S.M.J.G. Erkens
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1
Road networks are a cornerstone of transportation infrastructure, yet their long-term performance is severely challenged by a complex phenomenon known as aging. The aging of bituminous binders, a key component of asphalt pavements, leads to a progressive loss of flexibility and durability, resulting in premature cracking and expensive maintenance. Existing laboratory aging protocols often fail to accurately replicate real-world conditions, creating a significant gap between simulated and actual pavement performance. This discrepancy complicates the development of more durable and sustainable paving materials.
The central objective of this thesis is to address this gap by developing a robust, data-driven methodology to establish field-validated laboratory aging protocols for paving binders. To achieve this, the research was guided by four key questions: investigating the chemo-rheological effects of diverse environmental factors, developing a novel accelerated aging protocol, employing multivariate and machine learning methods to integrate data, and optimizing data pre-processing for spectral analysis.... ...
The central objective of this thesis is to address this gap by developing a robust, data-driven methodology to establish field-validated laboratory aging protocols for paving binders. To achieve this, the research was guided by four key questions: investigating the chemo-rheological effects of diverse environmental factors, developing a novel accelerated aging protocol, employing multivariate and machine learning methods to integrate data, and optimizing data pre-processing for spectral analysis.... ...
Road networks are a cornerstone of transportation infrastructure, yet their long-term performance is severely challenged by a complex phenomenon known as aging. The aging of bituminous binders, a key component of asphalt pavements, leads to a progressive loss of flexibility and durability, resulting in premature cracking and expensive maintenance. Existing laboratory aging protocols often fail to accurately replicate real-world conditions, creating a significant gap between simulated and actual pavement performance. This discrepancy complicates the development of more durable and sustainable paving materials.
The central objective of this thesis is to address this gap by developing a robust, data-driven methodology to establish field-validated laboratory aging protocols for paving binders. To achieve this, the research was guided by four key questions: investigating the chemo-rheological effects of diverse environmental factors, developing a novel accelerated aging protocol, employing multivariate and machine learning methods to integrate data, and optimizing data pre-processing for spectral analysis....
The central objective of this thesis is to address this gap by developing a robust, data-driven methodology to establish field-validated laboratory aging protocols for paving binders. To achieve this, the research was guided by four key questions: investigating the chemo-rheological effects of diverse environmental factors, developing a novel accelerated aging protocol, employing multivariate and machine learning methods to integrate data, and optimizing data pre-processing for spectral analysis....
A Multiscale Framework for Predicting Bituminous Material Behaviour
Integrating Multiphysics Modelling, Finite Element Analysis and Machine Learning
Asphalt pavements carry the weight of modern transportation infrastructure, yet their complex behavior remains incompletely understood. These materials operate across a remarkable range of scales—from nanoscale molecular interactions in bitumen to microscale aggregate bonding and macroscale pavement performance. The hierarchical nature of bituminous materials, spanning from SARA fractions (Saturates, Aromatics, Resins, Asphaltenes) at the molecular level through mastic and mortar to complete mixtures, creates intricate relationships that traditional single-scale approaches fail to capture adequately. Understanding how these materials age, degrade, and ultimately fail under real-world conditions requires a fundamentally new approach that bridges multiple scales and physics domains.
This research introduces a multiscale and multiphysics framework that advances how we understand and predict bituminous mixture behavior. The integration of finite element methods (FEM), machine learning (ML), and physics-informed neural networks (PINNs) creates connections between material chemistry and mechanical performance across the complete hierarchical structure. The approach addresses several critical challenges that have long hindered pavement engineering: the complexity of cross-scale interactions, the separation of chemical aging from mechanical response, and the difficulty of identifying hidden relationships in high-dimensional material data.
At the heart of this framework lies a coupling of chemical aging processes with mechanical degradation. This work quantitatively links chemical aging—tracked through carbonyl area evolution—to mechanical property changes across multiple scales. The temporal gap between long-term chemical transformations and short-term mechanical responses is bridged through this approach, capturing how oxidative aging fundamentally alters material behavior over a pavement’s service life. This chemical-mechanical coupling is implemented through an enhanced Maxwell model that incorporates aging effects directly into the constitutive framework, validated against experimental data to ensure reliability in real-world applications.
The framework leverages advanced machine learning techniques to unlock hidden patterns in both experimental and numerical data, revealing critical relationships between material composition, environmental conditions, and performance metrics. A bidirectional neural network serves dual purposes: the forward model predicts rheological behavior from chemical composition and environmental conditions, while the inverse model determines optimal SARA fractions required to achieve specific performance targets. This data-driven discovery approach identifies previously unknown correlations that traditional analytical methods might miss, enabling more informed material design and optimization strategies.
The multiphysics integration couples temperature effects, oxygen diffusion, and carbonyl area into a unified computational environment. The framework establishes quantitative links between nanoscale molecular structure and macroscale pavement performance, revealing how aggregate morphology, filler characteristics, and void distribution collectively govern mixture behavior. The thesis develops this framework through seven interconnected chapters, beginning with multiscale mechanical modeling at binder, mastic, and mixture scales, advancing through aging prediction using physics-informed neural networks, progressing to chemical-mechanical coupling implementation, and culminating in machine learning-driven optimization and inverse design.
Each component builds toward a comprehensive understanding of bituminous materials that transforms theoretical insights into practical engineering applications, providing both deep scientific understanding and actionable design tools validated against experimental data. As infrastructure faces increasing demands from environmental change and sustainability imperatives, this integrated framework provides the scientific foundation needed to design pavements that are not just durable, but optimized for their specific conditions. The research bridges fundamental materials science with applied engineering, offering a transformative approach to understanding and predicting the behavior of one of the world’s most widely used construction materials.
...
This research introduces a multiscale and multiphysics framework that advances how we understand and predict bituminous mixture behavior. The integration of finite element methods (FEM), machine learning (ML), and physics-informed neural networks (PINNs) creates connections between material chemistry and mechanical performance across the complete hierarchical structure. The approach addresses several critical challenges that have long hindered pavement engineering: the complexity of cross-scale interactions, the separation of chemical aging from mechanical response, and the difficulty of identifying hidden relationships in high-dimensional material data.
At the heart of this framework lies a coupling of chemical aging processes with mechanical degradation. This work quantitatively links chemical aging—tracked through carbonyl area evolution—to mechanical property changes across multiple scales. The temporal gap between long-term chemical transformations and short-term mechanical responses is bridged through this approach, capturing how oxidative aging fundamentally alters material behavior over a pavement’s service life. This chemical-mechanical coupling is implemented through an enhanced Maxwell model that incorporates aging effects directly into the constitutive framework, validated against experimental data to ensure reliability in real-world applications.
The framework leverages advanced machine learning techniques to unlock hidden patterns in both experimental and numerical data, revealing critical relationships between material composition, environmental conditions, and performance metrics. A bidirectional neural network serves dual purposes: the forward model predicts rheological behavior from chemical composition and environmental conditions, while the inverse model determines optimal SARA fractions required to achieve specific performance targets. This data-driven discovery approach identifies previously unknown correlations that traditional analytical methods might miss, enabling more informed material design and optimization strategies.
The multiphysics integration couples temperature effects, oxygen diffusion, and carbonyl area into a unified computational environment. The framework establishes quantitative links between nanoscale molecular structure and macroscale pavement performance, revealing how aggregate morphology, filler characteristics, and void distribution collectively govern mixture behavior. The thesis develops this framework through seven interconnected chapters, beginning with multiscale mechanical modeling at binder, mastic, and mixture scales, advancing through aging prediction using physics-informed neural networks, progressing to chemical-mechanical coupling implementation, and culminating in machine learning-driven optimization and inverse design.
Each component builds toward a comprehensive understanding of bituminous materials that transforms theoretical insights into practical engineering applications, providing both deep scientific understanding and actionable design tools validated against experimental data. As infrastructure faces increasing demands from environmental change and sustainability imperatives, this integrated framework provides the scientific foundation needed to design pavements that are not just durable, but optimized for their specific conditions. The research bridges fundamental materials science with applied engineering, offering a transformative approach to understanding and predicting the behavior of one of the world’s most widely used construction materials.
...
Asphalt pavements carry the weight of modern transportation infrastructure, yet their complex behavior remains incompletely understood. These materials operate across a remarkable range of scales—from nanoscale molecular interactions in bitumen to microscale aggregate bonding and macroscale pavement performance. The hierarchical nature of bituminous materials, spanning from SARA fractions (Saturates, Aromatics, Resins, Asphaltenes) at the molecular level through mastic and mortar to complete mixtures, creates intricate relationships that traditional single-scale approaches fail to capture adequately. Understanding how these materials age, degrade, and ultimately fail under real-world conditions requires a fundamentally new approach that bridges multiple scales and physics domains.
This research introduces a multiscale and multiphysics framework that advances how we understand and predict bituminous mixture behavior. The integration of finite element methods (FEM), machine learning (ML), and physics-informed neural networks (PINNs) creates connections between material chemistry and mechanical performance across the complete hierarchical structure. The approach addresses several critical challenges that have long hindered pavement engineering: the complexity of cross-scale interactions, the separation of chemical aging from mechanical response, and the difficulty of identifying hidden relationships in high-dimensional material data.
At the heart of this framework lies a coupling of chemical aging processes with mechanical degradation. This work quantitatively links chemical aging—tracked through carbonyl area evolution—to mechanical property changes across multiple scales. The temporal gap between long-term chemical transformations and short-term mechanical responses is bridged through this approach, capturing how oxidative aging fundamentally alters material behavior over a pavement’s service life. This chemical-mechanical coupling is implemented through an enhanced Maxwell model that incorporates aging effects directly into the constitutive framework, validated against experimental data to ensure reliability in real-world applications.
The framework leverages advanced machine learning techniques to unlock hidden patterns in both experimental and numerical data, revealing critical relationships between material composition, environmental conditions, and performance metrics. A bidirectional neural network serves dual purposes: the forward model predicts rheological behavior from chemical composition and environmental conditions, while the inverse model determines optimal SARA fractions required to achieve specific performance targets. This data-driven discovery approach identifies previously unknown correlations that traditional analytical methods might miss, enabling more informed material design and optimization strategies.
The multiphysics integration couples temperature effects, oxygen diffusion, and carbonyl area into a unified computational environment. The framework establishes quantitative links between nanoscale molecular structure and macroscale pavement performance, revealing how aggregate morphology, filler characteristics, and void distribution collectively govern mixture behavior. The thesis develops this framework through seven interconnected chapters, beginning with multiscale mechanical modeling at binder, mastic, and mixture scales, advancing through aging prediction using physics-informed neural networks, progressing to chemical-mechanical coupling implementation, and culminating in machine learning-driven optimization and inverse design.
