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G.A. van Nederveen
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1
The increasing digitization of the construction industry creates an urgent need for construction managers to be proficient in Building Information Modeling (BIM) and information systems. This paper investigates how to integrate these topics effectively into a broad and diverse Construction Management and Engineering (CME) master’s curriculum. This has led to a flexible educational model that balances theoretical grounding with hands-on project work. The findings show that while a single course can successfully raise awareness and introduce key concepts, students sometimes struggle with abstract modeling and data management topics. Nevertheless, the approach can indeed foster deeper engagement and inspire further exploration.
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The increasing digitization of the construction industry creates an urgent need for construction managers to be proficient in Building Information Modeling (BIM) and information systems. This paper investigates how to integrate these topics effectively into a broad and diverse Construction Management and Engineering (CME) master’s curriculum. This has led to a flexible educational model that balances theoretical grounding with hands-on project work. The findings show that while a single course can successfully raise awareness and introduce key concepts, students sometimes struggle with abstract modeling and data management topics. Nevertheless, the approach can indeed foster deeper engagement and inspire further exploration.
Journal article
(2025)
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Richie Maskam, Alireza Amiri-Simkooei, Sander Van Nederveen, Maarten Visser, Mohammad Fotouhi
Purpose – This study aims to automate the visual inspection of piling sheets in water channel construction using artificial intelligence (AI). By employing image classification and object detection techniques, the research focuses on extracting and analysing geometric features to enhance the accuracy and efficiency of the inspection process. It also addresses key challenges associated with the unique characteristics of construction materials and the limited variability of available inspection datasets. Design/methodology/approach – Convolutional neural networks (CNNs) with varying complexities are employed for image classification, across four and six classes, and for object detection of piling sheets in water channel environments. A dataset provided by Witteveen + Bos is preprocessed to generate training sets, and the CNN architectures are optimized for enhanced performance. The accuracy and efficiency of the proposed models are evaluated and compared against traditional manual inspection methods. Findings – The AI-driven approach significantly reduces processing time, evaluating 40, 000 images in just 11.9 h, compared to approximately one month using manual assessment. The 4-class classification model achieves an accuracy of 96%, while the 6-class model attains 72%. The object detection model produces a mean average precision (mAP) of 79%. These results meet the performance standards set by the Dutch company Witteveen + Bos, which demonstrate the effectiveness of AI in automating the inspection of piling sheets. Originality/value – This study introduces a novel AI-based approach for assessing piling sheets, demonstrating substantial improvements over traditional inspection methods. It introduces a systematic evaluation of various CNN architectures and hyperparameters to optimize the models specifically for piling sheet inspection rather than relying on off-the-shelf solutions. The use of CNNs for both image classification and object detection adheres to relevant Dutch engineering standards. Notably, the reduction in processing time, from one month to around 12 h, represents a major advancement in the efficiency of civil engineering inspections.
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Purpose – This study aims to automate the visual inspection of piling sheets in water channel construction using artificial intelligence (AI). By employing image classification and object detection techniques, the research focuses on extracting and analysing geometric features to enhance the accuracy and efficiency of the inspection process. It also addresses key challenges associated with the unique characteristics of construction materials and the limited variability of available inspection datasets. Design/methodology/approach – Convolutional neural networks (CNNs) with varying complexities are employed for image classification, across four and six classes, and for object detection of piling sheets in water channel environments. A dataset provided by Witteveen + Bos is preprocessed to generate training sets, and the CNN architectures are optimized for enhanced performance. The accuracy and efficiency of the proposed models are evaluated and compared against traditional manual inspection methods. Findings – The AI-driven approach significantly reduces processing time, evaluating 40, 000 images in just 11.9 h, compared to approximately one month using manual assessment. The 4-class classification model achieves an accuracy of 96%, while the 6-class model attains 72%. The object detection model produces a mean average precision (mAP) of 79%. These results meet the performance standards set by the Dutch company Witteveen + Bos, which demonstrate the effectiveness of AI in automating the inspection of piling sheets. Originality/value – This study introduces a novel AI-based approach for assessing piling sheets, demonstrating substantial improvements over traditional inspection methods. It introduces a systematic evaluation of various CNN architectures and hyperparameters to optimize the models specifically for piling sheet inspection rather than relying on off-the-shelf solutions. The use of CNNs for both image classification and object detection adheres to relevant Dutch engineering standards. Notably, the reduction in processing time, from one month to around 12 h, represents a major advancement in the efficiency of civil engineering inspections.
