Simulation of power system behavior is a highly useful tool for planning, analysis of stability, and operator training. Traditionally, small power system studies are dominated by the time taken to solve the machine dynamics equations, while larger studies are dominated by the time taken to solve the network equations. With the trend towards more sophisticated and realistic modeling, the size and complexity of simulations of a power system grow tremendously. The ever-increasing need for computational power can be satisfied by the application of distributed simulation. Also power systems are distributed in nature. The terrestrial power systems are divided into groups and controlled by different Regional Transmission Organization (RTO). Each RTO owns the detailed parameter for the area under control, but only limited data and boundary measurement of the external network. Thus, performing power system analysis in such case is a challenge. Also, simulating a large-scale power system with detailed modeling of the components causes a heavy computational burden. One possible way of relieving this problem is to decouple the network into subsystems and solve the subsystem respectively, and then combine the results of the subsystems to get the solution. The way to decouple a network and represent the missing part will affect the result greatly. Also, due to information distribution in the dispatch centers, a problem of doing power system analysis with limited data available arises. The equivalents for other networks need to be constructed to analyze power system. In this research work, a distributed simulation algorithm is proposed to handle the issues above. A history of distributed simulation is briefly introduced. A generalized coupling method dealing with natural coupling is proposed. Distributed simulation models are developed and demonstrated in Virtual Test Bed (VTB). The models are tested with different network configurations. The test results are presented and analyzed. The performance of the distributed simulation is compared with the steady state result and time domain simulation result. Satisfactory results are achieved.

The previously developed watershed hydrological and water quality model for St. Louis Bay watershed by Kieffer (2002) was refined and calibrated. The aspects of model development refinement included development of fertilization-related nutrient input parameters, evaluation of nutrient input methods, development of plant uptake-related nutrient input parameters, non-cropland simulation using PQUAL module, and recalibration of hydrology in Jourdan River. The related information of typical cropland management practice based on consultation from Mississippi State University Extention Service personnel was integrated into the watershed model. In addition, the Mississippi Department of Environmental Quality (MDEQ) observed water quality data were analyzed to evaluate the appropriateness of current watershed delineation and assess the health of the stream based on the MDEQ proposed numerical water quality target. The refined watershed model was calibrated in Wolf Rover and Jourdan River using both USGS and MDEQ observed water quality data. The concentrations of water quality constituents calculated from the developed watershed model will be provided as boundary conditions for the developed Bay hydrodynamic and water quality model for Total Maximum Daily Load studies.

This study reports the development and validation of a modified two-equation eddy-viscosity turbulence model for computational fluid dynamics prediction of transitional and turbulent flows. The existing terms of the standard k-w model have been modified to include transitional flow effects, within the framework of Reynolds-averaged, eddy-viscosity turbulence modeling. The new model has been implemented into the commercially available flow solver FLUENT and the Mississippi State University SimCenter developed flow solver U2NCLE. Test cases included flow over a flat plate, a 2-D circular cylinder in a crossflow, a 3-D cylindrical body and three conical geometries, which represent the nose-cones of aerodynamic vehicles such as missiles. The results illustrate the ability of the model to yield reasonable predictions of transitional flow behavior using a simple modeling framework, including an appropriate response to freestream turbulence quantities, boundary-layer separation, and angle of attack.

Bacillus subtilis capable of producing surfactin was cultured to evaluate effects of microbial cell mass on natural gas hydrate formation, dissociation, and stability characteristics. The direct molecular influences of microbial cell wall polymers inhibited gas hydrate formation significantly, decreased hydrate formation rates, and increased dissociation rates. Upon the introduction of bentonite, significant synergy was observed in the system in the form of a catalytic effect. Microbes cultured from seafloor seawater-saturated sediments collected from Mississippi Canyon 118 (MC-118) produced similar effects and generalized the observed trends. MC-118 cultures also produced biosurfactant in several culture media, which was shown to catalyze natural gas hydrate formation in porous media. Microorganisms inhabit gas hydrate macrostructures and consume hydrocarbons and other substrates from within. Sulfate reduction and anaerobic hydrocarbon oxidation occurred within gas hydrate during incubations with MC-118 indigenous consortia. A mathematical model was developed to explore the diffusion-reaction implications in massive seafloor gas hydrates.

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