Optimization of Aggregate Characteristic Parameters for Asphalt Binder—Aggregate System under Moisture Susceptibility Condition Based on Random Forest Analysis Model

Water damage to asphalt pavements is a common occurrence that lowers the quality of service they can offer and causes several traffic problems. The loss of adhesion characteristics in the system of the asphalt binder and aggregate is the primary source of the problem of water damage in asphalt mixes...

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Main Authors: Shenyang Cao, Ping Li, Xueli Nan, Zhao Yi, Mengkai Sun
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/13/8/4732
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author Shenyang Cao
Ping Li
Xueli Nan
Zhao Yi
Mengkai Sun
author_facet Shenyang Cao
Ping Li
Xueli Nan
Zhao Yi
Mengkai Sun
author_sort Shenyang Cao
collection DOAJ
description Water damage to asphalt pavements is a common occurrence that lowers the quality of service they can offer and causes several traffic problems. The loss of adhesion characteristics in the system of the asphalt binder and aggregate is the primary source of the problem of water damage in asphalt mixes. A number of things, including the impact of aggregate characteristics on asphalt binder—aggregate systems’ adhesion characteristics, have been proven. Through the use of random forest analysis, this study seeks to maximize the screening of aggregate characteristic factors. In this research, the morphology characterization, chemical composition, and phase composition of the five aggregates were first studied, and their relevant characteristic parameters were calculated. A method of engineering evaluation of the resistance of asphalt mixtures to water damage was used to assess the water susceptibility of the five asphalt binder—aggregate systems. Next, utilizing the fuzzy comprehensive evaluation analysis approach, a thorough study of the water susceptibility of the five asphalt binder—aggregate systems was conducted. Finally, sensitivity analysis of the aggregate characteristic parameters was carried out by a random forest analysis model, so as to achieve the optimal screening of the aggregate characteristic parameters. The results showed that, during sensitivity analysis of each parameter of aggregate properties using random forest analysis, the SiO<sub>2</sub> content of the aggregate had the highest importance, and the roughness had the highest importance among the morphology characterizations. The water susceptibility of the asphalt binder—aggregate system could be expressed by the SiO<sub>2</sub> content and roughness of the aggregate characteristic parameters.
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spelling doaj.art-ecf25ea090934cf3abd4422c8e31774a2023-11-17T18:08:26ZengMDPI AGApplied Sciences2076-34172023-04-01138473210.3390/app13084732Optimization of Aggregate Characteristic Parameters for Asphalt Binder—Aggregate System under Moisture Susceptibility Condition Based on Random Forest Analysis ModelShenyang Cao0Ping Li1Xueli Nan2Zhao Yi3Mengkai Sun4School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, ChinaSchool of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, ChinaSchool of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, ChinaSchool of Civil Engineering, Lanzhou Jiaotong University, Lanzhou 730070, ChinaSchool of Civil Engineering, Lanzhou Jiaotong University, Lanzhou 730070, ChinaWater damage to asphalt pavements is a common occurrence that lowers the quality of service they can offer and causes several traffic problems. The loss of adhesion characteristics in the system of the asphalt binder and aggregate is the primary source of the problem of water damage in asphalt mixes. A number of things, including the impact of aggregate characteristics on asphalt binder—aggregate systems’ adhesion characteristics, have been proven. Through the use of random forest analysis, this study seeks to maximize the screening of aggregate characteristic factors. In this research, the morphology characterization, chemical composition, and phase composition of the five aggregates were first studied, and their relevant characteristic parameters were calculated. A method of engineering evaluation of the resistance of asphalt mixtures to water damage was used to assess the water susceptibility of the five asphalt binder—aggregate systems. Next, utilizing the fuzzy comprehensive evaluation analysis approach, a thorough study of the water susceptibility of the five asphalt binder—aggregate systems was conducted. Finally, sensitivity analysis of the aggregate characteristic parameters was carried out by a random forest analysis model, so as to achieve the optimal screening of the aggregate characteristic parameters. The results showed that, during sensitivity analysis of each parameter of aggregate properties using random forest analysis, the SiO<sub>2</sub> content of the aggregate had the highest importance, and the roughness had the highest importance among the morphology characterizations. The water susceptibility of the asphalt binder—aggregate system could be expressed by the SiO<sub>2</sub> content and roughness of the aggregate characteristic parameters.https://www.mdpi.com/2076-3417/13/8/4732asphalt binder—aggregate systemadhesionmoisture susceptibilityrandom forest analysis modeloptimization
spellingShingle Shenyang Cao
Ping Li
Xueli Nan
Zhao Yi
Mengkai Sun
Optimization of Aggregate Characteristic Parameters for Asphalt Binder—Aggregate System under Moisture Susceptibility Condition Based on Random Forest Analysis Model
Applied Sciences
asphalt binder—aggregate system
adhesion
moisture susceptibility
random forest analysis model
optimization
title Optimization of Aggregate Characteristic Parameters for Asphalt Binder—Aggregate System under Moisture Susceptibility Condition Based on Random Forest Analysis Model
title_full Optimization of Aggregate Characteristic Parameters for Asphalt Binder—Aggregate System under Moisture Susceptibility Condition Based on Random Forest Analysis Model
title_fullStr Optimization of Aggregate Characteristic Parameters for Asphalt Binder—Aggregate System under Moisture Susceptibility Condition Based on Random Forest Analysis Model
title_full_unstemmed Optimization of Aggregate Characteristic Parameters for Asphalt Binder—Aggregate System under Moisture Susceptibility Condition Based on Random Forest Analysis Model
title_short Optimization of Aggregate Characteristic Parameters for Asphalt Binder—Aggregate System under Moisture Susceptibility Condition Based on Random Forest Analysis Model
title_sort optimization of aggregate characteristic parameters for asphalt binder aggregate system under moisture susceptibility condition based on random forest analysis model
topic asphalt binder—aggregate system
adhesion
moisture susceptibility
random forest analysis model
optimization
url https://www.mdpi.com/2076-3417/13/8/4732
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AT pingli optimizationofaggregatecharacteristicparametersforasphaltbinderaggregatesystemundermoisturesusceptibilityconditionbasedonrandomforestanalysismodel
AT xuelinan optimizationofaggregatecharacteristicparametersforasphaltbinderaggregatesystemundermoisturesusceptibilityconditionbasedonrandomforestanalysismodel
AT zhaoyi optimizationofaggregatecharacteristicparametersforasphaltbinderaggregatesystemundermoisturesusceptibilityconditionbasedonrandomforestanalysismodel
AT mengkaisun optimizationofaggregatecharacteristicparametersforasphaltbinderaggregatesystemundermoisturesusceptibilityconditionbasedonrandomforestanalysismodel