Cost and quality are key properties of a product, possibly even the two most important. Onedefinition of quality is fitness for purpose. Load-bearing products, i.e. structural components,loose their fitness for purpose if they fail. Thus, the ability to withstand failure is a fundamentalmeasure of quality for structural components. Reliability based design optimization(RBDO) is an approach for development of structural components which aims to minimizethe cost while constraining the probability of failure. However, the computational effort ofan RBDO applied to large-scale engineering problems has prohibited it from employment inindustrial applications. This thesis presents methods for computationally efficient RBDO.A review of the work presented on RBDO algorithms reveals that three constituentsof an RBDO algorithm has rendered significant attention; i ) the solution strategy for andnumerical treatment of the probabilistic constraints, ii ) the surrogate model, and iii) theexperiment design. A surrogate model is ”a model of a model”, i.e. a computationally cheapapproximation of a physics-based but computationally expensive computer model. It is fittedto responses from the physics-motivated model obtained via a thought-through combinationof experiments called an experiment design.In Paper A, the general algorithm for RBDO employed in this work, including the sequentialapproximation procedure used to treat the probabilistic constraints, is laid out. A singleconstraint approximation point (CAP) is used to save computational effort with acceptablelosses in accuracy. The approach is used to optimize a truck component and incorporatesthe effect that production related design variables like machining and shot peening have onfatigue life.The focus in Paper B is on experiment design. An algorithm employed to construct anovel experiment design for problems with multiple constraints is presented. It is based onan initial screening and uses the specific problem structure to combine one-factor-at-a-timeexperiments to a several-factors-at-a-time experiment design which reduces computationaleffort.In Paper C, a surrogate model tailored for RBDO is introduced. It is motivated by appliedsolid mechanics considerations and the use of the first order reliability method to evaluate theprobabilistic constraint. An optimal CAP is furthermore deduced from the surrogate model.In Paper D, the paradigm to use sets of experiments rather than one experiment at atime is challenged. A new procedure called experiments on demand (EoD) is presented. TheEoD procedure utilizes the core of RBDO to quantify the demand for new experiments andaugments it by a D-optimality criterion for added robustness and numerical stability. / QC 20120229

The phenomenon known as Negative Bias Temperature Instability (NBTI) impacts the operational characteristics of Complementary Metal Oxide Semiconductor (CMOS) devices, and tends to have a stronger effect on p-channel devices. This instability is observed with an applied "on" biasing during normal operation and can be accelerated with thermal stress. A normal applied electrical bias on CMOS transistors can lead to the generation of interface states at the junction of the gate oxide and the transistor channel. The hydrogen that normally passivates the interface states can diffuse away from the interface. As a result, the threshold voltage and transconductance will change. These interface states can be measured to determine the susceptibility to NBTI of the devices. For this purpose, a charge pumping experiment and other On-the-Fly techniques at certain temperatures can provide the interface state density and other valuable data. NBTI can impact current technological fabrication processes, such as those provided to the government from IBM. This paper explains this testing of current submicron transistor technology that will be used for military applications. / US Navy (USN) author.

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 Operations Research)--Naval Postgraduate School, September 1990. / Thesis Advisor(s): Woods, W.M. Second Reader: Bailey, Michael. "September 1990." Description based on title screen as viewed on December 15, 2009. DTIC Identifier(s): Intervals, Estimates, Parametric Analysis. Author(s) subject terms: Reliability, Confidence Limit, Parametric, Normal, Unknown Means and Variances. Includes bibliographical references (p. 53-54). Also available in print.

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).

No description available.