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contributor authorCharles A. Donnelly
contributor authorSushobhan Sen
contributor authorJulie M. Vandenbossche
date accessioned2024-04-27T20:54:01Z
date available2024-04-27T20:54:01Z
date issued2023/12/01
identifier other10.1061-JPEODX.PVENG-1334.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4296202
description abstractSuperload (SL) vehicles have unique axle configurations and high axle weights, indicating the potential for a low number of SL applications to cause significant fatigue damage to a jointed plain concrete pavement (JPCP). The current JPCP fatigue model in the AASHTO Pavement Mechanistic-Empirical (ME) Design Guide is unable to account for damage caused by SLs because the stress prediction models within it do not consider these unique axle configurations. As a result, it is not possible to account for the potential fatigue damage accumulation caused by SL applications or identify critical conditions that contribute to damage accumulation using Pavement ME. To address this, a critical, SL stress-prediction model was developed that can be used along with the current fatigue damage model. Typical SL configurations in Pennsylvania were identified based on available permit data, and a database of critical tensile stresses generated by these SLs for various JPCP structures was developed using finite element analysis. This database was used to train a series of artificial neural networks (ANNs), which predict critical tensile stress as a function of SL axle configuration, temperature gradient, and pavement structure. The method for determining fatigue damage accumulation using the ANNs to predict stresses is then presented.
publisherASCE
titleFatigue Damage Prediction for Superload Vehicles in Pennsylvania on Jointed Plain Concrete Pavements
typeJournal Article
journal volume149
journal issue4
journal titleJournal of Transportation Engineering, Part B: Pavements
identifier doi10.1061/JPEODX.PVENG-1334
journal fristpage04023029-1
journal lastpage04023029-11
page11
treeJournal of Transportation Engineering, Part B: Pavements:;2023:;Volume ( 149 ):;issue: 004
contenttypeFulltext


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