Master of Science / Department of Mechanical Engineering / Donald L. Fenton / This project was done to determine the effectiveness of different methods of mitigating the effects of an ammonia release through a pressure relief device in an ammonia refrigeration system. Several methods were considered, and five were selected for further study. The methods chosen for further study were discharge into a tank containing standing water, discharge into the atmosphere, discharge into a flare, discharge into a wet scrubber, and an emergency pressure control system. Discharge into a tank containing standing water is the most common method in existence today but several people in the ammonia refrigeration industry have questioned its reliability. The methods were compared based on a quantitative risk analysis, combining failure rates of each system with ammonia dispersion modeling and the monetized health effects of a system’s failure to contain an ammonia release. It was determined that the release height had a greater influence on the downwind cost impact than any other variable, including weather conditions and release from multiple sources. The discharge into a tank containing standing water was determined to have the lowest failure rate, while the flare system was found to be the most effective in terms of relative overall release consequent cost. The emergency pressure control system is now required by the codes, and any of the other mitigation systems would be very effective when used in conjunction with the emergency pressure control system.

This research is aimed at assessing the quantitative risks involved with an ethanol pipeline. Pipelines that run from the Midwest, where the vast majority of ethanol is produced, to the target areas where reformulated gasoline is required (California, Texas Gulf Coast, New England Atlantic Coast) will be of particular interest. The goal is to conduct a quantitative risk assessment on the pipeline, truck, and rail transportation modes to these areas. As a result of the quantitative risk assessment, we are able to compare the risk associated with the different modes of transportation for ethanol. In order to perform and compare the quantitative risk assessment, the following challenges are addressed: • Identify target areas requiring reformulated gasoline • Map detailed route for each transportation mode to all three target areas • Perform a quantitative risk assessment for each transportation mode • Compare quantitative risk assessment results for each route and transportation mode The focus is on California, Texas Gulf Coast, and New England Atlantic Coast because of the large volume. It is beneficial to look at these areas as opposed to the smaller areas because pipeline transportation requires very large volumes. In order to find a meaningful comparison between all three transportation modes, only the areas with the three large volumes were evaluated. Since the risk assessment is completed using historical data, each route is segmented in a way that is consistent with the data that is available. All of the curves support the hypothesis that pipeline transportation poses the least societal risk when transporting ethanol from the Midwest to target areas. Rail transportation poses the largest amount of societal risk. While overall rail incidents are not as frequent as road incidents, the frequency of a fatality is much higher when an incident does occur.

This research is aimed at assessing the quantitative risks involved with an ethanol pipeline. Pipelines that run from the Midwest, where the vast majority of ethanol is produced, to the target areas where reformulated gasoline is required (California, Texas Gulf Coast, New England Atlantic Coast) will be of particular interest. The goal is to conduct a quantitative risk assessment on the pipeline, truck, and rail transportation modes to these areas. As a result of the quantitative risk assessment, we are able to compare the risk associated with the different modes of transportation for ethanol. In order to perform and compare the quantitative risk assessment, the following challenges are addressed: 1) Identify target areas requiring reformulated gasoline 2) Map detailed route for each transportation mode to all three target areas 3) Perform a quantitative risk assessment for each transportation mode 4) Compare quantitative risk assessment results for each route and transportation mode The focus is on California, Texas Gulf Coast, and New England Atlantic Coast because of the large volume. It is beneficial to look at these areas as opposed to the smaller areas because pipeline transportation requires very large volumes. In order to find a meaningful comparison between all three transportation modes, only the areas with the three large volumes were evaluated. Since the risk assessment is completed using historical data, each route is segmented in a way that is consistent with the data that is available. All of the curves support the hypothesis that pipeline transportation poses the least societal risk when transporting ethanol from the Midwest to target areas. Rail transportation poses the largest amount of societal risk. While overall rail incidents are not as frequent as road incidents, the frequency of a fatality is much higher when an incident does occur.

Dust and hybrid mixture explosions continue to occur in industrial processes that handle fine powders and flammable gases. Considerable research is therefore conducted throughout the world with the objective of both preventing the occurrence and mitigating the consequences of such events. In the current work, research has been undertaken to help advance the field of dust explosion prevention and mitigation from an emphasis on hazards to a focus on risk. Employing the principles of quantitative risk assessment (QRA) of dust and hybrid mixture explosions, a methodological framework for the management of these risks has been developed. The Quantitative Risk Management Framework (QRMF) is based on hazard identification via credible accident scenarios for dust explosions, followed by probabilistic Fault Tree Analysis (using Relex – Reliability Excellence – software) and consequence severity analysis, represented by maximum explosion pressure, (using DESC – Dust Explosion Simulation Code – software). Identification of risk reduction measures in the framework is accomplished in a hierarchical manner by considering inherent safety measures, passive and active engineered devices, and procedural measures. Dust explosion tests to determine icing and granulated sugar dust explosibility characteristics have been achieved in a 20-L Siwek chamber, and, accordingly, DESC fuel files were built and DESC has validated. Three industrial case studies are presented to show how the QRMF could has been helpful in reducing dust and hybrid mixture explosion risk at the Imperial Sugar refinery, the Semabla grain storage silo, and a hypothetical 400-m3 polyethylene storage silo. DESC simulations and Probit equation for structural damage provide the destructive percentage of each pressure zone in the simulations, followed by probabilistic FTA that were achieved for the first two case studies, before and after applying the framework. Detailed individual and societal risks calculations were made and F-N curves plotted for the two processes. The polyethylene silo case study is presented to show how inherent safety measures can be helpful in reducing dust and hybrid mixture explosion risk. The framework showed significant risk reduction to the point where the residual risks are acceptable for both processes. Finally, assessment results are compared and improvements measured. / The research main objective is: to manage the risks of any expected dust or hybrid mixture explosion in industrial complexes (large-scale).

