness. Key risks identified were related to the carbon fibre reinforced polymer (CFRP) canister of the mortar system and risks of underperformance due to pressure leaks in the system during flight. These critical risks were successfully reduced through redesign and testing activities in the risk treatment phase of the case study. The final Risk Management Guideline was developed by incorporating the lessons learned from applying the approach to the case study. By applying the developed framework to a real-world scenario, this research went beyond theoretical considerations and demonstrated the practical applicability of the socio-technical system approach in mitigating risks associated with parachute mortars on sounding rockets. The combination of a practical case study, a socio-technical approach, and risk management on sounding rocket subsystems is considered novel and has the potential to advance risk management activities in this domain.
The research also identified several future research directions. These include performing more case studies on smaller technical subsystems using a socio-technical systems approach, exploring and establishing consensus on definitions and boundaries of socio-technical systems, integrating qualitative results of human reliability analysis with risk management methods, and defining objective methods for risk evaluation and establishing risk acceptance criteria. Overall, this thesis research contributes to the field of risk management by addressing the unique challenges of parachute mortars on sounding rockets through a socio-technical systems perspective. The developed risk management guideline, validated through a practical case study, provides valuable insights and practical applications for mitigating risks in this specific context. It is anticipated that this research will facilitate further advancements in risk management activities for parachute mortars and socio-technical systems while also having the potential to be applied to other sounding rocket subsystems. ...
The research was initiated with a comprehensive review of the relevant literature, which identified several gaps in the existing knowledge. These included a lack of detailed coverage on risk identification, assessment, and evaluation in case studies, limited information on parachute mortar systems specific to sounding rockets, and a lack of application of socio-technical systems to technical subsystems in spaceflight. The primary objective of this study was to develop a comprehensive risk management guideline specifically tailored for parachute mortar systems, integrating a socio-technical systems approach. The guideline aimed to be grounded in conventional risk management practices while being validated through a practical case study to ensure its feasibility. Throughout the research, various results were obtained. The evaluation of conventional risk management methods, including ISO31010, industry practices and socio-technical views, led to the initial design of the risk management approach. This approach was then applied to a case study involving the DARE mortar, allowing for the reflection on each method’s effectiveness. Key risks identified were related to the carbon fibre reinforced polymer (CFRP) canister of the mortar system and risks of underperformance due to pressure leaks in the system during flight. These critical risks were successfully reduced through redesign and testing activities in the risk treatment phase of the case study. The final Risk Management Guideline was developed by incorporating the lessons learned from applying the approach to the case study. By applying the developed framework to a real-world scenario, this research went beyond theoretical considerations and demonstrated the practical applicability of the socio-technical system approach in mitigating risks associated with parachute mortars on sounding rockets. The combination of a practical case study, a socio-technical approach, and risk management on sounding rocket subsystems is considered novel and has the potential to advance risk management activities in this domain.
The research also identified several future research directions. These include performing more case studies on smaller technical subsystems using a socio-technical systems approach, exploring and establishing consensus on definitions and boundaries of socio-technical systems, integrating qualitative results of human reliability analysis with risk management methods, and defining objective methods for risk evaluation and establishing risk acceptance criteria. Overall, this thesis research contributes to the field of risk management by addressing the unique challenges of parachute mortars on sounding rockets through a socio-technical systems perspective. The developed risk management guideline, validated through a practical case study, provides valuable insights and practical applications for mitigating risks in this specific context. It is anticipated that this research will facilitate further advancements in risk management activities for parachute mortars and socio-technical systems while also having the potential to be applied to other sounding rocket subsystems. ...
The executive summary offers a concise overview of the thesis research conducted, focusing on enabling risk management for parachute mortars on sounding rockets from a socio-technical perspective. The study aimed to address safety and performance risks associated with these systems and bridge the gap between theoretical risk management methods and practical applications.
