Results 241 to 250 of about 6,982,333 (284)

Model for forecasting ruts in rutting tester

Sixth International RILEM Symposium on Performance Testing and Evaluation of Bituminous Materials, 2003
The results of research on the rheological parameters of mineral-asphalt mixes subjected to the creep test in the Nottingham Asphalt Tester (NAT) are presented. The rheological parameters were determined through the approximation of the experimental creep curves by the theoretical curves for three viscoelastic models: the Maxwell model, the Burgers ...
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Modeling wheel-induced rutting in soils: Rolling

Journal of Terramechanics, 2009
Theoretical models for predicting penetration of non-driving (towed) rigid cylindrical wheels rolling on frictional/cohesive soils are presented. The models allow for investigating the influence of soil parameters and wheel geometry on the relationship between the inclined rolling force and wheel sinkage in the presence of permanently formed ruts.
J.P. Hambleton, A. Drescher
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Development of a rutting index parameter based on the stress sweep rutting test and permanent deformation shift model

International Journal of Pavement Engineering, 2020
The use of index parameters to evaluate the performance of asphalt mixtures has become an important process for making informed pavement material decisions.
Amir Ghanbari, Benjamin Shane Underwood, Youngsoo Richard Kim   +2 more
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Rutting progression models for light duty pavements

International Journal of Pavement Engineering, 2016
AbstractDeterioration models allow road managers to assess current condition and to predict future conditions of their road networks. Due to heavy vehicle axle repetitions and the effect of environmental factors, permanent deformation (rutting) develops gradually in the wheel paths and impacts on structural and surface performance of flexible pavements.
Alaswadko, Nahla, Hassan, Rayya
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Mechanistic rutting modelling of a LTPP road structure

2019
A new Mechanistic-Empirical (M-E) approach is under development to predict the structural degradation of road structures as a function of time.
S. Erlingsson, A.W. Ahmed
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Mechanistic-Empirical Rut Prediction Model for In-Service Pavements

Transportation Research Record: Journal of the Transportation Research Board, 2000
Rutting is a major mode of failure in flexible pavements. Development of accurate predictive rut performance models is an ongoing pursuit of the pavement engineering community. This has resulted in a plethora of rut prediction models ranging from purely mechanistic to empirical.
Hyung Bae Kim, Neeraj Buch, Dong-Yeob Park   +2 more
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Predicting a Model for Modified Asphalt Cement Rutting Parameters

Key Engineering Materials, 2021
This paper aims to investigate the relationship between the Superpave rutting parameter of asphalt (G﹡/sin δ) by conducting Dynamic Shear Rheometer (DSR) tests with the rut depth values obtained by the wheel track device. The twenty asphalt mixtures have been prepared with twenty types of unmodified asphalts and Polymer-Modified Binders (PMBs). SBS was
Mohammed Abbas Al-Jumaili, Hamid Athab Al-Jameel   +1 more
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Developing a four‐layer system rutting model in highway

Journal of the Chinese Institute of Engineers, 2005
Abstract A four‐layer rutting model was developed to account for material property changes in the progression of accumulated compressive plastic strains in all roadway layers on the basis of traffic passing in this study. This paper demonstrates that incorporating the mechanistic‐empirical approach in the prediction of rutting provides value ...
Chih‐Hsien Lin, Wei‐Chyum Chen
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Rutting Corrugation Modelling with SIMPACK

2006
info:eu-repo/semantics ...
Collette, C., Chollet, H., Bastaits, Renaud, Preumont, André   +3 more
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Implementation framework of the UIUC aggregate base rutting model

International Journal of Pavement Engineering, 2019
ABSTRACTThis paper presents findings from a research study focused on calibrating and improving the robustness of a permanent deformation model for unbound aggregate base/subbase materials, recentl...
Issam I. A. Qamhia, Maziar Moaveni, Yong-Hoon Byun, Bin Feng, Erol Tutumluer   +4 more
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