IMAP-WFO
A holistic optimization tool for bottom fixed offshore wind farm design and control
Offshore wind farms, critical for sustainable energy production, face the challenge of optimization among many parameters influencing key performance indicators in competitive ways. This research introduces the novel Integrative Maximized Aggregated Preference Wind Farm Optimization (IMAP-WFO) framework – a comprehensive tool designed to enhance flexibility, accuracy, and uncertainty quantification in offshore wind farm design and operation. Existing methods often fall short due to limitations in adaptability and precision, especially when modeling complex multi-physical behaviors under uncertain conditions. IMAP-WFO overcomes these limitations by combining advanced statistical techniques and simulation methods. At its core are parametric design performance functions, capturing critical aspects of wind farm behavior, including energy production, material usage, and structural fatigue. These functions rely on Kriging meta-models. To address inherent uncertainty, Monte Carlo simulations provide a probabilistic assessment of outcomes. IMAP-WFO's true innovation lies in translating technical functions into socio-economic objectives, including sustainability metrics, annual energy production, capital expenditure, operational expenditure, model uncertainty, and lifetime fatigue. Stakeholders can dynamically weigh these objectives based on their preferences. A validation process ensures the accuracy of design performance functions, comparing simulated results with real-world data. IMAP-WFO's application is demonstrated through case studies: optimizing the levelized cost of energy and exploring wind farm control strategies.
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Offshore wind farms, critical for sustainable energy production, face the challenge of optimization among many parameters influencing key performance indicators in competitive ways. This research introduces the novel Integrative Maximized Aggregated Preference Wind Farm Optimization (IMAP-WFO) framework – a comprehensive tool designed to enhance flexibility, accuracy, and uncertainty quantification in offshore wind farm design and operation. Existing methods often fall short due to limitations in adaptability and precision, especially when modeling complex multi-physical behaviors under uncertain conditions. IMAP-WFO overcomes these limitations by combining advanced statistical techniques and simulation methods. At its core are parametric design performance functions, capturing critical aspects of wind farm behavior, including energy production, material usage, and structural fatigue. These functions rely on Kriging meta-models. To address inherent uncertainty, Monte Carlo simulations provide a probabilistic assessment of outcomes. IMAP-WFO's true innovation lies in translating technical functions into socio-economic objectives, including sustainability metrics, annual energy production, capital expenditure, operational expenditure, model uncertainty, and lifetime fatigue. Stakeholders can dynamically weigh these objectives based on their preferences. A validation process ensures the accuracy of design performance functions, comparing simulated results with real-world data. IMAP-WFO's application is demonstrated through case studies: optimizing the levelized cost of energy and exploring wind farm control strategies.
Journal article
(2023)
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Marco van der Zwaag, Tong Wang, Hans Bakker, Sander van Nederveen, A. C.B. Schuurman, Douwe Bosma
Facing circular transition challenges, building circularity should be evaluated in the early design phase to reduce the risks of circular and environmental performance problems found in later project phases. However, due to the current design workflow, such practice is hindered because there is not enough information to evaluate building circularity in detail in the early design phases. An improved workflow to emphasize circularity more in the early design phase is thus needed. This research explores the current workflow and designs an improved workflow by developing an automated decision support system to assess early design phase building circularity with limited available information, aiming to improve the working efficiency and efficacy. This automated system helps in data-driven decision-making by integrating different data sources and presenting the calculated results interactively with business intelligence interfaces. The interfaces involve different types of evaluations based on the data availability in both schematic design and detail design sub-phases. It also visualizes the data quality and future scenarios. This system has been designed based on interviews and literature studies, and verified and validated with practitioners. This study serves as a starting point to rethink the workflow to improve circularity with currently available technology.