The research was initiated with a comprehensive review of the relevant literature, which identified several gaps in the existing knowledge. These included a lack of detailed coverage on risk identification, assessment, and evaluation in case studies, limited information on parachute mortar systems specific to sounding rockets, and a lack of application of socio-technical systems to technical subsystems in spaceflight. The primary objective of this study was to develop a comprehensive risk management guideline specifically tailored for parachute mortar systems, integrating a socio-technical systems approach. The guideline aimed to be grounded in conventional risk management practices while being validated through a practical case study to ensure its feasibility. Throughout the research, various results were obtained. The evaluation of conventional risk management methods, including ISO31010, industry practices and socio-technical views, led to the initial design of the risk management approach. This approach was then applied to a case study involving the DARE mortar, allowing for the reflection on each method’s effectiveness. Key risks identified were related to the carbon fibre reinforced polymer (CFRP) canister of the mortar system and risks of underperformance due to pressure leaks in the system during flight. These critical risks were successfully reduced through redesign and testing activities in the risk treatment phase of the case study. The final Risk Management Guideline was developed by incorporating the lessons learned from applying the approach to the case study. By applying the developed framework to a real-world scenario, this research went beyond theoretical considerations and demonstrated the practical applicability of the socio-technical system approach in mitigating risks associated with parachute mortars on sounding rockets. The combination of a practical case study, a socio-technical approach, and risk management on sounding rocket subsystems is considered novel and has the potential to advance risk management activities in this domain.
The research also identified several future research directions. These include performing more case studies on smaller technical subsystems using a socio-technical systems approach, exploring and establishing consensus on definitions and boundaries of socio-technical systems, integrating qualitative results of human reliability analysis with risk management methods, and defining objective methods for risk evaluation and establishing risk acceptance criteria. Overall, this thesis research contributes to the field of risk management by addressing the unique challenges of parachute mortars on sounding rockets through a socio-technical systems perspective. The developed risk management guideline, validated through a practical case study, provides valuable insights and practical applications for mitigating risks in this specific context. It is anticipated that this research will facilitate further advancements in risk management activities for parachute mortars and socio-technical systems while also having the potential to be applied to other sounding rocket subsystems.
The research was initiated with a comprehensive review of the relevant literature, which identified several gaps in the existing knowledge. These included a lack of detailed coverage on risk identification, assessment, and evaluation in case studies, limited information on parachute mortar systems specific to sounding rockets, and a lack of application of socio-technical systems to technical subsystems in spaceflight. The primary objective of this study was to develop a comprehensive risk management guideline specifically tailored for parachute mortar systems, integrating a socio-technical systems approach. The guideline aimed to be grounded in conventional risk management practices while being validated through a practical case study to ensure its feasibility. Throughout the research, various results were obtained. The evaluation of conventional risk management methods, including ISO31010, industry practices and socio-technical views, led to the initial design of the risk management approach. This approach was then applied to a case study involving the DARE mortar, allowing for the reflection on each method’s effectiveness. Key risks identified were related to the carbon fibre reinforced polymer (CFRP) canister of the mortar system and risks of underperformance due to pressure leaks in the system during flight. These critical risks were successfully reduced through redesign and testing activities in the risk treatment phase of the case study. The final Risk Management Guideline was developed by incorporating the lessons learned from applying the approach to the case study. By applying the developed framework to a real-world scenario, this research went beyond theoretical considerations and demonstrated the practical applicability of the socio-technical system approach in mitigating risks associated with parachute mortars on sounding rockets. The combination of a practical case study, a socio-technical approach, and risk management on sounding rocket subsystems is considered novel and has the potential to advance risk management activities in this domain.
The research also identified several future research directions. These include performing more case studies on smaller technical subsystems using a socio-technical systems approach, exploring and establishing consensus on definitions and boundaries of socio-technical systems, integrating qualitative results of human reliability analysis with risk management methods, and defining objective methods for risk evaluation and establishing risk acceptance criteria. Overall, this thesis research contributes to the field of risk management by addressing the unique challenges of parachute mortars on sounding rockets through a socio-technical systems perspective. The developed risk management guideline, validated through a practical case study, provides valuable insights and practical applications for mitigating risks in this specific context. It is anticipated that this research will facilitate further advancements in risk management activities for parachute mortars and socio-technical systems while also having the potential to be applied to other sounding rocket subsystems.
