Falling weight deflectometer （FWD） testing has been used to evaluate structural condition of pavements to predict the layer moduli using backcalculation process. However, the predicted pavement layer moduli sometime...Falling weight deflectometer （FWD） testing has been used to evaluate structural condition of pavements to predict the layer moduli using backcalculation process. However, the predicted pavement layer moduli sometimes may not be accurate even if computed and measured deflection basin has fulfilled the standard and is in concurrence with certain tolerable limits. The characteristics of pavement structure, including pavement layer thickness condition and temperature variation, affect the predicted pavement structural capacity and back calculated layer modulus. The main objective of this study is to analyze the FVc＇D test results of flexible pavement in Western Australia to predict the pavement structural capacity. Collected data includes, in addition to FWD measurements, core data and pavement distress surveys. Results showed that the dynamic analysis of falling weight deflectometer test and prediction for the strength of character of flexible pavement layer moduli have been achieved, and algorithms for interpretation of the deflection basin have been improved. The variations of moduli of all layers along the length of sections for majority of the projects are accurate and consistent with measured and computed pre- diction. However, some of the projects had some inconsistent with modulus values along the length of the sections. Results are reasonable but consideration should be taken to fix varied pavement layers moduli sections.展开更多
A comparative subgrade moduli study is carried out by static and dynamic deflection methods using lightweight deflectometer and conventional Benkelman beam deflec- tometer on low volume road. Field and laboratory test...A comparative subgrade moduli study is carried out by static and dynamic deflection methods using lightweight deflectometer and conventional Benkelman beam deflec- tometer on low volume road. Field and laboratory tests are performed at 40 test locations on in-service road of 2 km stretch that contains three common types of cohesive soils （CH, CI, and CL）. Pavement static and dynamic responses are estimated to ascertain static, backcalculated, and composite moduli of subgrade. The backcalculated and composite moduli of subgrade is validated at given moisture content using repeated triaxial test. Static moduli values are on lower side as compared with dynamic moduli values whereas the composite, and laboratory moduli of subgrade are approximately consistent with 2% to 7% variation, respectively. Correlation analyses between static and dynamic moduli of different types of subgrade soils depict good correlation of determination （R2） varies between 0.75 and 0.91. Subsequently, validation of static moduli with California bearing ratio （CBR） related subgrade moduli shows moderate correlation of 0.67 to 0.74 whereas dynamic moduli shows good correlation of 0.74 to 0.93 for different types of soils, respectively. Therefore, the comparative analysis shows that lightweight deflectometer provides reliable subgrade moduli values, and it can be used as a quick subgrade strength evaluating tool for low volume roads.展开更多
An extensive experimental-mechanistic study was conducted to reveal the relationship between the light weight deflectometer(LWD)measured deflections and the degree of compaction of pavement base materials.Both laborat...An extensive experimental-mechanistic study was conducted to reveal the relationship between the light weight deflectometer(LWD)measured deflections and the degree of compaction of pavement base materials.Both laboratory experiments and test pits experiments were performed with different types of pavement base materials.The modulus based maximum allowable LWD deflections under different structural and compaction conditions were developed for the most commonly used pavement base aggregate in Indiana.The maximum allowable deflections are based on the equivalent subgrade modulus and the thickness of the layer to be compacted.It is emphasized that the LWD deflections must be measured as soon as the material is compacted or before the moisture content decreases beyond a specified range.Therefore,the maximum allowable deflections are specified in terms of the difference between the actual moisture content and the optimum moisture content.The maximum allowable deflection values provide a sound basis for compaction quality control using LWD devices.展开更多
