New Relationships Between Falling Weight Deflectometer Deflections and Asphalt Pavement Layer Condition Indicators

Xu, Bing; Ranjithan, S. Ranji; Kim, Y. Richard

doi:10.3141/1806-06

Cited by 72 publications

(41 citation statements)

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“…from the applied load, has been shown to be an excellent indicator of the strain of the asphalt layer in a flexible pavement (Xu et al 2002;Thyagarajan et al 2011). Given that the SCI is based on the difference between two measurements, it can be directly calculated using the TSD deflection slope measurements as shown in equation 1.The relationships developed for determining the strain for full depth pavements and aggregate base pavements are presented in equations 2 and 3, respectively:…”

Section: Estimating Pavement Structural Health Indicesmentioning

confidence: 99%

Capabilities and Potential Applications of Continuous Pavement Deflection Measuring Devices

Flintsch¹,

Bryce²,

Katicha³

2014

Geo-Congress 2014 Technical Papers

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Continuous pavement deflection measurment devices, or continuous deflectometers, were recently evaluated as part of a recent Strategic Highway Research Program 2 project number R06(F). Multiple devices were assessed, their capabilities evaluated and practical applications identified and illustrated. The objective of this paper is to present the results of a study that evaluated current technologies implemented in continuous deflection measuring devices with a focus on their potential use to obtain network level structural indices that can be used to support pavement management decisions. The evaluated indices are the Surface Curvature Index (SCI), the Base Damage Index (BDI), the strain at the bottom of the asphalt layer, and the effective structural number (SN eff ). These indices were calculated using the Traffic Speed Deflectometer (TSD) which is a continuous deflection device that was evaluated in the study and compared with indices calculated using the Falling Weight Deflectometer (FWD). The results suggest reasonable agreement between the TSD and FWD for the purpose of network level pavement management.

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Section: Estimating Pavement Structural Health Indicesmentioning

confidence: 99%

Capabilities and Potential Applications of Continuous Pavement Deflection Measuring Devices

Flintsch¹,

Bryce²,

Katicha³

2014

Geo-Congress 2014 Technical Papers

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“…On the basis of their finite element (FE) analyses, Xu et al (2001) found that for a certain thickness of the AC layer, the AC moduli and SCI values exhibit an approximately linear relationship in a log-log scale. The SCI has the same meaning as AUPP, that is, lower SCI values mean higher pavement stiffnesses.…”

Section: Deflection Basin Parameters Of Fwd Measurements At Ncat Testmentioning

confidence: 99%

Nondestructive Testing to Identify Delaminations Between HMA Layers, Volume 3 - Controlled Evaluation Reports

Heitzman¹,

Maser²,

Tran³

et al. 2013

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Asphalt pavements with delamination problems experience considerable early damage because delaminations provide paths for moisture damage and the development of damage such as stripping, slippage cracks, and pavement deformation. Early detection of the existence, extent, and depth of delaminations in asphalt pavements is key for determining the appropriate rehabilitation strategy and thus extending the life of the given pavement. Disciplines Civil and Environmental Engineering T R A N S P O R T A T I O N R E S E A R C H B O RepoRt S2-R06D-RW-3 The Second S T R A T E G I C H I G H W A Y R E S E A R C H P R O G R Copyright InformationAuthors herein are responsible for the authenticity of their materials and for obtaining written permissions from publishers or persons who own the copyright to any previously published or copyrighted material used herein.The second Strategic Highway Research Program grants permission to reproduce material in this publication for classroom and not-for-profit purposes. Permission is given with the understanding that none of the material will be used to imply TRB, AASHTO, or FHWA endorsement of a particular product, method, or practice. It is expected that those reproducing material in this document for educational and not-for-profit purposes will give appropriate acknowledgment of the source of any reprinted or reproduced material. For other uses of the material, request permission from SHRP 2.Note: SHRP 2 report numbers convey the program, focus area, project number, and publication format. Report numbers ending in "w" are published as web documents only. NoticeThe project that is the subject of this report was a part of the second Strategic Highway Research Program, conducted by the Transportation Research Board with the approval of the Governing Board of the National Research Council.The members of the technical committee selected to monitor this project and review this report were chosen for their special competencies and with regard for appropriate balance. The Second Strategic Highway Research ProgramAmerica's highway system is critical to meeting the mobility and economic needs of local communities, regions, and the nation. Developments in research and technology-such as advanced materials, communications technology, new data collection technologies, and human factors science-offer a new opportunity to improve the safety and reliability of this important national resource. Breakthrough resolution of significant transportation problems, however, requires concentrated resources over a short time frame. Reflecting this need, the second Strategic Highway Research Program (SHRP 2) has an intense, large-scale focus, integrates multiple fields of research and technology, and is fundamentally different from the broad, mission-oriented, discipline-based research programs that have been the mainstay of the highway research industry for half a century.

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“… The surface curvature index (SCI), which is related to the Young modulus of the AC layer (Xu et al, 2002a, 2002b) and defined as where D 0 and D 300 are the deflections measured at the point where the load is applied and at 30.48 cm (12 in.) from it, respectively, in the FWD test. D 900 , which is the deflection measured at 91.44 cm (36 in.)…”

Section: Model Implementation For Pavement Performancementioning

confidence: 99%

“…1. The surface curvature index (SCI), which is related to the Young modulus of the AC layer (Xu et al, 2002a(Xu et al, , 2002b and defined as…”

Section: Selection Of the Input Variablesmentioning

confidence: 99%

Prediction of Pavement Performance through Neuro-Fuzzy Reasoning

Bianchini

Bandini

2010

Computer-Aided Civil and Infrastructure Engineering

116

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Government agencies and consulting companies in charge of pavement management face the challenge of maintaining pavements in serviceable conditions throughout their life from the functional and structural standpoints. For this, the assessment and prediction of the pavement conditions are crucial. This study proposes a neuro‐fuzzy model to predict the performance of flexible pavements using the parameters routinely collected by agencies to characterize the condition of an existing pavement. These parameters are generally obtained by performing falling weight deflectometer tests and monitoring the development of distresses on the pavement surface. The proposed hybrid model for predicting pavement performance was characterized by multilayer, feedforward neural networks that led the reasoning process of the IF‐THEN fuzzy rules. The results of the neuro‐fuzzy model were superior to those of the linear regression model in terms of accuracy in the approximation. The proposed neuro‐fuzzy model showed good generalization capability, and the evaluation of the model performance produced satisfactory results, demonstrating the efficiency and potential of these new mathematical modeling techniques.

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New Relationships Between Falling Weight Deflectometer Deflections and Asphalt Pavement Layer Condition Indicators

Cited by 72 publications

References 1 publication

Capabilities and Potential Applications of Continuous Pavement Deflection Measuring Devices

Capabilities and Potential Applications of Continuous Pavement Deflection Measuring Devices

Nondestructive Testing to Identify Delaminations Between HMA Layers, Volume 3 - Controlled Evaluation Reports

Prediction of Pavement Performance through Neuro-Fuzzy Reasoning

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