Quantitative risk analysis as a tool in process design

La Quantitative Risk Analysis costituisce un valido strumento per la determinazione del rischio associato ad un’installazione industriale e per la successiva attuazione di piani di emergenza. Tuttavia, la sua applicazione nella progettazione di un lay-out richiede la scelta di un criterio in grado di valutare quale sia la disposizione ottimale al fine di minimizzare il rischio. In tal senso, le numerose procedure esistenti, sebbene efficaci, risultano piuttosto faticose e time-consuming. Nel presente lavoro viene dunque proposto un criterio semplice ed oggettivo per comparare i risultati di QRA applicate a differenti designs. Valutando l’area racchiusa nelle curve iso-rischio, vengono confrontate dapprima le metodologie esistenti per lo studio dell’effetto domino, e successivamente, viene applicata al caso di serbatoi in pressione una procedura integrata di Quantitative Risk Domino Assessment. I risultati ottenuti dimostrano chiaramente come sia possibile ridurre notevolmente il rischio di un’attività industriale agendo sulla disposizione delle apparecchiature, con l’obiettivo di limitare gli effetti di possibili scenari accidentali.

A framework for risk analysis in automotive cybersecurity

We address the problem of automotive cybersecurity from the point of view of Threat Analysis and Risk Assessment (TARA). The central question that motivates the thesis is the one about the acceptability of risk, which is vital in taking a decision about the implementation of cybersecurity solutions. For this purpose, we develop a quantitative framework in which we take in input the results of risk assessment and define measures of various facets of a possible risk response; we then exploit the natural presence of trade-offs (cost versus effectiveness) to formulate the problem as a multi-objective optimization. Finally, we develop a stochastic model of the future evolution of the risk factors, by means of Markov chains; we adapt the formulations of the optimization problems to this non-deterministic context. The thesis is the result of a collaboration with the Vehicle Electrification division of Marelli, in particular with the Cybersecurity team based in Bologna; this allowed us to consider a particular instance of the problem, deriving from a real TARA, in order to test both the deterministic and the stochastic framework in a real world application. The collaboration also explains why in the work we often assume the point of view of a tier-1 supplier; however, the analyses performed can be adapted to any other level of the supply chain.

Sensitivity analysis of QRA to the occurrence frequencies of top-events: a case study

L’obiettivo del lavoro di tesi è stato quello di valutare la sensitività dell’analisi quantitativa del rischio (QRA, Quantitative Risk Analysis) alla frequenza di accadimento degli scenari di rilascio delle sostanze pericolose ovvero dei top-events. L’analisi di rischio è stata condotta applicando, ad uno stabilimento a rischio di incidente rilevante della Catalogna, i passaggi procedurali previsti dall’istruzione 14/2008 SIE vigente in quella regione. L’applicazione di questa procedura ha permesso di ottenere le curve isorischio, che collegano i punti attorno allo stabilimento aventi lo stesso valore del rischio locale. Le frequenze base dei top-events sono state prese innanzitutto dalla linea guida BEVI, e successivamente ai fini dell’analisi di sensitività, sono stati considerati sia i valori forniti da altre 3 autorevoli linee guida sia i valori ottenuti considerando incrementi delle frequenze base del 20%, 30%, 50%, 70%, 200%, 300%, 500%, 700%, 1000%, 2000%, 3000%, 4000%, 5000%. L’analisi delle conseguenze è stata condotta tramite i software EFFECTS ed ALOHA, mentre ai fini della ricomposizione del rischio è stato utilizzato il codice RISKCURVES. La sensitività alle frequenze dei top-events è stata valutata in termini di variazione del diametro massimo delle curve isorischio, con particolare attenzione a quella corrispondente a 10-6 ev/anno, che rappresenta il limite di accettabilità del rischio per la pianificazione territoriale nell’intorno dello stabilimento. E’ stato così dimostrato che l’estensione delle curve isorischio dipende in maniera molto forte dalla frequenza dei top-events e che l’utilizzo di dati di frequenza provenienti da linee guida diverse porta a curve isorischio di dimensioni molto differenti. E’ dunque confermato che la scelta delle frequenze degli scenari incidentali rappresenta, nella conduzione dell’analisi di rischio, un passaggio delicato e cruciale.

A framework for the environmental risk assessment of offshore carbon storage in CCS systems

Carbon capture and storage (CCS) represents an interesting climate mitigation option, however, as for any other human activity, there is the impelling need to assess and manage the associated risks. This study specifically addresses the marine environmental risk posed by CO2 leakages associated to CCS subsea engineering system, meant as offshore pipelines and injection / plugged and abandoned wells. The aim of this thesis work is to start approaching the development of a complete and standardized practical procedure to perform a quantified environmental risk assessment for CCS, with reference to the specific activities mentioned above. Such an effort would be of extreme relevance not only for companies willing to implement CCS, as a methodological guidance, but also, by uniformizing the ERA procedure, to begin changing people’s perception about CCS, that happens to be often discredited due to the evident lack of comprehensive and systematic methods to assess the impacts on the marine environment. The backbone structure of the framework developed consists on the integration of ERA’s main steps and those belonging to the quantified risk assessment (QRA), in the aim of quantitatively characterizing risk and describing it as a combination of magnitude of the consequences and their frequency. The framework developed by this work is, however, at a high level, as not every single aspect has been dealt with in the required detail. Thus, several alternative options are presented to be considered for use depending on the situation. Further specific studies should address their accuracy and efficiency and solve the knowledge gaps emerged, in order to establish and validate a final and complete procedure. Regardless of the knowledge gaps and uncertainties, that surely need to be addressed, this preliminary framework already finds some relevance in on field applications, as a non-stringent guidance to perform CCS ERA, and it constitutes the foundation of the final framework.

L'analisi di rischio nel trasporto stradale di merci pericolose: due software a confronto

Confronto tra due software specifici per l'analisi di rischio nel trasporto stradale di merci pericolose (TRAT GIS 4.1 e QRAM 3.6) mediante applicazione a un caso di studio semplice e al caso reale di Casalecchio di Reno, comune della provincia di Bologna.

Multiphase flow in porous media: meta-modeling techniques for sensitivity analysis and risk assessment

One of the biggest challenges that contaminant hydrogeology is facing, is how to adequately address the uncertainty associated with model predictions. Uncertainty arise from multiple sources, such as: interpretative error, calibration accuracy, parameter sensitivity and variability. This critical issue needs to be properly addressed in order to support environmental decision-making processes. In this study, we perform Global Sensitivity Analysis (GSA) on a contaminant transport model for the assessment of hydrocarbon concentration in groundwater. We provide a quantification of the environmental impact and, given the incomplete knowledge of hydrogeological parameters, we evaluate which are the most influential, requiring greater accuracy in the calibration process. Parameters are treated as random variables and a variance-based GSA is performed in a optimized numerical Monte Carlo framework. The Sobol indices are adopted as sensitivity measures and they are computed by employing meta-models to characterize the migration process, while reducing the computational cost of the analysis. The proposed methodology allows us to: extend the number of Monte Carlo iterations, identify the influence of uncertain parameters and lead to considerable saving computational time obtaining an acceptable accuracy.