Thesis etd-09102021-192306 |
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Thesis type
Tesi di laurea magistrale
Author
MARRONI, GIULIA
URN
etd-09102021-192306
Thesis title
Risk assessment of integrated safety-security scenarios in process facilities
Department
INGEGNERIA CIVILE E INDUSTRIALE
Course of study
INGEGNERIA CHIMICA
Supervisors
relatore Prof. Landucci, Gabriele
Keywords
- assessment
- Bayesian
- domino
- effect
- networks
- probabilistic
- risk
- security
- vulnerability
Graduation session start date
01/10/2021
Availability
Withheld
Release date
01/10/2024
Summary
In the last twenty years, security concerns have become relevant for the process industry, especially for plants that process and store significant quantities of hazardous substances. Security science shares some theoretical foundations with operational safety, in which risk assessment techniques are well established. Furthermore, safety and security are not two unrelated fields, as the existence of domino effect, and the intervention of safety countermeasures in security events makes the two disciplines deeply linked.
However, the intentionality aspect of security makes it necessary to develop new techniques for risk assessment.
The most consolidated techniques for assessing security risk provide qualitative or at most semi-quantitative results. The development of a quantitative metric for risk assessment is essential to quantify the vulnerability of a plant and to assess the performance of existing protections against external attacks.
Vulnerability assessment of chemical equipment presents some criticalities, since in the existing literature many attack vectors have not yet been studied in detail. The first objective of this thesis work is, therefore, to expand existing fragility models, focusing on attacks with explosives, firearms, and incendiary weapons.
The quantitative assessment of vulnerability will be done using Bayesian Networks, an advanced probabilistic tool. The use of Bayesian Networks also allows to obtain a quantitative risk assessment, which in this work was evaluated on an economic basis.
The results of this thesis work will show how the development of new fragility models highlights new critical aspects of chemical plants, especially regarding protection measures against external attacks; moreover, it will be shown that Bayesian Networks can be an excellent tool to support decision-making activities in security, due to the possibility of including different perspectives for risk assessment within the analysis.
However, the intentionality aspect of security makes it necessary to develop new techniques for risk assessment.
The most consolidated techniques for assessing security risk provide qualitative or at most semi-quantitative results. The development of a quantitative metric for risk assessment is essential to quantify the vulnerability of a plant and to assess the performance of existing protections against external attacks.
Vulnerability assessment of chemical equipment presents some criticalities, since in the existing literature many attack vectors have not yet been studied in detail. The first objective of this thesis work is, therefore, to expand existing fragility models, focusing on attacks with explosives, firearms, and incendiary weapons.
The quantitative assessment of vulnerability will be done using Bayesian Networks, an advanced probabilistic tool. The use of Bayesian Networks also allows to obtain a quantitative risk assessment, which in this work was evaluated on an economic basis.
The results of this thesis work will show how the development of new fragility models highlights new critical aspects of chemical plants, especially regarding protection measures against external attacks; moreover, it will be shown that Bayesian Networks can be an excellent tool to support decision-making activities in security, due to the possibility of including different perspectives for risk assessment within the analysis.
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