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Facing circular transition challenges, building circularity should be evaluated in the early design phase to reduce the risks of circular and environmental performance problems found in later project phases. However, due to the current design workflow, such practice is hindered because there is not enough information to evaluate building circularity in detail in the early design phases. An improved workflow to emphasize circularity more in the early design phase is thus needed. This research explores the current workflow and designs an improved workflow by developing an automated decision support system to assess early design phase building circularity with limited available information, aiming to improve the working efficiency and efficacy. This automated system helps in data-driven decision-making by integrating different data sources and presenting the calculated results interactively with business intelligence interfaces. The interfaces involve different types of evaluations based on the data availability in both schematic design and detail design sub-phases. It also visualizes the data quality and future scenarios. This system has been designed based on interviews and literature studies, and verified and validated with practitioners. This study serves as a starting point to rethink the workflow to improve circularity with currently available technology.
Building Information Models (BIM) should reflect all aspects and phases of the construction projects life cycle. However, in current contractor practices, a proliferation of different information systems has arisen, each of which in turn illuminates a different information model dimension (nD) for usually only one construction project management purpose. To solve this problem it seems obvious to build a unique overarching system based on a single prescribed data modelling structure. We argue that this attempt is unrealistic, will not serve industrial practitioners and has failed already several times. We propose to link BIM to the concept of Systems Integration (SI), to develop tailormade and integrative information systems for its intended multidimensional (nD) modelling and construction projects management purpose: i.e. a targeted BIMSI fit for nD purpose enhancing better construction projects management. In this paper this nD BIMSI concept is introduced and demonstrated by a number of grassroot projects, which have been developed and validated in close cooperation with the AEC industrial practice and construction management and (civil) engineering master student projects at TU Delft. An overview of these grass root development projects is provided. These projects show how the BIMSI concept improves construction project management in areas such as generative design, safety during construction, and AI applications for effective budgeting. The focus of these projects is not on extending or evaluating BIM knowledge and theory, but rather on transforming BIM concepts into integrative information systems to solve real life problems. Finally, a state of the art education concept developed at the TU Delft is presented to demonstrate its unique position in master education on information systems for the construction industry. This so-called Open Design Learning (ODL) education integrates the nD BIMSI concept to better prepare students for both industrial and R&D construction project management practices.
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Building Information Models (BIM) should reflect all aspects and phases of the construction projects life cycle. However, in current contractor practices, a proliferation of different information systems has arisen, each of which in turn illuminates a different information model dimension (nD) for usually only one construction project management purpose. To solve this problem it seems obvious to build a unique overarching system based on a single prescribed data modelling structure. We argue that this attempt is unrealistic, will not serve industrial practitioners and has failed already several times. We propose to link BIM to the concept of Systems Integration (SI), to develop tailormade and integrative information systems for its intended multidimensional (nD) modelling and construction projects management purpose: i.e. a targeted BIMSI fit for nD purpose enhancing better construction projects management. In this paper this nD BIMSI concept is introduced and demonstrated by a number of grassroot projects, which have been developed and validated in close cooperation with the AEC industrial practice and construction management and (civil) engineering master student projects at TU Delft. An overview of these grass root development projects is provided. These projects show how the BIMSI concept improves construction project management in areas such as generative design, safety during construction, and AI applications for effective budgeting. The focus of these projects is not on extending or evaluating BIM knowledge and theory, but rather on transforming BIM concepts into integrative information systems to solve real life problems. Finally, a state of the art education concept developed at the TU Delft is presented to demonstrate its unique position in master education on information systems for the construction industry. This so-called Open Design Learning (ODL) education integrates the nD BIMSI concept to better prepare students for both industrial and R&D construction project management practices.