A falling weight deflectometer is a testing device used in civil engineering to measure and evaluate the physical properties of pavements,such as the modulus of the subgrade reaction(Y1)and the elastic modulus of the ...A falling weight deflectometer is a testing device used in civil engineering to measure and evaluate the physical properties of pavements,such as the modulus of the subgrade reaction(Y1)and the elastic modulus of the slab(Y2),which are crucial for assessing the structural strength of pavements.In this study,we developed a novel hybrid artificial intelligence model,i.e.,a genetic algorithm(GA)-optimized adaptive neuro-fuzzy inference system(ANFIS-GA),to predict Y1 and Y2 based on easily determined 13 parameters of rigid pavements.The performance of the novel ANFIS-GA model was compared to that of other benchmark models,namely logistic regression(LR)and radial basis function regression(RBFR)algorithms.These models were validated using standard statistical measures,namely,the coefficient of correlation(R),mean absolute error(MAE),and root mean square error(RMSE).The results indicated that the ANFIS-GA model was the best at predicting Y1(R=0.945)and Y2(R=0.887)compared to the LR and RBFR models.Therefore,the ANFIS-GA model can be used to accurately predict Y1 and Y2 based on easily measured parameters for the appropriate and rapid assessment of the quality and strength of pavements.展开更多
Effective pavement maintenance and rehabilitation decisions rely on both pavement functional and structural condition data. Traditionally, state transportation agencies prioritize pavement segments based on functional...Effective pavement maintenance and rehabilitation decisions rely on both pavement functional and structural condition data. Traditionally, state transportation agencies prioritize pavement segments based on functional conditions, often neglecting structural assessments due to the time, cost, and labor involved with methods like the Falling Weight Deflectometer (FWD). The objective of this paper to develop machine learning models—Random Forest (RF) and eXtreme Gradient Boosting (XGBoost)—to predict pavement Surface Curvature Index (SCI), a key indicator of pavement structural condition, as a cost-effective alternative to frequent FWD testing. Using 3016 samples from the Long-Term Pavement Performance (LTPP) program, the models were trained and tested with variables such as surface layer condition at year 0, thickness, pavement age, environmental, and traffic data. XGBoost outperformed RF, achieving R2, RMSE, and MAE values of 0.90, 0.64, and 0.41, respectively, compared to RF’s 0.80, 0.90, and 0.51. The study highlights the importance of machine learning applications in predicting pavement structural conditions, offering precise models that can help transportation agencies optimize maintenance planning and resource allocation.展开更多
To relieve the increasing traffic load, many early built highways need to be widened or reconstructed. The rapid performance detection to existing subgrades is important to their reasonable evaluation and maximized ut...To relieve the increasing traffic load, many early built highways need to be widened or reconstructed. The rapid performance detection to existing subgrades is important to their reasonable evaluation and maximized utilization. Based on five kinds of soils taken from an existing highway in southern China, three commonly detecting methods were used to determine their moisture contents, compaction degrees and resilient moduli. The results showed that the measured moisture contents were greater than the design value, and the compaction degrees decreased sharply compared to the original ones. The moisture and heat exchange produced a decrease in the resilient modulus of plate loading test(PLT) from the standard 60 MPa down to 40 MPa. Afterwards, the portable falling weight deflectometer(PFWD) and dynamic cone penetrometer(DCP) were used to evaluate the subgrade performances. The measured PFWD moduli and the DCP penetration rates were correlated with the resilient moduli of PLT, deflections of the Beckman beam test, compaction degrees and moisture contents. The correlation analysis indicates that both of two methods are suitable in rapid detecting subgrade performances, but PFWD method is more recommended for it has higher accuracy and efficiency.展开更多
By using the falling weight deflectometer（FWD）,the dynamic loading tests on different thickness of asphalt mixture pavement in different temperature were performed.The experimental results show that the effects of t...By using the falling weight deflectometer（FWD）,the dynamic loading tests on different thickness of asphalt mixture pavement in different temperature were performed.The experimental results show that the effects of temperature on dynamic properties of asphalt mixture are significant,and the thickness of asphalt mixture is also another important influence factor.The comparisons indicate that effect of temperature on the behaviors of dynamic loading properties and static loading properties of asphalt mixture were quite different.展开更多
Based on system identification theory and FWD testing data, the effect of thickness error on backcalculating pavement layer moduli is studied and the method of singular value decomposition (SVD) is presented to solve ...Based on system identification theory and FWD testing data, the effect of thickness error on backcalculating pavement layer moduli is studied and the method of singular value decomposition (SVD) is presented to solve the morbidity problem of sensitivity matrix in this paper.The results show that the thickness error has great effects on the backcalculated pavement layer moduli. The error of backcalculated moduli can be controlled within the range of ±15% by limiting the thickness error within the range of ±5%.展开更多
