Brian G. Williams

In-flight oxidation of aluminum in the twin-wire electric arc process

This paper examines the in-flight oxidation of aluminum sprayed in air using the twin-wire electric arc (TWEA) thermal spray process. Aerodynamic shear at the droplet surface increases the amount of in-flight oxidation by promoting entrainment of the surface oxides within the molten droplet and continually exposing fresh fluid available for oxidation. Mathematical predictions herein confirm experimental measurements that reveal an elevated, nearly constant surface temperature (∼2273 K) of the droplets during flight. The calculated oxide volume fraction of a “typical” droplet with internal circulation compares favorably to the experimentally determined oxide content (3.3–12.7%) for a typical TWEA-sprayed aluminum coating sprayed onto a room temperature substrate. It is concluded that internal circulation within the molten aluminum droplet is a significant source of oxidation. This effect produces an oxide content nearly two orders of magnitude larger than that of a droplet without continual oxidation.

Intelligent Techniques for Star-Pattern Recognition

This work presents the study of two different approaches for the attitude determination of space vehicles. The Neural Network approach is based on a simple Kohonen network, where the characteristics of a star distribution within the Field Of View (FOV) are matched against an on-board stored star map. The second approach utilizes a Genetic Algorithm (GA). The GA minimizes the discrepancy between the characteristics of the stars inside the FOV and a candidate FOV selected from the star map. Preliminary simulations indicate that both approaches work well and deliver good accuracy in determining the bore sight direction of the space vehicle with respect to the star map.Copyright

Numerical Investigation of Melting With Internal Heat Generation in a Vertical Cylindrical Geometry

There have been significant efforts by the heat transfer community to investigate the melting phenomenon of materials. These efforts have included the analytical development of equations to represent melting, the numerical development of computer codes to assist in the modeling, and the collection of experimental data. The understanding of the melting phenomenon has application in several areas of interest, for example, the melting of a phase change material used as a thermal storage medium as well as the melting of the fuel bundle in a nuclear power plant during an accident scenario. The objective of this paper is to present a numerical investigation, using computational fluid dynamics (CFD), of melting with internal heat generation for a vertical cylindrical geometry. As a precursor to the development of this numerical model, two classical configurations were also modeled. The first configuration consists of pure convection (no phase change) of a liquid with an external heat source and the second is melting with an externally applied heat source. For both of these two configurations, the numerical results were compared with experimental data from previous work.Copyright

Intelligent Star Pattern Recognition for Attitude Determination: the "Lost in Space" Problem

This paper presents a novel approach to the attitude determination problem of space vehicles. The proposed algorithm utilizes a modified Genetic Algorithm (GA) to solve the “lost in space” star pattern recognition problem associated with star tracker attitude determination systems. Characteristics of the stars that are visible within the Field of View (FOV) – reflected on an image taken by the onboard star tracker – are formulated using simple geometric descriptions. The proposed GA minimizes the discrepancy between the characteristics of the stars inside the actual FOV and a candidate FOV selected from the on board stored star map. The global minimum of the discrepancy represents the inertial coordinates of the FOV bore-sight. The concept of a Spiral Genetic Algorithms (SGA) is proposed where the search area decreases for consecutive GA, with consequently tighter constraints, making it converge to the desired location. Also the algorithm presented has the capability of determining the rotational angle between the spacecraft’s coordinate system and that of a real star map. Simulation results indicate competitive results to current star trackers in terms of accuracy.

Hybrid Optimization Algorithm Using Enhanced Continuous Tabu Search and Genetic Algorithm for Parameter Estimation

A new algorithm using Enhanced Continuous Tabu Search (ECTS) and genetic algorithm (GA) is proposed for parameter estimation problems. The proposed algorithm combines the respective strengths of ECTS and GA. The ECTS is a modified Tabu Search (TS), which has good search capabilities for large search spaces. In this work, the ECTS is used to define smaller search spaces, which are used in a second stage by a GA to find the respective local minima. The ECTS covers the global search space by using a TS concept called diversification and then selects the most promising regions in the search space. Once the promising areas in the search space are identified, the proposed algorithm employs another TS concept called intensification in order to search the promising area thoroughly. The proposed algorithm is tested with benchmark multimodal functions for which the global minimum is known. In addition, the novel algorithm is used for parameter estimation problems, where standard estimation algorithms encounter problems estimating the parameters in an un-biased fashion. The simulation results indicate the effectiveness of the proposed hybrid algorithm.Copyright

Optimization of a Star Pattern Recognition Algorithm for Attitude Determination Using a Multi-Objective Genetic Algorithm

