Multi-gene genetic programming extension of AASHTO M-E for design oflow-volume concrete pavements  

作　　者：Haoran Li Lev Khazanovich 

机构地区：[1]Department of Civil and Environmental Engineering,University of Pittsburgh,Pittsburgh,PA 15261,USA

出　　处：《Journal of Road Engineering》2022年第3期252-266,共15页道路工程学报（英文）

基　　金：the financial support from the University of Pittsburgh Anthony Gill Chair and the Impactful Resilient Infrastructure Science and Engineering Consortium(IRISE)at University of Pittsburgh.

摘　　要：The American Association of State Highway and Transportation Officials Mechanistic-Empirical Pavement DesignGuide (AASHTO M-E) offers an opportunity to design more economical and sustainable high-volume rigid pavementscompared to conventional design guidelines. It is achieved through optimizing pavement structural andthickness design under specified climate and traffic conditions using advanced M-E principles, thereby minimizingeconomic costs and environmental impact. However, the implementation of AASHTO M-E design for low-volumeconcrete pavements using AASHTOWare Pavement ME Design (Pavement ME) software is often overly conservative.This is because Pavement ME specifies the minimum design thickness of concrete slab as 152.4 mm (6 in.). Thispaper introduces a novel extension of the AASHTO M-E framework for the design of low-volume joint plain concretepavements (JPCPs) without modification of Pavement ME. It utilizes multi-gene genetic programming (MGGP)-based computational models to obtain rapid solutions for JPCP damage accumulation and long-term performanceanalyses. The developed MGGP models simulate the fatigue damage and differential energy accumulations. Thispermits the prediction of transverse cracking and joint faulting for a wide range of design input parameters and axlespectrum. The developed MGGP-based models match Pavement ME-predicted cracking and faulting for rigidpavements with conventional concrete slab thicknesses and enable rational extrapolation of performance predictionfor thinner JPCPs. This paper demonstrates how the developed computational model enables sustainable lowvolumepavement design using optimized ME solutions for Pittsburgh, PA, conditions.

关 键 词：Mechanistic-empirical pavement design guide Low-volume roads Concrete pavement Transverse cracking Joint faulting Multi-gene genetic programming(MGGP) 

分 类 号：U416.216[交通运输工程—道路与铁道工程]