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  • 标题:Preliminary Findings for a Prediction Model of Road Surface Macrotexture
  • 本地全文:下载
  • 作者:Mauro D’Apuzzo ; Mauro D’Apuzzo ; Azzurra Evangelisti
  • 期刊名称:Procedia - Social and Behavioral Sciences
  • 印刷版ISSN:1877-0428
  • 出版年度:2012
  • 卷号:53
  • 页码:1109-1118
  • DOI:10.1016/j.sbspro.2012.09.960
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe aim of this work is to present a prediction model of macro-texture based on bituminous mix properties. Following a review of existing prediction models where an in-depth critical analysis has been performed, several statistical models are presented where the macro-texture expressed in terms of mean texture depth depends on bituminous mixtures volumetric and grading properties. Different mixtures have been examined and experimental data have been derived from several technical papers or from ad hoc field and laboratory investigations. Data have been combined in order to obtain a more general prediction model, which presents a high level of applicability.
  • 关键词:Surface texture;Tire-road friction;Prediction model;Mean texture depht
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