Several studies have been conducted in the pavement area to try to understand the elastoplastic behavior of unbound granular materials(UGMs)under cyclic loading.This paper presents a literature review on the permanent...Several studies have been conducted in the pavement area to try to understand the elastoplastic behavior of unbound granular materials(UGMs)under cyclic loading.This paper presents a literature review on the permanent deformation phenomenon of UGMs when they form granular layers in flexible pavement structures.The factors affecting the resistance to permanent deformation are presented and described,and the evolution of the mathematical equations most used to predict the deformation in these materials under cyclic loading is shown.Conclusions and recommendations for future studies are presented at the end of the manuscript.Despite the substantial number of researches carried out on the subject,the elastoplastic behavior of UGMs has not yet been fully understood.These heterogeneous and anisotropic materials change their behavior mainly with stress magnitude and water content,but they are also strongly dependent on the way factors such as gradation,density,porosity,morphology,chemical and mineralogical composition,temperature,among others,interact.Generally,most of the mathematical equations that try to predict the accumulation of permanent deformation in UGMs are empirical,based on repeated load triaxial(RLT)tests,they cannot simulate the three components of cyclic stress to which a UGM is subjected in a pavement,their parameters are difficult to determine experimentally and do not show physical meaning(they are obtained by regression).In recent years,studies to evaluate the use of recycled aggregates and the effect of temperature(mainly at low temperatures)have increased.Likewise,the use of various technological tools such as artificial neural network(ANN)modeling,and so forth,has increased.展开更多
When a vehicle moves over a flexible pavement structure,it generates loading and unloading cycles that produce recoverable(resilient)and permanent(plastic)deformations in the granular base and subbase layers,which are...When a vehicle moves over a flexible pavement structure,it generates loading and unloading cycles that produce recoverable(resilient)and permanent(plastic)deformations in the granular base and subbase layers,which are made of unbound granular materials(UGMs).The primary parameter used to evaluate the resilient response of UGMs in pavements is the resilient modulus(MR).The MR is widely used in calculating stress-strain states for flexible pavement design and as a control parameter during the construction process.It is also employed to understand the progression of distresses,such as fatigue cracking and rutting.The main objective of this study was to conduct a literature review on the resilient behavior of UGMs.This manuscript presents and describes the MR and the factors that influence it.It also outlines the evolution of the mathematical equations most commonly used to estimate and predict this physical parameter.Conclusions and recommendations for future research are provided at the end of the article.Despite the large amount of research done on the subject,the resilient behavior of UGM has not yet been fully understood.This is since these materials are highly heterogeneous and show nonlinear-anisotropic behavior under different cyclic loading paths and water contents.Likewise,these materials undergo different behaviors depending on their macro and microscopic properties(gradation,density,porosity,texture,mineralogy,particle geometry and orientation,temperature,among others).On the other hand,the main limitation of the mathematical equations is that their parameters are difficult to determine experimentally and are not constants of the material(they are state variables that can change with multiple factors).Additionally,these equations do not consider the boundary conditions to which UGM in pavements are exposed.Moreover,they are obtained from repeated load triaxial(RLT)tests,which cannot simulate the three cyclic stress components(vertical,horizontal,and shear)to which UGMs are subjected in a pavement.In recent years,there has been an increase in studies evaluating the use of recycled aggregates and the effect of temperature(particularly at subzero temperatures),but more research is still needed to reach definitive conclusions.展开更多
This study aims to quantify the susceptibility of granular materials used in pavements to changes in moisture content and propose a correlation model to incorporate this susceptibility into seasonal analyses.The fines...This study aims to quantify the susceptibility of granular materials used in pavements to changes in moisture content and propose a correlation model to incorporate this susceptibility into seasonal analyses.The fines content and the percentage of fractured coarse aggregates were identified as direct indicators of the resilient modulus susceptibility to changes in water content.The results showed that the percentage of fractured coarse aggregates particles(FR)has a more significant impact on the resilient modulus(Er)of crushed granular materials used in pavement construction than the combined indicator of the fines content and sample volumetrics(nf).Crushed granular materials with a higher percentage of fractured coarse aggregates are relatively insensitive to changes in the degree of saturation,but become more sensitive as the fine fraction porosity decreases.An adjusted model was proposed based on the existing formulation,but considers a complex parameter to describe and adjust the sensitivity of base granular materials to variations in moisture content with respect to fabrication charac-teristics,fines content and volumetric properties.The model shows that the variation of Er values is below10%for fully crushed granular materials.However,it reaches approximately±12%for materials with 75%of crushed coarse aggregates andþ40%and-25%for materials with FR=50%.This model could help select good ag-gregates characteristics and adjust grain-size distribution for environments where significant moisture content variations can occur in the pavement system,such as in the Province of Quebec(Canada).As it is based on pa-rameters that can be easily determined or estimated,it also represents a valuable tool for detailed design and analysis that can consider material characteristics.展开更多
