A mechanistic-empirical approach to characterizing subgrade support and pavement structural condition for network-level applications.

摘要

Texas spends nearly {dollar}1 billion each year building new pavements and repairing or rebuilding existing pavements. The Texas Transportation Commission, through the Texas Department of Transportation (TxDOT), manages funding and project programming using the Unified Transportation Program (UTP), the Statewide Transportation Improvement Program (STIP) and a three-year financial plan. Categories established in the UTP specify the intended use of funds that are allocated to the TxDOT Districts according to criteria such as traffic volume and pavement condition. The TxDOT Pavement Management Information System (PMIS) is used to monitor and report pavement condition, identify funding needs and evaluate various funding scenarios.; PMIS algorithms are used to calculate a combined pavement functional and structural Condition Score by multiplying together the Distress and Ride scores and other factors. PMIS can also be used to predict performance or determine the theoretical age of a selected pavement section in order to estimate how long it will take to reach an unacceptable condition. Subgrade support, traffic, and other factors are used as input data in the performance and aging equations. A countywide, average subgrade support value is used rather than measurements taken on the particular pavement.; The purpose of this study is to develop and validate a procedure for estimating representative subgrade support and pavement structural condition values for use in PMIS. The procedure, NETFWD, incorporates a database containing approximately 8.5 million hypothetical pavement structure records. Each record contains fields for layer thickness and moduli, hypothetical Falling Weight Deflectometer (FWD) deflections, and calculated stresses and strains for a three-layer pavement structure. The database is searched by matching PMIS FWD deflections to the hypothetical deflections associated with each record. Matched records are screened using knowledge about district pavement design practices. The best candidate pavement section is then selected based on minimum deflection error. A backcalculated subgrade modulus and the AASHTO effective Structural Number (SNeff) can then be determined using the information contained in the matched record. PMIS deflection data were analyzed using Modulus 5.1, MODCOMP4 and NETFWD. The results indicate that NETFWD provides sufficiently accurate estimates of subgrade support and pavement structural condition for network-level applications.