热混合沥青动态模量预测模型的建立及骨料类型及其电化学性能的影响研究

Mouhamed Lamine Chérif Aidara, Makhaly Bâ, A. Carter
{"title":"热混合沥青动态模量预测模型的建立及骨料类型及其电化学性能的影响研究","authors":"Mouhamed Lamine Chérif Aidara, Makhaly Bâ, A. Carter","doi":"10.4236/ojce.2020.103018","DOIUrl":null,"url":null,"abstract":"The most famous model known in prediction of dynamic modulus for asphalt concretes is the Witczak and Hirsh models. \nThese models didn’t use the mineralogical and chemical properties of aggregates. \nWitczak models used the passing or refusal percentage to sieve diameters and Hirsh \nmodel used the volumetric \nanalysis. All models developed until now considered that the aggregates were geotechnical \nconforming to standards. In this study the first mineralogical and chemical properties \nwere considered through the percentage of silica in the rock source of aggregates \nand the electric aggregate particles charge zeta. Dynamic modulus values used for \nregression process are determined from complex modulus test on nine asphalt concretes \nmix designed with aggregate types (basalt of Diack, quartzite of Bakel and Limestone \nof Bandia). Between Twelve initial inputs, the statistical regression by exclusion process keeps only seven parameters \nas input for the model. The mineralogical model showed good accuracy with R2 equal to 0.09. The student test on the model parameters showed that all the parameters \nincluded in the model were meaningful with good p inferior to 0.05. The Fisher test \non the model showed the same result. The analysis of the sensitivity of the mineralogical \nmodel to zeta potential showed that the dynamic modulus increases with the positive zeta-potentials and decreases with the negative zeta-potentials. The analysis \nof the sensitivity of the mineralogical model to the silica showed that the dynamic \nmodulus decreases with the increase of the silica.","PeriodicalId":302856,"journal":{"name":"Open Journal of Civil Engineering","volume":"204 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of a Dynamic Modulus Prediction Model for Hot Mixture Asphalt and Study of the Impact of Aggregate Type and Its Electrochemical Properties\",\"authors\":\"Mouhamed Lamine Chérif Aidara, Makhaly Bâ, A. Carter\",\"doi\":\"10.4236/ojce.2020.103018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The most famous model known in prediction of dynamic modulus for asphalt concretes is the Witczak and Hirsh models. \\nThese models didn’t use the mineralogical and chemical properties of aggregates. \\nWitczak models used the passing or refusal percentage to sieve diameters and Hirsh \\nmodel used the volumetric \\nanalysis. All models developed until now considered that the aggregates were geotechnical \\nconforming to standards. In this study the first mineralogical and chemical properties \\nwere considered through the percentage of silica in the rock source of aggregates \\nand the electric aggregate particles charge zeta. Dynamic modulus values used for \\nregression process are determined from complex modulus test on nine asphalt concretes \\nmix designed with aggregate types (basalt of Diack, quartzite of Bakel and Limestone \\nof Bandia). Between Twelve initial inputs, the statistical regression by exclusion process keeps only seven parameters \\nas input for the model. The mineralogical model showed good accuracy with R2 equal to 0.09. The student test on the model parameters showed that all the parameters \\nincluded in the model were meaningful with good p inferior to 0.05. The Fisher test \\non the model showed the same result. The analysis of the sensitivity of the mineralogical \\nmodel to zeta potential showed that the dynamic modulus increases with the positive zeta-potentials and decreases with the negative zeta-potentials. The analysis \\nof the sensitivity of the mineralogical model to the silica showed that the dynamic \\nmodulus decreases with the increase of the silica.\",\"PeriodicalId\":302856,\"journal\":{\"name\":\"Open Journal of Civil Engineering\",\"volume\":\"204 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Open Journal of Civil Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4236/ojce.2020.103018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Journal of Civil Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4236/ojce.2020.103018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在预测沥青混凝土的动态模量方面,最著名的模型是Witczak和Hirsh模型。这些模型没有使用聚集体的矿物学和化学性质。Witczak模型使用筛选直径的通过或拒绝百分比,Hirsh模型使用体积分析。到目前为止开发的所有模型都认为骨料符合岩土标准。在本研究中,首先考虑了矿物和化学性质,通过硅的百分比在岩石来源的团聚体和电团聚体粒子电荷zeta。回归过程中使用的动态模量值是通过对9种骨料类型(Diack玄武岩、Bakel石英岩和Bandia石灰石)设计的沥青混凝土配合比的复模量试验确定的。在12个初始输入之间,排除过程的统计回归只保留7个参数作为模型的输入。矿物学模型具有较好的精度,R2 = 0.09。对模型参数的学生检验表明,模型中包含的所有参数都是有意义的,p < 0.05。Fisher对模型的检验也得出了同样的结果。矿物学模型对zeta电位的敏感性分析表明,动态模量随zeta电位的增大而增大,随zeta电位的减小而减小。矿物学模型对二氧化硅的敏感性分析表明,动态模量随二氧化硅含量的增加而减小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Development of a Dynamic Modulus Prediction Model for Hot Mixture Asphalt and Study of the Impact of Aggregate Type and Its Electrochemical Properties
The most famous model known in prediction of dynamic modulus for asphalt concretes is the Witczak and Hirsh models. These models didn’t use the mineralogical and chemical properties of aggregates. Witczak models used the passing or refusal percentage to sieve diameters and Hirsh model used the volumetric analysis. All models developed until now considered that the aggregates were geotechnical conforming to standards. In this study the first mineralogical and chemical properties were considered through the percentage of silica in the rock source of aggregates and the electric aggregate particles charge zeta. Dynamic modulus values used for regression process are determined from complex modulus test on nine asphalt concretes mix designed with aggregate types (basalt of Diack, quartzite of Bakel and Limestone of Bandia). Between Twelve initial inputs, the statistical regression by exclusion process keeps only seven parameters as input for the model. The mineralogical model showed good accuracy with R2 equal to 0.09. The student test on the model parameters showed that all the parameters included in the model were meaningful with good p inferior to 0.05. The Fisher test on the model showed the same result. The analysis of the sensitivity of the mineralogical model to zeta potential showed that the dynamic modulus increases with the positive zeta-potentials and decreases with the negative zeta-potentials. The analysis of the sensitivity of the mineralogical model to the silica showed that the dynamic modulus decreases with the increase of the silica.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Interchange Sight Distance and Design: Aspects and Implementation A Slip-Force Device for Maintaining Constant Lateral Pressure on Retaining Structures in Expansive Soils Practical Engineering Behavior of Egyptian Collapsible Soils, Laboratory and In-Situ Experimental Study Structural Health Monitoring for Reinforced Concrete Containment Using Inner Electrical Resistivity Method Hardening Properties of Foamed Concrete with Circulating Fluidized Bed Boiler Ash, Blast Furnace Slag, and Desulfurization Gypsum as the Binder
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1