1 resultado para Complex biological systems
em CUNY Academic Works
Filtro por publicador
- KUPS-Datenbank - Universität zu Köln - Kölner UniversitätsPublikationsServer (1)
- Repository Napier (2)
- University of Cagliari UniCA Eprints (1)
- ABACUS. Repositorio de Producción Científica - Universidad Europea (1)
- Aberdeen University (2)
- Abertay Research Collections - Abertay University’s repository (1)
- Aberystwyth University Repository - Reino Unido (3)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (29)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (14)
- Aquatic Commons (3)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (18)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (4)
- Aston University Research Archive (41)
- Biblioteca de Teses e Dissertações da USP (5)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (12)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (14)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (6)
- Biodiversity Heritage Library, United States (1)
- Bioline International (1)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (24)
- Boston University Digital Common (2)
- Brock University, Canada (3)
- Bucknell University Digital Commons - Pensilvania - USA (6)
- Bulgarian Digital Mathematics Library at IMI-BAS (5)
- CaltechTHESIS (20)
- Cambridge University Engineering Department Publications Database (39)
- CentAUR: Central Archive University of Reading - UK (43)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (16)
- Cochin University of Science & Technology (CUSAT), India (13)
- Coffee Science - Universidade Federal de Lavras (1)
- Collection Of Biostatistics Research Archive (1)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (2)
- CORA - Cork Open Research Archive - University College Cork - Ireland (5)
- CUNY Academic Works (1)
- Dalarna University College Electronic Archive (1)
- Deakin Research Online - Australia (44)
- Department of Computer Science E-Repository - King's College London, Strand, London (1)
- Digital Commons - Michigan Tech (1)
- Digital Commons at Florida International University (10)
- Digital Howard @ Howard University | Howard University Research (1)
- Digital Peer Publishing (2)
- Digital Repository at Iowa State University (1)
- DigitalCommons - The University of Maine Research (1)
- DigitalCommons@The Texas Medical Center (7)
- DigitalCommons@University of Nebraska - Lincoln (5)
- DRUM (Digital Repository at the University of Maryland) (2)
- Duke University (8)
- Ecology and Society (1)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (1)
- FUNDAJ - Fundação Joaquim Nabuco (1)
- Glasgow Theses Service (5)
- Greenwich Academic Literature Archive - UK (3)
- Helda - Digital Repository of University of Helsinki (9)
- Illinois Digital Environment for Access to Learning and Scholarship Repository (4)
- Indian Institute of Science - Bangalore - Índia (49)
- INSTITUTO DE PESQUISAS ENERGÉTICAS E NUCLEARES (IPEN) - Repositório Digital da Produção Técnico Científica - BibliotecaTerezine Arantes Ferra (2)
- Instituto Politécnico do Porto, Portugal (7)
- Lume - Repositório Digital da Universidade Federal do Rio Grande do Sul (2)
- Martin Luther Universitat Halle Wittenberg, Germany (1)
- Massachusetts Institute of Technology (7)
- Memorial University Research Repository (1)
- National Center for Biotechnology Information - NCBI (36)
- Nottingham eTheses (9)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (3)
- Portal de Revistas Científicas Complutenses - Espanha (1)
- Publishing Network for Geoscientific & Environmental Data (5)
- QSpace: Queen's University - Canada (2)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (44)
- Queensland University of Technology - ePrints Archive (109)
- RDBU - Repositório Digital da Biblioteca da Unisinos (1)
- Repositorio Académico de la Universidad Nacional de Costa Rica (2)
- Repositório Científico da Universidade de Évora - Portugal (2)
- Repositório digital da Fundação Getúlio Vargas - FGV (3)
- Repositório Institucional da Universidade de Aveiro - Portugal (3)
- Repositório Institucional da Universidade Federal do Rio Grande - FURG (2)
- Repositorio Institucional de la Universidad de Málaga (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (77)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (3)
- SAPIENTIA - Universidade do Algarve - Portugal (1)
- School of Medicine, Washington University, United States (1)
- Universidad de Alicante (6)
- Universidad del Rosario, Colombia (16)
- Universidad Politécnica de Madrid (27)
- Universidade Estadual Paulista "Júlio de Mesquita Filho" (UNESP) (2)
- Universidade Federal de Uberlândia (1)
- Universidade Federal do Pará (3)
- Universidade Federal do Rio Grande do Norte (UFRN) (11)
- Universita di Parma (1)
- Universitat de Girona, Spain (5)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (5)
- Université de Lausanne, Switzerland (2)
- Université de Montréal, Canada (11)
- Université Laval Mémoires et thèses électroniques (2)
- University of Michigan (2)
- University of Queensland eSpace - Australia (25)
- University of Southampton, United Kingdom (1)
- University of Washington (6)
- WestminsterResearch - UK (1)
- Worcester Research and Publications - Worcester Research and Publications - UK (1)
Resumo:
When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. In general, this type of techniques based on analytical models can be seen as an application of the well-known fault detection and isolation theory for complex industrial systems. Nonetheless, the assumption of single leak scenarios is usually made considering a certain leak size pattern which may not hold in real applications. Upgrading a leak detection and localization method based on a direct modeling approach to handle multiple-leak scenarios can be, on one hand, quite straightforward but, on the other hand, highly computational demanding for large class of water distribution networks given the huge number of potential water loss hotspots. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios and large class of water distribution networks. This method can be seen as an upgrade of the above mentioned method based on a direct modeling approach in which a global search method based on genetic algorithms has been integrated in order to estimate those network water loss hotspots and the size of the leaks. This is an inverse / direct modeling method which tries to take benefit from both approaches: on one hand, the exploration capability of genetic algorithms to estimate network water loss hotspots and the size of the leaks and on the other hand, the straightforwardness and reliability offered by the availability of an accurate hydraulic model to assess those close network areas around the estimated hotspots. The application of the resulting method in a DMA of the Barcelona water distribution network is provided and discussed. The obtained results show that leakage detection and localization under multiple-leak scenarios may be performed efficiently following an easy procedure.