Faculty Publications

Now showing 1 - 4 of 4

Fuzzy uncertainty and its applications in reinforced concrete structures
(Emerald Group Holdings Ltd., 2020) Worabo Woju, U.W.; Balu, A.S.
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. © 2020, Emerald Publishing Limited.
Structural damage identification of bridge using high dimensional model representation
(Bellwether Publishing, Ltd., 2021) Naveen, B.O.; Balu, A.S.
Any engineering structure under the action of various internal and external factors like changes in the material properties, inadequate design, faulty construction, deterioration due to malfunctioning are susceptible to damages. In the past, many methods have attempted to identify damage by solving an inverse problem, which inevitably needs an analytical model. However, often the construction of these analytical model requires considerable effort in building a mathematical framework with acceptable level of accuracy and reliability which makes these approaches less attractive. To circumvent this complexity, this work presents a computationally efficient approach in structural damage identification using high dimensional model representation. © 2020 Taylor & Francis Group, LLC.
Analysis of structural systems with imprecise uncertainties using high dimensional model representation
(World Scientific, 2021) Spoorthi, S.K.; Balu, A.S.
Uncertainties present in any structural system inherently affect the performance and design of the system. The sources of uncertainties serve the basis for delineating the types as aleatory or epistemic. The probabilistic models can be considered as the most valuable strategies to deal with aleatory uncertainties, while convex models, possibility theory, evidence theory and Bayesian probability theory can be used to deal with epistemic uncertainty. However, when only scarce datasets are available and knowledge is incomplete, a more general framework, such as probability-box, is more appropriate to describe the uncertainty. Furthermore, analysis of complex and multi-dimensional structures is expensive and time consuming when numerical techniques are used. Therefore, simulation of such structures for many realisation of uncertain input becomes a challenging task in the uncertainty analysis. In this paper, complex structural systems with imprecise uncertain input are studied and evaluated efficiently by High Dimensional Model Representation based uncertainty analysis. © 2021 World Scientific Publishing Company.
Belief reliability of structures with hybrid uncertainties
(Springer Science and Business Media B.V., 2024) Metagudda, S.H.; Balu, A.S.
Reliability of structures is evaluated by considering uncertainties present in the system, which can be characterized into aleatory and epistemic. Inherent randomness in the physical environment leads to aleatory, whereas insufficient knowledge about the system leads to epistemic uncertainty. For the reliability evaluation, ascertaining the sources of uncertainties poses a great challenge since both uncertainties coexist widely in structural systems. Aleatory uncertainties are quantified by probabilistic measures (such as first order reliability method, second order reliability method and Monte Carlo techniques), whereas epistemic uncertainties are quantified by various non-probabilistic approaches (such as interval analysis methods, evidence theory, possibility theory and fuzzy theory). However, major issues like interval extension problem and duality conditions that lead to overestimation hinder the versatility of application of such methods, thus uncertainty theory has been emerged to overcome these limitations. Given the existing uncertainties and limitations, a hybrid strategy has been constructed and referred to as “belief reliability”. A belief reliability metric is integration of three key factors: design margin, aleatory and epistemic uncertainty factor to evaluate the reliability of the structural system. In this paper, Monte Carlo simulation is adopted to account for aleatory uncertainty. On the other hand, epistemic uncertainty is quantified through adjustment factor approach using FMEA (failure mode effective analysis). Numerical examples are presented to substantiate the proposed methodology being applied to variety of problems both implicit and explicit nature in structural engineering. © Springer Nature B.V. 2024.

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