A comprehensive field and laboratory test programme and electronic database of pavement material properties for MEPDG. Issue Volume 20:Issued 5(2019) (4th May 2019)

• Record Type: Journal Article
• Authors: Ng, Kam; Hutson, Zachary; Ksaibati, Khaled; Wulff, Shaun S.
• Is Part Of: International journal of pavement engineering. Volume 20:Issued 5(2019)
• Page Start: 600
• Page End: 614
• Publication Date: 2019-05-04
• Subjects: MEPDG -- pavement -- resilient modulus -- subgrade; Pavements -- Design and construction -- Periodicals; Highway engineering -- Periodicals; 625.805
• DOI: 10.1080/10298436.2017.1316846
• Languages: English
• ISSNs: 1029-8436

Abstract

ABSTRACT: To locally calibrate the Mechanistic-Empirical Pavement Design Guide (MEPDG) for the state of Wyoming, a comprehensive test programme and analyses were conducted. The field test programme included falling weight deflectometer tests, standard penetration tests, dynamic cone penetration tests and soil sampling. These field tests were conducted at 12 locations or 36 sites in the state of Wyoming. Subgrade soils collected from the field were characterised by a series of laboratory soil tests including resilient modulus tests, resistance-value tests and standard Proctor density tests. This test programme accumulated significant valuable soil data for local MEPDG calibrations. To efficiently store the results from the field and laboratory testing, an electronic WYO ming MEP DG Database was developed using Microsoft® Access. Specific data or inputs requested by user are efficiently and easily sorted, filtered and queried using the database. Laboratory measured resilient modulus, resistance-values and standard Proctor properties of subgrade materials were used to develop both multivariate and univariate multi-regression models to accurately estimate resilient modulus for MEPDG Level 2 design inputs. Statistical parameters were used to effectively evaluate the performance of developed regression models. The resistance-value and optimum moisture content of subgrade soils were determined as important predictors in both models. The research outcomes facilitate the local calibration and implementation of the MEPDG.