Thesis (M.S.)--Ohio University, June, 1995. / Title from PDF t.p.

Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Allen, Janet K.; Committee Member: Choi, Seung-Kyum; Committee Member: Mistree, Farrokh. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (M.App.Sc.) - Carleton University, 2004. / Includes bibliographical references (p. 102-105). Also available in electronic format on the Internet.

19 Dec 2004. / Published through the Information Bridge: DOE Scientific and Technical Information. "IS-T 2359" Dongping Xu. 12/19/2004. Report is also available in paper and microfiche from NTIS.

This diploma thesis deals with the subject of modeling high strength glued joints which are used during barrier crashtest simulations according to EuroNCAP methods. The purpose of the thesis is to design a metodology of modelling glued joints which will give acceptable results of its behavior during experiment.

This work contributes to the rapid approximation of solutions to optimization problems that are constrained by iteratively solved transport simulations. Given an objective function, a set of candidate decision variables and a black-box transport simulation that is solved by iteratively attaining a (deterministic or stochastic) equilibrium, the proposed method approximates the best decision variable out of the candidate set without having to run the transport simulation to convergence for every single candidate decision variable. This method can be inserted into a broad class of optimization algorithms or search heuristics that implement the following logic: (i) Create variations of a given, currently best decision variable, (ii) identify one out of these variations as the new currently best decision variable, and (iii) iterate steps (i) and (ii) until no further improvement can be attained. A probabilistic and an asymptotic performance bound are established and exploited in the formulation of an efficient heuristic that is tailored towards tight computational budgets. The efficiency of the method is substantiated through a comprehensive simulation study with a non-trivial road pricing problem. The method is compatible with a broad range of simulators and requires minimal parametrization.

A study has been performed to determine the advantages and disadvantages of variable thrust and variable specific impulse (Isp) trajectories for solar system exploration. There have been several numerical research efforts for variable thrust, variable Isp, power-limited trajectory optimization problems. All of these results conclude that variable thrust, variable Isp (variable specific impulse, or VSI) engines are superior to constant thrust, constant Isp (constant specific impulse, or CSI) engines. However, most of these research efforts assume a mission from Earth to Mars, and some of them further assume that these planets are circular and coplanar. Hence they still lack the generality. This research has been conducted to answer the following questions: - Is a VSI engine always better than a CSI engine or a high thrust engine for any mission to any planet with any time of flight considering lower propellant mass as the sole criterion? - If a planetary swing-by is used for a VSI trajectory, is the fuel savings of a VSI swing-by trajectory better than that of a CSI swing-by or high thrust swing-by trajectory? To support this research, an unique, new computer-based interplanetary trajectory calculation program has been created. This program utilizes a calculus of variations algorithm to perform overall optimization of thrust, Isp, and thrust vector direction along a trajectory that minimizes fuel consumption for interplanetary travel. It is assumed that the propulsion system is power-limited, and thus the compromise between thrust and Isp is a variable to be optimized along the flight path. This program is capable of optimizing not only variable thrust trajectories but also constant thrust trajectories in 3-D space using a planetary ephemeris database. It is also capable of conducting planetary swing-bys. Using this program, various Earth-originating trajectories have been investigated and the optimized results have been compared to traditional CSI and high thrust trajectory solutions. Results show that VSI rocket engines reduce fuel requirements for any mission compared to CSI rocket engines. Fuel can be saved by applying swing-by maneuvers for VSI engines, but the effects of swing-bys due to VSI engines are smaller than that of CSI or high thrust engines.

In this thesis, we first develop a new method called penalty function with memory (PFM). PFM consists of a penalty parameter and a measure of constraint violation and it converts a discrete optimization via simulation (DOvS) problem with stochastic constraints into a series of DOvS problems without stochastic constraints. PFM determines a penalty of a visited solution based on past results of feasibility checks on the solution. Specifically, assuming a minimization problem, a penalty parameter of PFM, namely the penalty sequence, diverges to infinity for an infeasible solution but converges to zero almost surely for any strictly feasible solution under certain conditions. For a feasible solution located on the boundary of feasible and infeasible regions, the sequence converges to zero either with high probability or almost surely. As a result, a DOvS algorithm combined with PFM performs well even when optimal solutions are tight or nearly tight. Second, we design an optimal water quality monitoring network for river systems. The problem is to find the optimal location of a finite number of monitoring devices, minimizing the expected detection time of a contaminant spill event while guaranteeing good detection reliability. When uncertainties in spill and rain events are considered, both the expected detection time and detection reliability need to be estimated by stochastic simulation. This problem is formulated as a stochastic DOvS problem with the objective of minimizing expected detection time and with a stochastic constraint on the detection reliability; and it is solved by a DOvS algorithm combined with PFM. Finally, we improve PFM by combining it with an approximate budget allocation procedure. We revise an existing optimal budget allocation procedure so that it can handle active constraints and satisfy necessary conditions for the convergence of PFM.

Diss. (sammanfattning). Umeå : Sveriges lantbruksuniv. / Härtill 4 uppsatser.

The diploma thesis is focused on verifying the success of prediction models mean monthly flows for strategy control storage function of water management system. The success of prediction models is tested during three different periods. To determine the predicted inflows into the reservoirs is applied to the generator artificial flow series LTMA using the Monte Carlo method and the classical model of neuron networks. During the solution is applying the principles of adaptive control. The adaptive control is compared with simple control for improved outflow.