In the wake of the 2015 Paris Agreement on climate change, global efforts have intensified to reduce carbon emissions and transition to renewable energy sources such as solar and wind power. However, the asymmetry in energy production and consumption among nations, coupled with the seasonal and temporal intermittency and geographical variations of renewables, has highlighted the need for efficient energy transport solutions. Hydrogen has emerged as a promising candidate due to its high energy density and the fact that it only produces water when burned. Governments, both at the national and international levels, have outlined ambitious roadmaps for green hydrogen production and utilization, as seen in the EU's REPowerEU package aligned with the EU Green Deal and Japan's "Basic H2 strategy." Two prominent importers of hydrogen, Japan and The Netherlands, have been actively involved in shaping the future of international green hydrogen supply chains (IGHSC).
However, as plans for IGHSC development gain momentum, so does the recognition of the need for resilient characteristics within these supply chains. They must be designed to withstand, adapt to, and recover from unexpected disruptions effectively. This research aims to address this need by developing a guideline for establishing a resilience design methodology specific to IGHSC, using Japan and The Netherlands as examples of significant future importers.
The primary research question guiding this thesis is: What guidelines can be established to design and maintain resilience within an international green hydrogen supply chain, with Japan and The Netherlands as exploratory importers?
The research approach combines extensive literature review, analysis, and interviews within a qualitative exploratory framework. A theoretical framework was constructed to uncover the interconnections between various theories and fields of study. This framework not only unveiled previously unnoticed associations but also elucidated the disruptions and resilience mechanisms inherent to IGHSC. Two novel optional IGHSC configurations were identified and introduced, and a comprehensive catalog of relevant disruptions, along with their respective domains, was created. Through a rigorous evaluation of existing research on disruptions and the enhancement of categorization schemes, this study developed a new structure for categorizing potential IGHSC disruptions systematically. These disruptions were categorized based on their potential domains of origin.
The concept of resilience was subsequently defined and categorized into two distinct phases and three scopes, providing a structured framework for designing and maintaining resilience within an IGHSC. Recognizing that the establishment of a global hydrogen economy is pivotal for achieving global net-zero goals, it becomes imperative to prioritize the design and maintenance of resilient IGHSC. This thesis presents a newly developed guideline that contributes to the design and maintenance of resilience within an IGHSC, serving as a crucial step towards realizing a sustainable and reliable global hydrogen economy. ...
However, as plans for IGHSC development gain momentum, so does the recognition of the need for resilient characteristics within these supply chains. They must be designed to withstand, adapt to, and recover from unexpected disruptions effectively. This research aims to address this need by developing a guideline for establishing a resilience design methodology specific to IGHSC, using Japan and The Netherlands as examples of significant future importers.
The primary research question guiding this thesis is: What guidelines can be established to design and maintain resilience within an international green hydrogen supply chain, with Japan and The Netherlands as exploratory importers?
The research approach combines extensive literature review, analysis, and interviews within a qualitative exploratory framework. A theoretical framework was constructed to uncover the interconnections between various theories and fields of study. This framework not only unveiled previously unnoticed associations but also elucidated the disruptions and resilience mechanisms inherent to IGHSC. Two novel optional IGHSC configurations were identified and introduced, and a comprehensive catalog of relevant disruptions, along with their respective domains, was created. Through a rigorous evaluation of existing research on disruptions and the enhancement of categorization schemes, this study developed a new structure for categorizing potential IGHSC disruptions systematically. These disruptions were categorized based on their potential domains of origin.
The concept of resilience was subsequently defined and categorized into two distinct phases and three scopes, providing a structured framework for designing and maintaining resilience within an IGHSC. Recognizing that the establishment of a global hydrogen economy is pivotal for achieving global net-zero goals, it becomes imperative to prioritize the design and maintenance of resilient IGHSC. This thesis presents a newly developed guideline that contributes to the design and maintenance of resilience within an IGHSC, serving as a crucial step towards realizing a sustainable and reliable global hydrogen economy. ...
