Impact is a large and complex field. It embraces both structures as simple as a nail, and more complex systems, such as a car collision. A central feature of impact theory is finding the dependence between the velocities before and after impact. The transformation law of the velocities in an impact interaction can be represented in a purely geometric form, and therefore in the simplest cases, in describing the motion of systems with impacts, it is possible to get by with entirely elementary tools. However, in most engineering applications, the mechanical interactions occurring during a collision are complex. Therefore, impact is usually described by highly complicated mathematical models that can easily lead to cumbersome intricacies. Hitherto, the theories that have been developed either involve a fairly heavy amount of calculations or are severely oversimplified, and, therefore, limited in their application. Our purpose is first to describe the dynamics of a planar collision with as simple equations as possible, and secondly to extract information from those equations with the least and simplest computation. We achieve our task by combining a Kane's dynamical analysis, a simplified model of the deformation of the contact area during impact, and a numerical integration of a set of ordinary differential equations. Subsequently, we verify the consistency, accuracy and efficiency of our results by comparison to those from earlier theories. / Graduation date: 1996

Graduation date: 1995

Neural networks are models which have been developed to simulate the anatomy of the nervous system. The connection between the elements of these networks, the so called artificial neurons, is similar to the connection between the biological neurons. In developing neural networks people are trying to create systems which have the same computational and communication properties as the brain. On the basis of the things we know from neurophysiology the first models for the neural networks are developed. One of these networks was the perceptron, which is one of the most used neural networks. In this thesis we'll study this special neural network. When the input vectors of the perceptron can be linearly separated into two categories, this network can be trained to correctly classify these input vectors. However in most practical cases the linearly separability assumption isn't satisfied. That's why the main part of this study is devoted to the case where the input vectors aren't linearly separable. / Graduation date: 1995

The success of civil engineering construction in cold regions often depends on the assessment of the potential for frost heave. Over the past two decades two models have been presented to the engineering community to identify the frost heave potential, namely: (1) the segregation potential (SP), and (2) the discrete ice lens (DIL) models. These models are based on ice segregation parameters which can be obtained from simple laboratory freezing tests. However, the reliability of the ice segregation parameters obtained from the laboratory freezing tests is still in question. In recognition of the need to improve the reliability of the measurement of ice segregation parameters in a frost heave test, a study was conducted to: (1) investigate several improvements in the step freezing test used to measure ice segregation parameters, (2) examine several approximations used to interpret the laboratory step freezing test results, (3) demonstrate the compatibility of the SP and DIL parameters, (4) propose a method to obtain reliable ice segregation parameters, and (5) demonstrate the applicability of the DIL model to address field frost heave problems. The results of the study indicated: (1) the accuracy of measured ice segregation parameters may be improved if step freezing tests are conducted under shallower temperature gradients and the water intake velocity is accurately and continuously monitored, (2) inappropriate approximations may produce a significant error in the measurement of ice segregation parameters, (3) SP may be defined either by the ratios of the (i) heave velocity/1.09 to the overall temperature gradient of the frozen soil, or (ii) water intake velocity to the temperature gradient of the frozen fringe, (4) the SP and DIL ice segregation parameters are compatible, and (5) the reliability of both models is improved through the demonstration of the compatibility of the ice segregation parameters. The application of the frost heave prediction models was studied based on ice segregation parameters determined with the improved laboratory procedure. A practical method to predict the influence of the groundwater level using the DIL ice segregation parameters was proposed. A probabilistic approach for the DIL frost heave model was developed. / Graduation date: 1994

Graduation date: 1994

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Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 1990. / Thesis Advisor(s): Johnson, Laura. Second Reader: Parry, Sam H. "September 1990." Description based on title screen as viewed on December 21, 2009. DTIC Identifier(s): Chemical Warfare Casualties, Chemical Warfare Agents, Mathematical Models. Author(s) subject terms: Chemical Casualties, Chemical Warfare, Regression, CHEMCAS. Includes bibliographical references (p. 36-37). Also available in print.

Thesis (Ph. D.)--Ohio State University, 1978. / Includes vita. Includes bibliographical references (leaves 196-199). Available online via OhioLINK's ETD Center.

Dissertation (Ph.D. in Operations Research)--Naval Postgraduate School, September 1990. / Dissertation supervisor: Bradley, Gordon H. "September 1990." Description based on title screen viewed on December 17, 2009. DTIC Descriptor(s): Mathematical models, sizes (dimensions), validation, models, programming languages, drug addiction, algebra, mathematical programming, language, junctions, calculus, homogeneity, integrated systems, mathematical logic. DTIC Identifier(s): Programming languages, mathematical models, calculus, linear programming. Author(s) subject terms: Data types, integrated modeling, linear programming, model validation, mathematical programming software, special purpose languages. Includes bibliographical references (p. 129-132). Also available in print.