A identificação das incertezas envolvidas no processo de estudo, possibilita que a tomada de decisão seja realizada de forma clara e científica Abrahamsson (2001). Será feito um estudo crítico das diversas etapas envolvidas nos estudos de risco e confiabilidade, buscando identificar as incertezas envolvidas, descobrir a sua natureza e estabelecer formas adequadas de trata-las. Vários aspectos de incertezas serão discutidos. Qual o papel das incertezas no processo de tomada de decisão? Que etapas do processo de análise de risco produzirão incertezas? Quais os tipos de incertezas existentes? Como os órgãos de normalização estão tratando o problema de incerteza? Por final será apresentada uma proposta metodológica que auxilie na minimização das incertezas e que facilite, no futuro próximo possível a criação de normas que melhorem o grau de exatidão nos estudos de riscos e de alguma forma os Estudos relacionados com Análise de Risco possam melhorar em qualidade. / The identification of the uncertainties involved in the study, enables the decisionmaking is carried out in a clear and scientific Abrahamsson (2001). There will be a critical study of the various steps involved in studies of risk and reliability, identifying the uncertainties involved, discover the nature and stablish appropriate ways to treat them. Several aspects of uncertainties will be discussed. What is the role of uncertainties in the process of decision making? What stages of risk analysis will produce uncertainties? What types of uncertainty? As the standardization bodies are addressing the problem of uncertainty? By the end will be presented a methodology to assist in reducing the uncertainties and to facilitate in the near future it possible to create standards to improve the degree of accuracy in studies of risks and somehow the studies related to Risk Analysis to improve quality.

Natural gas and petroleum are non-renewable and scarce energy sources. Although, it is well known that hydrocarbon reserves are depleting through the years, oil and gas remain the principal source of energy upon which our society is strongly dependent. Hence, optimization and accurate planning of hydrocarbon production are the main keys to making it safer, more efficient, and cheaper. One of the tools commonly used to evaluate the optimization of oil/gas production system is the process simulation modeling. A hydrocarbon production system typically consists of at least one underground reservoir where several wells have been drilled into the hydrocarbon-bearing rock to form a fixed topology network. Wells are interconnected with manifolds to transport the gas or oil to a storage or sale location. The process simulation consists of calculating the total hydrocarbon production for the given production system. The pressure in the wellbore is the main variable in determining the hydrocarbon production process. When oil/gas is produced, the pressure decreases until production cannot be sustained. If the well is shut down, the pressure at the wellbore increases because of the natural gas flow coming from the reservoir. In addition, artificial lift techniques, such as water injection, gas lift and pump systems can be incorporated into the simulation program. The oil/gas production has been also modeled as a multi-period optimization case to incorporate the possibility of different demands, cost and overall time behavior. The current field optimization approaches take in account the availability in a general way, adding to the planning a lot of uncertainty. The proposed study includes a suitable analysis of the likelihood of equipment failure, which will predict the availability of the equipment in a certain period of time to perform a more accurate planning. In this work, we have integrated the availability analysis to the model described above. The availability of a system is analyzed by Monte Carlo simulation, which involves the modeling of the probabilities of failure, the type of failure, the time to repair associated with each failure, and time of occurrence for a field system. The availability model performed reduces significantly the uncertainties on a multi-period planning production of either oil or gas, predicting the probability of failure and the downtime related to the hydrocarbon production through its lifetime. In this study, the unavailability of the equipment was quantified, reporting a subsea equipment downtime of approximately 7%. As a result, new production planning is accomplished in the effective work period, which will be beneficial in financial risk decisions such as a government’s deliverability contracts.