Each component builds toward a comprehensive understanding of bituminous materials that transforms theoretical insights into practical engineering applications, providing both deep scientific understanding and actionable design tools validated against experimental data. As infrastructure faces increasing demands from environmental change and sustainability imperatives, this integrated framework provides the scientific foundation needed to design pavements that are not just durable, but optimized for their specific conditions. The research bridges fundamental materials science with applied engineering, offering a transformative approach to understanding and predicting the behavior of one of the world’s most widely used construction materials.
This research introduces a multiscale and multiphysics framework that advances how we understand and predict bituminous mixture behavior. The integration of finite element methods (FEM), machine learning (ML), and physics-informed neural networks (PINNs) creates connections between material chemistry and mechanical performance across the complete hierarchical structure. The approach addresses several critical challenges that have long hindered pavement engineering: the complexity of cross-scale interactions, the separation of chemical aging from mechanical response, and the difficulty of identifying hidden relationships in high-dimensional material data.
At the heart of this framework lies a coupling of chemical aging processes with mechanical degradation. This work quantitatively links chemical aging—tracked through carbonyl area evolution—to mechanical property changes across multiple scales. The temporal gap between long-term chemical transformations and short-term mechanical responses is bridged through this approach, capturing how oxidative aging fundamentally alters material behavior over a pavement’s service life. This chemical-mechanical coupling is implemented through an enhanced Maxwell model that incorporates aging effects directly into the constitutive framework, validated against experimental data to ensure reliability in real-world applications.
The framework leverages advanced machine learning techniques to unlock hidden patterns in both experimental and numerical data, revealing critical relationships between material composition, environmental conditions, and performance metrics. A bidirectional neural network serves dual purposes: the forward model predicts rheological behavior from chemical composition and environmental conditions, while the inverse model determines optimal SARA fractions required to achieve specific performance targets. This data-driven discovery approach identifies previously unknown correlations that traditional analytical methods might miss, enabling more informed material design and optimization strategies.
The multiphysics integration couples temperature effects, oxygen diffusion, and carbonyl area into a unified computational environment. The framework establishes quantitative links between nanoscale molecular structure and macroscale pavement performance, revealing how aggregate morphology, filler characteristics, and void distribution collectively govern mixture behavior. The thesis develops this framework through seven interconnected chapters, beginning with multiscale mechanical modeling at binder, mastic, and mixture scales, advancing through aging prediction using physics-informed neural networks, progressing to chemical-mechanical coupling implementation, and culminating in machine learning-driven optimization and inverse design.
Each component builds toward a comprehensive understanding of bituminous materials that transforms theoretical insights into practical engineering applications, providing both deep scientific understanding and actionable design tools validated against experimental data. As infrastructure faces increasing demands from environmental change and sustainability imperatives, this integrated framework provides the scientific foundation needed to design pavements that are not just durable, but optimized for their specific conditions. The research bridges fundamental materials science with applied engineering, offering a transformative approach to understanding and predicting the behavior of one of the world’s most widely used construction materials.
Heavy petroleum streams such as heavy crudes, residues, and bitumen support modern energy and infrastructure, yet their properties vary strongly with composition, temperature, and chemical history. Because these materials consist of chemically diverse and evolving molecular populations rather than well-defined compounds, conventional structure–property correlations often lack robustness.
This dissertation develops a composition-based structure–property framework that combines Molecular Dynamics simulations with neural-network surrogate models to predict thermophysical and mechanical properties directly from molecular descriptors and temperature.
By enabling near-instantaneous property screening, comparison, and optimization of candidate formulations, the resulting draw-and-predict workflow enhances engineering design, accelerating the development of advanced hydrocarbon materials for next-generation energy and infrastructure systems. ...
This dissertation develops a composition-based structure–property framework that combines Molecular Dynamics simulations with neural-network surrogate models to predict thermophysical and mechanical properties directly from molecular descriptors and temperature.
By enabling near-instantaneous property screening, comparison, and optimization of candidate formulations, the resulting draw-and-predict workflow enhances engineering design, accelerating the development of advanced hydrocarbon materials for next-generation energy and infrastructure systems. ...
Heavy petroleum streams such as heavy crudes, residues, and bitumen support modern energy and infrastructure, yet their properties vary strongly with composition, temperature, and chemical history. Because these materials consist of chemically diverse and evolving molecular populations rather than well-defined compounds, conventional structure–property correlations often lack robustness.
This dissertation develops a composition-based structure–property framework that combines Molecular Dynamics simulations with neural-network surrogate models to predict thermophysical and mechanical properties directly from molecular descriptors and temperature.
By enabling near-instantaneous property screening, comparison, and optimization of candidate formulations, the resulting draw-and-predict workflow enhances engineering design, accelerating the development of advanced hydrocarbon materials for next-generation energy and infrastructure systems.
This dissertation develops a composition-based structure–property framework that combines Molecular Dynamics simulations with neural-network surrogate models to predict thermophysical and mechanical properties directly from molecular descriptors and temperature.
By enabling near-instantaneous property screening, comparison, and optimization of candidate formulations, the resulting draw-and-predict workflow enhances engineering design, accelerating the development of advanced hydrocarbon materials for next-generation energy and infrastructure systems.
Healing in Bitumen
Towards a pragmatic approach to quantify healing ability in asphalt binders
The primary objective of this research was therefore to improve the fundamental understanding of healing in bitumen and to develop a reliable test method capable of assessing the healing performance of both traditional and innovative asphalt binders.
The research includes a comprehensive review of the state of the art, revealing that healing in asphalt is difficult to quantify due to ongoing debate regarding the definition and measurement of damage. Many existing tests focus on damage restoration without a well-defined initial damage state, contributing to highly test-dependent and inconsistent healing results. The literature also indicates that there is a conceptual healing model derived from polymer science which is widely accepted. However, it level of detail and validation is limited for bituminous materials.
To address these shortcomings, a novel two-piece healing test was developed using a Dynamic Shear Rheometer in tensile mode. This setup enables precise control of parameters governing contact development like normal force at the healing interface, temperature and healing duration. The use of an artificial damage at the start of a healing period ensures a known damage level, allowing for a clearer view on the healed performance. The set-up can address wide range of healing periods, ranging from 12 seconds to more than a week, allowing for detailed investigation of both short- and long-term healing behaviour.
Experimental results demonstrate that at least half of strength restoration originates from adhesion at the healing interface, emphasizing the importance of contact formation and interfacial stresses during healing. Healing was found to occur rapidly, with a substantial portion of recovery taking place within the first few minutes. This observation, combined with the short rest periods typical of heavily trafficked road networks, suggests that short-duration healing tests may capture the most relevant aspects of healing in practice. However, the finding that toughness recovers more slowly than strength highlights potential implications for fatigue performance and warrants further investigation.
The existing healing model was extended by incorporating normal force, surface roughness, and surface energy as governing parameters. Overall, this research advances the understanding of binder healing, underscores the dominant role of adhesion, and provides a foundation for developing practical, predictive healing tests that support sustainable pavement design.
...
The research includes a comprehensive review of the state of the art, revealing that healing in asphalt is difficult to quantify due to ongoing debate regarding the definition and measurement of damage. Many existing tests focus on damage restoration without a well-defined initial damage state, contributing to highly test-dependent and inconsistent healing results. The literature also indicates that there is a conceptual healing model derived from polymer science which is widely accepted. However, it level of detail and validation is limited for bituminous materials.
To address these shortcomings, a novel two-piece healing test was developed using a Dynamic Shear Rheometer in tensile mode. This setup enables precise control of parameters governing contact development like normal force at the healing interface, temperature and healing duration. The use of an artificial damage at the start of a healing period ensures a known damage level, allowing for a clearer view on the healed performance. The set-up can address wide range of healing periods, ranging from 12 seconds to more than a week, allowing for detailed investigation of both short- and long-term healing behaviour.
Experimental results demonstrate that at least half of strength restoration originates from adhesion at the healing interface, emphasizing the importance of contact formation and interfacial stresses during healing. Healing was found to occur rapidly, with a substantial portion of recovery taking place within the first few minutes. This observation, combined with the short rest periods typical of heavily trafficked road networks, suggests that short-duration healing tests may capture the most relevant aspects of healing in practice. However, the finding that toughness recovers more slowly than strength highlights potential implications for fatigue performance and warrants further investigation.
The existing healing model was extended by incorporating normal force, surface roughness, and surface energy as governing parameters. Overall, this research advances the understanding of binder healing, underscores the dominant role of adhesion, and provides a foundation for developing practical, predictive healing tests that support sustainable pavement design.
...
The primary objective of this research was therefore to improve the fundamental understanding of healing in bitumen and to develop a reliable test method capable of assessing the healing performance of both traditional and innovative asphalt binders.
The research includes a comprehensive review of the state of the art, revealing that healing in asphalt is difficult to quantify due to ongoing debate regarding the definition and measurement of damage. Many existing tests focus on damage restoration without a well-defined initial damage state, contributing to highly test-dependent and inconsistent healing results. The literature also indicates that there is a conceptual healing model derived from polymer science which is widely accepted. However, it level of detail and validation is limited for bituminous materials.
To address these shortcomings, a novel two-piece healing test was developed using a Dynamic Shear Rheometer in tensile mode. This setup enables precise control of parameters governing contact development like normal force at the healing interface, temperature and healing duration. The use of an artificial damage at the start of a healing period ensures a known damage level, allowing for a clearer view on the healed performance. The set-up can address wide range of healing periods, ranging from 12 seconds to more than a week, allowing for detailed investigation of both short- and long-term healing behaviour.
Experimental results demonstrate that at least half of strength restoration originates from adhesion at the healing interface, emphasizing the importance of contact formation and interfacial stresses during healing. Healing was found to occur rapidly, with a substantial portion of recovery taking place within the first few minutes. This observation, combined with the short rest periods typical of heavily trafficked road networks, suggests that short-duration healing tests may capture the most relevant aspects of healing in practice. However, the finding that toughness recovers more slowly than strength highlights potential implications for fatigue performance and warrants further investigation.
The existing healing model was extended by incorporating normal force, surface roughness, and surface energy as governing parameters. Overall, this research advances the understanding of binder healing, underscores the dominant role of adhesion, and provides a foundation for developing practical, predictive healing tests that support sustainable pavement design.