In the wake of the 2015 Paris Agreement on climate change, global efforts have intensified to reduce carbon emissions and transition to renewable energy sources such as solar and wind power. However, the asymmetry in energy production and consumption among nations, coupled with the seasonal and temporal intermittency and geographical variations of renewables, has highlighted the need for efficient energy transport solutions. Hydrogen has emerged as a promising candidate due to its high energy density and the fact that it only produces water when burned. Governments, both at the national and international levels, have outlined ambitious roadmaps for green hydrogen production and utilization, as seen in the EU's REPowerEU package aligned with the EU Green Deal and Japan's "Basic H2 strategy." Two prominent importers of hydrogen, Japan and The Netherlands, have been actively involved in shaping the future of international green hydrogen supply chains (IGHSC).
However, as plans for IGHSC development gain momentum, so does the recognition of the need for resilient characteristics within these supply chains. They must be designed to withstand, adapt to, and recover from unexpected disruptions effectively. This research aims to address this need by developing a guideline for establishing a resilience design methodology specific to IGHSC, using Japan and The Netherlands as examples of significant future importers.
The primary research question guiding this thesis is: What guidelines can be established to design and maintain resilience within an international green hydrogen supply chain, with Japan and The Netherlands as exploratory importers?
The research approach combines extensive literature review, analysis, and interviews within a qualitative exploratory framework. A theoretical framework was constructed to uncover the interconnections between various theories and fields of study. This framework not only unveiled previously unnoticed associations but also elucidated the disruptions and resilience mechanisms inherent to IGHSC. Two novel optional IGHSC configurations were identified and introduced, and a comprehensive catalog of relevant disruptions, along with their respective domains, was created. Through a rigorous evaluation of existing research on disruptions and the enhancement of categorization schemes, this study developed a new structure for categorizing potential IGHSC disruptions systematically. These disruptions were categorized based on their potential domains of origin.
The concept of resilience was subsequently defined and categorized into two distinct phases and three scopes, providing a structured framework for designing and maintaining resilience within an IGHSC. Recognizing that the establishment of a global hydrogen economy is pivotal for achieving global net-zero goals, it becomes imperative to prioritize the design and maintenance of resilient IGHSC. This thesis presents a newly developed guideline that contributes to the design and maintenance of resilience within an IGHSC, serving as a crucial step towards realizing a sustainable and reliable global hydrogen economy.
However, as plans for IGHSC development gain momentum, so does the recognition of the need for resilient characteristics within these supply chains. They must be designed to withstand, adapt to, and recover from unexpected disruptions effectively. This research aims to address this need by developing a guideline for establishing a resilience design methodology specific to IGHSC, using Japan and The Netherlands as examples of significant future importers.
The primary research question guiding this thesis is: What guidelines can be established to design and maintain resilience within an international green hydrogen supply chain, with Japan and The Netherlands as exploratory importers?
The research approach combines extensive literature review, analysis, and interviews within a qualitative exploratory framework. A theoretical framework was constructed to uncover the interconnections between various theories and fields of study. This framework not only unveiled previously unnoticed associations but also elucidated the disruptions and resilience mechanisms inherent to IGHSC. Two novel optional IGHSC configurations were identified and introduced, and a comprehensive catalog of relevant disruptions, along with their respective domains, was created. Through a rigorous evaluation of existing research on disruptions and the enhancement of categorization schemes, this study developed a new structure for categorizing potential IGHSC disruptions systematically. These disruptions were categorized based on their potential domains of origin.
The concept of resilience was subsequently defined and categorized into two distinct phases and three scopes, providing a structured framework for designing and maintaining resilience within an IGHSC. Recognizing that the establishment of a global hydrogen economy is pivotal for achieving global net-zero goals, it becomes imperative to prioritize the design and maintenance of resilient IGHSC. This thesis presents a newly developed guideline that contributes to the design and maintenance of resilience within an IGHSC, serving as a crucial step towards realizing a sustainable and reliable global hydrogen economy.
This project aims to answer the question of how cross-plant safety can be improved in a general way, including the prevention of domino effects. The main research question is: How do we improve collaboration between companies in a chemical cluster, in so that an overall safety gain is achieved? From the literature review and the interviews a list of the main drivers and impediments have been created.
There are 10 drivers that drive cross-company collaboration on safety: (1) Economic benefits, (2) Reduction of safety and security risk, (3) Support of decision-making on the prevention of domino effects, (4) Improvement of efficiency in safety training, (5) Improvement of efficiency
of safety management, (6) Improvement of safety inspection and maintenance of infrastructure, facilities and services that are related to domino effect prevention, and a few more that are removed due to confidential matters.
