Evaluation of Dynamic Modulus of HMA Sigmoidal Prediction Models and Optimization by Approach of U.S. Mesh Sieve by AFNOR and LC Mesh Sieve

Evaluation of Dynamic Modulus of HMA Sigmoidal Prediction Models and Optimization by Approach of U.S. Mesh Sieve by AFNOR and LC Mesh Sieve

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摘要 Pavement design tools are not universal. Indeed, in the sizing of pavements in the USA, the prediction models used in the calculation of the dynamic modulus of HMA are not adapted to the characterization of the mineral skeleton of the HMA mix designed with the French method. This article aims to assess the predictive models of the dynamic modulus used in the mechanistic-empirical design for their use in the design of bituminous pavements, and to develop new predictive models taking into account the sieve series LC and AFNOR standards. A total of six types of mixtures were subjected to the determination of complex modulus testing by direct tensile-compression on cylindrical specimens (26-700 LC) over a temperature range (5) and frequency (5) data. Dynamic modulus prediction models |E*| are studied Witczak model 1999 and model Witczak 2006. These models do not take into account the AFNOR or LC mesh sieve, an approach was made in relation to the US mesh sieve to replace ρ200 (0.075 mm), ρ4 (4.76 mm), ρ38 (9.5 mm) and ρ34 (19 mm) respectively by the AFNOR mesh P0.08 (0.08 mm), R5 (5 mm), R10 (10 mm) and R14 (14 mm). The result is the production of two models whose are evaluated by correlation with the values |E*| of modulus measured in the laboratory is satisfactory (R2 = 0.83 respectively R2 = 0.71 and p-value = 0.00). The optimization of these approximate models gave new models with the same frame as the original models and a better correlation with the data observed in the laboratory (respectively R2 = 0. 95 and R2 = 0.91 p-value = 0.00). Pavement design tools are not universal. Indeed, in the sizing of pavements in the USA, the prediction models used in the calculation of the dynamic modulus of HMA are not adapted to the characterization of the mineral skeleton of the HMA mix designed with the French method. This article aims to assess the predictive models of the dynamic modulus used in the mechanistic-empirical design for their use in the design of bituminous pavements, and to develop new predictive models taking into account the sieve series LC and AFNOR standards. A total of six types of mixtures were subjected to the determination of complex modulus testing by direct tensile-compression on cylindrical specimens (26-700 LC) over a temperature range (5) and frequency (5) data. Dynamic modulus prediction models |E*| are studied Witczak model 1999 and model Witczak 2006. These models do not take into account the AFNOR or LC mesh sieve, an approach was made in relation to the US mesh sieve to replace ρ200 (0.075 mm), ρ4 (4.76 mm), ρ38 (9.5 mm) and ρ34 (19 mm) respectively by the AFNOR mesh P0.08 (0.08 mm), R5 (5 mm), R10 (10 mm) and R14 (14 mm). The result is the production of two models whose are evaluated by correlation with the values |E*| of modulus measured in the laboratory is satisfactory (R2 = 0.83 respectively R2 = 0.71 and p-value = 0.00). The optimization of these approximate models gave new models with the same frame as the original models and a better correlation with the data observed in the laboratory (respectively R2 = 0. 95 and R2 = 0.91 p-value = 0.00).

作者 Mouhamed Lamine Chérif Aidara Makhaly Ba Alan Carter Mouhamed Lamine Chérif Aidara;Makhaly Ba;Alan Carter(UFR Sciences de l’Ingénieur, Université de Thiès, Thiès, Sénégal;Ecole de Technologie Supérieure (ETS), Director of Pavement BituminousMaterials Laboratory (LCMB), Montréal, Canada)

机构地区 UFR Sciences de l’Ingénieur Ecole de Technologie Supérieure (ETS)

出处《Open Journal of Civil Engineering》 2020年第3期195-212,共18页 土木工程期刊（英文）

关键词 Dynamic Modulus Mechanistic-Empirical Design US SIEVE MESH HMA AFNOR LC Dynamic Modulus Mechanistic-Empirical Design US Sieve Mesh HMA AFNOR LC

分类号 O17 [理学—基础数学]

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Open Journal of Civil Engineering

2020年第3期

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Evaluation of Dynamic Modulus of HMA Sigmoidal Prediction Models and Optimization by Approach of U.S. Mesh Sieve by AFNOR and LC Mesh Sieve

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