Fuzzy approach in the uncertainty analysis of the water distribution network of Becej

Branisavljević, Nemanja; Ivetić, Marko

doi:10.1080/10286600600789425

Cited by 32 publications

(15 citation statements)

References 2 publications

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“…The method required solving several nonlinear optimization problems. Branisavljevic and Ivetic (2006) used genetic algorithm for solving the nonlinear optimization models for finding the uncertainty in dependent parameters considering uncertainty in roughness of old pipes. Bhave and Gupta (2006) Gupta and Bhave (2007) showed that dependent parameters change monotonically with independent parameters and suggested a simple method in which the impact of the change of independent parameters on a dependent parameter is determined in the first stage.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Several methodologies have been suggested in the recent past to show how parameter uncertainty is propagated to dependent parameters by considering uncertain parameters as fuzzy (Revelli and Ridolfi 2002, Branisavljevic and Ivetic 2006, Shibu and Reddy 2011, Spiliotis and Tsakiris 2012. All these methods assume that uncertain demands are satisfied at all demand nodes which may not be true.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy Analysis of Pressure-Deficient Water Distribution Networks

Gupta

Harkutiya

Dongre

et al. 2014

World Environmental and Water Resources Congress 2014

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Future water demands and pipe roughness coefficients used in the design of water distribution networks (WDNs) have a high degree of uncertainty. Fuzzy analysis of WDNs provide how the uncertainties in independent or basic parameters (such as nodal demands and pipe roughness coefficients) are propagated to dependent or derived parameters (such as pipe flows, pipe velocities and available pressure heads). Usually demand dependent analysis is used for such analysis. A WDN may be pressure-deficient or may become pressure-deficient because of high pipe roughness or inadequate pump pressure and may not be able to meet desired demands at all nodes. Thus, it is desirable to consider the nodal outflows as unknown and as a function of available pressure heads under pressure-deficient conditions. An approach for fuzzy analysis of a WDN which takes into account pressure-deficient condition using node flow analysis is presented in this paper. The proposed methodology is illustrated with example network taken from literature. The methodology is useful in identifying vulnerable zones in WDNs and can be extended for reliability analysis under uncertainty of nodal demands and pipe roughness coefficients. Comparison of results with usual demand-dependent analysis shows that proposed method is better in identifying vulnerable zones.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fuzzy Analysis of Pressure-Deficient Water Distribution Networks

Gupta

Harkutiya

Dongre

et al. 2014

World Environmental and Water Resources Congress 2014

View full text Add to dashboard Cite

show abstract

“…The advantage of the affinity hydration model relies on the fact that only few parameters have to be calibrated to predict cement hydration kinetics. Despite Equation (4) having less parameters and performing reasonably well on non-blended cements [32], prediction mismatches are likely observed at either early (t = 1 to 3 days) or later stages (t > 14 days) when simulating the kinetics of blended cements. Notice that, at present, blended cements represent the greatest share of commercialized cement and tend to contain less and less clinker [1].…”

Section: Affinity Hydration Modelmentioning

confidence: 99%

Fuzzy affinity hydration model

Silva

Šmilauer

2015

Journal of Intelligent &Amp; Fuzzy Systems

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Time-dependent hydration process of Portland cement presents a complex system with several uncertainties. A presented four-parametric affinity hydration model captures well the hydration kinetics when three parameters are treated as fuzzy numbers. The equations for the fuzzy affinity hydration model are derived using Zadeh's extension principle, which allows for simplifying calculations to obtain a fuzzy solution. The fuzzy model validates Portland cements with different mineral compositions, watercement ratii raging from 0.16 to 0.50, and curing temperatures varying from 10 to 30 • C. Also, the fuzzy model is verified against CEMHYD3D and s-shape hydration model. In summary, validation and verification results show that the fuzzy model permits to predict vague conditions without lacking the credibility of results.

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“…This procedure for calculating the output ␣-cut interval boundaries is innovative and differs significantly from the common approaches on the subject on two aspects: • if the model output value is monotonic in the space of input variable intervals, then extremes are calculated only by using extreme values of input variable intervals as input data; • otherwise, an optimization method is required for determining the output extremes [2,22].…”

Section: Application Of Fuzzy Numbersmentioning

confidence: 99%

Embankment dam break: Uncertainty of outflow based on fuzzy representation of breach formation parameters

Tsakiris¹,

Spiliotis²

2014

Journal of Intelligent &Amp; Fuzzy Systems

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The failure of an embankment dam results in an outflow hydrograph with catastrophic consequences to the downstream valley, especially when populations at risk are located close to the dam. The estimation of the outflow from the created breach is the key information for delineating the area at risk and the estimation of the associated potential consequences. This paper studies the uncertainty of breach parameter estimations by using fuzzy set theory and its impact on the outflow from the breach. For simulating the breach formation and the development of outflow hydrograph, a simplified analytical solver, which was recently presented by the authors, is used. The solver is based on the assumptions of prismatic reservoir, the parabolic shape of the breach and the constant rate of vertical erosion. The parameters, which are represented as triangular fuzzy numbers, are: (i) the characteristic parameter of the parabolic shape of the breach and (ii) the rate of vertical erosion. It was concluded that the approach for estimating the outflow differs, depending on the cause of fuzziness. The approach for estimating the outflow differs according to the parameter which exhibits fuzziness in its estimation. In fact, the uncertainty of outflow is to a great extent dependent on the uncertainty of estimation of vertical erosion and to a much lesser extent on the characteristic of the breach shape.

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Fuzzy approach in the uncertainty analysis of the water distribution network of Becej

Cited by 32 publications

References 2 publications

Fuzzy Analysis of Pressure-Deficient Water Distribution Networks

Fuzzy Analysis of Pressure-Deficient Water Distribution Networks

Fuzzy affinity hydration model

Embankment dam break: Uncertainty of outflow based on fuzzy representation of breach formation parameters

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