Additionally ten impediments have been found that hamper collaboration on cluster safety: (1) Communication and information sharing impediment, (2) Knowledge gaps, (3) Mistrust among companies, (4) Collaboration costs, (5) Difference in interest, (6) Insufficient policy and legislation support, (7) Cluster risk identification and recognition gaps, (8) Confidential issues and restrictions from mother company, and a few more that are removed due to confidential matters.
The conventional QRA framework is not build for cluster-wide safety and could be improved. The improved QRA includes a loop for additional analysis of installations that are affected by escalations of other installations. Further research could be done in analysing the link between types of collaborations (sharing information, learning from each other, sharing facilities & equipment, etc.) and the drivers and impediments. ...
There are 10 drivers that drive cross-company collaboration on safety: (1) Economic benefits, (2) Reduction of safety and security risk, (3) Support of decision-making on the prevention of domino effects, (4) Improvement of efficiency in safety training, (5) Improvement of efficiency
of safety management, (6) Improvement of safety inspection and maintenance of infrastructure, facilities and services that are related to domino effect prevention, and a few more that are removed due to confidential matters.
Additionally ten impediments have been found that hamper collaboration on cluster safety: (1) Communication and information sharing impediment, (2) Knowledge gaps, (3) Mistrust among companies, (4) Collaboration costs, (5) Difference in interest, (6) Insufficient policy and legislation support, (7) Cluster risk identification and recognition gaps, (8) Confidential issues and restrictions from mother company, and a few more that are removed due to confidential matters.
The conventional QRA framework is not build for cluster-wide safety and could be improved. The improved QRA includes a loop for additional analysis of installations that are affected by escalations of other installations. Further research could be done in analysing the link between types of collaborations (sharing information, learning from each other, sharing facilities & equipment, etc.) and the drivers and impediments. ...
This project aims to answer the question of how cross-plant safety can be improved in a general way, including the prevention of domino effects. The main research question is: How do we improve collaboration between companies in a chemical cluster, in so that an overall safety gain is achieved? From the literature review and the interviews a list of the main drivers and impediments have been created.
There are 10 drivers that drive cross-company collaboration on safety: (1) Economic benefits, (2) Reduction of safety and security risk, (3) Support of decision-making on the prevention of domino effects, (4) Improvement of efficiency in safety training, (5) Improvement of efficiency
of safety management, (6) Improvement of safety inspection and maintenance of infrastructure, facilities and services that are related to domino effect prevention, and a few more that are removed due to confidential matters.
Additionally ten impediments have been found that hamper collaboration on cluster safety: (1) Communication and information sharing impediment, (2) Knowledge gaps, (3) Mistrust among companies, (4) Collaboration costs, (5) Difference in interest, (6) Insufficient policy and legislation support, (7) Cluster risk identification and recognition gaps, (8) Confidential issues and restrictions from mother company, and a few more that are removed due to confidential matters.
The conventional QRA framework is not build for cluster-wide safety and could be improved. The improved QRA includes a loop for additional analysis of installations that are affected by escalations of other installations. Further research could be done in analysing the link between types of collaborations (sharing information, learning from each other, sharing facilities & equipment, etc.) and the drivers and impediments.
There are 10 drivers that drive cross-company collaboration on safety: (1) Economic benefits, (2) Reduction of safety and security risk, (3) Support of decision-making on the prevention of domino effects, (4) Improvement of efficiency in safety training, (5) Improvement of efficiency
of safety management, (6) Improvement of safety inspection and maintenance of infrastructure, facilities and services that are related to domino effect prevention, and a few more that are removed due to confidential matters.
Additionally ten impediments have been found that hamper collaboration on cluster safety: (1) Communication and information sharing impediment, (2) Knowledge gaps, (3) Mistrust among companies, (4) Collaboration costs, (5) Difference in interest, (6) Insufficient policy and legislation support, (7) Cluster risk identification and recognition gaps, (8) Confidential issues and restrictions from mother company, and a few more that are removed due to confidential matters.