The research includes a comprehensive review of the state of the art, revealing that healing in asphalt is difficult to quantify due to ongoing debate regarding the definition and measurement of damage. Many existing tests focus on damage restoration without a well-defined initial damage state, contributing to highly test-dependent and inconsistent healing results. The literature also indicates that there is a conceptual healing model derived from polymer science which is widely accepted. However, it level of detail and validation is limited for bituminous materials.
To address these shortcomings, a novel two-piece healing test was developed using a Dynamic Shear Rheometer in tensile mode. This setup enables precise control of parameters governing contact development like normal force at the healing interface, temperature and healing duration. The use of an artificial damage at the start of a healing period ensures a known damage level, allowing for a clearer view on the healed performance. The set-up can address wide range of healing periods, ranging from 12 seconds to more than a week, allowing for detailed investigation of both short- and long-term healing behaviour.
Experimental results demonstrate that at least half of strength restoration originates from adhesion at the healing interface, emphasizing the importance of contact formation and interfacial stresses during healing. Healing was found to occur rapidly, with a substantial portion of recovery taking place within the first few minutes. This observation, combined with the short rest periods typical of heavily trafficked road networks, suggests that short-duration healing tests may capture the most relevant aspects of healing in practice. However, the finding that toughness recovers more slowly than strength highlights potential implications for fatigue performance and warrants further investigation.
The existing healing model was extended by incorporating normal force, surface roughness, and surface energy as governing parameters. Overall, this research advances the understanding of binder healing, underscores the dominant role of adhesion, and provides a foundation for developing practical, predictive healing tests that support sustainable pavement design.
Interactions of moisture and oxidative ageing mechanisms in paving binders
Towards improving durability of pavements
Extensive transportation infrastructure is crucial for enabling efficient transportation and fostering economic development. However, the operation of roadways contributes to escalating environmental and societal issues, including noise pollution and carbon emissions. To achieve a balance between economy, environment, and society, growing focus is being placed on enhancing the durability and sustainability of asphalt pavement in all aspects. A pivotal factor contributing to the deterioration of asphalt pavement performance is the degradation of bitumen properties, significantly affected traffic and climate conditions. The latter is primarily related to two key processes: oxidative aging and moisture in bitumen. Extensive studies have been undertaken to investigate the moisture and ageing behavior while large variations have been reported due to the complexity of these behavior, the diversity of bitumen types, and the variability of environmental conditions. Such discrepancies complicate the formulation of bituminous binders and mixtures that mitigates these issues.
The objectives of this thesis are centered on gaining a thorough understanding of the mechanisms behind moisture and ageing behavior in bitumen, working towards a fully coupled moisture and ageing behavior in bitumen and their impact on bituminous materials. To figure out the complex moisture and aging effects in bitumen, it is essential to initiate from a simpler scenario without involving too many variables and then gradually take into consideration more factors affecting the moisture and ageing processes.
Guided by this principle, the moisture diffusion behavior in bitumen and its effects on bitumen properties are initially investigated. To obtain fundamental insights into the moisture mechanisms, both experiments and molecular dynamics simulations are conducted for mutual interpretation and corroboration. Results show that the moisture in bitumen consists of three states: free water characterized by a constant diffusion coefficient and a saturated concentration, immobile water bonded to polar functional groups
with a maximum concentration dependent on the number of these available groups, and water clusters, whose diffusion coefficient is significantly lower compared to free water and varies with cluster size.
The effects of ageing on the physicochemical and rheological properties of bitumen derived from diverse crude oil sources are evaluated and the physicochemicalrheological relationship is elucidated. The direct analysis of specific parameters and the chemometric analysis of full curves obtained from various chemical, physical, and rheological tests are combined for more accurate and extensive characterization. Results provide new insights into the chemo-mechanical relationship of bitumen, demonstrate the high capability of comprehensive information embedded in FTIR spectra and GPC curve in characterizing various rheological properties, and guide the selection of key physicochemical and rheological parameters for the evaluation of bitumen degradation. To characterize the impact of ageing on the moisture diffusion behavior in bitumen including moisture diffusion coefficient and absorption amount, the moisture transport in aged bitumen is measured through dynamic vapor sorption. The key factors determining moisture diffusion coefficient and moisture absorption are fractional free volume and polarity of bitumen. The changes of these two factors with increasing ageing level integratedly lead to increased activation energy for the diffusion of free water and reduced enthalpy of its adsorption. Simultaneously, the ageing kinetics of bitumen films are affected by the presence of moisture. The presence of moisture can inhibit oxidative reaction through the competitive diffusion between oxygen and moisture while the removal of moisture accelerates it due to additional diffusing pathways created by the diffusion of water molecules, especially water clusters.
In conclusion, this thesis provides in-depth insights into the understanding and evaluation of moisture diffusion and oxidative reaction in bitumen, as well as their respective effects on bitumen properties. The effects of moisture on the ageing process and that of ageing on the moisture behavior elucidated in this thesis establish a robust foundation for the modelling of fully coupled moisture-ageing effects in bituminous binders. These findings provide valuable guidance for the design, construction, and maintenance of porous asphalt pavement aiming at improved pavement durability and sustainability. ...
The objectives of this thesis are centered on gaining a thorough understanding of the mechanisms behind moisture and ageing behavior in bitumen, working towards a fully coupled moisture and ageing behavior in bitumen and their impact on bituminous materials. To figure out the complex moisture and aging effects in bitumen, it is essential to initiate from a simpler scenario without involving too many variables and then gradually take into consideration more factors affecting the moisture and ageing processes.
Guided by this principle, the moisture diffusion behavior in bitumen and its effects on bitumen properties are initially investigated. To obtain fundamental insights into the moisture mechanisms, both experiments and molecular dynamics simulations are conducted for mutual interpretation and corroboration. Results show that the moisture in bitumen consists of three states: free water characterized by a constant diffusion coefficient and a saturated concentration, immobile water bonded to polar functional groups
with a maximum concentration dependent on the number of these available groups, and water clusters, whose diffusion coefficient is significantly lower compared to free water and varies with cluster size.
The effects of ageing on the physicochemical and rheological properties of bitumen derived from diverse crude oil sources are evaluated and the physicochemicalrheological relationship is elucidated. The direct analysis of specific parameters and the chemometric analysis of full curves obtained from various chemical, physical, and rheological tests are combined for more accurate and extensive characterization. Results provide new insights into the chemo-mechanical relationship of bitumen, demonstrate the high capability of comprehensive information embedded in FTIR spectra and GPC curve in characterizing various rheological properties, and guide the selection of key physicochemical and rheological parameters for the evaluation of bitumen degradation. To characterize the impact of ageing on the moisture diffusion behavior in bitumen including moisture diffusion coefficient and absorption amount, the moisture transport in aged bitumen is measured through dynamic vapor sorption. The key factors determining moisture diffusion coefficient and moisture absorption are fractional free volume and polarity of bitumen. The changes of these two factors with increasing ageing level integratedly lead to increased activation energy for the diffusion of free water and reduced enthalpy of its adsorption. Simultaneously, the ageing kinetics of bitumen films are affected by the presence of moisture. The presence of moisture can inhibit oxidative reaction through the competitive diffusion between oxygen and moisture while the removal of moisture accelerates it due to additional diffusing pathways created by the diffusion of water molecules, especially water clusters.
In conclusion, this thesis provides in-depth insights into the understanding and evaluation of moisture diffusion and oxidative reaction in bitumen, as well as their respective effects on bitumen properties. The effects of moisture on the ageing process and that of ageing on the moisture behavior elucidated in this thesis establish a robust foundation for the modelling of fully coupled moisture-ageing effects in bituminous binders. These findings provide valuable guidance for the design, construction, and maintenance of porous asphalt pavement aiming at improved pavement durability and sustainability. ...
Extensive transportation infrastructure is crucial for enabling efficient transportation and fostering economic development. However, the operation of roadways contributes to escalating environmental and societal issues, including noise pollution and carbon emissions. To achieve a balance between economy, environment, and society, growing focus is being placed on enhancing the durability and sustainability of asphalt pavement in all aspects. A pivotal factor contributing to the deterioration of asphalt pavement performance is the degradation of bitumen properties, significantly affected traffic and climate conditions. The latter is primarily related to two key processes: oxidative aging and moisture in bitumen. Extensive studies have been undertaken to investigate the moisture and ageing behavior while large variations have been reported due to the complexity of these behavior, the diversity of bitumen types, and the variability of environmental conditions. Such discrepancies complicate the formulation of bituminous binders and mixtures that mitigates these issues.
The objectives of this thesis are centered on gaining a thorough understanding of the mechanisms behind moisture and ageing behavior in bitumen, working towards a fully coupled moisture and ageing behavior in bitumen and their impact on bituminous materials. To figure out the complex moisture and aging effects in bitumen, it is essential to initiate from a simpler scenario without involving too many variables and then gradually take into consideration more factors affecting the moisture and ageing processes.
Guided by this principle, the moisture diffusion behavior in bitumen and its effects on bitumen properties are initially investigated. To obtain fundamental insights into the moisture mechanisms, both experiments and molecular dynamics simulations are conducted for mutual interpretation and corroboration. Results show that the moisture in bitumen consists of three states: free water characterized by a constant diffusion coefficient and a saturated concentration, immobile water bonded to polar functional groups
with a maximum concentration dependent on the number of these available groups, and water clusters, whose diffusion coefficient is significantly lower compared to free water and varies with cluster size.
The effects of ageing on the physicochemical and rheological properties of bitumen derived from diverse crude oil sources are evaluated and the physicochemicalrheological relationship is elucidated. The direct analysis of specific parameters and the chemometric analysis of full curves obtained from various chemical, physical, and rheological tests are combined for more accurate and extensive characterization. Results provide new insights into the chemo-mechanical relationship of bitumen, demonstrate the high capability of comprehensive information embedded in FTIR spectra and GPC curve in characterizing various rheological properties, and guide the selection of key physicochemical and rheological parameters for the evaluation of bitumen degradation. To characterize the impact of ageing on the moisture diffusion behavior in bitumen including moisture diffusion coefficient and absorption amount, the moisture transport in aged bitumen is measured through dynamic vapor sorption. The key factors determining moisture diffusion coefficient and moisture absorption are fractional free volume and polarity of bitumen. The changes of these two factors with increasing ageing level integratedly lead to increased activation energy for the diffusion of free water and reduced enthalpy of its adsorption. Simultaneously, the ageing kinetics of bitumen films are affected by the presence of moisture. The presence of moisture can inhibit oxidative reaction through the competitive diffusion between oxygen and moisture while the removal of moisture accelerates it due to additional diffusing pathways created by the diffusion of water molecules, especially water clusters.