Attitude determination for unmanned spacecrafts usually employs star trackers. The specifications for these devices dictate fast, reliable, robust, and autonomous algorithms to satisfy various mission constraints. This results into simple algorithms for reduced power consumption and reduced overall weight. Optimizing a Star Pattern Recognition Algorithm (SPRA), using an imbedded star map, requires the optimization of the genetic operators that constitute the SPRA and the control parameters within the SPRA. Simultaneous optimization of the control parameters of the SPRA results into a multi-objective and multi-parameter constrained optimization problem. The optimizing of genetic algorithms is often time consuming and rather tedious by nature. In this work, a Multi-Objective Genetic Algorithm (MOGA) acting as a meta-level GA is applied together with a double objective transition selection scheme to achieve the optimization. This approach results in significantly expediting the cost assignment process. By evolving a pareto set, an optimization population element rule is determined to exist between the control parameters of the SPRA. The existence of this rule ensures effective balance between population exploitation and exploration in the algorithm estimation process. This leads to effective solutions for finding the optimum with multiple concurrent objectives while taking the constraints into consideration. Simulation results using the optimized parameters for the SPRA indicate an improvement of the recognition accuracy from less than 60% to 100% as well as a reduction of the processing time of over 2000 generations to under 250 generations at 99% precision.Copyright

Scaling Analysis for the Use of Air in Place of Helium for a Heated Flow Experiment

The Modular High Temperature Gas-Cooled Reactor (MHTGR) has been chosen as a reference design for the Next Generation Nuclear Plant (NGNP) project. This reactor consists of concentric stacks of graphite blocks containing embedded fuel elements. Helium will be used as the coolant and will flow through designed coolant channels interspaced axially within the graphite blocks as well as in the gaps separating the blocks (called the bypass flow). A key phenomenon that may lead to localized hot spots in the reactor is the degradation of heat transfer effects in the bypass flow due to geometry distortions. Geometry distortions are the result of the graphite blocks being irradiated with energetic neutrons as well as coefficient of thermal expansion effects due to temperature changes. Idaho State University is studying heat transfer within the bypass flow and is developing an experiment to study the deterioration of heat transfer in the bypass flow stemming from these geometry distortions. Experimental data gathered from this project will be used to benchmark numerical codes used in the design and safety analysis of the MHTGR.Baseline MHTGR operating conditions are for a system pressure of approximately 7 MPa and a helium exit temperature from the reactor of approximately 850 °C. In place of using helium at these extreme conditions, it is our desire to perform the experiments with air entering the experiment at atmospheric pressure and temperature. Additionally, it is desirable to have an open-air system as opposed to a closed helium system. In order to quantify the impacts on temperature increase as well as pressure drop, a scaling analysis will be performed to compare the respective values from both helium and air. Important non-dimensional parameters, such as Reynolds number, non-dimensional heat flux, the acceleration factor, and non-dimensional buoyancy, will be matched for the various conditions in order to provide a similitude between the helium and air. These factors cannot be matched all at once, except by using actual conditions. The range of Reynolds number will be chosen to ensure an operating regime from the purely laminar to completely turbulent. This paper presents the results of this scaling analysis.Copyright

Saturated-Subcooled Stratified Flow in Horizontal Pipes

Advanced light water reactor systems are designed to use passive emergency core cooling systems with horizontal pipes that provide highly subcooled water from water storage tanks or passive heat exchangers to the reactor vessel core under accident conditions. Because passive systems are driven by density gradients, the horizontal pipes often do not flow full and thus have a free surface that is exposed to saturated steam and stratified flow is present.

Experiments to Investigate Flow Regime Transition for Steam and Subcooled Water From Stratified Flow to Slug Flow in Horizontal Pipe

Steam flowing over horizontally-stratified subcooled water in a circular-cross-section pipe may result in condensation-induced water hammer (CIWH). This subject has been studied by a number of researchers and representative data are given by Bjorge and Griffith 1986 who studied the conditions that lead to CIWH. Bjorge & Griffith give a good description of the phenomena including its precursors and characteristics.© 2008 ASME

Providing the Basis for Innovative Improvements in Advanced LWR Reactor Passive Safety Systems Design: An Educational R&D Project

This project characterizes typical two-phase stratified flow conditions in advanced water reactor horizontal pipe sections, following activation of passive cooling systems. It provides (1) a means to educate nuclear engineering students regarding the importance of two-phase stratified flow in passive cooling systems to the safety of advanced reactor systems and (2) describes the experimental apparatus and process to measure key parameters essential to consider when designing passive emergency core cooling flow paths that may encounter this flow regime. Based on data collected, the state of analysis capabilities can be determined regarding stratified flow in advanced reactor systems and the best paths forward can be identified to ensure that the nuclear industry can properly characterize two-phase stratified flow in passive emergency core cooling systems.