In order to more effectively design large, complex systems, risk must be accounted for throughout the design process. A systematic way to account for risk is by using system model simulation. During the conceptual design phase, functional models can be drawn to help the engineer design their system's functional architecture....
In 1993 The Oregon Department of Environmental Quality developed a Cross-media Comparative Risk Assessment model to address certain regulatory concerns. Due to budget constraints the model was never beta tested. Now in 1995, the X-media project has been reopened, and the model revised, and tested. Specific revisions include: 1) Upgrade...
In this dissertation, we study two risk models. First, we consider the dual risk process which models the surplus of a company that incurs expenses at a constant rate and earns random positive gains at random times. When the surplus is invested in a risky asset following a geometric Brownian...
This thesis considers one of the classical problems in the actuarial mathematics literature, the decay of the probability of ruin in the collective risk model. The
claim number process N(t) is assumed to be a renewal process, the resulting model
being referred as the Sparre Andersen risk model. The inter-claim...
The nuclear industry has long relied upon bounding parametric analyses in predicting the safety margins of reactor designs undergoing design-basis accidents. These methods have been known to return highly-conservative results, limiting the operating conditions of the reactor. The Best-Estimate Plus Uncertainty (BEPU) method using a modernized version of the Code-Scaling,...
Two methods of radiation dose assessment were evaluated for the Cs-137 in soil ⇒ leafy vegetable ⇒ human consumption exposure pathway at three fictitious contaminated sites in California, Colorado, and Florida. An annual dose equation was developed and per USEPA risk assessment guidelines, traditional, single point annual dose estimates were...
Statistical modeling has evolved around building increasingly more complex models, even though it is common knowledge among statisticians that an optimal model size usually exists for any given data set. Having overly complex models leads to imprecise parameter estimates and tends to increase the subjective role of the modeler, which...
Stock assessments for many U.S. Pacific coast groundfish stocks are developed using the catch-at-age method known as Stock Synthesis. In this work a simulation package was developed and used to evaluate the sensitivity of the Stock Synthesis program. More specifically, the evaluation focused on the impacts of input data errors...
An insurance company, having an initial capital u, receives premiums continuously and pays claims of random sizes at random times. A classical result states that if the rate of premium, c, exceeds the average of the claims paid per unit time, ⋋μ, then the ruin probability decays exponentially fast as...
A model of agricultural decision making is developed and tested in this thesis. The expected value of utility evaluated under alternative outcomes is directly maximized in a nonlinear programming model. Two features of the model distinguished it from traditional risk programming models. First, alternative attitudes towards the assumption of risk...