The pavement layered structures are composed of surface layer,road base and multi-layered soil foundation.They can be undermined over time by repeated vehicle loads.In this study,a hybrid numerical method which can ev...The pavement layered structures are composed of surface layer,road base and multi-layered soil foundation.They can be undermined over time by repeated vehicle loads.In this study,a hybrid numerical method which can evaluate the displacement responses of pavement structures under dynamic falling weight deflectometer(FWD)loads.The proposed method consists of two parts:(a)the dynamic stiffness matrices of the points at the surface in the frequency domain which is based on the domain-transformation and dual vector form equation,and(b)interpolates the dynamic stiffness matrices by a continues rational function of frequency.The mixed variables formulation(MVF)can treat multiple degree of freedom systems with considering the coupling term between degree of freedoms.The accuracy of the developed method has been demonstrated by comparison between the proposed method and published results from the other method.Then the proposed method can be applied as a forward calculation technique to emulate the falling weight deflectometer test for multi-layered pavement structures.展开更多
Previous research studies have successfully demonstrated the use of artificial neural network (ANN) models for predicting critical structural responses and layer moduli of highway flexible pavements. The primary objec...Previous research studies have successfully demonstrated the use of artificial neural network (ANN) models for predicting critical structural responses and layer moduli of highway flexible pavements. The primary objective of this study was to develop an ANN-based approach for backcalculation of pavement moduli based on heavy weight deflectometer (HWD) test data, especially in the analysis of airport flexible pavements subjected to new generation aircraft (NGA). Two medium-strength sub-grade flexible test sections, at the National Airport Pavement Test Facility (NAPTF), were modeled using a finite element (FE) based pavement analysis program, which can consider the non-linear stress-dependent behavior of pavement geomaterials. A multi-layer, feed-forward network which uses an error-backpropagation algorithm was trained to approximate the HWD back-calculation function using the FE program generated synthetic database. At the NAPTF, test sections were subjected to Boeing 777 (B777) trafficking on one lane and Boeing 747 (B747) trafficking on the other lane using a test machine. To monitor the effect of traffic and climatic variations on pavement structural responses, HWD tests were conducted on the trafficked lanes and on the untrafficked centerline of test sections as trafficking progressed. The trained ANN models were successfully applied on the actual HWD test data acquired at the NAPTF to predict the asphalt concrete moduli and non-linear subgrade moduli of the me-dium-strength subgrade flexible test sections.展开更多
Rubblization technique has been extensively used to repair the damaged concrete pavement and has proven successful in developed countries like the US and Europe. It has not been fully adopted in developing region like...Rubblization technique has been extensively used to repair the damaged concrete pavement and has proven successful in developed countries like the US and Europe. It has not been fully adopted in developing region like the Middle East and this paper presents the design and construction challenges posed while assessing damaged concrete runway in empty quarter of Saudi Arabia. <span style="font-family:Verdana;">A number of design options for repairs for runway pavement were consi</span><span style="font-family:Verdana;">dered and rubblization was chosen as a preferred option for repair. This paper includes the consideration for the assessment and adoption of the concrete rubblized modulus value using the falling weight deflectometer, optimization </span><span style="font-family:Verdana;">of the tests for the whole runway using the Heavy Weight Deflectometer</span><span style="font-family:Verdana;"> HWD testing to replace pits, safely working around the utilities, reasonable assumption of drop height of the pavement and installation of utility conduits in the rubblized layer. Findings of the paper demonstrates resolving</span><span><span><span style="font-family:;" "=""> </span></span></span><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;">technical issues which are not very well covered in the Federal Aviation Authority (FAA) EB-66 such as the additional test strips, minimum areas of rubblization for assessment using test pits, drop in the height of concrete surface and fixing of utilities in rubblized pavement. The case study demonstrates that the rubblization can be successfully carried out in remote locations like empty quarter of Saudi Arabia with carefully carried out detailed site investigations, adopt</span><span style="font-family:Verdana;">ing correct assumed design rubblization modulus, quality control using </span><span style="font-family:Verdana;">HWD, protection of utilities while rubblizing and use of polymer modified asphalt for successful project deployment.</span></span></span></span>展开更多
