4 resultados para Natural disasters

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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In order to handle Natural disasters, emergency areas are often individuated over the territory, close to populated centres. In these areas, rescue services are located which respond with resources and materials for population relief. A method of automatic positioning of these centres in case of a flood or an earthquake is presented. The positioning procedure consists of two distinct parts developed by the research group of Prof Michael G. H. Bell of Imperial College, London, refined and applied to real cases at the University of Bologna under the coordination of Prof Ezio Todini. There are certain requirements that need to be observed such as the maximum number of rescue points as well as the number of people involved. Initially, the candidate points are decided according to the ones proposed by the local civil protection services. We then calculate all possible routes from each candidate rescue point to all other points, generally using the concept of the "hyperpath", namely a set of paths each one of which may be optimal. The attributes of the road network are of fundamental importance, both for the calculation of the ideal distance and eventual delays due to the event measured in travel time units. In a second phase, the distances are used to decide the optimum rescue point positions using heuristics. This second part functions by "elimination". In the beginning, all points are considered rescue centres. During every interaction we wish to delete one point and calculate the impact it creates. In each case, we delete the point that creates less impact until we reach the number of rescue centres we wish to keep.

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The so called cascading events, which lead to high-impact low-frequency scenarios are rising concern worldwide. A chain of events result in a major industrial accident with dreadful (and often unpredicted) consequences. Cascading events can be the result of the realization of an external threat, like a terrorist attack a natural disaster or of “domino effect”. During domino events the escalation of a primary accident is driven by the propagation of the primary event to nearby units, causing an overall increment of the accident severity and an increment of the risk associated to an industrial installation. Also natural disasters, like intense flooding, hurricanes, earthquake and lightning are found capable to enhance the risk of an industrial area, triggering loss of containment of hazardous materials and in major accidents. The scientific community usually refers to those accidents as “NaTechs”: natural events triggering industrial accidents. In this document, a state of the art of available approaches to the modelling, assessment, prevention and management of domino and NaTech events is described. On the other hand, the relevant work carried out during past studies still needs to be consolidated and completed, in order to be applicable in a real industrial framework. New methodologies, developed during my research activity, aimed at the quantitative assessment of domino and NaTech accidents are presented. The tools and methods provided within this very study had the aim to assist the progress toward a consolidated and universal methodology for the assessment and prevention of cascading events, contributing to enhance safety and sustainability of the chemical and process industry.

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Over the last decades the impact of natural disasters to the global environment is becoming more and more severe. The number of disasters has dramatically increased, as well as the cost to the global economy and the number of people affected. Among the natural disaster, flood catastrophes are considered to be the most costly, devastating, broad extent and frequent, because of the tremendous fatalities, injuries, property damage, economic and social disruption they cause to the humankind. In the last thirty years, the World has suffered from severe flooding and the huge impact of floods has caused hundreds of thousands of deaths, destruction of infrastructures, disruption of economic activity and the loss of property for worth billions of dollars. In this context, satellite remote sensing, along with Geographic Information Systems (GIS), has become a key tool in flood risk management analysis. Remote sensing for supporting various aspects of flood risk management was investigated in the present thesis. In particular, the research focused on the use of satellite images for flood mapping and monitoring, damage assessment and risk assessment. The contribution of satellite remote sensing for the delineation of flood prone zones, the identification of damaged areas and the development of hazard maps was explored referring to selected cases of study.

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Il patrimonio culturale sopravvissuto fino ai giorni nostri nonostante calamità naturali ed eventi catastrofici è oggi sempre più in pericolo: gli eventi naturali, accelerati e resi ancora più distruttivi dagli effetti del cambiamento climatico, lo scoppio continuo di nuovi conflitti armati e l’inconsapevolezza con cui gli uomini sfruttano il territorio comportano un aumento dei rischi e dei possibili danni ad un patrimonio che, tuttavia, è di importanza vitale per la crescita dell’umanità. Per evitare che il patrimonio culturale venga disperso o distrutto, è necessario applicare misure di prevenzione e protezione mirate, utilizzando in maniera efficiente gli strumenti disponibili; lo scopo ultimo della prevenzione e della protezione deve essere la resilienza, che va costruita attraverso la conoscenza e l’attenta pianificazione della gestione del patrimonio. Il presente lavoro di ricerca si propone dunque di analizzare i metodi e le strategie utilizzabili per la valutazione e la gestione del rischio applicati ai beni culturali, verificando a quale livello di consapevolezza si è giunti a livello sia nazionale che internazionale, passando in rassegna le tecnologie che permettono di proteggere il patrimonio agevolando il lavoro di mitigazione del rischio e applicando un prototipo di calcolo e analisi del rischio al caso studio del Museo di Nonantola, in provincia di Modena.