Infrastructures are subjected to rapidly changing future developments. These future developments, in combination with the complex nature of infrastructure systems, involves assessing multiple variables and their underlying relations. It is hard for asset managers to incorporate this dynamic uncertainty and complexity in their long-term plans. Moreover, it is perceived as challenging to translate the effects from network-level interventions to operation level and thereby develop a shared policy for an infrastructure network in which all stakeholders are involved. Since infrastructures are the backbones of our economies, insight is required in the magnitude and time of occurrence of future developments in order to optimize asset performances. This study proposed a multivariate simulation approach, as a strategic decision-support tool. Insight was created in the challenges associated with the long-term planning within complex and dynamic infrastructure systems to implement interventions on a more substantial and informed basis.
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Infrastructures are subjected to rapidly changing future developments. These future developments, in combination with the complex nature of infrastructure systems, involves assessing multiple variables and their underlying relations. It is hard for asset managers to incorporate this dynamic uncertainty and complexity in their long-term plans. Moreover, it is perceived as challenging to translate the effects from network-level interventions to operation level and thereby develop a shared policy for an infrastructure network in which all stakeholders are involved. Since infrastructures are the backbones of our economies, insight is required in the magnitude and time of occurrence of future developments in order to optimize asset performances. This study proposed a multivariate simulation approach, as a strategic decision-support tool. Insight was created in the challenges associated with the long-term planning within complex and dynamic infrastructure systems to implement interventions on a more substantial and informed basis.
Journal article
(2019)
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M. Havelaar, W. Jaspers, Sander van Nederveen, Willem Auping, Rogier Wolfert
Infrastructure asset managers are challenged by rapid changes around the world such as urbanisation and climate change. They have to deal with multiple complex and dynamic infrastructure systems that can influence each other and that can be influenced by various uncertain factors. Traditional planning methods are not well suited to complex and dynamic infrastructure environments. However, there are various alternative methods that can be used. This paper presents a simulation model for adaptive long-term infrastructure planning. For this model, a combination of planning and simulation methods is used that can cope with complex and dynamic (infrastructure) environments (i.e. system dynamics, exploratory modelling and analysis and adaptive pathways). This methodology is illustrated with a case consisting of a road system and a lock system in the Netherlands. The approach should be tested further in other cases, but it shows promise in improving the support of infrastructure decision-making in a complex, dynamic and uncertain infrastructure environment.
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Infrastructure asset managers are challenged by rapid changes around the world such as urbanisation and climate change. They have to deal with multiple complex and dynamic infrastructure systems that can influence each other and that can be influenced by various uncertain factors. Traditional planning methods are not well suited to complex and dynamic infrastructure environments. However, there are various alternative methods that can be used. This paper presents a simulation model for adaptive long-term infrastructure planning. For this model, a combination of planning and simulation methods is used that can cope with complex and dynamic (infrastructure) environments (i.e. system dynamics, exploratory modelling and analysis and adaptive pathways). This methodology is illustrated with a case consisting of a road system and a lock system in the Netherlands. The approach should be tested further in other cases, but it shows promise in improving the support of infrastructure decision-making in a complex, dynamic and uncertain infrastructure environment.
