A high resolution x-ray tomography system was used to study chopped fiber polymeric composites made of polypropylene resin, nickel coated carbon fiber and Eglass fiber. Procedures are developed to obtain micro-structured features of importance. In-situ tensile testing system was developed and integrated into the existing hardware for tomography equipment to study the evolution of damage and micro-structural features as a function of mechanical stress. High resolution x-ray tomographic images of glass fiber were collected and viewed on a micron scale. The radiographs were reconstructed to visualize the fiber content of the samples in three dimensional volume. In addition, glass fiber dogbone specimens were tested on a miniature tensile machine using x-ray tomography to view deformation of the samples in high resolution. Fractures in the chopped glass composite were observed for x-ray microscopy showing the dominant failure mechanism of the sample are low interfacial strength and adhesion between the fiber and matrix. Cracks were not observed until after failure by fiber pull-out using the digital microscopy method. Using SEM microscopy method, resin cracking and fiber debonding was observed for a carbon fiber with vinyl ester resin while under tensile loading. Important micro-structural information relationship with and mechanical behavior including variation modulus, yield and ultimate strength are discussed.

The research aims are to enable the decision maker of an integrated vendor-buyer system under Consignment Stock (CS) policy to make the optimal/sub-optimal production/replenishment decisions when some general and realistic critical factors are considered. In the system, the vendor produces one product at a finite rate and ships the outputs by a number of equal-sized lots within a production cycle. Under a long-term CS agreement, the vendor maintains a certain inventory level at the buyers warehouse, and the buyer compensates the vendor only for the consumed products. The holding cost consists of a storage component and a financial component. Moreover, both of the cases that the unit holding costs may be higher at the buyer or at the vendor are considered. Based upon such a system, four sets of inventory models are developed each of which considers one more factor than the former. The first set of models allows a controllable lead-time with an additional investment and jointly determines the shipping size, the number of shipments, and the lead time, that minimize the yearly joint total expected cost (JTEC) of the system. The second set of models considers a buyers capacity limitation which causes some shipments to be delayed so that the arrival of these shipments does not cause the buyers inventory to go beyond its limitation. As a result, the number of delayed shipments is added as the fourth decision variable. A variable demand rate is allowed in the third set of models. Uncertainty caused by the varying demand are controlled by a safety factor, which becomes the fifth decision variable. Finally, the risk of obsolescence of the product is considered in the fourth model. The first model is solved analytically, whereas the rest are not, mainly because of the complexity of the problem and the number of variables being considered. Three doubly-hybrid meta-heuristic algorithms that combine two different hybrid meta-heuristic algorithms are developed to provide a solution procedure for the rest of models. Numerical experiments illustrate the solution procedures and reveal the effects of the buyers capacity limitation, the effects of the variable demand rate, and the effects of the risk of obsolescence, on the system. Furthermore, sensitivity analysis shows that some of the system parameters (such as the backorder penalty, the extra space penalty, the ratio of the unit holding cost of the vendor over that of the buyer) are very influential to the joint system total cost and the optimal solutions of the decision variables.

Efficient crystallization in raw sugar production is the result of a combination of factors and responses that meet specific criteria. Matching a sugar quality standard, maximizing sugar yield, maximizing crystallization equipment capacity and minimizing heat requirement are all necessary optimization criteria. A double centrifugation or purge of C-magma is intended to improve raw sugar whole color by the reduction of color recirculation with the sugar crystal. Combining a three boiling crystallization scheme with a second centrifugation after the last crystallization stage required optimizing the input/output product parameters (purities) and the location of the liquid recycle component (double purge molasses) for efficient integration. Sugars and JMP® were software programs used to solve this multiple-response optimization problem using a multistage approach. The optimization strategy went from actual data correlations, experimental design, computer simulations and surrogate models to a desirability approach that transformed the problem from multiple-objective functions into a single objective function, the overall desirability. The implementation of the double purge system by three Louisiana sugar factories confirmed the reduction of whole color of raw sugar, up to 47%, and the linear relation between double purge magma purity and raw sugar whole color. An overall desirability expression was applied to find the optimal input/output product parameters of the double purge system for different scenarios using JMP® optimization algorithm. Optimal control parameters and recycle determined by this strategy matched the average settings used during actual operation at the 2013 sugarcane crop season. In addition, surrogate models were used to evaluate the importance of the random and control parameters for each response and for each syrup purity scenario. This optimization strategy offers an approach not only to evaluate the importance of several product parameters or the optimal settings, but also offers a better understanding for sugar factory processes and for troubleshooting specific undesired responses. In the future this optimization strategy may be applicable for integrating additional equipment and for improvements of existing process stages at any sugar facility