Railway transitions experience differential movements due to differences in track system stiffness,track damping characteristics,foundation type,ballast settlement from fouling and/or degradation,as well as fill and s...Railway transitions experience differential movements due to differences in track system stiffness,track damping characteristics,foundation type,ballast settlement from fouling and/or degradation,as well as fill and subgrade settlement.This differential movement is especially problematic for high speed rail infrastructure as the 'bump' at the transition is accentuated at high speeds.Identification of different factors contributing towards this differential movement,as well as development of design and maintenance strategies to mitigate the problem is imperative for the safe and economical operation of both freight and passenger rail networks.This paper presents the research framework and initial instrumentation details from an ongoing research effort at the University of Illinois at Urbana-Champaign.Three bridge approaches experiencing recurrent geometry problems were instrumented using multidepth deflectometers(MDDs) and strain gages to identify different factors contributing to the development of differential movements.展开更多
The modulus deviation of base material calculated from the data of falling weight deflectometer （FWD） was used to evaluate the uniformity of road base so as to reflect the construction quality. Four parameters,the r...The modulus deviation of base material calculated from the data of falling weight deflectometer （FWD） was used to evaluate the uniformity of road base so as to reflect the construction quality. Four parameters,the repeatability standard deviation of the data in the same driveway, the reproducibility standard deviation of the data in the different driveway, the consistency statistics value of the data in the different driveway, and the consistency statistics value of the data in the same driveway, were introduced for the construction uniformity analysis. The experimental result shows that the materials modulus calculated from FWD has a highly correlative relationship with the uniformity of road base.展开更多
Maputo Airport was initially constructed to serve mixed traffic of light and medium aircrafts. With its opening to heavier aircrafts such as B727, DC10, Airbus 340, etc. , structural improvements have become necessary...Maputo Airport was initially constructed to serve mixed traffic of light and medium aircrafts. With its opening to heavier aircrafts such as B727, DC10, Airbus 340, etc. , structural improvements have become necessary. For this purpose, structural evaluation were described and performed using falling weight deflectometer. Results show that while subgrade response to loads appears more consistent with depth, surface layer of the pavement is significantly influenced by the layer thickness as well as mechanical properties of pavement materials. Load magnitude also affects pavement performance. But loading conditions show an equivalent or even greater influence on pavement performance.展开更多
Various technical studies have shown that impact-stiffness modulus values, defined as the ratio of the FWD （falling-weight deflectometer） impact load to its consequent central deflection, can be used to evaluate the...Various technical studies have shown that impact-stiffness modulus values, defined as the ratio of the FWD （falling-weight deflectometer） impact load to its consequent central deflection, can be used to evaluate the PCN （pavement classification number） of a particular flexible or rigid airport pavement, fn a previous study, use was made of the old dynamic stiffness modulus procedure developed by the USCOE （US Army Corps of Engineers）, this procedure was correlated with various FWD measurements conducted on several runways and taxiways in Israel, together with in-situ borings and the use of the new COMFAA-3.0 software. The results, obtained only for flexible pavements, were checked against the relevant results of full-scale trafficking tests conducted by the FAA （Federal Administration Aviation） at its National Airport Pavement Test Facility. The present study analyzes new FWD measurements and in-situ borings conducted on additional rigid and all-asphaltic runways and taxiways in Israel in order to formulate an updated correlative equation for these types of pavements. The paper concludes with an updated recommendation for the use of impact-stiffness modulus outputs from FWD measurements in order to determine the PCN of any type of pavement directly on the basis of local experience.展开更多
