A fuzzy approach for considering uncertainty in transient analysis of pipe networks

被引:15
作者
Haghighi, Ali [1 ]
Keramat, Alireza [2 ]
机构
[1] Shahid Chamran Univ Ahvaz, Dept Civil Engn, Ahvaz, Iran
[2] Jundi Shapur Univ Technol, Dept Engn, Dezful, Iran
关键词
fuzzy sets; pipe networks; transient analysis; uncertainties; NEURAL-NETWORK; MODEL;
D O I
10.2166/hydro.2012.191
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Uncertain parameters in the transient analysis of pipe networks lead to uncertain responses. Typical uncertainties are nodal demand, pipe friction coefficient and wave speed, which not only are imprecise in nature but also change significantly over time. Exploiting the fuzzy set theory and a simple scheme of the simulated annealing method, a conceptual model is developed. It can take into account the uncertainties of conventional transient analysis. This model helps designers of pipe systems in finding out the extent to which uncertainties in the inputs can spread to the transient highest and lowest pressures. A real piping system is analyzed herein as the case study. The results show that the transient extreme pressures can be highly affected by the uncertainties.
引用
收藏
页码:1024 / 1035
页数:12
相关论文
共 39 条
[1]  
[Anonymous], 2010, HDB METAHEURISTICS
[2]   Automated objective classification of daily circulation patterns for precipitation and temperature downscaling based on optimized fuzzy rules [J].
Bárdossy, A ;
Stehlík, J ;
Caspary, HJ .
CLIMATE RESEARCH, 2002, 23 (01) :11-22
[3]  
Bardossy A., 1995, Fuzzy Rule-Based Modeling with applications to Geophysical, Biological and Engineering Systems
[4]   Optimal design of water distribution networks for fuzzy demands [J].
Bhave, PR ;
Gupta, R .
CIVIL ENGINEERING AND ENVIRONMENTAL SYSTEMS, 2004, 21 (04) :229-245
[5]   FUZZY-PROGRAMMING APPROACH TO MULTICRITERIA DECISION-MAKING TRANSPORTATION PROBLEM [J].
BIT, AK ;
BISWAL, MP ;
ALAM, SS .
FUZZY SETS AND SYSTEMS, 1992, 50 (02) :135-141
[6]  
Buckley J.J., 1987, OPTIMIZATION MODELS, P226
[7]   Counterpropagation fuzzy-neural network for city flood control system [J].
Chang, Fi-John ;
Chang, Kai-Yao ;
Chang, Li-Chiu .
JOURNAL OF HYDROLOGY, 2008, 358 (1-2) :24-34
[8]  
Chaudhry M., 1987, APPL HYDRAULIC TRANS
[9]   Fuzzy iteration methodology for reservoir flood control operation [J].
Cheng, CT ;
Chau, KW .
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, 2001, 37 (05) :1381-1388
[10]   Applicability of neuro-fuzzy techniques in predicting ground-water vulnerability: a GIS-based sensitivity analysis [J].
Dixon, B .
JOURNAL OF HYDROLOGY, 2005, 309 (1-4) :17-38