Fuzzy Logic Applications in Civil Engineering: A Structured Review of Methods, Applications, and Research Gaps

Abstract

Civil engineering systems are complex because materials, construction processes, environmental circumstances, and human judgement interact. Statistics and determinism neglect engineering decision-making's subjectivity and ambiguity. Fuzzy logic has been a popular soft-computing method for modelling imprecise data using linguistic variables and rule-based reasoning in recent decades. This work examines fuzzy logic in reinforced concrete quality evaluation, structural and geotechnical engineering, and construction management. A representative selection of peer-reviewed research is analysed by application areas, fuzzy inference system (FIS) types (Mamdani and Takagi–Sugeno), membership function design, rule-base formulation, defuzzification approaches, and integration with MCDM and hybrid intelligent models Under uncertainty in limited or subjective data, fuzzy logic-based frameworks are interpretable, transparent, and flexible. Model calibration, validation robustness, repeatability, and scalability are research and methodological constraints. Future civil engineering research should support BIM-enabled decision-support frameworks and data-informed fuzzy systems.