Flexible pavements rely heavily on unbound granular materials for their base and subbase layers,where their performance under repetitive loading is critical.This performance is gauged by two main parameters:resilient ...Flexible pavements rely heavily on unbound granular materials for their base and subbase layers,where their performance under repetitive loading is critical.This performance is gauged by two main parameters:resilient modulus and permanent deformation,which are influenced by both intrinsic material properties such as gradation,moisture content,and density and external factors such as applied stress and load repetitions.Over time,variations in these elements can lead to diminished strength and increased non-recoverable strain,highlighting the necessity for routine evaluation of the pavement's resilient behavior to maintain its longevity and durability.Given the practical difficulties of frequent field testing,computational models have emerged as vital tools for simulating the resilient modulus and predicting plastic strain,incorporating diverse influencing factors,and calibrated with lab and in-situ data.This paper delves into the properties affecting the resilient behavior of unbound granular pavement materials,emphasizing that stress level and moisture content significantly impact the resilient modulus,while load cycles and stress level notably influence permanent deformation.Central to this study is the exploration of the integrated effect of these factors on resilient behavior.Additionally,it evaluates the current landscape of computational modeling,showcasing the capabilities of the most used models for predicting these parameters through comparative analysis of existing literature.It suggests that to enhance pavement reliability and durability,models must evolve to include predictions on density and gradation for future improvement.This study further identifies key causes of pavement deterioration,helping develop targeted rehabilitation strategies and select accurate models for predicting resilience,ensuring robust pavement design.Furthermore,this review advances the field by merging new insights on the resilience of unbound granular materials with a critical evaluation of computational models.It introduces fresh perspectives and trends,bridging gaps in earlier reviews and paving the way for future research in pavement engineering.展开更多
Moisture accumulation within road pavements,particularly in unbound granular materials with or without thin sprayed seals,presents significant challenges in high-rainfall regions such as Queensland.This infiltration o...Moisture accumulation within road pavements,particularly in unbound granular materials with or without thin sprayed seals,presents significant challenges in high-rainfall regions such as Queensland.This infiltration often leads to various forms of pavement distress,eventually causing irreversible damage to the pavement structure.The moisture content within pavements exhibits considerable dynamism and directly influenced by environmental factors such as precipitation,air temperature,and relative humidity.This variability underscores the importance of monitoring moisture changes using real-time climatic data to assess pavement conditions for operational management or incorporating these effects during pavement design based on historical climate data.Consequently,there is an increasing demand for advanced,technology-driven methodologies to predict moisture variations based on climatic inputs.Addressing this gap,the present study employs five traditional machine learning(ML)algorithms,K-nearest neighbors(KNN),regression trees,random forest,support vector machines(SVMs),and gaussian process regression(GPR),to forecast moisture levels within pavement layers over time,with varying algorithm complexities.Using data collected from an instrumented road in Brisbane,Australia,which includes pavement moisture and climatic factors,the study develops predictive models to forecast moisture content at future time steps.The approach incorporates current moisture content,rather than averaged values,along with seasonality(both daily and annual),and key climatic factors to predict next step moisture.Model performance is evaluated using R2,MSE,RMSE,and MAPE metrics.Results show that ML algorithms can reliably predict long-term moisture variations in pavements,provided optimal hyperparameters are selected for each algorithm.The best-performing algorithms include KNN(the number of neighbours equals to 15),medium regression tree,medium random forest,coarse SVM,and simple GPR,with medium random forest outperforming the others.The study also identifies the optimal hyperparameter combinations for each algorithm,offering significant advancements in moisture prediction tools for pavement technology。展开更多