In conclusion, this thesis provides in-depth insights into the understanding and evaluation of moisture diffusion and oxidative reaction in bitumen, as well as their respective effects on bitumen properties. The effects of moisture on the ageing process and that of ageing on the moisture behavior elucidated in this thesis establish a robust foundation for the modelling of fully coupled moisture-ageing effects in bituminous binders. These findings provide valuable guidance for the design, construction, and maintenance of porous asphalt pavement aiming at improved pavement durability and sustainability.
The objectives of this thesis are centered on gaining a thorough understanding of the mechanisms behind moisture and ageing behavior in bitumen, working towards a fully coupled moisture and ageing behavior in bitumen and their impact on bituminous materials. To figure out the complex moisture and aging effects in bitumen, it is essential to initiate from a simpler scenario without involving too many variables and then gradually take into consideration more factors affecting the moisture and ageing processes.
Guided by this principle, the moisture diffusion behavior in bitumen and its effects on bitumen properties are initially investigated. To obtain fundamental insights into the moisture mechanisms, both experiments and molecular dynamics simulations are conducted for mutual interpretation and corroboration. Results show that the moisture in bitumen consists of three states: free water characterized by a constant diffusion coefficient and a saturated concentration, immobile water bonded to polar functional groups
with a maximum concentration dependent on the number of these available groups, and water clusters, whose diffusion coefficient is significantly lower compared to free water and varies with cluster size.
The effects of ageing on the physicochemical and rheological properties of bitumen derived from diverse crude oil sources are evaluated and the physicochemicalrheological relationship is elucidated. The direct analysis of specific parameters and the chemometric analysis of full curves obtained from various chemical, physical, and rheological tests are combined for more accurate and extensive characterization. Results provide new insights into the chemo-mechanical relationship of bitumen, demonstrate the high capability of comprehensive information embedded in FTIR spectra and GPC curve in characterizing various rheological properties, and guide the selection of key physicochemical and rheological parameters for the evaluation of bitumen degradation. To characterize the impact of ageing on the moisture diffusion behavior in bitumen including moisture diffusion coefficient and absorption amount, the moisture transport in aged bitumen is measured through dynamic vapor sorption. The key factors determining moisture diffusion coefficient and moisture absorption are fractional free volume and polarity of bitumen. The changes of these two factors with increasing ageing level integratedly lead to increased activation energy for the diffusion of free water and reduced enthalpy of its adsorption. Simultaneously, the ageing kinetics of bitumen films are affected by the presence of moisture. The presence of moisture can inhibit oxidative reaction through the competitive diffusion between oxygen and moisture while the removal of moisture accelerates it due to additional diffusing pathways created by the diffusion of water molecules, especially water clusters.
In conclusion, this thesis provides in-depth insights into the understanding and evaluation of moisture diffusion and oxidative reaction in bitumen, as well as their respective effects on bitumen properties. The effects of moisture on the ageing process and that of ageing on the moisture behavior elucidated in this thesis establish a robust foundation for the modelling of fully coupled moisture-ageing effects in bituminous binders. These findings provide valuable guidance for the design, construction, and maintenance of porous asphalt pavement aiming at improved pavement durability and sustainability.
Pavements of enhanced longevity would be expected to withstand long-term traffic as well as varying environmental conditions reducing in this way the major maintenance needs. Considering also the adoption of long-term contracts by road authorities, long-life pavements have started to attract the interest of road contractors worldwide. New and relatively new binders specially designed to produce long-life pavements have been proposed to minimize the regular maintenance and reconstruction operations. Among others, one promising technology to reach this goal is the epoxy modified asphalt binder, or epoxy-asphalt. Nevertheless, the addition of epoxy resins to asphalt binders may result in materials of inferior properties. Thermosetting epoxy resins may not mix homogeneously in asphalt binders leading to immiscible or partially miscible binders, which are mostly phase-separated materials. The phase-separated epoxy-asphalt binders can become brittle and thus more prone to cracking, leading the pavements to fail. Only a few epoxy products are applicable in asphalt binders, and the knowledge of incorporating chemistry to develop miscible epoxy binders remains unknown. For this to be the case, this thesis aims to provide a fundamental approach to elucidate the chemical and physical processes that determine the phase behavior of these binders. A vital role in implementing the thermosetting epoxy-asphalt binders also plays the curing. To obtain fundamental insights into the material curing, multi-physics models and experimental methods are considered in this research to identify and assess the curing-induced changes of epoxy-asphalt. The development of rheological properties that reflect the material workability is determined by laboratory experiments and used as input to multi-physics simulations. As the ultimate scope of implementing the epoxy-asphalt is to increase the longevity of pavements, the oxidation-induced changes of epoxy-asphalt materials as a function of time are evaluated as well in this research to prove their high aging resistance for wearing courses. Within the same framework, emphasis is also given to the effect of epoxy-asphalt on the durability and mechanical performance characteristics of an asphalt concrete mix. In conclusion, this thesis contributes to elucidating the factors that determine the curing- and oxidation-induced changes of epoxy-asphalt and understanding what bears miscible binders. The modeling and experimental programs discussed throughout the thesis can help to provide the fundamental knowledge to design and develop new binders and binding systems of the desired properties and characteristics.
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Pavements of enhanced longevity would be expected to withstand long-term traffic as well as varying environmental conditions reducing in this way the major maintenance needs. Considering also the adoption of long-term contracts by road authorities, long-life pavements have started to attract the interest of road contractors worldwide. New and relatively new binders specially designed to produce long-life pavements have been proposed to minimize the regular maintenance and reconstruction operations. Among others, one promising technology to reach this goal is the epoxy modified asphalt binder, or epoxy-asphalt. Nevertheless, the addition of epoxy resins to asphalt binders may result in materials of inferior properties. Thermosetting epoxy resins may not mix homogeneously in asphalt binders leading to immiscible or partially miscible binders, which are mostly phase-separated materials. The phase-separated epoxy-asphalt binders can become brittle and thus more prone to cracking, leading the pavements to fail. Only a few epoxy products are applicable in asphalt binders, and the knowledge of incorporating chemistry to develop miscible epoxy binders remains unknown. For this to be the case, this thesis aims to provide a fundamental approach to elucidate the chemical and physical processes that determine the phase behavior of these binders. A vital role in implementing the thermosetting epoxy-asphalt binders also plays the curing. To obtain fundamental insights into the material curing, multi-physics models and experimental methods are considered in this research to identify and assess the curing-induced changes of epoxy-asphalt. The development of rheological properties that reflect the material workability is determined by laboratory experiments and used as input to multi-physics simulations. As the ultimate scope of implementing the epoxy-asphalt is to increase the longevity of pavements, the oxidation-induced changes of epoxy-asphalt materials as a function of time are evaluated as well in this research to prove their high aging resistance for wearing courses. Within the same framework, emphasis is also given to the effect of epoxy-asphalt on the durability and mechanical performance characteristics of an asphalt concrete mix. In conclusion, this thesis contributes to elucidating the factors that determine the curing- and oxidation-induced changes of epoxy-asphalt and understanding what bears miscible binders. The modeling and experimental programs discussed throughout the thesis can help to provide the fundamental knowledge to design and develop new binders and binding systems of the desired properties and characteristics.
Crumb rubber modified bitumen
Experimental characterization and modelling
A sustainable pavement, which can minimize environmental impacts through the reduction of energy consumption, natural resources and associated emissions while meeting all performance conditions and standards, is in urgent need to combat the climate change. The current scenario of depleting crude oil, reduced quarry zones, and stringent environmental regulations has driven the use of waste materials and by-products in pavement applications. The utilization of crumb rubber from scrap tires for bitumen modification has become a common engineering practice since last century...
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A sustainable pavement, which can minimize environmental impacts through the reduction of energy consumption, natural resources and associated emissions while meeting all performance conditions and standards, is in urgent need to combat the climate change. The current scenario of depleting crude oil, reduced quarry zones, and stringent environmental regulations has driven the use of waste materials and by-products in pavement applications. The utilization of crumb rubber from scrap tires for bitumen modification has become a common engineering practice since last century...
Pavement undergoes a fast deterioration process either due to the damages induced by weather conditions, an increase in traffic flow and load, or passive factors like aging of infrastructure. Thus requiring periodic rehabilitation measures to maintain the condition of the underlying asset.
Since damages on the asphalt road, impose economic setbacks and concern for the users, governmental authorities are looking for a proactive approach to detect and classify distresses in their "early" stages. As a reason, governmental authorities like the Province of Zuid-Holland (PZH) yearly inspect the road network, which was optimal until now, but as the traffic flows are increasing and weather conditions are worsening, a new approach is required to mitigate the need for a frequent, cost-effective and reliable inspection method.
Modern data sources such as smartphones are the biggest data generators. Having an intriguing number of sensors and in-built features, governmental and private authorities are just starting to acknowledge the potential of such crowd-sourced data generators. In this research data-types like vibration and imagery were gathered and synthesized to assess the efficiency and accuracy of the 3 data-driven models.
A 7-step methodology was implemented to build all the machine learning models. At first, vibration data was gathered to detect road anomalies and predict the International Roughness Index (IRI), by building a Random Forest decision tree. Secondly, a Convolution Neural Network (CNN) was constructed and utilized to classify pavement surface distresses. The last model, is a next step towards autonomously distinguishing the classified distress with its severity ranking. A Deep Neural Network (DNN) called EnDec (Encoder & Decoder) architecture was built and trained on the Dutch supercomputer called "cartesius", by utilizing multi-threading opportunities, to objectively segment the given pavement surface distress.
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Pavement undergoes a fast deterioration process either due to the damages induced by weather conditions, an increase in traffic flow and load, or passive factors like aging of infrastructure. Thus requiring periodic rehabilitation measures to maintain the condition of the underlying asset.
Since damages on the asphalt road, impose economic setbacks and concern for the users, governmental authorities are looking for a proactive approach to detect and classify distresses in their "early" stages. As a reason, governmental authorities like the Province of Zuid-Holland (PZH) yearly inspect the road network, which was optimal until now, but as the traffic flows are increasing and weather conditions are worsening, a new approach is required to mitigate the need for a frequent, cost-effective and reliable inspection method.