Aiming at the assessment of road structural conditions,a method of combining ground penetrating radar(GPR)and falling weight deflectometer(FWD)for assessing the pavement structural integrity and strength was proposed ...Aiming at the assessment of road structural conditions,a method of combining ground penetrating radar(GPR)and falling weight deflectometer(FWD)for assessing the pavement structural integrity and strength was proposed in this study.First,3D GPR was performed to detect the thickness and internal distress of pavement structural layers using the canny edge detection and you only look once version eight(YOLOv8)detection algorithms.Results showed that the error of thickness extraction was approximately 3%,and the distress detection achieved a mean average precision(m AP)of 0.859 and an inference time of11.43 ms with a GTX 1070 GPU.Then,the extracted thickness was used for the modulus(E)inversion of pavement structure layers based on FWD test data and regression analysis.Finally,the distress ratio inside pavement structures(DRIPS)was proposed as a structural integrity index.The relationship between E and DRIPS was revealed and showed a good correlation.The greater the DRIPS value,the worse the pavement structural integrity and strength.It provides a reference for the evaluation of road structural conditions.This strategy proved to be reliable for nondestructive testing and evaluation of road structures,which could improve the comprehensiveness and effectiveness for evaluating road structural conditions.展开更多
基金financial support by Australia GovernmentCurtin University
文摘Falling weight deflectometer （FWD） testing has been used to evaluate structural condition of pavements to predict the layer moduli using backcalculation process. However, the predicted pavement layer moduli sometimes may not be accurate even if computed and measured deflection basin has fulfilled the standard and is in concurrence with certain tolerable limits. The characteristics of pavement structure, including pavement layer thickness condition and temperature variation, affect the predicted pavement structural capacity and back calculated layer modulus. The main objective of this study is to analyze the FVc＇D test results of flexible pavement in Western Australia to predict the pavement structural capacity. Collected data includes, in addition to FWD measurements, core data and pavement distress surveys. Results showed that the dynamic analysis of falling weight deflectometer test and prediction for the strength of character of flexible pavement layer moduli have been achieved, and algorithms for interpretation of the deflection basin have been improved. The variations of moduli of all layers along the length of sections for majority of the projects are accurate and consistent with measured and computed pre- diction. However, some of the projects had some inconsistent with modulus values along the length of the sections. Results are reasonable but consideration should be taken to fix varied pavement layers moduli sections.
文摘A comparative subgrade moduli study is carried out by static and dynamic deflection methods using lightweight deflectometer and conventional Benkelman beam deflec- tometer on low volume road. Field and laboratory tests are performed at 40 test locations on in-service road of 2 km stretch that contains three common types of cohesive soils （CH, CI, and CL）. Pavement static and dynamic responses are estimated to ascertain static, backcalculated, and composite moduli of subgrade. The backcalculated and composite moduli of subgrade is validated at given moisture content using repeated triaxial test. Static moduli values are on lower side as compared with dynamic moduli values whereas the composite, and laboratory moduli of subgrade are approximately consistent with 2% to 7% variation, respectively. Correlation analyses between static and dynamic moduli of different types of subgrade soils depict good correlation of determination （R2） varies between 0.75 and 0.91. Subsequently, validation of static moduli with California bearing ratio （CBR） related subgrade moduli shows moderate correlation of 0.67 to 0.74 whereas dynamic moduli shows good correlation of 0.74 to 0.93 for different types of soils, respectively. Therefore, the comparative analysis shows that lightweight deflectometer provides reliable subgrade moduli values, and it can be used as a quick subgrade strength evaluating tool for low volume roads.
基金supported in part by the Joint Transportation Research Program administered by the Indiana Department of Transportation and Purdue University。
文摘An extensive experimental-mechanistic study was conducted to reveal the relationship between the light weight deflectometer(LWD)measured deflections and the degree of compaction of pavement base materials.Both laboratory experiments and test pits experiments were performed with different types of pavement base materials.The modulus based maximum allowable LWD deflections under different structural and compaction conditions were developed for the most commonly used pavement base aggregate in Indiana.The maximum allowable deflections are based on the equivalent subgrade modulus and the thickness of the layer to be compacted.It is emphasized that the LWD deflections must be measured as soon as the material is compacted or before the moisture content decreases beyond a specified range.Therefore,the maximum allowable deflections are specified in terms of the difference between the actual moisture content and the optimum moisture content.The maximum allowable deflection values provide a sound basis for compaction quality control using LWD devices.
基金We acknowledge the support provided by the University of Transport Technology.