Thesis (Ph. D.)--Ohio State University, 2004. / Title from first page of PDF file. Document formatted into pages; contains x, 86 p.; also includes graphics Includes bibliographical references (p. 84-86). Available online via OhioLINK's ETD Center

A identificação das incertezas envolvidas no processo de estudo, possibilita que a tomada de decisão seja realizada de forma clara e científica Abrahamsson (2001). Será feito um estudo crítico das diversas etapas envolvidas nos estudos de risco e confiabilidade, buscando identificar as incertezas envolvidas, descobrir a sua natureza e estabelecer formas adequadas de trata-las. Vários aspectos de incertezas serão discutidos. Qual o papel das incertezas no processo de tomada de decisão? Que etapas do processo de análise de risco produzirão incertezas? Quais os tipos de incertezas existentes? Como os órgãos de normalização estão tratando o problema de incerteza? Por final será apresentada uma proposta metodológica que auxilie na minimização das incertezas e que facilite, no futuro próximo possível a criação de normas que melhorem o grau de exatidão nos estudos de riscos e de alguma forma os Estudos relacionados com Análise de Risco possam melhorar em qualidade. / The identification of the uncertainties involved in the study, enables the decisionmaking is carried out in a clear and scientific Abrahamsson (2001). There will be a critical study of the various steps involved in studies of risk and reliability, identifying the uncertainties involved, discover the nature and stablish appropriate ways to treat them. Several aspects of uncertainties will be discussed. What is the role of uncertainties in the process of decision making? What stages of risk analysis will produce uncertainties? What types of uncertainty? As the standardization bodies are addressing the problem of uncertainty? By the end will be presented a methodology to assist in reducing the uncertainties and to facilitate in the near future it possible to create standards to improve the degree of accuracy in studies of risks and somehow the studies related to Risk Analysis to improve quality.

Note:

The international community faces a growing threat from nuclear terrorism. The complexity of the threats of nuclear terrorism, the variety of nuclear security measures that States can devote resources towards to address the threats, and the limited resources States have to invest in these nuclear security measures make it imperative that resources are applied in the most effective way possible. In this dissertation, we develop a quantitative, risk-based methodology that States can employ to gain a better understanding of the nuclear threat they face, assist them in determining what nuclear security measures they should invest in, and facilitate communication to stake-holders to request and justify investment in these measures. The risk-based methodology has been developed employing a combination of pathways analysis, game-theory, multiple-attribute utility analysis, decision theory and risk analysis. The methodology was designed to account for the wide variety of nuclear security measures that States can invest in, the range of possible consequences from different nuclear threats, and the severity of these consequences to the State. In addition, the methodology models the adversary's strategic decision making while accounting for the capabilities, motivations, and disincentives that may influence which nuclear threat a terrorist group will attempt. The methodology is introduced into a Visual Basic for Applications code, which we demonstrate through verification and qualitative validation tests. We then develop three State nuclear infrastructures with varying levels of complexity, meant to provide a realistic representation of real-world States. We then utilize the code to evaluate the risk of nuclear terrorism against terrorist threats that have different motivations for nuclear terrorism to demonstrate how different motivations for nuclear terrorism may affect both State-level risk and the State's optimal risk-reduction strategy. These risk analyses are then used to both evaluate various nuclear security strategies and determine which nuclear security measures will have the greatest risk-reduction value. Finally, we conduct a sensitivity analysis on capabilities of terrorist groups to understand how changes in these capabilities affect the State-level risk from nuclear terrorism.

