1 resultado para fatal accidents
em Instituto Politécnico do Porto, Portugal
Filtro por publicador
- Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España (1)
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- BORIS: Bern Open Repository and Information System - Berna - Suiça (56)
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- Chinese Academy of Sciences Institutional Repositories Grid Portal (12)
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- FAUBA DIGITAL: Repositorio institucional científico y académico de la Facultad de Agronomia de la Universidad de Buenos Aires (1)
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- Gallica, Bibliotheque Numerique - Bibliothèque nationale de France (French National Library) (BnF), France (50)
- Greenwich Academic Literature Archive - UK (13)
- Helda - Digital Repository of University of Helsinki (38)
- Indian Institute of Science - Bangalore - Índia (10)
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- Instituto Politécnico de Bragança (1)
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- Plymouth Marine Science Electronic Archive (PlyMSEA) (1)
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- Queensland University of Technology - ePrints Archive (243)
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- Repositório do Centro Hospitalar de Lisboa Central, EPE - Centro Hospitalar de Lisboa Central, EPE, Portugal (1)
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- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (34)
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- Universidad del Rosario, Colombia (5)
- Universidad Politécnica de Madrid (10)
- Universidade Federal do Pará (3)
- Universidade Federal do Rio Grande do Norte (UFRN) (3)
- Universitat de Girona, Spain (2)
- Université de Lausanne, Switzerland (2)
- Université de Montréal (1)
- Université de Montréal, Canada (23)
- University of Connecticut - USA (1)
- University of Michigan (233)
- University of Queensland eSpace - Australia (6)
Resumo:
Advances in technology have produced more and more intricate industrial systems, such as nuclear power plants, chemical centers and petroleum platforms. Such complex plants exhibit multiple interactions among smaller units and human operators, rising potentially disastrous failure, which can propagate across subsystem boundaries. This paper analyzes industrial accident data-series in the perspective of statistical physics and dynamical systems. Global data is collected from the Emergency Events Database (EM-DAT) during the time period from year 1903 up to 2012. The statistical distributions of the number of fatalities caused by industrial accidents reveal Power Law (PL) behavior. We analyze the evolution of the PL parameters over time and observe a remarkable increment in the PL exponent during the last years. PL behavior allows prediction by extrapolation over a wide range of scales. In a complementary line of thought, we compare the data using appropriate indices and use different visualization techniques to correlate and to extract relationships among industrial accident events. This study contributes to better understand the complexity of modern industrial accidents and their ruling principles.