Fuzzy uncertainty and its applications in reinforced concrete structures

Abstract

Purpose The aim of this paper is mainly to handle the fuzzy uncertainties present in structures appropriately. In general, uncertainties of variables are classified as aleatory and epistemic. The different sources of uncertainties in reinforced concrete structures include the randomness, mathematical models, physical models, environmental factors and gross errors. The effects of imprecise data in reinforced concrete structures are studied here by using fuzzy concepts. The aim of this paper is mainly to handle the uncertainties of variables with unclear boundaries. Design/methodology/approach To achieve the intended objective, the reinforced concrete beam subjected to flexure and shear was designed as per Euro Code (EC2). Then, different design parameters such as corrosion parameters, material properties and empirical expressions of time-dependent material properties were identified through a thorough literature review. Findings The fuzziness of variables was identified, and their membership functions were generated by using the heuristic method and drawn by MATLAB R2018a software. In addition to the identification of fuzziness of variables, the study further extended to design optimization of reinforced concrete structure by using fuzzy relation and fuzzy composition. Originality/value In the design codes of the concrete structure, the concrete grades such as C16/20, C20/25, C25/30, C30/37 and so on are provided and being adopted for design in which the intermediate grades are not considered, but using fuzzy concepts the intermediate grades of concrete can be recognized by their respective degree of membership. In the design of reinforced concrete structure using fuzzy relation and composition methods, the optimum design is considered when the degree of membership tends to unity. In addition to design optimization, the level of structural performance evaluation can also be carried out by using fuzzy concepts.

Advantages of fuzzy approach compared to probabilistic approach in project evaluation

“…According to Woju and Balu (2020), uncertainty is usually classified as random and fuzzy. Random uncertainty arises from the inherent randomness of the physical properties and environmental system, while fuzzy uncertainty stems from the lack of relevant knowledge and inaccurate information about the system (Li et al, 2016).…”

Finite-element modeling of partially prestressed concrete beams with unbonded tendon under monotonic loadings

“…The experimental investigations on the behavior of unbonded partially prestressed concrete (UPPSC) beam that is restricted to the surface measurements only are abundant in the literature, which is a time-consuming and expensive method, whereas the finite-element (FE) modeling of such beams using numerical software that predicts the complete information on the nonlinear behavior of prestressed concrete beams with cost-effective, reliable and abrupt JEDT 22,1 results is very scarce (Woju and Balu, 2020). Hence, in this paper, an attempt is made to demonstrate the complete nonlinear FE modeling approaches of UPPSC beams using the ANSYS package.…”

“…The following literature will provide information on the experimental study and FE simulations of prestressed concrete beams using the ANSYS package (Woju and Balu, 2020;Alluqmani, 2014Alluqmani, , 2021. To assess the influence of conventional steel percentage on the loaddeflection response and the stresses in unbonded steel tendon at failures, experimental study was done by Campbell and Chouinard (1991).…”