<p>Disturbances in the services provided by the infrastructuresystems—e.g. electric power supplies and communications—can have serious implications for everyday life,economic prosperity and national security. The disturbances canbe initiated by natural disasters, adverse weather, technicalfailures, human errors, sabotage, terrorism or acts of war. Theaim of this thesis is to study methods for proactivevulnerability analysis of electric power delivery networks(i.e. to analyze their sensitivity to threats and hazards), andto formalize vulnerability as a theoretical concept.</p><p>The thesis consists of three papers. In the first paper, wediscuss concepts and perspectives for developing a methodologyfor vulnerability studies with the help of the followingthemes: The properties of the infrastructure systems, threatsand hazards, vulnerability and consequence analysis, andmeasures for creating robust and resilient systems.</p><p>In the second paper we discuss how to assess vulnerabilityof power delivery systems with the help of standard powersystem performance indices. In two case studies, Swedish powerdelivery disturbance data is analyzed with statistical methods.We demonstrate that the disturbance size of large disturbancesfollows a power law distribution, and that the time betweendisturbances is exponentially distributed.</p><p>In third paper, we model electrical power networks asgraphs, and conduct empirical studies of two power transmissiongrids. We calculate values of topological characteristics ofthe networks and compare their error and attack tolerance, i.e.their performance when vertices are disabled, with twofrequently used model networks. Further, we perform a graphinfluenced vulnerability analysis of a fictitious powernetwork, and evaluate di.erent strategies to decrease thevulnerability of the system.</p>

This study analyzes the economic and geographic effects of alternative locations on risky investment decisions in a probabilistic framework. Historically, alternative locations for multi-million dollar investments are often evaluated with deterministic models that rely on expected values or best case/worst case scenarios. Stochastic simulation was used to estimate the probability distribution for select key output variables, including net present value (NPV), of a proposed biomass to ethanol production facility in three alternative regions in Texas. The simulated NPV probability distributions were compared using Stochastic Efficiency with Respect to a Function (SERF) to predict the location preference of decision makers with alternative levels of risk aversion. Risk associated with input availability and costs were analyzed for the proposed plant locations so each location resulted in different levels of economic viability and risk that would not have been observed with a traditional deterministic analysis. For all analyzed scenarios, the projected financial feasibility results show a positive NPV over the 16 year planning horizon with a small probability of being negative. The SERF results indicate the Central Region of Texas is preferred for risk averse decision makers compared to the Panhandle and Coastal Bend Regions. Risk premiums were calculated for the alternative locations and are consistent for all risk averse decision makers, indicating the ranking of alternative locations are robust. Positive community impacts and sensitivity elasticities for key variables were estimated in the model. The estimated positive economic gains for the local economy are quite large and indicate locating a production facility in the region could substantially impact the local economy. The calculated sensitivity elasticities show ethanol price, ethanol yield, and hydrogen price are the three variables that have the greatest affect on the feasibility of a biomass to ethanol production facility.

Construction projects are complicated and fraught with so many risks that many projects are unable to meet pre-defined project objectives. Managers of construction projects require decision support tools that can be used to identify, analyze and implement measures that can mitigate the effects of project risks. Several risk analysis techniques have been developed over the years to enable construction project managers to make useful decisions that can improve the chances of project success. These risk analysis techniques however fail to simultaneously address risks relating to cost, schedule and quality. Also, construction projects may have scarce resources and construction managers still bear the responsibility of ensuring that project goals are met. Certain projects require trade-offs between technical and managerial risks and managers need tools that can help them do this. This thesis evaluates the usefulness of the Advanced Programmatic Risk Analysis and Management Model (APRAM) as a decision support tool for managing construction projects. The development of a visitor center in Midland, Texas was used as a case study for this research. The case study involved the implementation of APRAM during the concept phase of project development to determine the best construction system that can minimize the expected cost of failure. A risk analysis performed using a more standard approach yielded an expected cost of failure that is almost eight times the expected cost of failure yielded by APRAM. This study concludes that APRAM is a risk analysis technique that can minimize the expected costs of failure by integrating project risks of time, budget and quality through the allocation of resources. APRAM can also be useful for making construction management decisions. All identified component or material configurations for each alternative system however, should be analyzed instead of analyzing only the lowest cost alternative for each system as proposed by the original APRAM model. In addition, it is not possible to use decision trees to determine the optimal allocation of management reserves that would mitigate managerial problems during construction projects. Furthermore, APRAM does not address the issue of safety during construction and assumes all identifiable risks can be handled with money.

No description available.