A state-of-the-art review was delivered in the manuscript to analyze the current situations and the advantages/disadvantages of resilient deformation related issues to the unbound granular material(UGM),including test...A state-of-the-art review was delivered in the manuscript to analyze the current situations and the advantages/disadvantages of resilient deformation related issues to the unbound granular material(UGM),including testing methods,influencing factors and constitutive models,through which the bottlenecks in UGM resilient deformation characterizations were located and new theories and future research recommendations were proposed.Compared with other testing methods,the hollow cylinder test and true triaxial test are the only two to determine the anisotropic moduli of the UGM.Although significant advantages are observed in more advanced test apparatus such as true triaxial test,further improvements should be made,such as more advanced process identification control algorithm,to more conveniently control the nine independent hydraulic system and accurately measure UGM anisotropic properties.Confusions and conflicts in understanding the influencing factors to UGM resilient modulus were located,such as the stress history,the residual stress,the dry density,the gradation/fine content and the freeze-thaw cycle,based on which future research could be conducted.Through reviewing evolutions of the UGM constitutive models and comparing their representativeness and complexity comprehensively,major drawbacks were discovered and a new theory was proposed afterward to modify the UGM constitutive model,although further validations are still needed.展开更多
Unbound granular materials(UGMs)are widely used as a base or a subbase in pavement construction.They are generally well graded and exhibit a higher peak strength than that of conventional cohesionless granular materia...Unbound granular materials(UGMs)are widely used as a base or a subbase in pavement construction.They are generally well graded and exhibit a higher peak strength than that of conventional cohesionless granular materials.By using a simplified version of granular solid hydrodynamics(GSH),a set of GSH material constants is determined for a UGM material.The deviatoric stress and volumetric strain caused by triaxial compression are calculated and then compared with experimental data.The results indicate that the GSH theory is able to describe such a special type of granular materials.展开更多
Unbound Granular Materials(UGM)base is widely used in permeable pavement structure for infiltration,water storage,and load bearing.However,because of large void content,UGM base easily deforms under repeated loads,res...Unbound Granular Materials(UGM)base is widely used in permeable pavement structure for infiltration,water storage,and load bearing.However,because of large void content,UGM base easily deforms under repeated loads,resulting in surface rutting and even reducing durability of permeable pavement.Thus,research on practical deformation prediction model of UGM base is necessary to improve the pavement structure design and evaluate the base layer construction quality.This study conducted laboratory and field tests to develop a deformation prediction model of UGM base under varied stress states.The deformation of UGM specimen was tested and analyzed through triaxial shear test and dynamic triaxial repeated load test,with varied confining pressures and Shear Stress-strength Ratios(SSR).A laboratory deformation model based on SSR was developed,and the linear relationship between total deformation and permanent deformation was obtained.The deformation of UGM base in situ was tested with Light Weight Deflectometer(LWD).The trends of laboratory deformation model and field test results were similar,and deformation prediction model for field was fitted.The values of parameters in permanent deformation model were recommended in varied stress ranges,based on mathematical analysis.Accordingly,the deformation of UGM base can be estimated.This study developed a model to estimate the permanent deformation of UGM based on deformation data from field and laboratory tests.展开更多
文摘Several studies have been conducted in the pavement area to try to understand the elastoplastic behavior of unbound granular materials(UGMs)under cyclic loading.This paper presents a literature review on the permanent deformation phenomenon of UGMs when they form granular layers in flexible pavement structures.The factors affecting the resistance to permanent deformation are presented and described,and the evolution of the mathematical equations most used to predict the deformation in these materials under cyclic loading is shown.Conclusions and recommendations for future studies are presented at the end of the manuscript.Despite the substantial number of researches carried out on the subject,the elastoplastic behavior of UGMs has not yet been fully understood.These heterogeneous and anisotropic materials change their behavior mainly with stress magnitude and water content,but they are also strongly dependent on the way factors such as gradation,density,porosity,morphology,chemical and mineralogical composition,temperature,among others,interact.Generally,most of the mathematical equations that try to predict the accumulation of permanent deformation in UGMs are empirical,based on repeated load triaxial(RLT)tests,they cannot simulate the three components of cyclic stress to which a UGM is subjected in a pavement,their parameters are difficult to determine experimentally and do not show physical meaning(they are obtained by regression).In recent years,studies to evaluate the use of recycled aggregates and the effect of temperature(mainly at low temperatures)have increased.Likewise,the use of various technological tools such as artificial neural network(ANN)modeling,and so forth,has increased.
