Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Water supply network is an essential element of urban water supply systems. The operation of a water supply system is inseparably connected with a risk of failure. The main problem in the risk of failure analysis of water mains is the uncertainty of the information collected on the description of failure. In order to consider the uncertainty of information, the theory of fuzzy sets was used. The fuzzification of frequency, severity and the consequences of the incident scenario is basic input for fuzzy risk analysis. The presented model is part of a complex model of risk management of failures in water mains and can be used in practice in system operator’s decision-making process. An adaptation of the fuzzy set theory to analyse risk of failure of water mains is not a standard approach. An effect of the analysis of different sources of risk can be used for the design of a more reliable safety system assurance.
Słowa kluczowe
Rocznik
Tom
Strony
255--264
Opis fizyczny
Bibliogr. 22 poz., rys., tab., wykr.
Twórcy
autor
- Rzeszów University of Technology, Rzeszów, Poland
Bibliografia
- [1] Braglia, M. & Frosolini, M., & Montanari, R. (2003). Fuzzy criticality assessment model for failure modes and effects analysis. International Journal of Quality & Reliability Management, 20 (4), 503-524.
- [2] Dubois, D., & Prade, H. (1980). Fuzzy sets and systems: Theory and application. New York: Academic Press.
- [3] Ezell, B. & Farr, J. & Wiese, I. (2000). Infrastructure risk analysis of municipal water distribution system. Journal of Infrastructure Systems, ASCE. 6 (3), 118-122.
- [4] Haimes, Y. Y., Moser, D. & Stakhin, E. Risk Based Decision Making in Water Resources Journal of Infrastructure Systems, ASCE, 12, 401-415.
- [5] Haimes, Y. Y. (1998). Risk Modeling, Assessment and Management. Wiley, New York.
- [6] Haimes, Y. Y. (2009). On the Complex definition of risk: a systems-based approach. Risk Analisys 29 (12), 1647-1654.
- [7] Hubbard D. W. (2009). The failure of risk management. Wiley. New York. 2009.
- [8] Karwowski, W. & Mital, A. (1986). Potential applications of fuzzy sets in industrial safety engineering. Fuzzy Sets System. 19, 105-120.
- [9] Kleiner, Y. & Rajani, B. B. & Sadiq, R. (2006). Failure risk management of buried infrastructure using fuzzy-based techniques. Journal of Water Supply Research and Technology: Aqua, 55 (2), 81-94.
- [10] Kleiner, Y. (2004). A fuzzy based method of soil corrosivity evaluation for predicting water main deterioration. Journal of Infrastructure Systems, ASCE.10 (4), 149-156.
- [11] Lee, H. M. (1996). Applying fuzzy set theory to evaluate the rate of aggregative risk in software development. Fuzzy Sets and Systems, 79, 323-336.
- [12] Mamdani, E. H. (1977). Application of fuzzy logic to approximate reasoning Rusing linguistic systems. Fuzzy Sets and Systems, 26, 1182-1191.
- [13] Markowski, A. & Mannan, S. (2008). Fuzzy risk matrix. Journal of Hazardous Materials, 59 (1), 152.
- [14] Rak, J. & Tchórzewska-Cieślak, B. (2006). Review of matrix methods for risk assessment in water supply system. Journal of Konbin, 1 (1), 67-76.
- [15] Sadig, R., Kleiner, Y., & Rajani, B. (2007). Water quality failures in distribution networks-risk analysis using fuzzy logic and evidential reasoning. Risk Analysis.27 (5), 1381-1394.
- [16] Sadiq, R., & Tesfamariam, S. (2009). Environmental decision-making under uncertainty using intuitionistic fuzzy analytic hierarchy process (IF-AHP). Stochastic Environmental Research and Risk Assessment, 23 (1), 75-91.
- [17] Shang-Lien, L. & Ruei-Shan, L. (2002). Diagnosing reservoir water quality using selforganizing maps and fuzzy theory. Water Reserch.36, 265-2274.
- [18] Tchórzewska-Cieślak B. (2007). Method of assessing of risk of failure in water supply system. European safety and reliability conference ESREL. Risk, Reliability and Societal Safety. Taylor & Francis, 2.1535-1539, Norway, Stavanger.
- [19] Tchórzewska-Cieślak, B, (2009) Water supply system reliability management. Environmental Protection Engineering. 35, 29-35.
- [20] Yager, R. R. (2004). On determination of strength of belief for decision support under uncertainty-Part II: fusing strengths of belief. Fuzzy sets and systems. 142. 129-142.
- [21] Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338-353.
- [22] Zio, E. (2009). Computational Methods for Reliability and Risk Analysis. Hardcover. 1-250.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3d9320cd-1787-46c5-a4c6-9022cf7f57fd