Air Force Institute of Technology Research Report 2007

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Computational and Physical Modelling of the Flow and Sediment Transport in a New Vortex-type Stormwater Retention Pond

Given the current water quality requirements for a stormwater retention pond, the civil and environmental engineering community requires accurate and efficient methods to explore the sediment removal of retention ponds. This research studied the use of Computational Fluid Dynamics (CFD) for modeling sediment retention ponds with comparison of the fluid flow results to in-house experimental data. This study provided insight on the pond design using single- and two-phase modeling approaches. This research highlighted the potential of using an Eulerian-Eulerian two-fluid model (TFM) approach, without the empirical ad hoc relations often used to determine the sediment concentration profile, for modeling flow and sediment in a new vortex-type pond design. This manuscript-based thesis documented four different studies. The first study summarized the fundamental concepts involved in the overall design of stormwater retention ponds. A comprehensive and in-depth description of different computational methods used in the literature for modeling stormwater retention ponds was given. Previous applications of CFD to modeling stormwater retention ponds was critically reviewed. The present position of multiphase modeling in the simulation of storage ponds was addressed, and possible directions for future development were outlined. The second study explored the potential of single-phase CFD modeling in a new vortex-type stormwater retention pond. The flow pattern in a 1:13.3 scale model of the vortex-type retention pond was characterized and some problematic recirculation zones were identified. The mean and fluctuating velocity fields in the pond were explored using computational and experimental methods. For the CFD modeling, the 3D Reynolds averaged Navier-Stokes (RANS) equations together with a k-ε turbulence model were solved using ANSYS Fluent 19.2. In general, the predictions and measurements were in good agreement. In the third study, an Eulerian-Eulerian TFM using constitutive equations based on granular kinetic theory, coupled with a low-Reynolds-number turbulence model, was used to predict the liquid and sediment transport in an equilibrium channel for fully-developed, steady, dilute flow. The particle-wall boundary condition was also investigated. The model predictions of the liquid and sediment velocity profiles, sediment concentration, turbulence statistics and fluctuating particle velocity field were documented against experimental data from the literature. In the last study, the TFM was implemented to assess pond performance and to provide insight on the sediment transport in the vortex-type stormwater retention pond for the case of steady, dilute flow with no sediment deposition. The model predictions of the liquid and sediment velocity profiles, and sediment concentration were documented. The study demonstrated the spatial distribution of sediment in the pond: the recirculation zones documented in the single-phase CFD study were characterized by relatively high concentrations of sediment. Overall, the current study demonstrated the application of single-phase CFD in detecting problematic regions such as low velocity zones and stagnation regions in a new pond design by providing a map of the flow patterns. This study also showed the application of two-phase CFD in the simulation of fluid and dilute sediment transport in the same pond as a step towards more comprehensive simulations, which in turn supports the goal of achieving higher water quality. No sediment deposition was included, which is the next step in applying the TFM formulation to retention pond studies

Littoral Cells, Longshore Transport and Wave Climate: An Examination of Littoral Transport Along the Western Shore of Prince Edward County, Ontario

This study discusses the wave climate and potential littoral transport along the western shore of Prince Edward County approximately two hours east of Toronto along the northern shoreline of Lake Ontario. The limestone headlands and barrier bars of the western coast are exposed toward a southwesterly fetch of approximately 200 km that can produce large offshore wave heights of 2–5 m. The wave model STWAVE was used to transform a standard set of wave conditions developed from recent hindcast data to examine fair weather, storm and extreme conditions for five directions between south and west-northwest along the shore. The resulting simulations indicate a complex nearshore wave environment and a pattern of alternating littoral transport directions resulting from shifting wave approach angles. A total of seven large littoral cells were defined in the study area with each cell having a smaller circulation pattern principally along the barrier systems. The data from this research project would benefit coastal managers in the region as the economy and climate experience change

