You are being redirected because this document is part of your ASTM Compass® subscription.
    This document is part of your ASTM Compass® subscription.


    Quantification of Masonry Deterioration Through Statistical Modelling -- A Case Study

    Published: 0

      Format Pages Price  
    PDF (280K) 14 $25   ADD TO CART
    Complete Source PDF (8.7M) 433 $55   ADD TO CART


    Structures of all types experience physical damage due to numerous conditions or circumstances. Errors in design, defective materials, improper construction, or poor workmanship can lead to deterioration or failure of building structures or components. Natural aging processes, chemical attack, or the effects of natural disasters create damage. Determining the precise causes or mechanisms responsible for the condition is important and the procedures for doing so have been well researched and published. Also important, however, is quantifying the amount of damage. Quantification is important so that accurate estimates of repair costs can be established, budgeting for the repairs, and for scheduling.

    This paper presents a case study concerning a condition survey of five nearly identical buildings constructed of fired clay masonry. Specifically, the surveying and estimation of spalled masonry units is discussed. In this case study, total damage is first assessed by means of two different and independent observational procedures, one of which suffers from incomplete data collection. Missing data are estimated using Poisson log-linear regression modelling of the relationship between damage assessments and a number of qualitative factors. The resulting two sets of predicted total damage estimates are then obtained through calibration techniques.


    statistics, failure investigations, condition assessments, damage, quantity estimates, spall, regression, condition survey, modelling, calibration, deterioration, non-destructive evaluation (NDE)

    Author Information:

    Whitlock, AR
    Senior Vice President, KCI Technologies, Inc., Manassas, VA

    Fairley, WB
    President, Analysis & Inference, Inc., Swarthmore, PA

    Izenman, AJ
    Professor, Temple University, Philadelphia, PA

    Committee/Subcommittee: C15.03

    DOI: 10.1520/STP19625S