Modern data sources such as smartphones are the biggest data generators. Having an intriguing number of sensors and in-built features, governmental and private authorities are just starting to acknowledge the potential of such crowd-sourced data generators. In this research data-types like vibration and imagery were gathered and synthesized to assess the efficiency and accuracy of the 3 data-driven models.
A 7-step methodology was implemented to build all the machine learning models. At first, vibration data was gathered to detect road anomalies and predict the International Roughness Index (IRI), by building a Random Forest decision tree. Secondly, a Convolution Neural Network (CNN) was constructed and utilized to classify pavement surface distresses. The last model, is a next step towards autonomously distinguishing the classified distress with its severity ranking. A Deep Neural Network (DNN) called EnDec (Encoder & Decoder) architecture was built and trained on the Dutch supercomputer called "cartesius", by utilizing multi-threading opportunities, to objectively segment the given pavement surface distress.
Despite therelevance of the road infrastructure, the mechanisms governing the mechanicalproperties of asphalt concrete pavements, are currently not sufficientlyunderstood. Many empirical models of different complexity are proposed in theliterature; however, (i) they all have below high (R2 =0.85) predictiveaccuracy; (ii) they are inflexible; and (iii) their prediction uncertainty isseldom quantified. This M.Sc. thesis aspires to overcome these three majorchallenges. It focuses on the prediction of three important mechanicalproperties of asphalt mixes: stiffness, resistance to permanent deformation,and indirect tensile strength (ITS). The used data are part of the NL-Labproject and represent six road work projects for asphalt concrete bottom andintermediate layers. The number of data points available for the threeproperties ranges from 100 to 400. Two approaches are used to predict thefunctional properties: multiple linear regression (MLR), and a machine learningtechnique: gradient boosting (GB). For both approaches the root-mean-squareerror is used as loss function and 5-fold cross-validation is applied to ensurea balanced fit. It is demonstrated on the NL-Lab dataset that (i) GB canachieve high and very high predictive accuracy; (ii) it is sufficientlyflexible to capture complex non-linear relationships; and (iii) its predictionuncertainty is low and can be estimated at the same computational cost asfitting a GB model. The predictive accuracy of the GB model significantlyoutperforms that of the MLR. For example, for stiffness: R2GB = 0.96 vs. R2MLR= 0.62, and for ITS: R2GB = 0.82 vs. R2MLR = 0.72. It is shown that the averagestandard deviation of the prediction uncertainty of the GB model is less thanhalf than that of the MLR model. Based on the completed analyses GB is stronglyrecommended over MLR for modelling asphalt concrete functional properties. Tothe author’s knowledge, this work is the first application of GB to modelasphalt concrete functional properties and the first that developed high andvery high predictive accuracy models for these properties. The results arepromising and encouraging further research into this subject. ...
Despite therelevance of the road infrastructure, the mechanisms governing the mechanicalproperties of asphalt concrete pavements, are currently not sufficientlyunderstood. Many empirical models of different complexity are proposed in theliterature; however, (i) they all have below high (R2 =0.85) predictiveaccuracy; (ii) they are inflexible; and (iii) their prediction uncertainty isseldom quantified. This M.Sc. thesis aspires to overcome these three majorchallenges. It focuses on the prediction of three important mechanicalproperties of asphalt mixes: stiffness, resistance to permanent deformation,and indirect tensile strength (ITS). The used data are part of the NL-Labproject and represent six road work projects for asphalt concrete bottom andintermediate layers. The number of data points available for the threeproperties ranges from 100 to 400. Two approaches are used to predict thefunctional properties: multiple linear regression (MLR), and a machine learningtechnique: gradient boosting (GB). For both approaches the root-mean-squareerror is used as loss function and 5-fold cross-validation is applied to ensurea balanced fit. It is demonstrated on the NL-Lab dataset that (i) GB canachieve high and very high predictive accuracy; (ii) it is sufficientlyflexible to capture complex non-linear relationships; and (iii) its predictionuncertainty is low and can be estimated at the same computational cost asfitting a GB model. The predictive accuracy of the GB model significantlyoutperforms that of the MLR. For example, for stiffness: R2GB = 0.96 vs. R2MLR= 0.62, and for ITS: R2GB = 0.82 vs. R2MLR = 0.72. It is shown that the averagestandard deviation of the prediction uncertainty of the GB model is less thanhalf than that of the MLR model. Based on the completed analyses GB is stronglyrecommended over MLR for modelling asphalt concrete functional properties. Tothe author’s knowledge, this work is the first application of GB to modelasphalt concrete functional properties and the first that developed high andvery high predictive accuracy models for these properties. The results arepromising and encouraging further research into this subject.
Master thesis
(2018)
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Joost Droogers, S. Erkens, E. Schlangen, Lambert Houben, B.W. Sluer, N.R.Z. Poeran
Asphalt concrete stiffness is currently only determined by tests in The Netherlands. A prediction model can be useful for mix design and verification purposes. In this paper existing asphalt concrete stiffness prediction models have been analysed. A database with 7 mixes has been build to assess these models. A study was performed on the relevance of binder and composition parameters for predicting asphalt concrete stiffness. Finally, a new model is proposed.
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Asphalt concrete stiffness is currently only determined by tests in The Netherlands. A prediction model can be useful for mix design and verification purposes. In this paper existing asphalt concrete stiffness prediction models have been analysed. A database with 7 mixes has been build to assess these models. A study was performed on the relevance of binder and composition parameters for predicting asphalt concrete stiffness. Finally, a new model is proposed.
Schiphol Airport and Heijmans are working together on the renewal of the Schiphol runways pavements. Currently the top layer is covered with a synthetic antiskid material called ASK. But the strong weather limitations for the installation of this material have opened the door for alternatives. Heijmans has proposed an innovative asphalt mixture that is able to provide similar and in some cases better surface performances compared with the ASK. This asphalt mixture is called Flightflex R and is a stone matrix asphalt. Consequently it is affected by the variability of the construction process. This thesis project focuses on the analysis of the best quality control procedure for this asphalt. The pavement surface needs to meet specific requirements and it is of interest to define a sampling methodology for the evaluation of the Texture Depth (TD). In particular the research aims to define the minimum number of samples that provides the highest reliability for the definition of the Mean Texture Depth (MTD) of the surface. To achieve this goal a theoretical approach is adopted. Starting from the collection of a consistent number of samples, the properties of the surface are analysed. In this process it is of interest to define the influence of the construction process on the surface quality. The information obtained are used to simulate bigger surfaces on which different sampling methodologies are tested. In particular three different methodologies are analysed: the current methodology called CROW, a Uniform methodology and a random methodology called Hammersley methodology. Thorough testing these sampling methodologies on the simulated surfaces it is possible to evaluate the relative error between the MTD of the simulated surfaces and the MTD of the samples taken. A Monte Carlo type of approach helps to define precisely which methodology performs better. The one with the lowest relative error and minimum required number of samples will be considered the most efficient. The simulation of the surfaces and the analysis of the sampling process highlights a correlation between the manufacturing signature and some sampling methodologies. In case of a correlation the reliability of the methodology decreases. In particular the CROW and the Uniform methodology present a form of correlation and thus have a lower reliability. The Hammersley methodology aims to simulate a random selection of samples and for this reason it does not enter in correlation with the surface patterns. The three aforementioned methodologies are in the last part of the research applied on a 500 m long section of the runway Polderbaan at Schiphol Airport. Although the Uniform methodology is less reliable it provides a 1% of relative error with only 70 samples. The Hammersley instead needs 180 samples to reach the same relative error but with a higher reliability. The CROW is the least performing. In fact it has a lower reliability than the Uniform strategy and it needs 170 samples to reach 1% relative error. The research helps highlighting the correlation between the manufacturing signature left by the construction process and the sampling strategy adopted. It also highlights the fact that a random distribution escapes this correlation and provides more reliable results. To conclude, the companies are suggested to use the Uniform methodology in case of short time available for the quality control measurements. This comes with a lowest reliability that has to be accepted. But in case a high reliability is required and sufficient time is available, the Hammersley strategy is considered more appropriate.
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Schiphol Airport and Heijmans are working together on the renewal of the Schiphol runways pavements. Currently the top layer is covered with a synthetic antiskid material called ASK. But the strong weather limitations for the installation of this material have opened the door for alternatives. Heijmans has proposed an innovative asphalt mixture that is able to provide similar and in some cases better surface performances compared with the ASK. This asphalt mixture is called Flightflex R and is a stone matrix asphalt. Consequently it is affected by the variability of the construction process. This thesis project focuses on the analysis of the best quality control procedure for this asphalt. The pavement surface needs to meet specific requirements and it is of interest to define a sampling methodology for the evaluation of the Texture Depth (TD). In particular the research aims to define the minimum number of samples that provides the highest reliability for the definition of the Mean Texture Depth (MTD) of the surface. To achieve this goal a theoretical approach is adopted. Starting from the collection of a consistent number of samples, the properties of the surface are analysed. In this process it is of interest to define the influence of the construction process on the surface quality. The information obtained are used to simulate bigger surfaces on which different sampling methodologies are tested. In particular three different methodologies are analysed: the current methodology called CROW, a Uniform methodology and a random methodology called Hammersley methodology. Thorough testing these sampling methodologies on the simulated surfaces it is possible to evaluate the relative error between the MTD of the simulated surfaces and the MTD of the samples taken. A Monte Carlo type of approach helps to define precisely which methodology performs better. The one with the lowest relative error and minimum required number of samples will be considered the most efficient. The simulation of the surfaces and the analysis of the sampling process highlights a correlation between the manufacturing signature and some sampling methodologies. In case of a correlation the reliability of the methodology decreases. In particular the CROW and the Uniform methodology present a form of correlation and thus have a lower reliability. The Hammersley methodology aims to simulate a random selection of samples and for this reason it does not enter in correlation with the surface patterns. The three aforementioned methodologies are in the last part of the research applied on a 500 m long section of the runway Polderbaan at Schiphol Airport. Although the Uniform methodology is less reliable it provides a 1% of relative error with only 70 samples. The Hammersley instead needs 180 samples to reach the same relative error but with a higher reliability. The CROW is the least performing. In fact it has a lower reliability than the Uniform strategy and it needs 170 samples to reach 1% relative error. The research helps highlighting the correlation between the manufacturing signature left by the construction process and the sampling strategy adopted. It also highlights the fact that a random distribution escapes this correlation and provides more reliable results. To conclude, the companies are suggested to use the Uniform methodology in case of short time available for the quality control measurements. This comes with a lowest reliability that has to be accepted. But in case a high reliability is required and sufficient time is available, the Hammersley strategy is considered more appropriate.
