Development of the MASW Method for Pavement Evaluation

Deterioration is a major issue for transportation infrastructure around the nation. Delamination, cracking, and many other failure modes in bridge decks and pavement systems are a daily issue in the continual maintenance of transportation systems. The extreme weather across the nation further exasperates the problem of failing infrastructure by increasing the wear and tear on transportation systems through more frequent freeze-thaw cycles and larger temperature swings. To combat these problems in an economic way, highway departments need non-destructive testing (NDT) methods to determine the condition of infrastructure and the rate of decay to better plan for future repairs and replacement of transportation systems. The Multi-Channel Analysis of Surface Waves (MASW) is a NDT method developed as an improvement to the Spectral Analysis of Surface Waves (SASW) method for dynamic characterization of soil for geophysical and geotechnical engineering problems. Improvements on the SASW method include: (1) faster data collection in the field, (2) simpler and faster data processing, (3) a more robust technique of developing the experimental dispersion curve in which multiple modes of propagation can be resolved, and (4) the ability to utilize both Rayleigh and Love wave dispersion in the inversion analysis. The MASW method is gaining widespread use in the geophysical and geotechnical communities and is one of the fastest growing methods for dynamic site characterization around the world. This is primarily because MASW provides the same benefits as SASW, but in a faster and more robust way. However, the method has yet to gain widespread use in the transportation sector. This research aims to develop the MASW method into a tool for characterization of concrete and asphalt pavements, bases, and subgrades for transportation projects. In addition, the method can be used to detect damage to infrastructure such as bridge decks. To develop the MASW method as a transportation tool, the study will: (1) determine the optimal field data collection parameters for both concrete and asphalt pavements including source type, source location, number of receivers, receiver spacing, and receiver coupling, (2) determine the practical vertical and horizontal resolution with depth of MASW given the optimal arrangement, which will provide a baseline for the method's ability to resolve problem areas in the pavement, base, and subgrade system, and (3) use MASW on real bridge decks and pavement surfaces that show signs of deterioration to determine if the method is able to detect the damage when the damage is already apparent by visual inspection. The results will be compared to results from more proven methods such as SASW and Impact Echo to insure the accuracy of MASW. Implementation will assist agencies in early detection of delaminations, cracks, and concrete deterioration, which can be critical for planning future repairs or replacement of the existing infrastructure.


    • English


    • Status: Active
    • Contract Numbers:


      SPTC 14.1-81

    • Sponsor Organizations:

      University of Arkansas, Fayetteville

      Department of Civil Engineering
      Fayetteville, AR  United States  72701

      Research and Innovative Technology Administration

      University Transportation Centers Program
      1200 New Jersey Avenue
      Washington, DC  United States  20590
    • Performing Organizations:

      University of Arkansas, Fayetteville

      Department of Civil Engineering
      Fayetteville, AR  United States  72701
    • Principal Investigators:

      Wood, Clinton

    • Start Date: 20140801
    • Expected Completion Date: 0
    • Actual Completion Date: 20150731
    • Source Data: RiP Project 37453

    Subject/Index Terms

    Filing Info

    • Accession Number: 01543094
    • Record Type: Research project
    • Source Agency: Southern Plains Transportation Center
    • Contract Numbers: DTRT13-G-UTC36, SPTC 14.1-81
    • Files: UTC, RiP
    • Created Date: Nov 5 2014 1:01AM