Biomethane gas (BMG), known for its sustainability, low environmental impact, and high profitability, has received wide attention in recent years. To facilitate the process of making strategic plans for building a BMG production system, this dissertation leverages the mathematical modeling and optimization techniques to minimize the supply chain cost for such a system. Typical elements in a BMG production system consist of the local farms that produce the feedstock, the hubs that collect and store the feedstock produced by farms, the reactors that generate BMG from the feedstock transported from the hubs, the condensers that liquefy the BMG from the reactors, and the delivery points that act as end distributors and accept the liquefied BMG from condensers. The logistics of a BMG production system can be divided into four stages: farm-to-hub (F2H) stage, hub-to-reactor (H2R) stage, reactor-to-condenser (R2C) stage, and condenser-to-delivery point (C2DP) stage. Depending on the variation on the elements and stages of a BMG production system, four supply chain configurations for BMG facility locations are proposed with increasing level of complexity: single-stage, single-reactor system (SS-SRS); single-stage, multi-reactor system (SS-MRS); three-stage, multi-facility system (TS-MFS); and four-stage, multi-facility system (FS-MFS). The objective for each configuration is to locate facilities optimally and to design the transportation/pipeline connecting network such that the supply chain cost, including the total of feedstock costs, labor costs, facilities building costs, and transportation/pipeline layout costs are minimized. A systematic approach, containing mathematical modeling and heuristic design, is proposed for each configuration. Numerical experiments are conducted for each designed heuristic to verify its performance.

As a result of increasing windstorm losses in the United States over the past 50 years, a variety of residential wind hazard mitigation methods have been suggested. Mitigation undoubtedly reduces windstorm losses; however, the expected economic risk reduction of mitigation practices over the life of the building depends on the building characteristics (i.e., capacity) and the intensity and occurrence of wind speeds (i.e., demand). Effective decision making requires estimation of potential future losses based on many variables. Many models, primarily mechanics-based simulation models, have been developed to predict building damage from wind events; however; fewer models of economic loss have been developed, although economic losses are more easily quantified over a spatial domain and have the potential for more effective widespread use. Additionally, many existing models consider damage and loss as a function of basic wind speed in open terrain and few address the variation in loss due to changes in surface roughness, although surface roughness is a critical component in surface wind speed. In spite of advancements in damage and loss modeling, the limitations of existing publications (e.g., geographically limited in scope, limited to specific building types, limited to specific events, limited to open terrain) prevent generalization and application of the results on a nationwide basis to support development of a mitigation decision-making framework. To address these limitations, this research presents a methodology to calculate tabular expected annual loss (EAL) results for 160 variations of one-story, single-family homes at each ASCE 7-10 wind contour through Monte Carlo simulation of local annual maximum wind speeds convolved with Hazus-MH economic loss functions for open terrain and non-open terrain. The results are integrated into a decision-making framework designed to provide customized consumer-level guidance to assist the mitigation decision-making process based on location, terrain, years of interest, and building configuration. The results provide practical results in an easy-to-use format to facilitate consumer-level mitigation decision making.