Conference paper
(2019)
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Maria Gkoika, Jeroen Coenders, Rob Nijsse, Sander van Nederveen, Sander Pasterkamp, Arend Rutgers
This paper presents a novel approach to modelling and documenting design knowledge: to use parametric technology to explicitly store knowledge which exists in a group of people (such as a company), so that it can be reused over many projects and grow over time when more projects are designed. This approach has been applied and tested on a test case of common concrete viaducts. The outcome constitutes the first iteration of the development of a parametric viaduct design platform, aimed for architects and structural engineers. The motivation was to counter the fragmentation of the Architecture, Engineering & Construction (AEC) industry, where each discipline encapsulates different knowledge areas, which results in miscommunication and the loss of valuable information and time. The suggested methodology aims at combining the BIM principles [1] with the concepts of parametric and associative design, as well as visual programming [2] to develop a common design platform for the architect and the structural engineer. Such a platform ensures that both disciplines are working on the same design and merges their different knowledge areas into one model. The knowledge model evolves from a top-down UML diagram into a user-friendly, parametric platform for viaduct design implemented in Dynamo [3].
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This paper presents a novel approach to modelling and documenting design knowledge: to use parametric technology to explicitly store knowledge which exists in a group of people (such as a company), so that it can be reused over many projects and grow over time when more projects are designed. This approach has been applied and tested on a test case of common concrete viaducts. The outcome constitutes the first iteration of the development of a parametric viaduct design platform, aimed for architects and structural engineers. The motivation was to counter the fragmentation of the Architecture, Engineering & Construction (AEC) industry, where each discipline encapsulates different knowledge areas, which results in miscommunication and the loss of valuable information and time. The suggested methodology aims at combining the BIM principles [1] with the concepts of parametric and associative design, as well as visual programming [2] to develop a common design platform for the architect and the structural engineer. Such a platform ensures that both disciplines are working on the same design and merges their different knowledge areas into one model. The knowledge model evolves from a top-down UML diagram into a user-friendly, parametric platform for viaduct design implemented in Dynamo [3].
BIM (building information modeling) can be the basis for carrying out various performance analyses. Sustainable infrastructure rating systems are suitable tools for assessing an infrastructure’s environmental performance. It is necessary to integrate them in the design process. The research adopted a thorough literature review to follow the development trends, interviews with professionals from the academia and industry, and a critical analysis of technical requirements for integrating BIM tools and infrastructure sustainability rating systems in the design process. This study propagates a conceptual framework for integrating sustainability rating systems by introducing BIM with a sustainability metric plug-in. The adoption of the proposed solution allows for what-if scenarios to better support the incorporation of sustainability into design decisions and the assessment of sustainability at the design phase of the infrastructure project. The framework is used to refine designs and ensure that sustainable goals are met and to demonstrate compliance with regulatory requirements. This paper concludes that greater emphasis should be placed on supporting technical requirements to facilitate the integration of BIM and sustainability rating systems. It defines the possibility of BIM adoption to influence the sustainable project performance in the infrastructure. This framework could streamline the sustainable design process and lead to more integrated infrastructure delivery.
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BIM (building information modeling) can be the basis for carrying out various performance analyses. Sustainable infrastructure rating systems are suitable tools for assessing an infrastructure’s environmental performance. It is necessary to integrate them in the design process. The research adopted a thorough literature review to follow the development trends, interviews with professionals from the academia and industry, and a critical analysis of technical requirements for integrating BIM tools and infrastructure sustainability rating systems in the design process. This study propagates a conceptual framework for integrating sustainability rating systems by introducing BIM with a sustainability metric plug-in. The adoption of the proposed solution allows for what-if scenarios to better support the incorporation of sustainability into design decisions and the assessment of sustainability at the design phase of the infrastructure project. The framework is used to refine designs and ensure that sustainable goals are met and to demonstrate compliance with regulatory requirements. This paper concludes that greater emphasis should be placed on supporting technical requirements to facilitate the integration of BIM and sustainability rating systems. It defines the possibility of BIM adoption to influence the sustainable project performance in the infrastructure. This framework could streamline the sustainable design process and lead to more integrated infrastructure delivery.