文摘When a vehicle moves over a flexible pavement structure,it generates loading and unloading cycles that produce recoverable(resilient)and permanent(plastic)deformations in the granular base and subbase layers,which are made of unbound granular materials(UGMs).The primary parameter used to evaluate the resilient response of UGMs in pavements is the resilient modulus(MR).The MR is widely used in calculating stress-strain states for flexible pavement design and as a control parameter during the construction process.It is also employed to understand the progression of distresses,such as fatigue cracking and rutting.The main objective of this study was to conduct a literature review on the resilient behavior of UGMs.This manuscript presents and describes the MR and the factors that influence it.It also outlines the evolution of the mathematical equations most commonly used to estimate and predict this physical parameter.Conclusions and recommendations for future research are provided at the end of the article.Despite the large amount of research done on the subject,the resilient behavior of UGM has not yet been fully understood.This is since these materials are highly heterogeneous and show nonlinear-anisotropic behavior under different cyclic loading paths and water contents.Likewise,these materials undergo different behaviors depending on their macro and microscopic properties(gradation,density,porosity,texture,mineralogy,particle geometry and orientation,temperature,among others).On the other hand,the main limitation of the mathematical equations is that their parameters are difficult to determine experimentally and are not constants of the material(they are state variables that can change with multiple factors).Additionally,these equations do not consider the boundary conditions to which UGM in pavements are exposed.Moreover,they are obtained from repeated load triaxial(RLT)tests,which cannot simulate the three cyclic stress components(vertical,horizontal,and shear)to which UGMs are subjected in a pavement.In recent years,there has been an increase in studies evaluating the use of recycled aggregates and the effect of temperature(particularly at subzero temperatures),but more research is still needed to reach definitive conclusions.
文摘This study aims to quantify the susceptibility of granular materials used in pavements to changes in moisture content and propose a correlation model to incorporate this susceptibility into seasonal analyses.The fines content and the percentage of fractured coarse aggregates were identified as direct indicators of the resilient modulus susceptibility to changes in water content.The results showed that the percentage of fractured coarse aggregates particles(FR)has a more significant impact on the resilient modulus(Er)of crushed granular materials used in pavement construction than the combined indicator of the fines content and sample volumetrics(nf).Crushed granular materials with a higher percentage of fractured coarse aggregates are relatively insensitive to changes in the degree of saturation,but become more sensitive as the fine fraction porosity decreases.An adjusted model was proposed based on the existing formulation,but considers a complex parameter to describe and adjust the sensitivity of base granular materials to variations in moisture content with respect to fabrication charac-teristics,fines content and volumetric properties.The model shows that the variation of Er values is below10%for fully crushed granular materials.However,it reaches approximately±12%for materials with 75%of crushed coarse aggregates andþ40%and-25%for materials with FR=50%.This model could help select good ag-gregates characteristics and adjust grain-size distribution for environments where significant moisture content variations can occur in the pavement system,such as in the Province of Quebec(Canada).As it is based on pa-rameters that can be easily determined or estimated,it also represents a valuable tool for detailed design and analysis that can consider material characteristics.
基金the financial and intellectual support provided by Queensland University of Technology(QUT)through its Higher Degree Research Program,which was instrumental in facilitating the successful execution of this research study。
文摘Flexible pavements rely heavily on unbound granular materials for their base and subbase layers,where their performance under repetitive loading is critical.This performance is gauged by two main parameters:resilient modulus and permanent deformation,which are influenced by both intrinsic material properties such as gradation,moisture content,and density and external factors such as applied stress and load repetitions.Over time,variations in these elements can lead to diminished strength and increased non-recoverable strain,highlighting the necessity for routine evaluation of the pavement's resilient behavior to maintain its longevity and durability.Given the practical difficulties of frequent field testing,computational models have emerged as vital tools for simulating the resilient modulus and predicting plastic strain,incorporating diverse influencing factors,and calibrated with lab and in-situ data.This paper delves into the properties affecting the resilient behavior of unbound granular pavement materials,emphasizing that stress level and moisture content significantly impact the resilient modulus,while load cycles and stress level notably influence permanent deformation.Central to this study is the exploration of the integrated effect of these factors on resilient behavior.Additionally,it evaluates the current landscape of computational modeling,showcasing the capabilities of the most used models for predicting these parameters through comparative analysis of existing literature.It suggests that to enhance pavement reliability and durability,models must evolve to include predictions on density and gradation for future improvement.This study further identifies key causes of pavement deterioration,helping develop targeted rehabilitation strategies and select accurate models for predicting resilience,ensuring robust pavement design.Furthermore,this review advances the field by merging new insights on the resilience of unbound granular materials with a critical evaluation of computational models.It introduces fresh perspectives and trends,bridging gaps in earlier reviews and paving the way for future research in pavement engineering.