Made available in DSpace on 2014-06-12T17:42:48Z (GMT). No. of bitstreams: 2 arquivo7684_1.pdf: 3197582 bytes, checksum: e9a5a1df323907fb05bb3c1b206c2fd5 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2011 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Recentes acidentes industriais, como vazamentos tóxicos, têm causado danos catastróficos ao meio ecológico (i.e. plantas e animais), de modo que um método efetivo para analisar riscos ecológicos tem sido demandado. Em primeiro lugar, este trabalho tem como objetivo propor uma metodologia capaz de quantificar riscos ecológicos inerentes a eventos raros como acidentes industriais. Utiliza-se a modelagem populacional para simular futuras mudanças na abundância populacional de espécies-chave em risco e, assim, estimar a probabilidade de extinção ou declínio, tempo para extinção e outras medidas, para cada cenário acidental. Assim, foi possível desenvolver uma abordagem que combina os danos ecológicos (previstos através da modelagem populacional) com a frequência de ocorrência do cenário acidental (estimada através de dados históricos e análise de confiabilidade). O resultado é uma curva de risco FN (similar ao resultado de uma análise de risco a humanos), onde N é o declínio populacional médio e F a frequência acumulada de acidentes com declínio maior ou igual a N. Em segundo lugar, o trabalho apresenta uma aplicação da metodologia para quantificar os riscos ecológicos provenientes de acidentes associados ao transporte e manuseio de petróleo que abastece uma refinaria no Complexo Industrial Portuário de Suape-PE, no Nordeste do Brasil. Esta instalação está localizada próxima a um rico ecossistema aquático de alta biodiversidade. A população de uma espécie nativa foi estrategicamente escolhida para representar o ecossistema, alguns cenários de derramamento de petróleo foram simulados e suas frequências de ocorrência estimadas. Para cada cenário acidental, a concentração de óleo que atinge a população foi prevista via modelagem de destino e transporte. Os riscos ecológicos foram quantificados e apresentados em uma curva FN. Uma análise de sensibilidade foi feita para explorar como mudanças em parâmetros específicos causam mudanças nas medidas de risco. Além disso, a incerteza foi medida como um intervalo (limite superior e inferior) para as medidas de riscos com base em cenários pessimistas e otimistas. Finalmente, a metodologia mostrou-se viável, eficiente, conveniente e flexível, apesar de que algumas melhorias ainda podem ser feitas e estas foram propostas para trabalhos futuros

Hazardous Materials (HazMat) are transported throughout Canada in a great number of road shipments. The transportation of HazMat poses special risks for neighboring population and environment. While HazMat accidents are rare events, they could be catastrophic in nature and could result in substantial damage to nearby communities. Effective emergency response plays an important role in the safe transportation of HazMat. Transportation of HazMat involves different parties, including shippers, regulators, and surrounding communities. While the shipping party is responsible for safe delivery of HazMat shipments, it is the responsibility of local emergency service agencies to respond to accidents occurring within their jurisdictions. In this research, the emergency response to HazMat transport accidents is assumed to be delegated exclusively to specially trained and equipped HazMat teams. This research proposes a new comprehensive systematic approach to determine the best location of HazMat teams on regional bases utilizing HazMat transport risk as a location criterion. The proposed model is the first to consider emergency response roles in HazMat transport risk analysis, and was intended as an optimization tool to be used by practitioners for HazMat emergency response planning. Additionally, the proposed model can be used to assess risk implications in regards to current locations of HazMat teams in a region, and to develop effective strategies for locating HazMat teams, such as closing and/or relocating teams in the region. The model investigates how HazMat team locations can be tailored to recognize the risk of transporting HazMat and would provide a more objective set of input alternatives into the multi-criteria decision making process of regionally locating HazMat teams. The proposed model was applied to the region of southwestern Ontario in effort to illustrate its features and capabilities in the HazMat emergency response planning and decision making process. Accordingly, the model provided very useful insights while reviewing several HazMat team location strategies for the southwestern Ontario region and investigating tradeoff among different factors. This research contributes to a better understanding of emergency response roles by reducing HazMat transport risks, and will greatly benefit both researchers and practitioners in the field of HazMat transport and emergency response.