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Conference paper
(2017)
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Bart Luiten, Michel Böhms, Aonghus O’Keeffe, Sander van Nederveen, Jaap Bakker, Lars Wikström
This paper evaluates experiences with applying a linked data approach for coping with the many challenges for information management in asset management from the perspective of National Road Authorities (NRAs). As influential players, NRAs are often the initiators of innovation in the civil infrastructure sector. In this paper we focus on specifying the information standards applied by NRAs, using a hybrid, semantically enhanced linked data approach. The linked data approach originates from the World Wide Web Consortium and can be used for modelling, storing, linking and retrieving road data; integrating existing asset management software applications and giving rise to new innovative software functionalities. It is called a ‘hybrid’ approach because it also incorporates and reuses existing non-linked data information standards originating from the worlds of Building Information Modelling (BIM), Geospatial Information Systems (GIS) and Systems Engineering (SE).
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This paper evaluates experiences with applying a linked data approach for coping with the many challenges for information management in asset management from the perspective of National Road Authorities (NRAs). As influential players, NRAs are often the initiators of innovation in the civil infrastructure sector. In this paper we focus on specifying the information standards applied by NRAs, using a hybrid, semantically enhanced linked data approach. The linked data approach originates from the World Wide Web Consortium and can be used for modelling, storing, linking and retrieving road data; integrating existing asset management software applications and giving rise to new innovative software functionalities. It is called a ‘hybrid’ approach because it also incorporates and reuses existing non-linked data information standards originating from the worlds of Building Information Modelling (BIM), Geospatial Information Systems (GIS) and Systems Engineering (SE).
Understanding effects of BIM on collaborative design and construction
An empirical study in China
In construction projects, Building Information Modeling (BIM) influences on the common way of collaboration, including the roles of different participants. The goal of this research is to explore current practices and identify the critical effects of BIM on collaborative design and construction. Through a focus group discussion and interviews with BIM related participants, we explored project professions' understandings of BIM implementation on collaborative design and construction and adopted the grounded theory to analyze the qualitative data. Eight concepts influencing the development of BIM collaboration are identified and classified: (1) IT capacity, (2) technology management, (3) attitude and behavior, (4) role-taking, (5) trust, (6) communication, (7) leadership, (8) learning and experience. We discussed the taxonomy of BIM effects into three dimensions: technology, people and process. Our findings provide empirical insights into the collaborative nature of BIM construction projects and highlight the importance of collaboration within project teams in BIM project delivery.
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In construction projects, Building Information Modeling (BIM) influences on the common way of collaboration, including the roles of different participants. The goal of this research is to explore current practices and identify the critical effects of BIM on collaborative design and construction. Through a focus group discussion and interviews with BIM related participants, we explored project professions' understandings of BIM implementation on collaborative design and construction and adopted the grounded theory to analyze the qualitative data. Eight concepts influencing the development of BIM collaboration are identified and classified: (1) IT capacity, (2) technology management, (3) attitude and behavior, (4) role-taking, (5) trust, (6) communication, (7) leadership, (8) learning and experience. We discussed the taxonomy of BIM effects into three dimensions: technology, people and process. Our findings provide empirical insights into the collaborative nature of BIM construction projects and highlight the importance of collaboration within project teams in BIM project delivery.
In principle, Building Information Modelling (BIM) should provide a basis for infrastructure information management during the whole life-cycle. In practice however, the use of BIM is normally limited to the design and construction phases. It seems that the use of BIM information in other life-cycle stages requires significant changes in the way BIM models are developed. In order to explore this issue, three different approaches for integration of BIM and life cycle information management are discussed, illustrated by three projects: London Crossrail, the EU-project V-Con and an experimental project at Volker.
...
In principle, Building Information Modelling (BIM) should provide a basis for infrastructure information management during the whole life-cycle. In practice however, the use of BIM is normally limited to the design and construction phases. It seems that the use of BIM information in other life-cycle stages requires significant changes in the way BIM models are developed. In order to explore this issue, three different approaches for integration of BIM and life cycle information management are discussed, illustrated by three projects: London Crossrail, the EU-project V-Con and an experimental project at Volker.