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Since Hurricane Katrina, extensive studies have been conducted aiming to optimize the transit vehicle routing in the event of an emergency evacuation. However, the vast majority of the studies focus on solving the deterministic vehicle routing problem that all the evacuation data are known in advance. These studies are generally not practical in dealing with real-world problems which involve considerable uncertainty in the evacuation data set. In this dissertation, a SmartEvac system is developed for dynamic vehicle routing optimization in emergency evacuation. The SmartEvac system is capable of processing dynamic evacuation data in real time, such as random pickup requests, travel time change, network interruptions. The objective is to minimize the total travel time for all transit vehicles. A column generation based online optimization model is integrated into the SmartEvac system. The optimization model is based on the following structure: a master problem model and a sub-problem model. The master problem model is used for routes selection from a restricted routes set while the sub-problem model is developed to progressively add new routes into the restricted routes set. The sub-problem is formulated as a shortest path problem with capacity constraint and is solved using a cycle elimination algorithm. When the evacuation data are updated, the SmartEvac system will reformulate the optimization model and generate a new routes set based on the existing routes set. The computational results on benchmark problems are compared to other studies in the literature. The SmartEvac system outperforms other approaches on most of the benchmark problems in terms of computation time and solution quality. CORSIM simulation is used as a test bed for the SmartEvac system. CORSIM Run-Time-Extension is developed for communications between the simulation and the SmartEvac system. A case study of the Hurricane Gustav emergency evacuation is conducted. Different scenarios corresponding to different situations that presented in the Hurricane Gustav emergency evacuation are proposed to evaluate the performance of the SmartEvac system in response to real-time data. The average processing time is 28.9 seconds and the maximum processing time is 171 seconds, which demonstrate the SmartEvac system’s capability of real-time vehicle routing optimization.

Precast concrete multistory buildings are used in an attempt to optimize the available construction space and reduce costs. However, little is known about predicting their capacity in a brittle response mode due to the sudden loss of a critical element that could induce a Progressive Collapse Scenario. Therefore, the National Institute for Standards and Technology (NIST) developed an explicit approach in the design of precast concrete systems that is intended to mitigate a progressive collapse by enhancing the rotational capacity of joints and the robustness of the structural system. A full-scale experiment was conducted to investigate the structural performance of a prototype design under a column-removal scenario. The test assembly frame, consisting of three columns and two beams, was subjected to a displacement controlled vertical force acting at the center to characterize the failure modes and collapse mechanisms. Brittleailures of critical structural elements were observed and significantly impacted the performance.

Underexplored environments such as soil samples continue to be an untapped source of bacterial strains with great potential to produce secondary metabolites for medicinal applications. As a result, these microorganisms represent a broad and yet unknown reservoir of new strains capable of producing these novel compounds. The current research primarily seeks to perform the isolation, purification, and characterization of secondary metabolites from a soil bacterium (Janthinobacterium lividum TAJX1901). The isolated soil bacterium was successfully cultured on rich media agar plates, followed by extraction using methanol and chloroform. The purification methods utilized include flash column chromatography, preparative thin-layer chromatography, and high-performance liquid chromatography. For structural elucidation, UV-Vis analysis, infrared spectroscopy, and nuclear magnetic resonance spectroscopy were employed. The extraction resulted in a dominant violet pigment soluble in methanol. Results revealed the presence of highly conjugated, polar, and aromatic compounds (violacein or relatives of violacein) and dioctyl phthalate (a contaminant).

Monoclonal antibodies are large, complex biomolecules that can be difficult to characterize. Characterization is important because of the various post translational modifications that can occur during manufacturing, processing, and storage. Some modifications can lead to efficacy and safety issues and therefore are heavily monitored. A leading way to monitor various modifications is by using liquid chromatography. The high sensitivity, reproducibility, and ability to quantitate analytes makes it very attractive for monoclonal antibody characterization. The large molecular size of monoclonal antibodies (150 kDa) makes them challenging to separate efficiently and with high enough resolution to be helpful. New column technologies that would help improve protein separation efficiencies and slectivities would greatly help in this challenging process. In this thesis, three novel bonded phases are developed for the separation of monoclonal antibodies including a weak anion and cation exchanger (WAX, CEX) for the separation of charged species as well as a novel hydrophilic interaction chromatography (HILIC) for the separation of glycoforms. Column develop is achieved by optimizing selectivity and improving efficiency of separations by altering particle surface chemistry.

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Most structural optimization procedures focus on minimizing the total volume of steel in an attempt to reduce overall costs. However, many other factors can have an effect on the overall cost of a structure. Base column demands in particular, can affect base plate sizes, anchorage, and foundation design. Researchers have found that present methods for estimating column demands are too conservative. Nonlinear time history analyzes were conducted on buckling-restrained braced frames of six heights. Optimized results were found considering three ductility constraints and two optimization objectives. The two optimization objectives were minimized total brace area and minimized base column demands. The results show that designs created by using a minimized column demand objective led to column demands that ranged from 2 to 6% lower than column demands in designs generated by a total brace area minimizing objective. The average brace areas of the designs produced by the total brace area minimizing objective were 25 to 80% less than the designs produced by the column demand minimizing objective. Results showed that large braces in the top stories did not have an effect on column demands in the ground level story. The results indicate that base column demands can be minimized by minimizing braces areas. However, braces areas cannot be minimized by minimizing base column demands.