The conventional QRA framework is not build for cluster-wide safety and could be improved. The improved QRA includes a loop for additional analysis of installations that are affected by escalations of other installations. Further research could be done in analysing the link between types of collaborations (sharing information, learning from each other, sharing facilities & equipment, etc.) and the drivers and impediments.
The current EU member states have set targets to reduce annual greenhouse emissions for 2021-2030. Sixty per cent of EU emissions include sectors like buildings, agriculture, non-ETS industry and waste. Much research cannot be found to reduce emissions in the buildings, houses and community-based scenarios. Therefore, this research focuses on developing an innovative model to make the community a hundred percent reliant on renewable energy sources. Renewable energy produces power variably depending upon external conditions. At times, the variability of renewable energy cannot be fed into the power grid due to network constraints or low demand leading to curtailment of the energy or selling the energy at zero marginal price. Therefore, the curtailment of energy and its intermittency is the biggest barrier in delaying the transition towards a hundred per cent of renewable power into the power systems. Robust energy storage technology is required to integrate with an intelligent control system to increase the penetration of renewable energy into the energy mix. To meet this requirement, “Green Hydrogen” produced can contribute to energy security by providing another energy carrier with different supply chains, producers, and markets, diversifying the energy mix, and improving the system’s resilience. To produce hydrogen, power to hydrogen technology is an innovative solution, and a framework needs to be developed to integrate this technology in the community using Industry 4.0.
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The current EU member states have set targets to reduce annual greenhouse emissions for 2021-2030. Sixty per cent of EU emissions include sectors like buildings, agriculture, non-ETS industry and waste. Much research cannot be found to reduce emissions in the buildings, houses and community-based scenarios. Therefore, this research focuses on developing an innovative model to make the community a hundred percent reliant on renewable energy sources. Renewable energy produces power variably depending upon external conditions. At times, the variability of renewable energy cannot be fed into the power grid due to network constraints or low demand leading to curtailment of the energy or selling the energy at zero marginal price. Therefore, the curtailment of energy and its intermittency is the biggest barrier in delaying the transition towards a hundred per cent of renewable power into the power systems. Robust energy storage technology is required to integrate with an intelligent control system to increase the penetration of renewable energy into the energy mix. To meet this requirement, “Green Hydrogen” produced can contribute to energy security by providing another energy carrier with different supply chains, producers, and markets, diversifying the energy mix, and improving the system’s resilience. To produce hydrogen, power to hydrogen technology is an innovative solution, and a framework needs to be developed to integrate this technology in the community using Industry 4.0.
The term “Green Hydrogen Economy” has been prevalent in the global economies in recent years. Interest in hydrogen as an energy carrier has increased due to the global increase in air pollution, greenhouse gas emissions and increased energy demand. The Netherlands aspires to be a European leader in hydrogen deployment, as hydrogen is widely seen as critical to achieving the 2050 climate targets. Residential heating accounts for roughly 12% of total energy consumption in the Netherlands, with natural gas combustion accounting for 71% of this proportion. However, growing controversy about natural gas usage makes this resource less favourable due to the earthquakes caused by natural gas extraction in the Dutch gas fields. Additionally, the Netherlands has a robust gas infrastructure capable of transporting green hydrogen. Thus, green hydrogen might prove helpful in ensuring both flexibility and continuity in domestic energy demand.
The goal of this study was to explore possibilities and problems associated with the transition of the Dutch built environment to green hydrogen-powered dwellings. The shift from a natural gas-powered environment to a green hydrogen-powered environment is envisioned as a transition. This transition could be possible when there is alignment between the different levels of the society (niche, regime and landscape). The barriers and enablers with regard to the transition to a green hydrogen-powered environment have been discussed and the suggestions to overcome these have also been found. The Multi-Level Perspective was used to map the barriers and the suggestions on the three levels (niche, regime and landscape). This resulted in an approximate set of actions along with the required timeline and the actors who could work to overcome the barriers. The mapping of barriers and enablers according to the Multi Level Perspective shows a big divide between enablers and barriers. This divide has to be filled in for a smooth transition to green hydrogen. The uncertainties surrounding the energy transition in the built environment contributes to its complexity. Stakeholders are hesitant to support hydrogen energy applications in the built environment due to a lack of laws governing hydrogen usage in the built environment and significant gaps in the legislation impeding the transportation and manufacture of sufficient quantities of green hydrogen. ...
