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Peacekeeping operations (PKO) have become a significant challenge to the German Armed Forces. For the development of tactics, techniques, procedures and equipment with combat operations, agent-based models have been developed, used and exploited for many years. Modeling and simulation of PKO, however, is still in a very early stage. This thesis develops an agent-based model to analyze PKO. Unlike many other multi-agent systems (MAS), it implements the rules of discrete event simulation. The chosen software architecture makes the model upgradeable and useful for a breadth of future applications. The modelâ s open architecture and the underlying principle of loosely coupled components make it easy to change or enhance the model. The software agentsâ design incorporates individuality, which is characterized by personality factors. Furthermore, the model is data-farmable. Required data inputs into the simulation tool, i.e., PKO scenarios, are formatted utilizing a state-of-theart technology called Extensible Markup Language (XML), which facilitates use of the data in nearly all computer software packages. The model executes multiple runs of multiple scenarios automatically, demonstrating a robust nature. Finally, an exemplary analysis demonstrates data-farming concepts on the effect of personality factor settings on the potential escalation of a PKO scenario. / German Army author.

Neste trabalho apresentamos os principais objetivos dos planejamentos experimentais em modelos de regressão. Na primeira parte do trabalho descrevemos os planejamentos com alavancagem constante, que permitem que todos os pontos amostrais exerçam a mesma influência nas estimativas dos parâmetros do modelo de regressão. Abordamos ainda outros tipos de planejamentos experimentais que obedecem a certos critérios como, por exemplo: G-otimalidade, D-otimalidade e Planejamentos ortogonais. Finalizando o trabalho foi apresentada uma análise prática em que as principais medidas estudadas foram aplicadas a um conjunto de dados reais. / This work presents the main objectives of the sampling plans in regression models. The first part of the study describes the planning with constant leverage, enabling all sampling points exercise the same influence on the estimatives of the parameters of the regression model. We still discussed other types of experimental plans that meet certain criteria, such as G-optimality, D-optimality and Planning orthogonal. Finally the work presented a practical analysis where the main measures were applied to a set of real data.

Thesis (Ph. D.)--University of Chicago, Dept. of Statistics, December 1997. / Includes bibliographical references. Also available on the Internet.

This research combines a statistical tool called experimental design/response surface methodology with reservoir modeling and flow simulation for the purpose of reservoir characterization. Very often, it requires large number of reservoir simulation runs for identifying significant reservoir modeling parameters impacting flow response and for history matching. Experimental design/response surface (ED/RS) is a statistical technique, which allows a systematic approach for minimizing the number of simulation runs to meet the two objectives mentioned above. This methodology may be applied to synthetic and field cases using existing statistical software tools. The application of ED/RS methodology for the purpose of reservoir characterization has been applied for two different objectives. The first objective is to address the uncertainties in the identification of the location and transmissibility of flow barriers in a field in the Gulf of Mexico. This objective is achieved by setting up a simple full-factorial design. The range of transmissibility of the barriers is selected using a Latin Hypercube Sampling (LHS). An analysis of variance (ANOVA) gives the significance of the location and transmissibility of barriers and comparison with decline-type curve analysis which gives us the most likely scenarios of the location and transmissibility of the flow barriers. The second objective is to identify significant geologic parameters in object-based and pixel-based reservoir models. This study is applied on a synthetic fluvial reservoir, whose characteristic feature is the presence of sinuous sand filled channels within a background of floodplain shale. This particular study reveals the impact of uncertainty in the reservoir modeling parameters on the flow performance. Box-Behnken design is used in this study to reduce the number of simulation runs along with streamline simulation for flow modeling purposes. In the first study, we find a good match between field data and that predicted from streamline simulation based on the most likely scenario. This validates the use of ED to get the most likely scenario for the location and transmissibility of flow barriers. It can be concluded from the second study that ED/RS methodology is a powerful tool along with a fast streamline simulator to screen large number of reservoir model realizations for the purpose of studying the effect of uncertainty of geologic modeling parameters on reservoir flow behavior.

Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xiv, 119 p.: ill. (some col.). Includes abstract and vita. Advisor: Theodore T. Allen, Dept. of Industrial and Systems Engineering. Includes bibliographical references (p. 111-119).

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Thesis (M.S.)--Virginia Polytechnic Institute, 1966. / Vita. Abstract. Includes bibliographical references (leaf 51). Also available via the Internet.

Thesis (Ph. D.)--University of North Texas, Aug., 2007. / Title from title page display. Includes bibliographical references.