Master thesis
(2018)
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Christian Gerald Daniel, S. Erkens, Xueyan Liu, Panos Apostolidis, Lambert Houben, Yuguang Yang, Ronald Diele, Henk Hilverink, Mahesh Moenielal
The use of synthetic fibres has been reported to enhance the performance of asphalt pavement materials in terms of permanent deformation, fatigue and thermal cracking. However, limited results about the benefits of synthetic fibres in the reinforced warm-mix asphaltic materials, and the exact mechanism of reinforcing the binding part in pavement structures is still unclear. This research aims firstly to examine the material at the warm mixed mortar level using a combination of two synthetic fibres (aramid and polyolefin) to conclude its fracture performance. Several laboratory tests were performed using specially designed experimental tools. Samples of three different fibre contents (0.05%, 0.1% and 0.5% of specimen weight) and two fibre lengths (19 and 38mm) were evaluated. In particular, pull-out tests, whose objective was to explore the interaction of fibre-matrix demonstrated a matrix-type of fracture; meaning that the adhesion of fibre-matrix is higher than the strength of the matrix itself, which implies a benefit of adding fibre to a mixture at high service temperature.
Summary
Moreover, direct tension tests were carried out with both monotonic and cyclic loading to measure the effect of the synthetic fibres on tensile strength, fracture energy and fatigue life of reinforced warm mixes under monotonic and cyclic tension load, respectively. These tension experiments concluded improvements on mechanical characteristics of warm mixed asphalt mortars when fibres were added, mainly applying higher dosages than the recommended by the fibres supplier. Overall, the current results elucidated that implementing dedicated material studies at micro-scales can assist on understanding the material performance and tailoring systems beyond sometimes recommended reinforcement dosages by the suppliers. Finally, a semi-circular bending test was performed as the largest scale of this research using various fibre amount composition as well as fibre length inside the bituminous mix, and the final results mainly correspond with the other examinations that have also been conducted. Therefore, the research methodology utilised in this thesis has been able to examine the reinforcement effect brought by the integration of synthetic fibre to failure performance of the warm mixed asphaltic mixture specifically regarding the cracking resistance extensively. ...
Summary
Moreover, direct tension tests were carried out with both monotonic and cyclic loading to measure the effect of the synthetic fibres on tensile strength, fracture energy and fatigue life of reinforced warm mixes under monotonic and cyclic tension load, respectively. These tension experiments concluded improvements on mechanical characteristics of warm mixed asphalt mortars when fibres were added, mainly applying higher dosages than the recommended by the fibres supplier. Overall, the current results elucidated that implementing dedicated material studies at micro-scales can assist on understanding the material performance and tailoring systems beyond sometimes recommended reinforcement dosages by the suppliers. Finally, a semi-circular bending test was performed as the largest scale of this research using various fibre amount composition as well as fibre length inside the bituminous mix, and the final results mainly correspond with the other examinations that have also been conducted. Therefore, the research methodology utilised in this thesis has been able to examine the reinforcement effect brought by the integration of synthetic fibre to failure performance of the warm mixed asphaltic mixture specifically regarding the cracking resistance extensively. ...
The use of synthetic fibres has been reported to enhance the performance of asphalt pavement materials in terms of permanent deformation, fatigue and thermal cracking. However, limited results about the benefits of synthetic fibres in the reinforced warm-mix asphaltic materials, and the exact mechanism of reinforcing the binding part in pavement structures is still unclear. This research aims firstly to examine the material at the warm mixed mortar level using a combination of two synthetic fibres (aramid and polyolefin) to conclude its fracture performance. Several laboratory tests were performed using specially designed experimental tools. Samples of three different fibre contents (0.05%, 0.1% and 0.5% of specimen weight) and two fibre lengths (19 and 38mm) were evaluated. In particular, pull-out tests, whose objective was to explore the interaction of fibre-matrix demonstrated a matrix-type of fracture; meaning that the adhesion of fibre-matrix is higher than the strength of the matrix itself, which implies a benefit of adding fibre to a mixture at high service temperature.
Summary
Moreover, direct tension tests were carried out with both monotonic and cyclic loading to measure the effect of the synthetic fibres on tensile strength, fracture energy and fatigue life of reinforced warm mixes under monotonic and cyclic tension load, respectively. These tension experiments concluded improvements on mechanical characteristics of warm mixed asphalt mortars when fibres were added, mainly applying higher dosages than the recommended by the fibres supplier. Overall, the current results elucidated that implementing dedicated material studies at micro-scales can assist on understanding the material performance and tailoring systems beyond sometimes recommended reinforcement dosages by the suppliers. Finally, a semi-circular bending test was performed as the largest scale of this research using various fibre amount composition as well as fibre length inside the bituminous mix, and the final results mainly correspond with the other examinations that have also been conducted. Therefore, the research methodology utilised in this thesis has been able to examine the reinforcement effect brought by the integration of synthetic fibre to failure performance of the warm mixed asphaltic mixture specifically regarding the cracking resistance extensively.
Summary
Moreover, direct tension tests were carried out with both monotonic and cyclic loading to measure the effect of the synthetic fibres on tensile strength, fracture energy and fatigue life of reinforced warm mixes under monotonic and cyclic tension load, respectively. These tension experiments concluded improvements on mechanical characteristics of warm mixed asphalt mortars when fibres were added, mainly applying higher dosages than the recommended by the fibres supplier. Overall, the current results elucidated that implementing dedicated material studies at micro-scales can assist on understanding the material performance and tailoring systems beyond sometimes recommended reinforcement dosages by the suppliers. Finally, a semi-circular bending test was performed as the largest scale of this research using various fibre amount composition as well as fibre length inside the bituminous mix, and the final results mainly correspond with the other examinations that have also been conducted. Therefore, the research methodology utilised in this thesis has been able to examine the reinforcement effect brought by the integration of synthetic fibre to failure performance of the warm mixed asphaltic mixture specifically regarding the cracking resistance extensively.
Nowadays, there is a need to reduce noise pollution due to the tyre-pavement interaction, especially in densely-populated areas, such as the Netherlands, where noise pollution is a major concern. A solution to this problem is the development of pavement surfaces with improved noise reduction characteristics. Previous attempts to develop low-noise pavement surfaces were not successful, mainly due to their poor mechanical performance and low durability. In this research the mechanical performance of three different low-noise pavement surface materials is investigated. The study was part of the Ultrastil Wegdek (USW) project in the Netherlands. The materials were evaluated with respect to their moisture susceptibility, stiffness, cohesive strength and bonding with the underlying layer. For three different low-noise road surfaces (LNRS), the stiffness was evaluated by means of dynamic modulus tests. Furthermore, indirect and direct tensile tests were carried out after long- and short-term moisture conditioning to estimate strength degradation. The interlayer bond strength was determined using uniaxial tension tests at dry and wet conditions. To evaluate the bond characteristics, also two-layer porous asphalt systems were tested as reference materials. The results show high difference in their properties as a result of the mixture composition. Especially, considering the effect of moisture is of paramount importance for these highly open-graded mixtures.
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Nowadays, there is a need to reduce noise pollution due to the tyre-pavement interaction, especially in densely-populated areas, such as the Netherlands, where noise pollution is a major concern. A solution to this problem is the development of pavement surfaces with improved noise reduction characteristics. Previous attempts to develop low-noise pavement surfaces were not successful, mainly due to their poor mechanical performance and low durability. In this research the mechanical performance of three different low-noise pavement surface materials is investigated. The study was part of the Ultrastil Wegdek (USW) project in the Netherlands. The materials were evaluated with respect to their moisture susceptibility, stiffness, cohesive strength and bonding with the underlying layer. For three different low-noise road surfaces (LNRS), the stiffness was evaluated by means of dynamic modulus tests. Furthermore, indirect and direct tensile tests were carried out after long- and short-term moisture conditioning to estimate strength degradation. The interlayer bond strength was determined using uniaxial tension tests at dry and wet conditions. To evaluate the bond characteristics, also two-layer porous asphalt systems were tested as reference materials. The results show high difference in their properties as a result of the mixture composition. Especially, considering the effect of moisture is of paramount importance for these highly open-graded mixtures.
The adaption of the functional characterization of asphalt concrete mixtures by the Dutch authorities, led to a big necessity in acquiring a fundamental understanding on its properties. In order to achieve this, the long-term project NL-Lab was initiated by InfraQuest in 2012. With the advantage of its longevity and the multiple parties contributing with material, testing and analysing, the knowledge aimed for, is gradually accumulating with the time passing. After 5 years of running, a considerable number of data have been collected and analysed, leading to many observations, that in turn raised questions and doubts. These doubts are the subject of this research, focusing on the functional characteristics of water sensitivity and permanent deformation.
A common problem for both properties regards the production and compaction of type-testing specimens. The practice so far suggests both stages to take place in laboratory conditions. However, there were indications that the performance of the same asphalt mixtures taken from the field instead of the lab, differed. Testing and comparing in terms of water sensitivity and permanent deformation, these indications were indeed repeated. Lab and field specimens did not match in performance in the majority of the tests, suggesting that differences between the two conditions are projected in differences in performance.
The second common problem also evolves around the type-testing, this time regarding the test procedure as a whole. It is a highly time and money consuming process that has to be repeated in a trial-and-error manner, until a satisfying mixture in terms of performance is found. The aim of this research was to limit this process as much as possible by replacing it with regression relations. For the water sensitivity test, the relations obtained were of a fairly good predicting quality, and could be eventually used in the preliminary mixture design. The permanent deformation relations however, were at low levels of predictability, due to the test’s high sensitivity in being reproduced and the inconsistent test setups used by the various contractors taking part in the project.
Focusing only on water sensitivity, the conditioning protocol described in the current standard, is considered as not very capable of capturing the property it aims for, and that it is conservative in the damage it causes to the mixture. Utilizing two conditioning protocols, MIST and Freeze-Thaw protocol, the standard method indeed was found to be the least damaging of all. With the MIST being the most destructive, at extreme levels in most cases, and the Freeze-Thaw following it, each method’s pros and cons were found.
The last aspect tested referred to the friction reduction method used during the permanent deformation test (triaxial cyclic compression). The old and new standard versions both prescribe two different materials, while the requirements for rutting remained unchanged. Testing using these two materials, Teflon and Latex, plus one new, it was found that the differences in the triaxial test output were major. Consequently, this mismatch means that inconsistent comparisons take place, leading to conclusions on rutting performance not representative of the actual situation.