The goal of this study was to explore possibilities and problems associated with the transition of the Dutch built environment to green hydrogen-powered dwellings. The shift from a natural gas-powered environment to a green hydrogen-powered environment is envisioned as a transition. This transition could be possible when there is alignment between the different levels of the society (niche, regime and landscape). The barriers and enablers with regard to the transition to a green hydrogen-powered environment have been discussed and the suggestions to overcome these have also been found. The Multi-Level Perspective was used to map the barriers and the suggestions on the three levels (niche, regime and landscape). This resulted in an approximate set of actions along with the required timeline and the actors who could work to overcome the barriers. The mapping of barriers and enablers according to the Multi Level Perspective shows a big divide between enablers and barriers. This divide has to be filled in for a smooth transition to green hydrogen. The uncertainties surrounding the energy transition in the built environment contributes to its complexity. Stakeholders are hesitant to support hydrogen energy applications in the built environment due to a lack of laws governing hydrogen usage in the built environment and significant gaps in the legislation impeding the transportation and manufacture of sufficient quantities of green hydrogen. ...
The term “Green Hydrogen Economy” has been prevalent in the global economies in recent years. Interest in hydrogen as an energy carrier has increased due to the global increase in air pollution, greenhouse gas emissions and increased energy demand. The Netherlands aspires to be a European leader in hydrogen deployment, as hydrogen is widely seen as critical to achieving the 2050 climate targets. Residential heating accounts for roughly 12% of total energy consumption in the Netherlands, with natural gas combustion accounting for 71% of this proportion. However, growing controversy about natural gas usage makes this resource less favourable due to the earthquakes caused by natural gas extraction in the Dutch gas fields. Additionally, the Netherlands has a robust gas infrastructure capable of transporting green hydrogen. Thus, green hydrogen might prove helpful in ensuring both flexibility and continuity in domestic energy demand.
The goal of this study was to explore possibilities and problems associated with the transition of the Dutch built environment to green hydrogen-powered dwellings. The shift from a natural gas-powered environment to a green hydrogen-powered environment is envisioned as a transition. This transition could be possible when there is alignment between the different levels of the society (niche, regime and landscape). The barriers and enablers with regard to the transition to a green hydrogen-powered environment have been discussed and the suggestions to overcome these have also been found. The Multi-Level Perspective was used to map the barriers and the suggestions on the three levels (niche, regime and landscape). This resulted in an approximate set of actions along with the required timeline and the actors who could work to overcome the barriers. The mapping of barriers and enablers according to the Multi Level Perspective shows a big divide between enablers and barriers. This divide has to be filled in for a smooth transition to green hydrogen. The uncertainties surrounding the energy transition in the built environment contributes to its complexity. Stakeholders are hesitant to support hydrogen energy applications in the built environment due to a lack of laws governing hydrogen usage in the built environment and significant gaps in the legislation impeding the transportation and manufacture of sufficient quantities of green hydrogen.
The goal of this study was to explore possibilities and problems associated with the transition of the Dutch built environment to green hydrogen-powered dwellings. The shift from a natural gas-powered environment to a green hydrogen-powered environment is envisioned as a transition. This transition could be possible when there is alignment between the different levels of the society (niche, regime and landscape). The barriers and enablers with regard to the transition to a green hydrogen-powered environment have been discussed and the suggestions to overcome these have also been found. The Multi-Level Perspective was used to map the barriers and the suggestions on the three levels (niche, regime and landscape). This resulted in an approximate set of actions along with the required timeline and the actors who could work to overcome the barriers. The mapping of barriers and enablers according to the Multi Level Perspective shows a big divide between enablers and barriers. This divide has to be filled in for a smooth transition to green hydrogen. The uncertainties surrounding the energy transition in the built environment contributes to its complexity. Stakeholders are hesitant to support hydrogen energy applications in the built environment due to a lack of laws governing hydrogen usage in the built environment and significant gaps in the legislation impeding the transportation and manufacture of sufficient quantities of green hydrogen.