2 resultados para BAYESIAN NETWORK
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
The efficiency of airport airside operations is often compromised by unplanned disruptive events of different kinds, such as bad weather, strikes or technical failures, which negatively influence the punctuality and regularity of operations, causing serious delays and unexpected congestion. They may provoke important impacts and economic losses on passengers, airlines and airport operators, and consequences may propagate in the air network throughout different airports. In order to identify strategies to cope with such events and minimize their impacts, it is crucial to understand how disruptive events affect airports’ performance. The research field related with the risk of severe air transport network disruptions and their impact on society is related to the concepts of vulnerability and resilience. The main objective of this project is to provide a framework that allows to evaluate performance losses and consequences due to unexpected disruptions affecting airport airside operations, supporting the development of a methodology for estimating vulnerability and resilience indicators for airport airside operations. The methodology proposed comprises three phases. In the first phase, airside operations are modelled in both the baseline and disrupted scenarios. The model includes all main airside processes and takes into consideration the uncertainties and dynamics of the system. In the second phase, the model is implemented by using a generic simulation software, AnyLogic. Vulnerability is evaluated by taking into consideration the costs related to flight delays, cancellations and diversions; resilience is determined as a function of the loss of capacity during the entire period of disruption. In the third phase, a Bayesian Network is built in which uncertain variables refer to airport characteristics and disruption type. The Bayesian Network expresses the conditional dependence among these variables and allows to predict the impacts of disruptions on an airside system, determining the elements which influence the system resilience the most.
Resumo:
Historical evidence shows that chemical, process, and Oil&Gas facilities where dangerous substances are stored or handled are target of deliberate malicious attacks (security attacks) aiming at interfering with normal operations. Physical attacks and cyber-attacks may generate events with consequences on people, property, and the surrounding environment that are comparable to those of major accidents caused by safety-related causes. The security aspects of these facilities are commonly addressed using Security Vulnerability/Risk Assessment (SVA/SRA) methodologies. Most of these methodologies are semi-quantitative and non-systematic approaches that strongly rely on expert judgment, leading to security assessments that are not reproducible. Moreover, they do not consider the synergies with the safety domain. The present 3-year research is aimed at filling the gap outlined by providing knowledge on security attacks, as well as rigorous and systematic methods supporting existing SVA/SRA studies suitable for the chemical, process, and Oil&Gas industry. The different nature of cyber and physical attacks resulted in the development of different methods for the two domains. The first part of the research was devoted to the development and statistical analysis of security databases that allowed to develop new knowledge and lessons learnt on security threats. Based on the obtained background, a Bow-Tie based procedure and two reverse-HazOp based methodologies were developed as hazard identification approaches for physical and cyber threats respectively. To support the quantitative estimation of the security risk, a quantitative procedure based on the Bayesian Network was developed allowing to calculate the probability of success of physical security attacks. All the developed methods have been applied to case studies addressing chemical, process and Oil&Gas facilities (offshore and onshore) proving the quality of the results that can be achieved in improving site security. Furthermore, the outcomes achieved allow to step forward in developing synergies and promoting integration among safety and security management.