Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Risk Assessment of Water Treatment Plants Using Fuzzy Fault Tree Analysis and Monte Carlo Simulation
https://orcid.org/http://orcid.org/0000-0002-8458-4538
Urban water supply, transmission, and distribution systems are considered as the basic infrastructures of each community. Deficiency of water resources in system leads to lack of some subscribers’ access to safe water at any time. The water treatment units have a high potential for massive crisis and importance of sustainable performance in water treatment plants, due to their special role in high quantity and quality water supply even in critical situations, requires a comprehensive approach in assessing and increasing the reliability. A comprehensive approach in assessing the performance of water treatment plants and reducing their vulnerability can lead to cost reduction of inappropriate performance in critical situations and also a focus on the most important vulnerable parts of water treatment plants to decrease their vulnerability, as well as cost-effective budgeting in recovery programs. In this research, due to the uncertainties in the input information, two methods of fuzzy fault tree analysis (FFTA) and fault tree analysis (FTA) based on Monte Carlo simulation were evaluated in Jalaliyeh water treatment plant in Tehran, and results of both approaches were compared in terms of uncertainty analysis. The results indicate the low to moderate failure risk in the treatment plant in both approaches and a small difference between results in both cases. Failure probability of top event for FFTA and Monte Carlo-based FTA methods is 0.194 and 0.27, respectively. In the basic event rating, it was found that threats such as inappropriate reservoir design, power equipment failure, transfer pipe failure, and inappropriate maintenance of the pumps play the major role in treatment plant failure.
Risk Assessment of Water Treatment Plants Using Fuzzy Fault Tree Analysis and Monte Carlo Simulation
https://orcid.org/http://orcid.org/0000-0002-8458-4538
Urban water supply, transmission, and distribution systems are considered as the basic infrastructures of each community. Deficiency of water resources in system leads to lack of some subscribers’ access to safe water at any time. The water treatment units have a high potential for massive crisis and importance of sustainable performance in water treatment plants, due to their special role in high quantity and quality water supply even in critical situations, requires a comprehensive approach in assessing and increasing the reliability. A comprehensive approach in assessing the performance of water treatment plants and reducing their vulnerability can lead to cost reduction of inappropriate performance in critical situations and also a focus on the most important vulnerable parts of water treatment plants to decrease their vulnerability, as well as cost-effective budgeting in recovery programs. In this research, due to the uncertainties in the input information, two methods of fuzzy fault tree analysis (FFTA) and fault tree analysis (FTA) based on Monte Carlo simulation were evaluated in Jalaliyeh water treatment plant in Tehran, and results of both approaches were compared in terms of uncertainty analysis. The results indicate the low to moderate failure risk in the treatment plant in both approaches and a small difference between results in both cases. Failure probability of top event for FFTA and Monte Carlo-based FTA methods is 0.194 and 0.27, respectively. In the basic event rating, it was found that threats such as inappropriate reservoir design, power equipment failure, transfer pipe failure, and inappropriate maintenance of the pumps play the major role in treatment plant failure.
Risk Assessment of Water Treatment Plants Using Fuzzy Fault Tree Analysis and Monte Carlo Simulation
https://orcid.org/http://orcid.org/0000-0002-8458-4538
Urban water supply, transmission, and distribution systems are considered as the basic infrastructures of each community. Deficiency of water resources in system leads to lack of some subscribers’ access to safe water at any time. The water treatment units have a high potential for massive crisis and importance of sustainable performance in water treatment plants, due to their special role in high quantity and quality water supply even in critical situations, requires a comprehensive approach in assessing and increasing the reliability. A comprehensive approach in assessing the performance of water treatment plants and reducing their vulnerability can lead to cost reduction of inappropriate performance in critical situations and also a focus on the most important vulnerable parts of water treatment plants to decrease their vulnerability, as well as cost-effective budgeting in recovery programs. In this research, due to the uncertainties in the input information, two methods of fuzzy fault tree analysis (FFTA) and fault tree analysis (FTA) based on Monte Carlo simulation were evaluated in Jalaliyeh water treatment plant in Tehran, and results of both approaches were compared in terms of uncertainty analysis. The results indicate the low to moderate failure risk in the treatment plant in both approaches and a small difference between results in both cases. Failure probability of top event for FFTA and Monte Carlo-based FTA methods is 0.194 and 0.27, respectively. In the basic event rating, it was found that threats such as inappropriate reservoir design, power equipment failure, transfer pipe failure, and inappropriate maintenance of the pumps play the major role in treatment plant failure.
Risk Assessment of Water Treatment Plants Using Fuzzy Fault Tree Analysis and Monte Carlo Simulation
Iran J Sci Technol Trans Civ Eng
Tabesh, Massoud (Autor:in) / Roozbahani, Abbas (Autor:in) / Hadigol, Farhad (Autor:in) / Ghaemi, Elham (Autor:in)
01.02.2022
16 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Fuzzy Monte Carlo Simulation and Risk Assessment in Construction
| Online Contents | 2010
Risk assessment of revetments by Monte Carlo simulation
| British Library Online Contents | 2004
Risk assessment of revetments by Monte Carlo simulation
| British Library Online Contents | 2006