Developing a Fuzzy Expert System for Diagnosing Chemical Deterioration in Reinforced Concrete Structures

Author:

Farahani Atiye1,Naderpour Hosein2ORCID,Konstantakatos Gerasimos3,Tarighat Amir4,Peymanfar Reza567ORCID,Asteris Panagiotis G.3ORCID

Affiliation:

1. Department of Civil Engineering, Tafresh University, Tafresh P.O. Box 39518-79611, Iran

2. Faculty of Civil Engineering, Semnan University, Semnan P.O. Box 35131-19111, Iran

3. Computational Mechanics Laboratory, School of Pedagogical and Technological Education, 14121 Heraklion, Greece

4. Department of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran P.O. Box 16788-15811, Iran

5. Department of Chemical Engineering, Energy Institute of Higher Education, Saveh P.O. Box 39177-67746, Iran

6. Department of Science, Iranian Society of Philosophers, Tehran P.O. Box 14778-93855, Iran

7. Peykareh Enterprise Development Co., Tehran P.O. Box 15149-45511, Iran

Abstract

The widespread application of reinforced concrete structures in different environmental conditions has underscored the need for effective maintenance and repair strategies. These structures offer numerous advantages, but are not impervious to the deleterious effects of chemical deterioration. The outcomes of this research hold significant implications for the management system of reinforced concrete structures. This study proposes the utilization of a fuzzy expert system as a means of enhancing the diagnosis of chemical deterioration in reinforced concrete structures that is a valuable tool for engineers and decision-makers involved in the maintenance and repair of these structures. The fuzzy expert system serves as an intelligent tool that can incorporate various symptoms of deterioration and inspection data to improve the accuracy and reliability of the diagnostic process. By integrating these inputs, the system evaluates 21 different data points, each representing a specific aspect of deterioration, on a scale ranging from 0 to 100. This numerical representation allows for a quantification of the level of deterioration, with 0 denoting minimal deterioration and 100 indicating severe deterioration. The effectiveness of the fuzzy expert system lies in its ability to process the vast amount of data and apply fuzzy operations on 352 fuzzy rules. These rules define the relationships between the inspection data, the type of deterioration, and its extent. Through this computational process, the fuzzy expert system can provide valuable insights into 10 distinct types of chemical deterioration, facilitating a more precise and comprehensive diagnosis. The implementation of the fuzzy expert system has the potential to revolutionize the field of diagnosing chemical deterioration in reinforced concrete structures. By addressing the limitations of traditional methods, this advanced approach can significantly improve the clarity and accuracy of the diagnostic process. The ability to obtain more precise information regarding the type and extent of deterioration is vital for developing effective maintenance and repair strategies. Ultimately, the fuzzy expert system holds great promise in enhancing the overall durability and performance of reinforced concrete structures in various environments.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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