文摘A falling weight deflectometer is a testing device used in civil engineering to measure and evaluate the physical properties of pavements,such as the modulus of the subgrade reaction(Y1)and the elastic modulus of the slab(Y2),which are crucial for assessing the structural strength of pavements.In this study,we developed a novel hybrid artificial intelligence model,i.e.,a genetic algorithm(GA)-optimized adaptive neuro-fuzzy inference system(ANFIS-GA),to predict Y1 and Y2 based on easily determined 13 parameters of rigid pavements.The performance of the novel ANFIS-GA model was compared to that of other benchmark models,namely logistic regression(LR)and radial basis function regression(RBFR)algorithms.These models were validated using standard statistical measures,namely,the coefficient of correlation(R),mean absolute error(MAE),and root mean square error(RMSE).The results indicated that the ANFIS-GA model was the best at predicting Y1(R=0.945)and Y2(R=0.887)compared to the LR and RBFR models.Therefore,the ANFIS-GA model can be used to accurately predict Y1 and Y2 based on easily measured parameters for the appropriate and rapid assessment of the quality and strength of pavements.
文摘Effective pavement maintenance and rehabilitation decisions rely on both pavement functional and structural condition data. Traditionally, state transportation agencies prioritize pavement segments based on functional conditions, often neglecting structural assessments due to the time, cost, and labor involved with methods like the Falling Weight Deflectometer (FWD). The objective of this paper to develop machine learning models—Random Forest (RF) and eXtreme Gradient Boosting (XGBoost)—to predict pavement Surface Curvature Index (SCI), a key indicator of pavement structural condition, as a cost-effective alternative to frequent FWD testing. Using 3016 samples from the Long-Term Pavement Performance (LTPP) program, the models were trained and tested with variables such as surface layer condition at year 0, thickness, pavement age, environmental, and traffic data. XGBoost outperformed RF, achieving R2, RMSE, and MAE values of 0.90, 0.64, and 0.41, respectively, compared to RF’s 0.80, 0.90, and 0.51. The study highlights the importance of machine learning applications in predicting pavement structural conditions, offering precise models that can help transportation agencies optimize maintenance planning and resource allocation.
基金Project(2017YFC0805307) supported by the National Key Research and Development Program of ChinaProjects(51878078, 51927814, 51911530215) supported by the National Natural Science Foundation of China+4 种基金Project(2018-025) supported by the Training Program for High-level Technical Personnel in Transportation Industry, ChinaProject (2018JJ1026) supported by the Excellent Youth Foundation of Natural Science Foundation of Hunan Province, ChinaProject(17A008) supported by the Key Project of Education Department of Hunan Province, ChinaProjects(kfj150103, kfj170104) supported by the Open Research Fund of State Engineering Laboratory of Highway Maintenance Technology, Changsha University of Science & Technology, ChinaProject(CX20190644) supported by the Postgraduate Scientific Research Innovation Project of Hunan Province, China。
文摘To relieve the increasing traffic load, many early built highways need to be widened or reconstructed. The rapid performance detection to existing subgrades is important to their reasonable evaluation and maximized utilization. Based on five kinds of soils taken from an existing highway in southern China, three commonly detecting methods were used to determine their moisture contents, compaction degrees and resilient moduli. The results showed that the measured moisture contents were greater than the design value, and the compaction degrees decreased sharply compared to the original ones. The moisture and heat exchange produced a decrease in the resilient modulus of plate loading test(PLT) from the standard 60 MPa down to 40 MPa. Afterwards, the portable falling weight deflectometer(PFWD) and dynamic cone penetrometer(DCP) were used to evaluate the subgrade performances. The measured PFWD moduli and the DCP penetration rates were correlated with the resilient moduli of PLT, deflections of the Beckman beam test, compaction degrees and moisture contents. The correlation analysis indicates that both of two methods are suitable in rapid detecting subgrade performances, but PFWD method is more recommended for it has higher accuracy and efficiency.
基金Funded by the Science and Technology Program of Communications Department of Henan Province (No.200612)
文摘By using the falling weight deflectometer（FWD）,the dynamic loading tests on different thickness of asphalt mixture pavement in different temperature were performed.The experimental results show that the effects of temperature on dynamic properties of asphalt mixture are significant,and the thickness of asphalt mixture is also another important influence factor.The comparisons indicate that effect of temperature on the behaviors of dynamic loading properties and static loading properties of asphalt mixture were quite different.
文摘Based on system identification theory and FWD testing data, the effect of thickness error on backcalculating pavement layer moduli is studied and the method of singular value decomposition (SVD) is presented to solve the morbidity problem of sensitivity matrix in this paper.The results show that the thickness error has great effects on the backcalculated pavement layer moduli. The error of backcalculated moduli can be controlled within the range of ±15% by limiting the thickness error within the range of ±5%.
