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Asphalt pavement skid resistance prediction method considering aggregate characteristics
The invention relates to an asphalt pavement anti-slide performance prediction method considering aggregate characteristics, which is used for predicting the anti-slide performance of an asphalt pavement by considering the aggregate characteristics. The prediction method comprises the following steps: selecting at least eight different types of aggregates, and testing the polishing value PSV, the rock abrasion value LAS, the Vickers hardness HV and the surface micro texture index Ra of the aggregates; mixing the aggregate with asphalt to prepare an asphalt mixture, and molding the asphalt mixture into a rut plate test piece; respectively measuring the anti-skid performance BPN; adopting a logarithmic model for fitting to obtain a relation model of the anti-slide performance and the loading times; fitting by adopting a multiple linear regression method to obtain a relational expression of A, LAS and HV; fitting by adopting a multiple linear regression method to obtain a relational expression of B, PSV and Ra; and respectively substituting A and B into a logarithmic model to obtain an anti-skid prediction model considering the aggregate characteristics. The anti-skid durability of asphalt pavements prepared from different aggregates can be compared, prediction is more reasonable, and the method has high practical value.
一种考虑集料特性的沥青路面抗滑性能预测方法,用于考虑集料特性对沥青路面进行抗滑性能预测。预测方法为:选取至少八种不同类型的集料,测试其磨光值PSV、洛杉矶磨耗值LAS、维氏硬度HV及表面微观纹理指标Ra;将集料与沥青混合后制备成沥青混合料,将其成型成车辙板试件;分别测定抗滑性能BPN;采用对数模型拟合得到抗滑性能与加载次数的关系模型;采用多元线性回归的方法拟合得到A与LAS和HV的关系表达式;采用多元线性回归的方法拟合得到B与PSV和Ra的关系表达式;将A、B分别带入到对数模型中得到考虑集料特性的抗滑预测模型。本发明可对比不同集料制备的沥青路面抗滑耐久性,预测更加合理,有较强的实用价值。
Asphalt pavement skid resistance prediction method considering aggregate characteristics
The invention relates to an asphalt pavement anti-slide performance prediction method considering aggregate characteristics, which is used for predicting the anti-slide performance of an asphalt pavement by considering the aggregate characteristics. The prediction method comprises the following steps: selecting at least eight different types of aggregates, and testing the polishing value PSV, the rock abrasion value LAS, the Vickers hardness HV and the surface micro texture index Ra of the aggregates; mixing the aggregate with asphalt to prepare an asphalt mixture, and molding the asphalt mixture into a rut plate test piece; respectively measuring the anti-skid performance BPN; adopting a logarithmic model for fitting to obtain a relation model of the anti-slide performance and the loading times; fitting by adopting a multiple linear regression method to obtain a relational expression of A, LAS and HV; fitting by adopting a multiple linear regression method to obtain a relational expression of B, PSV and Ra; and respectively substituting A and B into a logarithmic model to obtain an anti-skid prediction model considering the aggregate characteristics. The anti-skid durability of asphalt pavements prepared from different aggregates can be compared, prediction is more reasonable, and the method has high practical value.
一种考虑集料特性的沥青路面抗滑性能预测方法,用于考虑集料特性对沥青路面进行抗滑性能预测。预测方法为:选取至少八种不同类型的集料,测试其磨光值PSV、洛杉矶磨耗值LAS、维氏硬度HV及表面微观纹理指标Ra;将集料与沥青混合后制备成沥青混合料,将其成型成车辙板试件;分别测定抗滑性能BPN;采用对数模型拟合得到抗滑性能与加载次数的关系模型;采用多元线性回归的方法拟合得到A与LAS和HV的关系表达式;采用多元线性回归的方法拟合得到B与PSV和Ra的关系表达式;将A、B分别带入到对数模型中得到考虑集料特性的抗滑预测模型。本发明可对比不同集料制备的沥青路面抗滑耐久性,预测更加合理,有较强的实用价值。
Asphalt pavement skid resistance prediction method considering aggregate characteristics
一种考虑集料特性的沥青路面抗滑性能预测方法
LEI JUN'AN (author) / ZHAO FUJING (author)
2023-03-28
Patent
Electronic Resource
Chinese
IPC:
G01N
Untersuchen oder Analysieren von Stoffen durch Bestimmen ihrer chemischen oder physikalischen Eigenschaften
,
INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
/
C04B
Kalk
,
LIME
/
G06F
ELECTRIC DIGITAL DATA PROCESSING
,
Elektrische digitale Datenverarbeitung
Relationship of Aggregate Microtexture to Asphalt Pavement Skid Resistance
British Library Online Contents | 2007
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Online Contents | 2003
|