Engineering Commons^™

A Robust Method Of Solving Nonlinear Boundary Value Problems Via Modified Compromise Programming, John L. Zornick

Theses and Dissertations

This study is an extension of Ng's previous work in which goal programming was used to determine an approximate solution to a boundary value problem. This approach follows the same basic approach developed by Ng in which the method of collocation was recast as a compromise programming model. Hence, instead of solving a system of simultaneous nonlinear equations, one seeks a compromise solution which minimizes (in a weighted residual sense) a vector norm of the differential equation residuals. A difference in this approach is that it makes use of a genetic algorithm as the optimizing engine as opposed to the …

Response Surface Methodology As A Sensitivity Tool In Decision Analysis, David A. Meyers

Theses and Dissertations

The purpose of this study is to evaluate response surface methodology as a sensitivity analysis tool in the area of decision analysis. The advent of low-cost personal computer software, such as DPLTM, has created an accessible tool with the ability to frame and solve influence diagrams for decision problems. This study provides a comparison of current sensitivity analysis techniques vs those made possible through response surface methodology (RSM). Sensitivity analysis alternatives are demonstrated on a decision problem concerning the evaluation of force structure options for the Department of Defense. Sensitivity analysis is performed on both one-way and two-way perturbations of …

Groundwater Model Parameter Estimation Using Response Surface Methodology, Richard M. Cotman

Theses and Dissertations

This thesis examined the use of response surface methodology (RSM) to estimate the parameters of a finite-element groundwater model. An existing two-dimensional, steady-state flow model of a fractured carbonate groundwater system in southwestern Ohio served as the calibration target data set. A Plackett-Burman screening design showed that only four of the ten hydraulic conductivity zones significantly contributed to the output of the finite-element model. Also, the effective porosity parameter did not significantly affect the model's output. Using only the four significant hydraulic conductivity parameters; four two-level, four-factor designed experiments were conducted to exploit the first-order response surface defined by a …

A New Goodness-Of-Fit Test For The Gamma Distribution Based On Sample Spacings From Complete And Censored Samples, Huseyin Duman

Theses and Dissertations

This thesis studies a new goodness-of-fit test for the gamma distribution with known shape parameter. This test statistic, Z*, is based on spacings from complete or censored samples. The size of samples varied between 5 and 35. The critical value tables were generated for the Z* test statistic for complete and censored samples. The critical values were obtained for five different significance levels: 0.20 0.15, 0.10, 0.05, and 0.01. An extensive power study, containing 50,000 Monte Carlo runs was conducted using nine alternative distributions, H_a. It was observed that the Z* test statistic was more powerful against certain …

Estimation Of The Captive-Carry Survival Function For The Advanced Medium Range Air-To-Air Missile (Amraam), David R. Denhard

Theses and Dissertations

This thesis considers the problem of estimating the survival function of an item (probability that the item functions for a time greater than a given time t) from sampling data subject to partial right censoring (a portion of the items in the sampling data have not yet been observed to fail). Specifically the thesis describes several parametric and non-parametric statistical models that can be used when the sampling data is subject to partial right censoring. These models are applied to the case of estimating the captive-carry survival function of the AIM-120A Advanced Medium Range Air-to-Air Missile (AMRAAM).

Comparing Traditional Statistical Models With Neural Network Models: The Case Of The Relation Of Human Performance Factors To The Outcomes Of Military Combat, William Oliver Hedgepeth

Engineering Management & Systems Engineering Theses & Dissertations

Statistics and neural networks are analytical methods used to learn about observed experience. Both the statistician and neural network researcher develop and analyze data sets, draw relevant conclusions, and validate the conclusions. They also share in the challenge of creating accurate predictions of future events with noisy data.

Both analytical methods are investigated. This is accomplished by examining the veridicality of both with real system data. The real system used in this project is a database of 400 years of historical military combat. The relationships among the variables represented in this database are recognized as being hypercomplex and nonlinear.

The …