A fuzzy approach to reliability based design of storm water drain network

Gouri, R L and Srinivas, V V (2017) A fuzzy approach to reliability based design of storm water drain network. In: STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 31 (5). pp. 1091-1106.

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Abstract

This paper proposes an approach to estimate reliability of a storm water drain (SWD) network in fuzzy framework. It involves: (i) use of proposed fuzzy Monte-Carlo simulation (FMCS) methodology to estimate fuzzy reliability of conduits in the network, (ii) construction of a reliability block diagram (RBD) for the network (system) using suggested guidelines, and (iii) use of the RBD and reliability estimates of the conduits in the network to compute system reliability based on a proposed procedure. In addition, a system reliability based methodology is proposed for design/retrofitting of SWD network by optimization of its conduit dimensions. Conventionally used reliability analysis approaches assume that the cumulative distribution function (CDF) of performance function (marginal safety) of conduits follows Gaussian distribution, which cannot be ensured in the real world scenario. The proposed approach alleviates the need for making such assumptions and can account for linguistic ambiguity in variables defining the performance function. Effectiveness of the proposed approach is demonstrated on a hypothetical SWD network and a real network in Bangalore, India. Comparison of the results obtained from the proposed approach with those from conventional Monte-Carlo simulation (MCS) reliability assessment approach indicated that the estimate of system reliability and conduit reliability are higher with FMCS approach. Consequently, conduit dimensions required to attain required system (network) reliability could be expected to be lower when FMCS approach is used for designing or retrofitting a system.

Item Type:	Journal Article
Publication:	STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
Additional Information:	Copy right for this article belongs to the SPRINGER, 233 SPRING ST, NEW YORK, NY 10013 USA
Department/Centre:	Division of Mechanical Sciences > Civil Engineering
Date Deposited:	14 Jul 2017 04:57
Last Modified:	14 Jul 2017 04:57
URI:	http://eprints.iisc.ac.in/id/eprint/57373

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