Offshore oil spill detection using synthetic aperture radar

Among the different types of marine pollution, oil spill has been considered as a major threat to the sea ecosystems. The source of the oil pollution can be located on the mainland or directly at sea. The sources of oil pollution at sea are discharges coming from ships, offshore platforms or natural seepage from sea bed. Oil pollution from sea-based sources can be accidental or deliberate. Different sensors to detect and monitor oil spills could be onboard vessels, aircraft, or satellites. Vessels equipped with specialised radars, can detect oil at sea but they can cover a very limited area. One of the established ways to monitor sea-based oil pollution is the use of satellites equipped with Synthetic Aperture Radar (SAR).The aim of the work presented in this thesis is to identify optimum set of feature extracted parameters and implement methods at various stages for oil spill detection from Synthetic Aperture Radar (SAR) imagery. More than 200 images of ERS-2, ENVSAT and RADARSAT 2 SAR sensor have been used to assess proposed feature vector for oil spill detection methodology, which involves three stages: segmentation for dark spot detection, feature extraction and classification of feature vector. Unfortunately oil spill is not only the phenomenon that can create a dark spot in SAR imagery. There are several others meteorological and oceanographic and wind induced phenomena which may lead to a dark spot in SAR imagery. Therefore, these dark objects also appear similar to the dark spot due to oil spill and are called as look-alikes. These look-alikes thus cause difficulty in detecting oil spill spots as their primary characteristic similar to oil spill spots. To get over this difficulty, feature extraction becomes important; a stage which may involve selection of appropriate feature extraction parameters. The main objective of this dissertation is to identify the optimum feature vector in order to segregate oil spill and ‘look-alike’ spots. A total of 44 Feature extracted parameters have been studied. For segmentation, four methods; based on edge detection, adaptive theresholding, artificial neural network (ANN) segmentation and the other on contrast split segmentation have been implemented. Spot features are extracted from both the dark spots themselves and their surroundings. Classification stage was performed using two different classification techniques, first one is based on ANN and the other based on a two-stage processing that combines classification tree analysis and fuzzy logic. A modified feature vector, including both new and improved features, is suggested for better description of different types of dark spots. An ANN classifier using full spectrum of feature parameters has also been developed and evaluated. The implemented methodology appears promising in detecting dark spots and discriminating oil spills from look-alikes and processing time is well below any operational service requirements

Modelling and control strategies for hydrokinetic energy harnessing

The high prices and depletion of conventional energy resources and the environmental concern due to the high emission of CO2 gases have encouraged many researchers worldwide to explore a new field in renewable energy resources. The hydrokinetic energy harnessing in the river is one of the potential energies to ensure the continuity of clean, reliable, and sustainable energy for the future generation. The conventional hydropower required a special head, lots of coverage area, and some environmental issues. Conversely, the hydrokinetic system based on free stream flowing is one of the best options to provide the decentralised energy for rural and small-scale energy production. Lately, the effort of energy harnessing based on hydrokinetic technology is emerging significantly. Nevertheless, several challenges and issues need to be considered, such as turbine selection for energy conversion, generalised turbine model and control strategies for the grid and non-grid connection. To date, no detailed information on which turbines and turbine model are most suited to be implemented that match Malaysia’s river characteristics. Besides, a large oscillation has occurred on the output current and power during dynamic steady state due to the water variation and fluctuation in the river. Hence, reducing the energy extraction and controller efficiency for stand-alone and grid-connected systems, respectively. Therefore, the study aims to analyse the different turbine's design, proposed the turbine model, and propose the potential control strategies for stand-alone and grid-connected hydrokinetic energy harnessing in the river. In this work, three types of vertical axis turbines, including the H-Darrieus, Darrieus, and Gorlov with twelve different NACA and NREL hydrofoils, were analysed using the QBlade and MATLAB software, respectively. The effect of symmetrical and non-symmetrical geometry profiles, hydrofoils thicknesses, and turbine solidities have been compared to choose one of the best option turbines based on the highest power coefficient (CP) and a torque coefficient (CM), respectively. Subsequently, the turbine power model generalised equation has been proposed to represent the hydrokinetic turbine characteristic using a polynomial estimation equation. On the other hand, the MPPT control strategy is employed for the off-grid system using the sensorless method. The circuit topology based on an uncontrolled rectifier with the DC boost converter is implemented to regulate the rectifier output voltage through duty ratio. Subsequently, the metaheuristic method based on the combination of the Hill-Climbing Search (HCS) MPPT algorithm and the Fuzzy Logic Controller has been proposed to produce a variable step size compared to the fixed step size in conventional HCS algorithm. On the contrary, the dynamic model of the grid-connected hydrokinetic system has been linearised for small-signal stability analysis. The eigenvalues analysis-based approached has been applied to evaluate the system stability due to the small disturbance. The PI controller with the eigenvalues tracing method has been proposed to improve the system stability by reducing the oscillation frequency. The research outcomes indicated that the H-Darrieus with NACA 0018 was the best turbine for energy conversion in the river. Besides, the HCS-Fuzzy MPPT algorithm improved the energy extraction up to 88.30 % as well as reduced 74.47 % the oscillation compared to the SS-HCS MPPT. The stability of grid-connected hydrokinetic energy harnessing was improved up to 63.63 % by removing the oscillation frequency at states of λ8,9,10,11 as well as reducing 40.1 % oscillation of the generator stator current at the rotor side controller (RSC)