...
A common problem for both properties regards the production and compaction of type-testing specimens. The practice so far suggests both stages to take place in laboratory conditions. However, there were indications that the performance of the same asphalt mixtures taken from the field instead of the lab, differed. Testing and comparing in terms of water sensitivity and permanent deformation, these indications were indeed repeated. Lab and field specimens did not match in performance in the majority of the tests, suggesting that differences between the two conditions are projected in differences in performance.
The second common problem also evolves around the type-testing, this time regarding the test procedure as a whole. It is a highly time and money consuming process that has to be repeated in a trial-and-error manner, until a satisfying mixture in terms of performance is found. The aim of this research was to limit this process as much as possible by replacing it with regression relations. For the water sensitivity test, the relations obtained were of a fairly good predicting quality, and could be eventually used in the preliminary mixture design. The permanent deformation relations however, were at low levels of predictability, due to the test’s high sensitivity in being reproduced and the inconsistent test setups used by the various contractors taking part in the project.
Focusing only on water sensitivity, the conditioning protocol described in the current standard, is considered as not very capable of capturing the property it aims for, and that it is conservative in the damage it causes to the mixture. Utilizing two conditioning protocols, MIST and Freeze-Thaw protocol, the standard method indeed was found to be the least damaging of all. With the MIST being the most destructive, at extreme levels in most cases, and the Freeze-Thaw following it, each method’s pros and cons were found.
The last aspect tested referred to the friction reduction method used during the permanent deformation test (triaxial cyclic compression). The old and new standard versions both prescribe two different materials, while the requirements for rutting remained unchanged. Testing using these two materials, Teflon and Latex, plus one new, it was found that the differences in the triaxial test output were major. Consequently, this mismatch means that inconsistent comparisons take place, leading to conclusions on rutting performance not representative of the actual situation.
...
The adaption of the functional characterization of asphalt concrete mixtures by the Dutch authorities, led to a big necessity in acquiring a fundamental understanding on its properties. In order to achieve this, the long-term project NL-Lab was initiated by InfraQuest in 2012. With the advantage of its longevity and the multiple parties contributing with material, testing and analysing, the knowledge aimed for, is gradually accumulating with the time passing. After 5 years of running, a considerable number of data have been collected and analysed, leading to many observations, that in turn raised questions and doubts. These doubts are the subject of this research, focusing on the functional characteristics of water sensitivity and permanent deformation.
A common problem for both properties regards the production and compaction of type-testing specimens. The practice so far suggests both stages to take place in laboratory conditions. However, there were indications that the performance of the same asphalt mixtures taken from the field instead of the lab, differed. Testing and comparing in terms of water sensitivity and permanent deformation, these indications were indeed repeated. Lab and field specimens did not match in performance in the majority of the tests, suggesting that differences between the two conditions are projected in differences in performance.
The second common problem also evolves around the type-testing, this time regarding the test procedure as a whole. It is a highly time and money consuming process that has to be repeated in a trial-and-error manner, until a satisfying mixture in terms of performance is found. The aim of this research was to limit this process as much as possible by replacing it with regression relations. For the water sensitivity test, the relations obtained were of a fairly good predicting quality, and could be eventually used in the preliminary mixture design. The permanent deformation relations however, were at low levels of predictability, due to the test’s high sensitivity in being reproduced and the inconsistent test setups used by the various contractors taking part in the project.
Focusing only on water sensitivity, the conditioning protocol described in the current standard, is considered as not very capable of capturing the property it aims for, and that it is conservative in the damage it causes to the mixture. Utilizing two conditioning protocols, MIST and Freeze-Thaw protocol, the standard method indeed was found to be the least damaging of all. With the MIST being the most destructive, at extreme levels in most cases, and the Freeze-Thaw following it, each method’s pros and cons were found.
The last aspect tested referred to the friction reduction method used during the permanent deformation test (triaxial cyclic compression). The old and new standard versions both prescribe two different materials, while the requirements for rutting remained unchanged. Testing using these two materials, Teflon and Latex, plus one new, it was found that the differences in the triaxial test output were major. Consequently, this mismatch means that inconsistent comparisons take place, leading to conclusions on rutting performance not representative of the actual situation.
A common problem for both properties regards the production and compaction of type-testing specimens. The practice so far suggests both stages to take place in laboratory conditions. However, there were indications that the performance of the same asphalt mixtures taken from the field instead of the lab, differed. Testing and comparing in terms of water sensitivity and permanent deformation, these indications were indeed repeated. Lab and field specimens did not match in performance in the majority of the tests, suggesting that differences between the two conditions are projected in differences in performance.
The second common problem also evolves around the type-testing, this time regarding the test procedure as a whole. It is a highly time and money consuming process that has to be repeated in a trial-and-error manner, until a satisfying mixture in terms of performance is found. The aim of this research was to limit this process as much as possible by replacing it with regression relations. For the water sensitivity test, the relations obtained were of a fairly good predicting quality, and could be eventually used in the preliminary mixture design. The permanent deformation relations however, were at low levels of predictability, due to the test’s high sensitivity in being reproduced and the inconsistent test setups used by the various contractors taking part in the project.
Focusing only on water sensitivity, the conditioning protocol described in the current standard, is considered as not very capable of capturing the property it aims for, and that it is conservative in the damage it causes to the mixture. Utilizing two conditioning protocols, MIST and Freeze-Thaw protocol, the standard method indeed was found to be the least damaging of all. With the MIST being the most destructive, at extreme levels in most cases, and the Freeze-Thaw following it, each method’s pros and cons were found.
The last aspect tested referred to the friction reduction method used during the permanent deformation test (triaxial cyclic compression). The old and new standard versions both prescribe two different materials, while the requirements for rutting remained unchanged. Testing using these two materials, Teflon and Latex, plus one new, it was found that the differences in the triaxial test output were major. Consequently, this mismatch means that inconsistent comparisons take place, leading to conclusions on rutting performance not representative of the actual situation.
Master thesis
(2017)
-
Quanxin Xu, S. Erkens, Cor Kasbergen, Lambert Houben, Haneen Farah, A.R.G. van de Wall
Throughout the history of pavement structure, the parallel layer structure has dominated the structural design of pavements. In other words, the entire road pavement share a uniform thickness design regardless how many lanes there are. However, due to traffic regulations and driving habits, the traffic flow most probably does not distribute evenly on a multi-lane road. Modern pavement design methods usually choose the lane that bears the heaviest traffic load as the design lane to determine the thickness design of the entire pavement. Hence there could be a certain over-design in the less trafficked lanes. This study aims to propose and evaluate a new structural design for flexible pavement by reducing the thickness of asphalt layers of the lightly trafficked lanes.
The traffic data of a real motorway in the Netherlands was analysed, based on which a new pavement structural design of a 3-lane road was established. Two finite element models, for both original and new designs, were established in CAPA-3D to calculate the stress and strain responses under different traffic load combinations. Following the Dutch design method the fatigue and deformation performance predictions of the two pavement designs were executed and compared. The results showed that the new design indeed improve the material cost-efficiency without compromising the performance of the pavement structure.
Taking advantage of the finite element models, a real-life simulation was also applied. The strain output of the simulation was used to calculate the rutting depth following the American design method. Both calculated rutting depth and the deformation output of the real-time simulation supported the earlier conclusions. An extra simulation of truck platooning was briefly executed and discussed as well.
Furthermore, the construction and maintenance feasibilities of the new design were explored. It was proved that the new design can be constructed by the existing equipment and machines. The current maintenance methods and procedures can also be applied to the new design. ...
The traffic data of a real motorway in the Netherlands was analysed, based on which a new pavement structural design of a 3-lane road was established. Two finite element models, for both original and new designs, were established in CAPA-3D to calculate the stress and strain responses under different traffic load combinations. Following the Dutch design method the fatigue and deformation performance predictions of the two pavement designs were executed and compared. The results showed that the new design indeed improve the material cost-efficiency without compromising the performance of the pavement structure.
Taking advantage of the finite element models, a real-life simulation was also applied. The strain output of the simulation was used to calculate the rutting depth following the American design method. Both calculated rutting depth and the deformation output of the real-time simulation supported the earlier conclusions. An extra simulation of truck platooning was briefly executed and discussed as well.
Furthermore, the construction and maintenance feasibilities of the new design were explored. It was proved that the new design can be constructed by the existing equipment and machines. The current maintenance methods and procedures can also be applied to the new design. ...
Throughout the history of pavement structure, the parallel layer structure has dominated the structural design of pavements. In other words, the entire road pavement share a uniform thickness design regardless how many lanes there are. However, due to traffic regulations and driving habits, the traffic flow most probably does not distribute evenly on a multi-lane road. Modern pavement design methods usually choose the lane that bears the heaviest traffic load as the design lane to determine the thickness design of the entire pavement. Hence there could be a certain over-design in the less trafficked lanes. This study aims to propose and evaluate a new structural design for flexible pavement by reducing the thickness of asphalt layers of the lightly trafficked lanes.
The traffic data of a real motorway in the Netherlands was analysed, based on which a new pavement structural design of a 3-lane road was established. Two finite element models, for both original and new designs, were established in CAPA-3D to calculate the stress and strain responses under different traffic load combinations. Following the Dutch design method the fatigue and deformation performance predictions of the two pavement designs were executed and compared. The results showed that the new design indeed improve the material cost-efficiency without compromising the performance of the pavement structure.
Taking advantage of the finite element models, a real-life simulation was also applied. The strain output of the simulation was used to calculate the rutting depth following the American design method. Both calculated rutting depth and the deformation output of the real-time simulation supported the earlier conclusions. An extra simulation of truck platooning was briefly executed and discussed as well.
Furthermore, the construction and maintenance feasibilities of the new design were explored. It was proved that the new design can be constructed by the existing equipment and machines. The current maintenance methods and procedures can also be applied to the new design.
The traffic data of a real motorway in the Netherlands was analysed, based on which a new pavement structural design of a 3-lane road was established. Two finite element models, for both original and new designs, were established in CAPA-3D to calculate the stress and strain responses under different traffic load combinations. Following the Dutch design method the fatigue and deformation performance predictions of the two pavement designs were executed and compared. The results showed that the new design indeed improve the material cost-efficiency without compromising the performance of the pavement structure.
Taking advantage of the finite element models, a real-life simulation was also applied. The strain output of the simulation was used to calculate the rutting depth following the American design method. Both calculated rutting depth and the deformation output of the real-time simulation supported the earlier conclusions. An extra simulation of truck platooning was briefly executed and discussed as well.
