A fuzzy approach to reliability based design of storm water drain network
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...
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| Veröffentlicht in: | Stochastic environmental research and risk assessment 2017-07, Vol.31 (5), p.1091-1106 |
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| creator | Gouri, R. L. Srinivas, V. V. |
| description | 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. |
| doi_str_mv | 10.1007/s00477-016-1299-2 |
| format | Article |
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L. ; Srinivas, V. V.</creator><creatorcontrib>Gouri, R. L. ; Srinivas, V. V.</creatorcontrib><description>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.</description><identifier>ISSN: 1436-3240</identifier><identifier>EISSN: 1436-3259</identifier><identifier>DOI: 10.1007/s00477-016-1299-2</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Ambiguity ; Aquatic Pollution ; Chemistry and Earth Sciences ; Computational Intelligence ; Computer Science ; Computer simulation ; Conduits ; Design analysis ; Design engineering ; Design optimization ; Drainage ; Earth and Environmental Science ; Earth Sciences ; Environment ; Estimates ; Guidelines ; Math. Appl. in Environmental Science ; Mathematical models ; Monte Carlo simulation ; Network reliability ; Normal distribution ; Original Paper ; Physics ; Probability Theory and Stochastic Processes ; Reliability analysis ; Retrofitting ; Safety ; Statistics for Engineering ; Stormwater ; System reliability ; Waste Water Technology ; Water Management ; Water Pollution Control</subject><ispartof>Stochastic environmental research and risk assessment, 2017-07, Vol.31 (5), p.1091-1106</ispartof><rights>Springer-Verlag Berlin Heidelberg 2016</rights><rights>Stochastic Environmental Research and Risk Assessment is a copyright of Springer, 2017.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-db3e21ec11e9b856d30517300b9f0df5a5d379dbd1a47e99896cf487c96580613</citedby><cites>FETCH-LOGICAL-c316t-db3e21ec11e9b856d30517300b9f0df5a5d379dbd1a47e99896cf487c96580613</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00477-016-1299-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00477-016-1299-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Gouri, R. L.</creatorcontrib><creatorcontrib>Srinivas, V. V.</creatorcontrib><title>A fuzzy approach to reliability based design of storm water drain network</title><title>Stochastic environmental research and risk assessment</title><addtitle>Stoch Environ Res Risk Assess</addtitle><description>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.</description><subject>Ambiguity</subject><subject>Aquatic Pollution</subject><subject>Chemistry and Earth Sciences</subject><subject>Computational Intelligence</subject><subject>Computer Science</subject><subject>Computer simulation</subject><subject>Conduits</subject><subject>Design analysis</subject><subject>Design engineering</subject><subject>Design optimization</subject><subject>Drainage</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Environment</subject><subject>Estimates</subject><subject>Guidelines</subject><subject>Math. Appl. in Environmental Science</subject><subject>Mathematical models</subject><subject>Monte Carlo simulation</subject><subject>Network reliability</subject><subject>Normal distribution</subject><subject>Original Paper</subject><subject>Physics</subject><subject>Probability Theory and Stochastic Processes</subject><subject>Reliability analysis</subject><subject>Retrofitting</subject><subject>Safety</subject><subject>Statistics for Engineering</subject><subject>Stormwater</subject><subject>System reliability</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><issn>1436-3240</issn><issn>1436-3259</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kD1PwzAQhi0EEhX0B7BZYg7cxbGTG6uKj0qVWGC27NgphjYpdqqq_fWkCkIsTHfD-7x3ehi7QbhDgPI-ARRlmQGqDHOiLD9jEyyEykQu6fx3L-CSTVMKdmCkIEKYsMWMN7vj8cDNdhs7U7_zvuPRr4OxYR36A7cmecedT2HV8q7hqe_ihu9N7yN30YSWt77fd_Hzml00Zp389GdesbfHh9f5c7Z8eVrMZ8usFqj6zFnhc_Q1oidbSeUESCwFgKUGXCONdKIkZx2aovREFam6KaqyJiUrUCiu2O3YO_z7tfOp1x_dLrbDSY0EJCuVkxhSOKbq2KUUfaO3MWxMPGgEfZKmR2l6kKZP0nQ-MPnIpCHbrnz80_wv9A1P025X</recordid><startdate>20170701</startdate><enddate>20170701</enddate><creator>Gouri, R. 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V.</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7ST</scope><scope>7XB</scope><scope>88I</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>L6V</scope><scope>M2P</scope><scope>M7S</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0W</scope><scope>SOI</scope></search><sort><creationdate>20170701</creationdate><title>A fuzzy approach to reliability based design of storm water drain network</title><author>Gouri, R. L. ; Srinivas, V. V.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-db3e21ec11e9b856d30517300b9f0df5a5d379dbd1a47e99896cf487c96580613</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Ambiguity</topic><topic>Aquatic Pollution</topic><topic>Chemistry and Earth Sciences</topic><topic>Computational Intelligence</topic><topic>Computer Science</topic><topic>Computer simulation</topic><topic>Conduits</topic><topic>Design analysis</topic><topic>Design engineering</topic><topic>Design optimization</topic><topic>Drainage</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Environment</topic><topic>Estimates</topic><topic>Guidelines</topic><topic>Math. Appl. in Environmental Science</topic><topic>Mathematical models</topic><topic>Monte Carlo simulation</topic><topic>Network reliability</topic><topic>Normal distribution</topic><topic>Original Paper</topic><topic>Physics</topic><topic>Probability Theory and Stochastic Processes</topic><topic>Reliability analysis</topic><topic>Retrofitting</topic><topic>Safety</topic><topic>Statistics for Engineering</topic><topic>Stormwater</topic><topic>System reliability</topic><topic>Waste Water Technology</topic><topic>Water Management</topic><topic>Water Pollution Control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gouri, R. L.</creatorcontrib><creatorcontrib>Srinivas, V. V.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Environment Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Science Journals</collection><collection>ProQuest Engineering Database</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>DELNET Engineering & Technology Collection</collection><collection>Environment Abstracts</collection><jtitle>Stochastic environmental research and risk assessment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gouri, R. L.</au><au>Srinivas, V. V.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A fuzzy approach to reliability based design of storm water drain network</atitle><jtitle>Stochastic environmental research and risk assessment</jtitle><stitle>Stoch Environ Res Risk Assess</stitle><date>2017-07-01</date><risdate>2017</risdate><volume>31</volume><issue>5</issue><spage>1091</spage><epage>1106</epage><pages>1091-1106</pages><issn>1436-3240</issn><eissn>1436-3259</eissn><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.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00477-016-1299-2</doi><tpages>16</tpages></addata></record> |
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| subjects | Ambiguity Aquatic Pollution Chemistry and Earth Sciences Computational Intelligence Computer Science Computer simulation Conduits Design analysis Design engineering Design optimization Drainage Earth and Environmental Science Earth Sciences Environment Estimates Guidelines Math. Appl. in Environmental Science Mathematical models Monte Carlo simulation Network reliability Normal distribution Original Paper Physics Probability Theory and Stochastic Processes Reliability analysis Retrofitting Safety Statistics for Engineering Stormwater System reliability Waste Water Technology Water Management Water Pollution Control |
| title | A fuzzy approach to reliability based design of storm water drain network |
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