Accurate prediction of performance decay law is an important basis for long-term planning of maintenance strategy.The statistical regression prediction model is the most widely employed method to calculate pavement pe...Accurate prediction of performance decay law is an important basis for long-term planning of maintenance strategy.The statistical regression prediction model is the most widely employed method to calculate pavement performance due to its advantages such as the small amount of calculation and good accuracy,but the traditional prediction model seems not applicable to the high maintenance level areas with excellent pavement conditions.In this paper,the service life and the cumulative number of the axle load were determined as the independent variables of prediction models of pavement performance.The pavement condition index(PCI)and rutting depth index(RDI)were selected as maintenance decision control indexes to establish the unified prediction model of PCI and RDI respectively by applying the cosine deterioration equation.Results reveal that the deterioration law of PCI presents an anti-S type or concave type and the deterioration law of RDI shows an obvious concave type.The prediction model proposed in this study added the pavement maintenance standard factor d,which brings the model parameterα(reflecting the road life)and the deterioration equations are more applicable than the traditional standard equations.It is found that the fitting effects of PCI and RDI prediction models with different traffic grades are relatively similar to the actual service state of the pavements.展开更多
Effective prediction of pavement performance is essential for transportation agencies to appropriately strategize maintenance,rehabilitation,and reconstruction of roads.One of the primary performance indicators is the...Effective prediction of pavement performance is essential for transportation agencies to appropriately strategize maintenance,rehabilitation,and reconstruction of roads.One of the primary performance indicators is the international roughness index(IRI) which represents the pavement roughness.Correlating the pavement roughness to other performance measures has been under continuous development in the past decade.However,the drawback of existing correlations is that most of them are not practical yet reliable for prediction of roughness.In this study a novel approach was developed to predict the IRI,utilizing two data sets extracted from long term pavement performance(LTPP) database.The proposed methodology included the application of a hybrid technique which combines the gene expression programming(GEP) and artificial neural network(ANN).The developed algorithm showed reasonable performance for prediction of IRI using traffic parameters and structural properties of pavement.Furthermore,estimation of present IRI from historical data was evaluated through another set of LTPP data.The second prediction model also depicted a reasonable performance power.Further extension of the proposed models including different pavement types,traffic and environmental conditions would be desirable in future studies.展开更多
Autonomous vehicles(AVs), including trucks, are already available and their adoption is coming at a rapid pace. Despite the fact that this new transportation technology will travel on existing pavement infrastructure ...Autonomous vehicles(AVs), including trucks, are already available and their adoption is coming at a rapid pace. Despite the fact that this new transportation technology will travel on existing pavement infrastructure assets, the study and investigation of the AVs structural impact on pavements has not reached the same level of attention and maturity as other related research areas. Considering the extensive investment on pavement construction and maintenance, the necessity to fully understand these impacts in the long term, is becoming evident. The present paper presents and discusses currently published relevant research and findings on the quantification of the wheel wander potential impact,both negative and positive, offering potential insightful future areas of enquiry to help mold and shape future research for this emerging field. The paper focuses on the impact of the AVs zero lateral wheel wander on both new flexible pavement design and the damage accumulation within existing flexible pavement structures. Other wheel wander distributions(normal, uniform, etc.) are investigated as well. The outcome and findings are that the AVs zero lateral wheel wander has a definable negative structural impact on flexible pavement structures in comparison to current human-driven(non-autonomous) vehicles that tend to follow a normal lateral wheel wander distribution. However, under certain defined conditions(optimal wheel wander distribution), the pavement service life can be potentially extended.展开更多
In order to improve the high temperature stability and low temperature cracking resistance of asphalt mixtures,two varieties of admixtures(anti-rutting agent and lignin fiber) were selected and then combined.This is c...In order to improve the high temperature stability and low temperature cracking resistance of asphalt mixtures,two varieties of admixtures(anti-rutting agent and lignin fiber) were selected and then combined.This is called double-mixture technology.A series of tests about pavement performance of base asphalt mixtures and asphalt mixtures with admixture of anti-rutting agent or lignin fiber were conducted.Meanwhile sensitivity analyses were used to study the influence of three factors(i.e.,asphalt grade,aggregate type and gradation) on the high and low temperature performance and water stability of said asphalt mixtures.Test results indicated that the dynamic stability,residual stability,TSR and low temperature failure strain of asphalt mixtures have increased significantly with the additions of 0.40% anti-rutting agent and 0.36% lignin fiber.These results show that the high and low temperature and water stabilities of asphalt mixtures improve obviously.This supports the beneficial comprehensive effect of the double admixture.The problem of improving the asphalt mixtures performance with a single admixture is solved,in addition to also improving other pavement performance.Based on the sensitivity analysis,the most influential factors of dynamic stability,low temperature failure strain and TSR are the gradation,followed by asphalt grade and aggregate type.展开更多
基金the National Key Research and Development Program of China with Grant No.2018YFB1600100the National Natural Science Foundation of China with Grant No.51978219 and No.51878228.