Bone tissue engineering approaches using polymer/ceramic composites show promise as effective biocompatible, absorbable, and osteoinductive materials. A novel class of in situ polymerizing thiol-acrylate based copolymers synthesized via an amine-catalyzed Michael addition was studied for its potential to be used in bone defect repair. Both pentaerythritol triacrylate-co-trimethylolpropane tris(3-mercaptopropionate) (PETA-co-TMPTMP) and PETA-co-TMPTMP with hydroxyapatite composites were fabricated in solid cast and foamed forms. These materials were characterized chemically and mechanically followed by an in vitro evaluation of the biocompatibility and chemical stability in conjunction with human adipose-derived mesenchymal pluripotent stem cells (hASC). The solid PETA-co-TMPTMP with and without hydroxyapatite (HA) exhibited compressive strength in the range of 7-20 MPa, while the cytotoxicity and biocompatibility results demonstrate higher metabolic activity of hASC on PETA-co-TMPTMP than on a polycaprolactone control. SEM imaging of hASC show expected spindle shaped morphology when adhered to copolymer. Micro-CT analysis indicates open cell interconnected pores. Foamed PETA-co-TMPTMP HA composite shows promise as an alternative to FDA-approved biopolymers for bone tissue engineering applications. The results of the six week in vivo biocompatibility study using a posterior lumbar spinal fusion model demonstrate that PETA:HA can be foamed in vivo without serious adverse effects at the surgical site. Additionally, it was demonstrated that cells migrate into the interconnected pore volume are found within centers of ossification. Because the natural mechanical strength of materials is highly dependent on the crystal structure, four different silicate-derived ceramicsdiopside, akermanite, monticellite, and merwinite have been synthesized and evaluated for their potential as bone augments and grafts. This sparks our interest in the fabrication of polycaprolactone (PCL)/ceramic composites for potential use as scaffolds. Akermanite and monticellite exhibit better osteogenic properties than diopside and merwinite, suggesting that they might be the optimal material for fabricating bone scaffolds.

Text to animation is the conversion of textual instructions to animations following and depicting those instructions. Text to animation is important to fields such as crime scene investigation, military special operations and storytelling where text is utilized. It is also useful for physical therapy where a doctor can factor in disability parameters in the 3D models and determine the safest therapy exercises for patients. It can be used in robotics, where robot assistants can be instructed to perform tasks through text instructions. In this research, a system was created to generate 3D animation of workouts from their textual instructions. An algorithm was developed to generate animation sequences from test cases. The algorithm utilized an animation graph which was created from a training set of 100 workouts with the nodes as postures and the links as animation-clip names along with their action data. The algorithm is designed to find and generate the closest animations available. A testing set of 40 similar workouts was used to test the algorithm and obtain an output of sequence of animations which were later depicted by the Unity Game Engine. In user evaluations, for 25 of the 40 test workouts, or 62.5% of the test workouts, the animation was determined by the users, to have the same or almost the same human motions as compared to a video of a human performing the workout. Analysis of the 15 workouts that were not similar to the human video (37.5%) showed that their issues can be fixed and the animation search can be improved by training the animation graph on more varieties of the workouts and on different text instructions of the same workouts from different sources. For 64.5% of the 156 sentences of all the text workouts, the animations were determined to correctly depict the text instructions. This research provides an initial animation graph and animation library which can be expanded to include more poses and animations from other domains such as yoga or dance. In the future system has the potential to provide users with no 3D modelling/animation expertise, a way to create 3D animations with just texts.

Two attractive potential feed stocks for biofuel production are energycane and sweet sorghum due to the environmental adaptability, sugars concentration and yield. Evaluation and development of harvesting, transportation and storage practices is critical for bringing the production of these crops to industrial levels. This research aims to analyze the supply system of energy crops and evaluate the effect of different harvesting and storage in the yields of the feedstock and the efficiencies of the processes. Harvesting trials were conducted at St. Gabriel, LA for evaluating the feasibility of using energy crops as inputs for ethanol production. The parameters that were varied during the trials were: billet size, fan speed of the extraction system. Several operational indicators were estimated in the study: material yield (tons/acre), sugars yield (ton/acre), ethanol yield (liter/acre) and agronomic and efficiencies indicators of the supply stages of the system. A simulation of the conceived supply system was performed in order to measure and determine the feasibility of the operation. The objective function of the model was defined as the profit maximization of ethanol production. Twenty four scenarios were simulated and evaluated for determining the optimal solutions. It was evidenced that for increasing the sugars and ethanol yield from the energy crops, it was necessary to reduce the lead times of the operations, enabling to process the material shortly after harvesting. A feasible operation of the system was guarantee when a maximum distance of 35 miles was defined for transportation logistics and when an area of 100 acres was covered for collecting the feedstock.