Metal fire implications for advanced reactors. Part 2, PIRT results.

This report documents the results of a Phenomena Identification and Ranking Table (PIRT) exercise performed at Sandia National Laboratories (SNL) as well as the experimental and modeling program that have been designed based on the PIRT results. A PIRT exercise is a structured and facilitated expert elicitation process. In this case, the expert panel was comprised of nine recognized fire science and aerosol experts. The objective of a PIRT exercise is to identify phenomena associated with the intended application and to then rank the current state of knowledge relative to each identified phenomenon. In this particular PIRT exercise the intended application was sodium fire modeling related to sodium-cooled advanced reactors. The panel was presented with two specific fire scenarios, each based on a hypothetical sodium leak in an Advanced Breeder Test Reactor (ABTR) design. For both scenarios the figure of merit was the ability to predict the thermal and aerosol insult to nearby equipment (i.e. heat exchangers and other electrical equipment). When identifying phenomena of interest, and in particular when ranking phenomena importance and the adequacy of existing modeling tools and data, the panel was asked to subjectively weigh these factors in the context of the specified figure of merit. Given each scenario, the panel identified all those related phenomena that are of potential interest to an assessment of the scenario using fire modeling tools to evaluate the figure of merit. Each phenomenon is then ranked relative to its importance in predicting the figure of merit. Each phenomenon is then further ranked for the existing state of knowledge with respect to the ability of existing modeling tools to predict that phenomena, the underlying base of data associated with the phenomena, and the potential for developing new data to support improvements to the existing modeling tools. For this PIRT two hypothetical sodium leak scenarios were evaluated for the ABTR design. The first scenario was a leak in the hot side of the intermediate heat transport system (IHTS) resulting in a sodium pool fire. The second scenario was a leak in the cold side of the IHTS resulting in a sodium spray fire

Aeronautical engineering: A continuing bibliography with indexes (supplement 272)

This bibliography lists 719 reports, articles, and other documents introduced into the NASA scientific and technical information system in November, 1991. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Modelling of River Flows, Sediment and Contaminants Transport

This book presents five articles that are also part of a Special Issue titled: Modelling of River flows, Sediment and Contaminants Transport published in the Water Journal under the section: Water Erosion and Sediment Transport. It covers a wide range of topics, such as predicting the impacts of wildfires on sediment transport and water quality in a mountainous region and estimating the sediment erosion due to release of ice-jams in cold region rivers