基金The authors are grateful for the financial support of the National Key Research and Development Program of China(No.2016YFC0802400)the National Natural Science Foundation of China under Grant No.(51508203,51678536,41404096)+2 种基金the Outstanding Young Talent Research Fund of Zhengzhou University(1621323001)Program for Innovative Research Team(in Science and Technology)in University of Henan Province(18IRTSTHN007)the Program for Science and Technology Innovation Talents in Universities of Henan Province(Grant No.19HASTIT043),and the authors extend their sincere gratitude.
文摘The pavement layered structures are composed of surface layer,road base and multi-layered soil foundation.They can be undermined over time by repeated vehicle loads.In this study,a hybrid numerical method which can evaluate the displacement responses of pavement structures under dynamic falling weight deflectometer(FWD)loads.The proposed method consists of two parts:(a)the dynamic stiffness matrices of the points at the surface in the frequency domain which is based on the domain-transformation and dual vector form equation,and(b)interpolates the dynamic stiffness matrices by a continues rational function of frequency.The mixed variables formulation(MVF)can treat multiple degree of freedom systems with considering the coupling term between degree of freedoms.The accuracy of the developed method has been demonstrated by comparison between the proposed method and published results from the other method.Then the proposed method can be applied as a forward calculation technique to emulate the falling weight deflectometer test for multi-layered pavement structures.
文摘Previous research studies have successfully demonstrated the use of artificial neural network (ANN) models for predicting critical structural responses and layer moduli of highway flexible pavements. The primary objective of this study was to develop an ANN-based approach for backcalculation of pavement moduli based on heavy weight deflectometer (HWD) test data, especially in the analysis of airport flexible pavements subjected to new generation aircraft (NGA). Two medium-strength sub-grade flexible test sections, at the National Airport Pavement Test Facility (NAPTF), were modeled using a finite element (FE) based pavement analysis program, which can consider the non-linear stress-dependent behavior of pavement geomaterials. A multi-layer, feed-forward network which uses an error-backpropagation algorithm was trained to approximate the HWD back-calculation function using the FE program generated synthetic database. At the NAPTF, test sections were subjected to Boeing 777 (B777) trafficking on one lane and Boeing 747 (B747) trafficking on the other lane using a test machine. To monitor the effect of traffic and climatic variations on pavement structural responses, HWD tests were conducted on the trafficked lanes and on the untrafficked centerline of test sections as trafficking progressed. The trained ANN models were successfully applied on the actual HWD test data acquired at the NAPTF to predict the asphalt concrete moduli and non-linear subgrade moduli of the me-dium-strength subgrade flexible test sections.
文摘Rubblization technique has been extensively used to repair the damaged concrete pavement and has proven successful in developed countries like the US and Europe. It has not been fully adopted in developing region like the Middle East and this paper presents the design and construction challenges posed while assessing damaged concrete runway in empty quarter of Saudi Arabia. <span style="font-family:Verdana;">A number of design options for repairs for runway pavement were consi</span><span style="font-family:Verdana;">dered and rubblization was chosen as a preferred option for repair. This paper includes the consideration for the assessment and adoption of the concrete rubblized modulus value using the falling weight deflectometer, optimization </span><span style="font-family:Verdana;">of the tests for the whole runway using the Heavy Weight Deflectometer</span><span style="font-family:Verdana;"> HWD testing to replace pits, safely working around the utilities, reasonable assumption of drop height of the pavement and installation of utility conduits in the rubblized layer. Findings of the paper demonstrates resolving</span><span><span><span style="font-family:;" "=""> </span></span></span><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;">technical issues which are not very well covered in the Federal Aviation Authority (FAA) EB-66 such as the additional test strips, minimum areas of rubblization for assessment using test pits, drop in the height of concrete surface and fixing of utilities in rubblized pavement. The case study demonstrates that the rubblization can be successfully carried out in remote locations like empty quarter of Saudi Arabia with carefully carried out detailed site investigations, adopt</span><span style="font-family:Verdana;">ing correct assumed design rubblization modulus, quality control using </span><span style="font-family:Verdana;">HWD, protection of utilities while rubblizing and use of polymer modified asphalt for successful project deployment.</span></span></span></span>
文摘Railway transitions experience differential movements due to differences in track system stiffness,track damping characteristics,foundation type,ballast settlement from fouling and/or degradation,as well as fill and subgrade settlement.This differential movement is especially problematic for high speed rail infrastructure as the 'bump' at the transition is accentuated at high speeds.Identification of different factors contributing towards this differential movement,as well as development of design and maintenance strategies to mitigate the problem is imperative for the safe and economical operation of both freight and passenger rail networks.This paper presents the research framework and initial instrumentation details from an ongoing research effort at the University of Illinois at Urbana-Champaign.Three bridge approaches experiencing recurrent geometry problems were instrumented using multidepth deflectometers(MDDs) and strain gages to identify different factors contributing to the development of differential movements.