基金the financial and intellectual support provided by Queensland University of Technology(QUT),Australia,through its Higher Degree Research Program,which played a crucial role in the successful completion of this research study
文摘Moisture accumulation within road pavements,particularly in unbound granular materials with or without thin sprayed seals,presents significant challenges in high-rainfall regions such as Queensland.This infiltration often leads to various forms of pavement distress,eventually causing irreversible damage to the pavement structure.The moisture content within pavements exhibits considerable dynamism and directly influenced by environmental factors such as precipitation,air temperature,and relative humidity.This variability underscores the importance of monitoring moisture changes using real-time climatic data to assess pavement conditions for operational management or incorporating these effects during pavement design based on historical climate data.Consequently,there is an increasing demand for advanced,technology-driven methodologies to predict moisture variations based on climatic inputs.Addressing this gap,the present study employs five traditional machine learning(ML)algorithms,K-nearest neighbors(KNN),regression trees,random forest,support vector machines(SVMs),and gaussian process regression(GPR),to forecast moisture levels within pavement layers over time,with varying algorithm complexities.Using data collected from an instrumented road in Brisbane,Australia,which includes pavement moisture and climatic factors,the study develops predictive models to forecast moisture content at future time steps.The approach incorporates current moisture content,rather than averaged values,along with seasonality(both daily and annual),and key climatic factors to predict next step moisture.Model performance is evaluated using R2,MSE,RMSE,and MAPE metrics.Results show that ML algorithms can reliably predict long-term moisture variations in pavements,provided optimal hyperparameters are selected for each algorithm.The best-performing algorithms include KNN(the number of neighbours equals to 15),medium regression tree,medium random forest,coarse SVM,and simple GPR,with medium random forest outperforming the others.The study also identifies the optimal hyperparameter combinations for each algorithm,offering significant advancements in moisture prediction tools for pavement technology。
基金financed by Natural Science Foundation of Shaanxi Province,China (Grant Nos.2021JQ-280,2021JQ-293)Key Laboratory of Road and Traffic Engineering of the Ministry of Education,Tongji University (Grant No.K202102)+1 种基金National Natural Science Foundation of China (Grant No.51908057)Fundamental Research Funds for the Central Universities (Grant No.300102212211)。
文摘A state-of-the-art review was delivered in the manuscript to analyze the current situations and the advantages/disadvantages of resilient deformation related issues to the unbound granular material(UGM),including testing methods,influencing factors and constitutive models,through which the bottlenecks in UGM resilient deformation characterizations were located and new theories and future research recommendations were proposed.Compared with other testing methods,the hollow cylinder test and true triaxial test are the only two to determine the anisotropic moduli of the UGM.Although significant advantages are observed in more advanced test apparatus such as true triaxial test,further improvements should be made,such as more advanced process identification control algorithm,to more conveniently control the nine independent hydraulic system and accurately measure UGM anisotropic properties.Confusions and conflicts in understanding the influencing factors to UGM resilient modulus were located,such as the stress history,the residual stress,the dry density,the gradation/fine content and the freeze-thaw cycle,based on which future research could be conducted.Through reviewing evolutions of the UGM constitutive models and comparing their representativeness and complexity comprehensively,major drawbacks were discovered and a new theory was proposed afterward to modify the UGM constitutive model,although further validations are still needed.
基金The authors thank Prof.Yimin Jiang for scientific guidance and discussions.This work was supported by the National Key Basic Research Program of China(No.2010CB731504)the research funding from the State Key Laboratory of Hydroscience and Engineering,Tsinghua University(No.2010-TC-1).
文摘Unbound granular materials(UGMs)are widely used as a base or a subbase in pavement construction.They are generally well graded and exhibit a higher peak strength than that of conventional cohesionless granular materials.By using a simplified version of granular solid hydrodynamics(GSH),a set of GSH material constants is determined for a UGM material.The deviatoric stress and volumetric strain caused by triaxial compression are calculated and then compared with experimental data.The results indicate that the GSH theory is able to describe such a special type of granular materials.
基金supported by the National Key Research and Development Program of China(No.2018YFB1600100)the Fundamental Research Funds for the Central Universities(No.22120220177).
文摘Unbound Granular Materials(UGM)base is widely used in permeable pavement structure for infiltration,water storage,and load bearing.However,because of large void content,UGM base easily deforms under repeated loads,resulting in surface rutting and even reducing durability of permeable pavement.Thus,research on practical deformation prediction model of UGM base is necessary to improve the pavement structure design and evaluate the base layer construction quality.This study conducted laboratory and field tests to develop a deformation prediction model of UGM base under varied stress states.The deformation of UGM specimen was tested and analyzed through triaxial shear test and dynamic triaxial repeated load test,with varied confining pressures and Shear Stress-strength Ratios(SSR).A laboratory deformation model based on SSR was developed,and the linear relationship between total deformation and permanent deformation was obtained.The deformation of UGM base in situ was tested with Light Weight Deflectometer(LWD).The trends of laboratory deformation model and field test results were similar,and deformation prediction model for field was fitted.The values of parameters in permanent deformation model were recommended in varied stress ranges,based on mathematical analysis.Accordingly,the deformation of UGM base can be estimated.This study developed a model to estimate the permanent deformation of UGM based on deformation data from field and laboratory tests.