Following the financial crisis of 2008, the need for more robust techniques to quantify the capital charge for risk management has become a pressing problem. Under Basel II/III, banks are allowed to calculate the capital charge using internally developed models subject to regulatory approval. An interesting problem for the regulator is to compare the resulting figures against the required capital under worst case scenarios. The existing literature on the latter problem, which is based on the marginal problem, assumes that no a-priori information is known about the dependencies of contributing risks. These problems are linear optimisation problems over a constrained set of probability measures, discretisation of which leads to large scale LPs. But this approach is very conservative and cannot be implemented robustly in practice, due to the scarcity of historical data. In our approach, we take a less conservative strategy by incorporating dependence information contained in the data in a form that still leads to LPs, an important feature of such problems due to their high dimensionality. Conceptually, our model is the discretisation of an infinite dimensional linear optimisation problem over a set of probability measures. For some specific cases we can prove strong duality, opening up the approach of discretising the dual instead of the primal. This approach is preferable, as it yields better numerical results. In this work we also apply our model to model-free path-dependent option pricing. Use of delayed column generation techniques allows us to solve problems several orders of magnitude larger than via the standard simplex algorithm. For high-dimensional LPs we also implement Nesterov's smoothing technique to solve the problems.

Manitoba’s flooding is one of the principal sources of costs associated with flood disasters. Despite the tremendous financial investments in structural mitigation, flood cost, continue to rise. Currently at the national and provincial level, there exists no standardized operational framework and tool for flood risk assessment. The primary role of this research was two-fold. First, Hazus-MH a Quantitative Risk Assessment (QRA) tool was evaluated as a potential flood-loss estimation model in a Manitoba context. Secondly, to examine the application of a QRA tool in policy, a face-to-face questionnaire was completed with flood experts in municipal and provincial government and with consultants. The study results suggested that Hazus-MH has the potential to be applied as a standard QRA tool in Manitoba. This research found that developing a standard QRA tool in Manitoba, would empower communication between decision-makers, centralize data to support disaster planning, and reduce the cost of recovery. / May 2016

In recent years, cyber attacks and data fraud have become major issues to companies, businesses and nation states alike. The need for more accurate and reliable risk management models is therefore substantial. Today, cybersecurity risk management is often carried out on a qualitative basis, where risks are evaluated to a predefined set of categories such as low, medium or high. This thesis aims to challenge that practice, by presenting a model that quantitatively assesses risks - therefore named MaRiQ (Manage Risks Quantitatively). MaRiQ was developed based on collected requirements and contemporary literature on quantitative risk management. The model consists of a clearly defined flowchart and a supporting tool created in Excel. To generate scientifically validated results, MaRiQ makes use of a number of statistical techniques and mathematical functions, such as Monte Carlo simulations and probability distributions. To evaluate whether our developed model really was an improvement compared to current qualitative processes, we conducted a workshop at the end of the project. The organization that tested MaRiQexperienced the model to be useful and that it fulfilled most of their needs. Our results indicate that risk management within cybersecurity can and should be performed using more quantitative approaches than what is praxis today. Even though there are several potential developments to be made, MaRiQ demonstrates the possible advantages of transitioning from qualitative to quantitative risk management processes.

Hazardous Materials (HazMat) are transported throughout Canada in a great number of road shipments. The transportation of HazMat poses special risks for neighboring population and environment. While HazMat accidents are rare events, they could be catastrophic in nature and could result in substantial damage to nearby communities. Effective emergency response plays an important role in the safe transportation of HazMat. Transportation of HazMat involves different parties, including shippers, regulators, and surrounding communities. While the shipping party is responsible for safe delivery of HazMat shipments, it is the responsibility of local emergency service agencies to respond to accidents occurring within their jurisdictions. In this research, the emergency response to HazMat transport accidents is assumed to be delegated exclusively to specially trained and equipped HazMat teams. This research proposes a new comprehensive systematic approach to determine the best location of HazMat teams on regional bases utilizing HazMat transport risk as a location criterion. The proposed model is the first to consider emergency response roles in HazMat transport risk analysis, and was intended as an optimization tool to be used by practitioners for HazMat emergency response planning. Additionally, the proposed model can be used to assess risk implications in regards to current locations of HazMat teams in a region, and to develop effective strategies for locating HazMat teams, such as closing and/or relocating teams in the region. The model investigates how HazMat team locations can be tailored to recognize the risk of transporting HazMat and would provide a more objective set of input alternatives into the multi-criteria decision making process of regionally locating HazMat teams. The proposed model was applied to the region of southwestern Ontario in effort to illustrate its features and capabilities in the HazMat emergency response planning and decision making process. Accordingly, the model provided very useful insights while reviewing several HazMat team location strategies for the southwestern Ontario region and investigating tradeoff among different factors. This research contributes to a better understanding of emergency response roles by reducing HazMat transport risks, and will greatly benefit both researchers and practitioners in the field of HazMat transport and emergency response.