文摘The modulus deviation of base material calculated from the data of falling weight deflectometer （FWD） was used to evaluate the uniformity of road base so as to reflect the construction quality. Four parameters,the repeatability standard deviation of the data in the same driveway, the reproducibility standard deviation of the data in the different driveway, the consistency statistics value of the data in the different driveway, and the consistency statistics value of the data in the same driveway, were introduced for the construction uniformity analysis. The experimental result shows that the materials modulus calculated from FWD has a highly correlative relationship with the uniformity of road base.
文摘Maputo Airport was initially constructed to serve mixed traffic of light and medium aircrafts. With its opening to heavier aircrafts such as B727, DC10, Airbus 340, etc. , structural improvements have become necessary. For this purpose, structural evaluation were described and performed using falling weight deflectometer. Results show that while subgrade response to loads appears more consistent with depth, surface layer of the pavement is significantly influenced by the layer thickness as well as mechanical properties of pavement materials. Load magnitude also affects pavement performance. But loading conditions show an equivalent or even greater influence on pavement performance.
文摘Various technical studies have shown that impact-stiffness modulus values, defined as the ratio of the FWD （falling-weight deflectometer） impact load to its consequent central deflection, can be used to evaluate the PCN （pavement classification number） of a particular flexible or rigid airport pavement, fn a previous study, use was made of the old dynamic stiffness modulus procedure developed by the USCOE （US Army Corps of Engineers）, this procedure was correlated with various FWD measurements conducted on several runways and taxiways in Israel, together with in-situ borings and the use of the new COMFAA-3.0 software. The results, obtained only for flexible pavements, were checked against the relevant results of full-scale trafficking tests conducted by the FAA （Federal Administration Aviation） at its National Airport Pavement Test Facility. The present study analyzes new FWD measurements and in-situ borings conducted on additional rigid and all-asphaltic runways and taxiways in Israel in order to formulate an updated correlative equation for these types of pavements. The paper concludes with an updated recommendation for the use of impact-stiffness modulus outputs from FWD measurements in order to determine the PCN of any type of pavement directly on the basis of local experience.
基金sponsored by the National Key Research and Development Program of China(No.2021YFC3000074)the Xizang Autonomous Region 2024 Major Science and Technology Special Project(No.XZ202402ZD0008)the Xizang Autonomous Region 2024 Key Research and Development Plan(No.XZ202401ZY0082)。
文摘Aiming at the assessment of road structural conditions,a method of combining ground penetrating radar(GPR)and falling weight deflectometer(FWD)for assessing the pavement structural integrity and strength was proposed in this study.First,3D GPR was performed to detect the thickness and internal distress of pavement structural layers using the canny edge detection and you only look once version eight(YOLOv8)detection algorithms.Results showed that the error of thickness extraction was approximately 3%,and the distress detection achieved a mean average precision(m AP)of 0.859 and an inference time of11.43 ms with a GTX 1070 GPU.Then,the extracted thickness was used for the modulus(E)inversion of pavement structure layers based on FWD test data and regression analysis.Finally,the distress ratio inside pavement structures(DRIPS)was proposed as a structural integrity index.The relationship between E and DRIPS was revealed and showed a good correlation.The greater the DRIPS value,the worse the pavement structural integrity and strength.It provides a reference for the evaluation of road structural conditions.This strategy proved to be reliable for nondestructive testing and evaluation of road structures,which could improve the comprehensiveness and effectiveness for evaluating road structural conditions.
