{"title":"Numerical data for modelling pavement deflection behaviour under the TSD.","authors":"Abdelgader Abdelmuhsen, Jean-Michel Simonin, Franziska Schmidt, Denis Lievre, Alexis Cothenet, Murilo Freitas, Amine Ihamouten","doi":"10.1016/j.dib.2024.111135","DOIUrl":null,"url":null,"abstract":"<p><p>This dataset provides a numerical simulation of pavement mechanical behavior under Traffic Speed Deflectometer (TSD) measurements. It consists of simulated deflection slope data for various pavement structures and subgrade properties, generated using the Alizé-LCPC software, a standard tool in French pavement engineering. The dataset addresses limitations in traditional Falling Weight Deflectometer (FWD) methods, offering a more accurate and computationally efficient approach for estimating the Subgrade Resilient Modulus (M<sub>R</sub>) using machine learning models. This resource is valuable for researchers aiming to enhance pavement evaluation methods and develop predictive models for road infrastructure maintenance and assessment. The data are openly accessible, facilitating widespread research collaboration and the application of advanced data analytics in pavement engineering.</p>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"57 ","pages":"111135"},"PeriodicalIF":1.0000,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11647148/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.dib.2024.111135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
This dataset provides a numerical simulation of pavement mechanical behavior under Traffic Speed Deflectometer (TSD) measurements. It consists of simulated deflection slope data for various pavement structures and subgrade properties, generated using the Alizé-LCPC software, a standard tool in French pavement engineering. The dataset addresses limitations in traditional Falling Weight Deflectometer (FWD) methods, offering a more accurate and computationally efficient approach for estimating the Subgrade Resilient Modulus (MR) using machine learning models. This resource is valuable for researchers aiming to enhance pavement evaluation methods and develop predictive models for road infrastructure maintenance and assessment. The data are openly accessible, facilitating widespread research collaboration and the application of advanced data analytics in pavement engineering.
期刊介绍：
Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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