To improve the prediction accuracy of the International Roughness Index(IRI)of Jointed PlainConcrete Pavements(JPCP)and Continuously Reinforced Concrete Pavements(CRCP),a machine learning approach is developed in this study for the modelling,combining an improved Beetle Antennae Search(MBAS)algorithm and Random Forest(RF)model.The 10-fold cross-validation was applied to verify the reliability and accuracy of the model proposed in this study.The importance scores of all input variables on the IRI of JPCP and CRCP were analysed as well.The results by the comparative analysis showed the prediction accuracy of the IRI of the newly developed MBAS and RF hybrid machine learning model(RF-MBAS)in this study is higher,indicated by the RMSE and R values of 0.2732 and 0.9476 for the JPCP as well as the RMSE and R values of 0.1863 and 0.9182 for the CRCP.The accuracy of this obtained result far exceeds that of the IRI prediction model used in the traditional Mechanistic-Empirical Pavement Design Guide(MEPDG),indicating the great potential of this developed model.The importance analysis showed that the IRI of JPCP and CRCP was proportional to the corresponding input variables in this study,including the total joint faulting cumulated per KM(TFAULT),percent subgrade material passing the 0.075-mm Sieve(P_(200))and pavement surface area with flexible and rigid patching(all Severities)(PATCH)which scored higher.
为改善连续配筋混凝土与沥青面层间的黏结效果,提高复合式路面层间抗剪强度,以同步碎石封层层间抗剪强度为研究对象,采用“水泥混凝土+封层+沥青面层”的复合结构,以集料粒径、沥青洒布量、试验温度、混凝土基面构造深度、竖向压应力为变量,进行室内连续配筋混凝土-沥青混凝土(Continuously Reinforced Concrete Pavement-Asphalt Concrete,CRCP-AC)层间同步碎石封层(Synchronous Crushed Stone Seal Coat,SCSSC)抗剪模拟试验。结合三维有限元分析结果,确定了同步碎石封层最佳参数组合,提出了改善层间抗剪强度的建议。试验结果表明:集料粒径、沥青洒布量、试验温度、混凝土基面构造深度、竖向压应力对同步碎石封层层间抗剪强度产生了显著影响;相较于4.75~9.5mm粒径的集料,为获取更高的抗剪切强度,在工程实践中宜选择9.5~13.2mm粒径的碎石作为同步碎石封层用撒布料;使用粒径为9.5~13.2mm的集料时,最佳参数组合为沥青洒布量1.6kg/m^(2)+碎石撒布量8kg/m^(2)。