文摘Accurate prediction of performance decay law is an important basis for long-term planning of maintenance strategy.The statistical regression prediction model is the most widely employed method to calculate pavement performance due to its advantages such as the small amount of calculation and good accuracy,but the traditional prediction model seems not applicable to the high maintenance level areas with excellent pavement conditions.In this paper,the service life and the cumulative number of the axle load were determined as the independent variables of prediction models of pavement performance.The pavement condition index(PCI)and rutting depth index(RDI)were selected as maintenance decision control indexes to establish the unified prediction model of PCI and RDI respectively by applying the cosine deterioration equation.Results reveal that the deterioration law of PCI presents an anti-S type or concave type and the deterioration law of RDI shows an obvious concave type.The prediction model proposed in this study added the pavement maintenance standard factor d,which brings the model parameterα(reflecting the road life)and the deterioration equations are more applicable than the traditional standard equations.It is found that the fitting effects of PCI and RDI prediction models with different traffic grades are relatively similar to the actual service state of the pavements.
文摘Effective prediction of pavement performance is essential for transportation agencies to appropriately strategize maintenance,rehabilitation,and reconstruction of roads.One of the primary performance indicators is the international roughness index(IRI) which represents the pavement roughness.Correlating the pavement roughness to other performance measures has been under continuous development in the past decade.However,the drawback of existing correlations is that most of them are not practical yet reliable for prediction of roughness.In this study a novel approach was developed to predict the IRI,utilizing two data sets extracted from long term pavement performance(LTPP) database.The proposed methodology included the application of a hybrid technique which combines the gene expression programming(GEP) and artificial neural network(ANN).The developed algorithm showed reasonable performance for prediction of IRI using traffic parameters and structural properties of pavement.Furthermore,estimation of present IRI from historical data was evaluated through another set of LTPP data.The second prediction model also depicted a reasonable performance power.Further extension of the proposed models including different pavement types,traffic and environmental conditions would be desirable in future studies.
基金the European Union (European Social FundeE SF) through the operational programme “Human Resources Development, Education and Lifelong Learning” in the context of the project “Reinforcement of Postdoctoral Researcherse2nd Cycle” (MIS5033021), implemented by the State Scholarships Foundation (IΚY)。
文摘Autonomous vehicles(AVs), including trucks, are already available and their adoption is coming at a rapid pace. Despite the fact that this new transportation technology will travel on existing pavement infrastructure assets, the study and investigation of the AVs structural impact on pavements has not reached the same level of attention and maturity as other related research areas. Considering the extensive investment on pavement construction and maintenance, the necessity to fully understand these impacts in the long term, is becoming evident. The present paper presents and discusses currently published relevant research and findings on the quantification of the wheel wander potential impact,both negative and positive, offering potential insightful future areas of enquiry to help mold and shape future research for this emerging field. The paper focuses on the impact of the AVs zero lateral wheel wander on both new flexible pavement design and the damage accumulation within existing flexible pavement structures. Other wheel wander distributions(normal, uniform, etc.) are investigated as well. The outcome and findings are that the AVs zero lateral wheel wander has a definable negative structural impact on flexible pavement structures in comparison to current human-driven(non-autonomous) vehicles that tend to follow a normal lateral wheel wander distribution. However, under certain defined conditions(optimal wheel wander distribution), the pavement service life can be potentially extended.
基金funded by the National Natural Science Foundation of China(No.51108038 and No.51108039)the Special Fund for Basic Scientific Research of Central Colleges,Chang'an University(310821152004)Shaanxi Science and Technology Research Development Project(No.2013KJXX94 and No.2013KW24)
文摘In order to improve the high temperature stability and low temperature cracking resistance of asphalt mixtures,two varieties of admixtures(anti-rutting agent and lignin fiber) were selected and then combined.This is called double-mixture technology.A series of tests about pavement performance of base asphalt mixtures and asphalt mixtures with admixture of anti-rutting agent or lignin fiber were conducted.Meanwhile sensitivity analyses were used to study the influence of three factors(i.e.,asphalt grade,aggregate type and gradation) on the high and low temperature performance and water stability of said asphalt mixtures.Test results indicated that the dynamic stability,residual stability,TSR and low temperature failure strain of asphalt mixtures have increased significantly with the additions of 0.40% anti-rutting agent and 0.36% lignin fiber.These results show that the high and low temperature and water stabilities of asphalt mixtures improve obviously.This supports the beneficial comprehensive effect of the double admixture.The problem of improving the asphalt mixtures performance with a single admixture is solved,in addition to also improving other pavement performance.Based on the sensitivity analysis,the most influential factors of dynamic stability,low temperature failure strain and TSR are the gradation,followed by asphalt grade and aggregate type.
