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The overall goal of this research was to increase, relative to targeting recommendations, the cost-effectiveness of pollution reduction measures within a watershed. The goal was met through development of an optimization procedure for best management practice (BMP) placement at the watershed level. The procedure combines an optimization component, written in the C++ language, with spatially variable nonpoint source (NPS) prediction and economic analysis components, written in the ArcView geographic information system scripting language. The procedure is modular in design, allowing modifications or enhancements to the components while maintaining the overall theory. The optimization component uses a genetic algorithm to optimize a lexicographic multi-objective function of pollution reduction and cost increase. The procedure first maximizes pollution reduction to meet a specified goal, or maximum allowable load, and then minimizes cost increase. For the NPS component, a sediment delivery technique was developed and combined with the Universal Soil Loss Equation to predict average annual sediment yield at the watershed outlet. Although this evaluation considered only erosion, the NPS pollutant fitness score allows for evaluation of multiple pollutants, based on prioritization of each pollutant. The economic component considers farm-level public and private costs, accounting for crop productivity levels by soil and for enterprise budgets by field. The economic fitness score assigns higher fitness scores to scenarios in which costs decrease or are distributed more evenly across farms. Additionally, the economic score considers the amounts of cropland, hay, and pasture needed to meet feed and manure/poultry litter spreading requirements. Application to two watersheds demonstrated that the procedure optimized BMP placement, locating scenarios more cost-effective than a targeting strategy solution. The optimization procedure identified solutions with lower costs than the targeting strategy solution for the same level of pollution reduction. The benefit to cost ratio, including use of the procedure and implementation of resulting solutions, was demonstrated to be greater for the optimization procedure than for the targeting strategy. The optimization procedure identifies multiple near optimal solutions. Additionally, the procedure creates and evaluates scenarios in a repeated fashion without requiring human interaction. Thus, more scenarios can be evaluated than are feasible to evaluate manually. / Ph. D.

Dual response surface methodology (Vining and Myers (1990)) has been successfully used as a cost-effective approach to improve the quality of products and processes since Taguchi (Tauchi (1985)) introduced the idea of robust parameter design on the quality improvement in the United States in mid-1980s. The original procedure is to use the mean and the standard deviation of the characteristic to form a dual response system in linear model structure, and to estimate the model coefficients using least squares methods. In this dissertation, a Bayesian hierarchical approach is proposed to model the dual response system so that the inherent hierarchical variance structure of the response can be modeled naturally. The Bayesian model is developed for both univariate and multivariate dual response surfaces, and for both fully replicated and partially replicated dual response surface designs. To evaluate its performance, the Bayesian method has been compared with the original method under a wide range of scenarios, and it shows higher efficiency and more robustness. In applications, the Bayesian approach retains all the advantages provided by the original dual response surface modelling method. Moreover, the Bayesian analysis allows inference on the uncertainty of the model parameters, and thus can give practitioners complete information on the distribution of the characteristic of interest. / Ph. D.

Many industrial statisticians employ the techniques of Response Surface Methodology (RSM) to study and optimize products and processes. A second-order Taylor series approximation is commonly utilized to model the data; however, parametric models are not always adequate. In these situations, any degree of model misspecification may result in serious bias of the estimated response. Nonparametric methods have been suggested as an alternative as they can capture structure in the data that a misspecified parametric model cannot. Yet nonparametric fits may be highly variable especially in small sample settings which are common in RSM. Therefore, semiparametric regression techniques are proposed for use in the RSM setting. These methods will be applied to an elementary RSM problem as well as the robust parameter design problem. / Ph. D.

Decreasing the cycle time of panels in the printed circuit card manufacturing process has been a significant research topic over the past decade. The research objective in such literature has been to reduce the placement machine cycle times by finding the optimal placement sequences and component-feeder allocation for a given, fixed, panel component layout for a given machine type. Until now, no research has been found which allows the alteration of the panel configuration itself, when panelization is a part of that electronic panel design. This research will be the first effort to incorporate panelization into the cycle time reduction field. The PCB circuit design is not to be altered; rather, the panel design (i.e., the arrangement of the PCB in the panel) is altered to reduce the panel assembly time. Component placement problem models are developed for three types of machines: The automated insertion machine (AIM), the pick-and-place (PAPM) machine, and the rotary turret head machine (RTHM). Two solution procedures are developed which are based upon a genetic algorithm (GA) approach. One procedure simultaneously produces solutions for the best panel design and component placement sequence. The other procedure first selects a best panel design based upon an estimation of its worth to the minimization problem. Then that procedure uses a more traditional GA to solve for the component placement and component type allocation problem for that panel design. Experiments were conducted to discover situations where the consideration of panelization can make a significant difierence in panel assembly times. It was shown that the PAPM scenario benefits most from panelization and the RTHM the least, though all three machine types show improvements under certain conditions established in the experiments. NOTE: An updated copy of this ETD was added on 09/17/2010. / Ph. D.

This thesis presents a new active-passive treatment developed to reduce structural vibrations and their associated radiated sound. It is a contribution to the research of efficient and low cost devices that implement the advantages of active and passive noise control techniques. A theoretical model has been developed to investigate the potential of this new "active-passive distributed absorber". The model integrates new functions that make it extremely stable numerically. Using this model, a genetic algorithm has been used to optimize the shape of the active-passive distributed absorber. Prototypes have been designed and their potential investigated. The device subsequently developed can be described as a skin that can be mechanically and electrically tuned to reduce unwanted vibration and/or sound. It is constructed from the piezoelectric material polyvinylidene fluoride (PVDF) and thin layers of lead. The tested device is designed to weight less than 10% of the main structure and has a resonance frequency around 1000 Hz. Experiments have been conducted on a simply supported steal beam (24"x2"x1/4"). Preliminary results show that the new treatment out-performs active-passive point absorbers and conventional constrained layer damping material. The compact design and its efficiency make it suitable for many applications especially in the transportation industry. This new type of distributed absorber is totally original and represent a potential breakthrough in the field of acoustics and vibration control. / Master of Science