Furthermore, the construction and maintenance feasibilities of the new design were explored. It was proved that the new design can be constructed by the existing equipment and machines. The current maintenance methods and procedures can also be applied to the new design.
Master thesis
(2017)
-
Gianpaolo Baggio, S. Erkens, Lambert Houben, Rene Braam, J Stigter, D van der Ven, C.A.P.M. van Gurp
This thesis is a study on the cracking behaviour of road bases constructed with cement bound reclaimed asphalt (also known in the Netherlands as AGRAC). It is decided to focus on this material because of the few researches available on the topic although the material being widely applied, at least in the Netherlands. The
goal of adding cement to the recycled asphalt aggregate is primarily to increase the resistance to permanent deformation (rutting). But, as in all cement-bound materials, in the AGRAC base layer shrinkage cracks might occur which could reflect through the overlying asphalt layers. Because of this, during the last decades the cement content was reduced from the initial 4-5% down to 2-2.5% (by mass).
In order to study the cracking behaviour of AGRAC, in this research one grading and two cement contents (2% and 4% m/m) are considered. A series of tests is performed to evaluate the properties of the two AGRAC mixes at different values of curing time (up to 130 days) and 3 different temperatures (0, 15 and 30°C). The dependence on the curing time and temperature are considered because of the presence in the mix of cement and bitumen respectively. In particular the tests performed are: indirect tensile strength, modulus of elasticity, shrinkage, thermal deformation, Poisson’s ratio and relaxation. The mechanical properties retrieved from these tests are used as input in a model which predicts the occurrence of cracks in an AGRAC base. If cracks occur, the model characterizes the crack pattern in terms of time of occurrence of the cracks, crack spacing and crack width. The calculations are done in two cases: non-weakened (plain) and weakened (with joints) base.
From the laboratory tests performed a dependence of the mechanical properties of AGRAC on the material temperature is clearly visible. Interesting results are also derived from the model, which shows the influence of the time of construction of the base (the worst scenario is observed for construction in August) and the difference in the cracking behaviour between the two AGRAC mixes (2 and 4% cement m/m). It is observed that the AGRAC mix with 4% cement leads to a higher risk of cracking compared to AGRAC 2%. In the worst scenario of base with AGRAC 4% constructed in August many crack series occur with a very close final crack spacing. The model shows how in this case even applying saw-cuts in the base is inefficient in terms of controlling the crack formation process. ...
goal of adding cement to the recycled asphalt aggregate is primarily to increase the resistance to permanent deformation (rutting). But, as in all cement-bound materials, in the AGRAC base layer shrinkage cracks might occur which could reflect through the overlying asphalt layers. Because of this, during the last decades the cement content was reduced from the initial 4-5% down to 2-2.5% (by mass).
In order to study the cracking behaviour of AGRAC, in this research one grading and two cement contents (2% and 4% m/m) are considered. A series of tests is performed to evaluate the properties of the two AGRAC mixes at different values of curing time (up to 130 days) and 3 different temperatures (0, 15 and 30°C). The dependence on the curing time and temperature are considered because of the presence in the mix of cement and bitumen respectively. In particular the tests performed are: indirect tensile strength, modulus of elasticity, shrinkage, thermal deformation, Poisson’s ratio and relaxation. The mechanical properties retrieved from these tests are used as input in a model which predicts the occurrence of cracks in an AGRAC base. If cracks occur, the model characterizes the crack pattern in terms of time of occurrence of the cracks, crack spacing and crack width. The calculations are done in two cases: non-weakened (plain) and weakened (with joints) base.
From the laboratory tests performed a dependence of the mechanical properties of AGRAC on the material temperature is clearly visible. Interesting results are also derived from the model, which shows the influence of the time of construction of the base (the worst scenario is observed for construction in August) and the difference in the cracking behaviour between the two AGRAC mixes (2 and 4% cement m/m). It is observed that the AGRAC mix with 4% cement leads to a higher risk of cracking compared to AGRAC 2%. In the worst scenario of base with AGRAC 4% constructed in August many crack series occur with a very close final crack spacing. The model shows how in this case even applying saw-cuts in the base is inefficient in terms of controlling the crack formation process. ...
This thesis is a study on the cracking behaviour of road bases constructed with cement bound reclaimed asphalt (also known in the Netherlands as AGRAC). It is decided to focus on this material because of the few researches available on the topic although the material being widely applied, at least in the Netherlands. The
goal of adding cement to the recycled asphalt aggregate is primarily to increase the resistance to permanent deformation (rutting). But, as in all cement-bound materials, in the AGRAC base layer shrinkage cracks might occur which could reflect through the overlying asphalt layers. Because of this, during the last decades the cement content was reduced from the initial 4-5% down to 2-2.5% (by mass).
In order to study the cracking behaviour of AGRAC, in this research one grading and two cement contents (2% and 4% m/m) are considered. A series of tests is performed to evaluate the properties of the two AGRAC mixes at different values of curing time (up to 130 days) and 3 different temperatures (0, 15 and 30°C). The dependence on the curing time and temperature are considered because of the presence in the mix of cement and bitumen respectively. In particular the tests performed are: indirect tensile strength, modulus of elasticity, shrinkage, thermal deformation, Poisson’s ratio and relaxation. The mechanical properties retrieved from these tests are used as input in a model which predicts the occurrence of cracks in an AGRAC base. If cracks occur, the model characterizes the crack pattern in terms of time of occurrence of the cracks, crack spacing and crack width. The calculations are done in two cases: non-weakened (plain) and weakened (with joints) base.
From the laboratory tests performed a dependence of the mechanical properties of AGRAC on the material temperature is clearly visible. Interesting results are also derived from the model, which shows the influence of the time of construction of the base (the worst scenario is observed for construction in August) and the difference in the cracking behaviour between the two AGRAC mixes (2 and 4% cement m/m). It is observed that the AGRAC mix with 4% cement leads to a higher risk of cracking compared to AGRAC 2%. In the worst scenario of base with AGRAC 4% constructed in August many crack series occur with a very close final crack spacing. The model shows how in this case even applying saw-cuts in the base is inefficient in terms of controlling the crack formation process.
goal of adding cement to the recycled asphalt aggregate is primarily to increase the resistance to permanent deformation (rutting). But, as in all cement-bound materials, in the AGRAC base layer shrinkage cracks might occur which could reflect through the overlying asphalt layers. Because of this, during the last decades the cement content was reduced from the initial 4-5% down to 2-2.5% (by mass).
In order to study the cracking behaviour of AGRAC, in this research one grading and two cement contents (2% and 4% m/m) are considered. A series of tests is performed to evaluate the properties of the two AGRAC mixes at different values of curing time (up to 130 days) and 3 different temperatures (0, 15 and 30°C). The dependence on the curing time and temperature are considered because of the presence in the mix of cement and bitumen respectively. In particular the tests performed are: indirect tensile strength, modulus of elasticity, shrinkage, thermal deformation, Poisson’s ratio and relaxation. The mechanical properties retrieved from these tests are used as input in a model which predicts the occurrence of cracks in an AGRAC base. If cracks occur, the model characterizes the crack pattern in terms of time of occurrence of the cracks, crack spacing and crack width. The calculations are done in two cases: non-weakened (plain) and weakened (with joints) base.
From the laboratory tests performed a dependence of the mechanical properties of AGRAC on the material temperature is clearly visible. Interesting results are also derived from the model, which shows the influence of the time of construction of the base (the worst scenario is observed for construction in August) and the difference in the cracking behaviour between the two AGRAC mixes (2 and 4% cement m/m). It is observed that the AGRAC mix with 4% cement leads to a higher risk of cracking compared to AGRAC 2%. In the worst scenario of base with AGRAC 4% constructed in August many crack series occur with a very close final crack spacing. The model shows how in this case even applying saw-cuts in the base is inefficient in terms of controlling the crack formation process.
This internship was part of a programme that has been going on since 2012, and is called ‘NL-LAB’, standing for National Living Lab. This program deals with a very large database from asphalt tests and measurements, both in labs and in the field, provided by the contractors that cooperate with RWS. The questions set at the initiation of the project were:
1. How (well) do the functional characteristics relate to field performance?
2. Is testing on laboratory mixed and compacted the correct choice?
3. Are the current tests able to distinguish “good” from “bad” mixtures?
4. How accurate and reliable can the prediction of a mixture’s performance be, based on its volumetric properties?
Relating to this program, this technical report tries to answer the following: 1) To obtain a predictive formula (via a Regression analysis) that outputs the asphalt’s performance regarding Rutting and Water Sensitivity, and 2) Compare the field to the lab properties and locate inconsistencies or trends in their relation.
...
1. How (well) do the functional characteristics relate to field performance?
2. Is testing on laboratory mixed and compacted the correct choice?
3. Are the current tests able to distinguish “good” from “bad” mixtures?
4. How accurate and reliable can the prediction of a mixture’s performance be, based on its volumetric properties?
Relating to this program, this technical report tries to answer the following: 1) To obtain a predictive formula (via a Regression analysis) that outputs the asphalt’s performance regarding Rutting and Water Sensitivity, and 2) Compare the field to the lab properties and locate inconsistencies or trends in their relation.
...
This internship was part of a programme that has been going on since 2012, and is called ‘NL-LAB’, standing for National Living Lab. This program deals with a very large database from asphalt tests and measurements, both in labs and in the field, provided by the contractors that cooperate with RWS. The questions set at the initiation of the project were:
1. How (well) do the functional characteristics relate to field performance?
2. Is testing on laboratory mixed and compacted the correct choice?
3. Are the current tests able to distinguish “good” from “bad” mixtures?
4. How accurate and reliable can the prediction of a mixture’s performance be, based on its volumetric properties?
Relating to this program, this technical report tries to answer the following: 1) To obtain a predictive formula (via a Regression analysis) that outputs the asphalt’s performance regarding Rutting and Water Sensitivity, and 2) Compare the field to the lab properties and locate inconsistencies or trends in their relation.
1. How (well) do the functional characteristics relate to field performance?
2. Is testing on laboratory mixed and compacted the correct choice?
3. Are the current tests able to distinguish “good” from “bad” mixtures?
4. How accurate and reliable can the prediction of a mixture’s performance be, based on its volumetric properties?
Relating to this program, this technical report tries to answer the following: 1) To obtain a predictive formula (via a Regression analysis) that outputs the asphalt’s performance regarding Rutting and Water Sensitivity, and 2) Compare the field to the lab properties and locate inconsistencies or trends in their relation.