Tropical cyclone-generated storm surge frequently causes catastrophic damage in communities along the Gulf of Mexico. The prediction of landfalling or hypothetical storm surge magnitudes in U.S. Gulf Coast regions remains problematic, in part, because of the dearth of historic event parameter data, including accurate records of storm surge magnitude (elevation) at locations along the coast from hurricanes. While detailed historical records exist that describe hurricane tracks, these data have rarely been correlated with the resulting storm surge, limiting our ability to make statistical inferences, which are needed to fully understand the vulnerability of the U.S. Gulf Coast to hurricane-induced storm surge hazards. This dissertation addresses the need for reliable statistical storm surge estimation by proposing a probabilistic geodatabase-assisted methodology to generate a storm surge surface based on hurricane location and intensity parameters on a single desktop computer. The proposed methodology draws from a statistically representative synthetic tropical cyclone dataset to estimate hurricane track patterns and storm surge elevations. The proposed methodology integrates four modules: tropical cyclone genesis, track propagation, storm surge estimation, and a geodatabase. Implementation of the developed methodology will provide a means to study and improve long-term tropical cyclone activity patterns and predictions. Specific contributions are made to the current state of the art through each of the four modules. In the genesis module, improved representative data from historical genesis populations are achieved through implementation of a stratified-Monte-Carlo sampling method to simulate genesis locations for the North Atlantic Basin, avoiding potential non-representative clustering of sampled genesis locations. In the track module, the improved synthetic genesis locations are used as the starting point for a track location and intensity methodology that incorporates storm strength parameters into the synthetic tracks and improves the positional quality of synthetic tracks. In the surge module, high-resolution, computationally intensive storm surge model results are probabilistically integrated in a computationally fast-running platform. In the geodatabase module, historic and synthetic tropical cyclone genesis, track, and surge elevation data are combined for efficient storage and retrieval of storm surge data.

Simulated, 3D gaming environments have been used for a wide-range of applications including training, entertainment, and experimentation in an assortment of domains for some time. This can be attributed to their unique ability to emulate multifaceted situations that may be difficult to control, while affording participants the opportunity to operate in a relatively safe environment. In cybersecurity research, investigation of insider threat behavior is an endeavor that has received little attention in terms of available environments and resources for experimental manipulation. This research effort aimed to close this gap. A simulated, 3D gaming environment and accompanying scenarios were developed for utilization as a research application for a verification study. These constitute crucial components for proper development of insider threat detection tools and training applications. The aim was to use knowledge of performance, user stress state, and user perceptions of the simulation's graphic and usability qualities to verify the simulation for use in insider threat detection work. The objective of this simulated, 3D gaming environment and scenarios was to serve as a realistic and valid context for the development of insider threat identification methods. The scenario narrative involved a reenactment of computer system exploitation by an employee who is trying to acquire private financial information without authorization. In each scenario, the participant assumed the role of a financial investigator employed at a large financial institution. There were two conditions associated with this verification study (control and insider threat). Participants in the control condition performed all of their tasking as regular bank employees while participants assigned to the insider threat condition had to carry out a portion of their tasking as an insider threat. Findings indicated that participants found the simulated, 3D gaming environment engaging, and the simulations graphics usable and immersive. Additionally, the role manipulation resulted in a significant difference in the time it took to perform critical tasking (tasking that was illicit in the insider threat condition). Role manipulation did not produce significant differences in stress between conditions, but it was influential regarding the perceptions of the stress sources. The results suggest that this simulated, 3D gaming environment meets the needs of insider threat investigation and can be used to advance understanding of the nature of insider threat behavior.