Fuzzy Logic Approach to Risk Assessment Associated with Concrete Deterioration
Document Type
Article
Publication Date
3-1-2015
Abstract
Determining the level and importance of concrete deterioration in a given structure is a multivariate decision-making problem with parameters that vary extensively, depending on which specific structural element(s) is/are implicated. This paper presents the development of a tool to measure the extent of the criticality of the concrete deterioration to help quantify if the deterioration warrants intervention for repair. The decision-making logic is based on fuzzy set theory (FST), a well-developed tool used to address uncertainties in decision making. Investigation of the extent of deterioration is conducted using nondestructive testing (NDT) of concrete - specifically, the Schmidt hammer. An assessment is performed using the fuzzy logic analysis. The tool presented herein is generic enough to allow the user to encompass the criteria of the structure at hand and to render a judgment to determine the optimum timing for repair. The objective of this research is the development of a decision-support model that will provide quantifiable support for a decision maker's decisions and the demonstration of its use. This research also highlights an extensive area for further development. It provides a blueprint to achieve the overall goal of assessing deterioration. Through this model, users are able to develop a quantifiable metric to help support their decisions on the appropriate time for intervention and the repair procedure necessary. An analysis of the model illustrates that the system demonstrates utility for practical use.
Publication Title
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume
1
Issue
1
Digital Object Identifier (DOI)
10.1061/AJRUA6.0000811
E-ISSN
23767642
Citation Information
Malek, Tumeo, M., & Saliba, J. (2015). Fuzzy Logic Approach to Risk Assessment Associated with Concrete Deterioration. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems. Part A, Civil Engineering, 1(1), 4014004–. https://doi.org/10.1061/AJRUA6.0000811