Thesis (M.S.)--Naval Postgraduate School, 2002. / Thesis advisor(s): Donald R. Eaton, Lee Edwards. Includes bibliographical references (p. 101-104). Also available online.

Thesis (M.S. in Applied Science (Operations Research))--Naval Postgraduate School, June 2003. / Thesis advisor(s): David H. Olwell, Samuel E. Buttrey. Includes bibliographical references (p. 65). Also available online.

No description available.

Report (M.S.)--Virginia Polytechnic Institute and State University, 1994. / Abstract. Includes bibliographical references (leaves 82-89). Also available via the Internet.

Thesis (Ph. D.)--University of Washington, 1998. / Vita. Includes bibliographical references (p. [133]-162).

Thesis (Ph.D.)--University of Iowa, 2006. / Supervisor: Sharif Rahman. Includes bibliographical references (leaves 221-230).

Three fundamental problems of mechanical reliability are addressed. (1) computing the probability of failure, p(f), of a component having design factors with known statistical distributions and a limit state with a closed form algebraic expression (2) computing the probability of failure of a component having design factors with known distributions and a limit state which can only be expressed by a computer algorithm, and (3) deriving safety check expressions in a "design by reliability" approach. An algorithm for generating estimates of p(f) is presented. The method is an extension of, and demonstrated to be a significant improvement to, the widely used Rackwitz-Fiessler (R-F) method--a fast and efficient numerical method for performing reliability analysis. Comparisons were made for numerous examples, it was found that the error in p(f), using the proposed method, is typically about half of the error in R-F estimates. A method was proposed for computing p(f) when the relationship between design factors can be defined only using a computer algorithm, e.g., finite element analysis. A second order polynomial is constructed, using a simple curve fitting routine, to approximate the limit state in the neighborhood of the design point (i.e., a point close to the most likely value of the design variables at failure). Then the R-F method can be applied easily. It is demonstrated that this scheme is much faster than the Monte Carlo method in producing reasonable estimates of p(f). Methods of deriving safety check expressions for design codes and design criteria documents are studied. A Level I format employing partial safety factors derived from Level II methods is used to construct the safety check expressions which are suitable for code development. The procedures are demonstrated using numerous examples which include the problems where the limit states are complicated, i.e., the limit states are not explicitly defined.

Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Begovic, Miroslav; Committee Member: Hampton, Nigel; Committee Member: Harley, Ronald; Committee Member: Michaels, Thomas; Committee Member: Vidakovic, Brani. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Typescript (photocopy). / Digitized by Kansas Correctional Industries

The continuously developing requirements of the offshore oil and gas Operators are placing more stringent demands on the designers to produce optimised solutions, with reduced development schedules, and application of new technologies for extreme environmental and operational conditions. The compounding uncertainty of service conditions and in the design capabilities is causing the designer to over-design, conduct extensive pre-service testing and introduce design redundancy. As such, designers have been forced to turn to reliability techniques in order to quantify the life of their designs. This has extended as far as needing to integrate reliability concepts, tools and methodologies into the design process. In recent times, the industry has attempted to apply conventional reliability tools within the design process, in terms of failure identification and reliability quantification. However, the use of historical reliability data has shown to be a particular downfall. As such, there has been a drive to predict the reliability of mechanical components based on their underlying degradation and failure processes and mechanisms. Consequently, this research is initially concerned with the development of a methodology, including an assessment of existing methods, that could be used to more readily understand the underlying failure characteristics of a mechanical component in terms of material, geometrical, environmental and operational characteristics. A particular underlying mechanism has been chosen and mathematical models were developed that simulate its physical behaviour and its degradation characteristics. Additionally, due to the potential uncertainty in the models and limited understanding of the characteristics of the underlying mechanism, the model was simulated within a probabilistic framework, fundamentally by application of the stress strength interference modelling approach. Finally, the model and its parameters were assessed to determine how uncertain governing parameters could appear to lead to variations in the reliability of the actuator.