No / The effective maintenance scheduling of power system generators is very important for the economical and reliable operation of a power system. This represents a tough scheduling problem which continues to present a challenge for efficient optimization solution techniques. This paper presents the application of metaheuristic approaches, such as a genetic algorithm (GA), simulated annealing (SA) and their hybrid for generator maintenance scheduling (GMS) in power systems using an integer representation. This paper mainly focuses on the application of GA/SA and GA/SA/heuristic hybrid approaches. GA/SA hybrid uses the probabilistic acceptance criterion of SA within the GA framework. GA/SA/heuristic hybrid combines heuristic approaches within the GA/SA hybrid to seed the initial population. A case study is formulated in this paper as an integer programming problem using a reliability-based objective function and typical problem constraints. The implementation and performance of the metaheuristic approaches and their hybrid for the test case study are discussed. The results obtained are promising and show that the hybrid approaches are less sensitive to the variations of technique parameters and offer an effective alternative for solving the generator maintenance scheduling problem.

The present work was conducted with the intent of developing a high-fidelity numerical model of a unique combustion flow problem combining multi-phase fuel injection with substantial momentum and temperature into a highly complex turbulent flow. This important problem is very different from typical and more widely known liquid fuel combustion problems and is found in practice in pulverized coal combustors and ducted rocket ramjets. As the ducted rocket engine cycle is only now finding widespread use, it has received little research attention and was selected as a representative problem for this research. Prior to this work, a method was lacking domestically and internationally to effectively model the ducted rocket engine cycle with confidence. In the ducted rocket a solid fuel gas generator is used to deliver a fuel-rich multi-phase mixture to the combustion chamber. When a valve is used to vary the fuel generator pressure, and thereby the delivered fuel flowrate, the engine is known as a Variable Flow Ducted Rocket (VFDR). The Aerojet MARC-R282 ramjet engine represents the worlds first VFDR flown, and the first in operational use. Although performance requirements were met, improvements are sought in the understanding of the ramjet combustion process with a future aim of reducing the visible exhaust and correcting uneven combustor heating patterns. For this reason the MARC-R282 combustor was selected as the baseline geometry for the present research, serving to provide a documented baseline case for numerical modeling and also being a good candidate to benefit from an improved understanding of the combustion process. In order to proceed with the present research, experiments were first carried out to characterize the gas generator particulate exhaust in terms of composition and particle size. Equilibrium thermochemistry was used to supplement these data to develop a gas phase combustion model. The gas phase reactions and resulting particle definition were modeling using the FLUENT Computational Fluid Dynamics (CFD) code for the baseline GQM-163A Supersonic Sea Skimming Missile (SSST) operating conditions. These results were compared to direct-connect ramjet ground tests in order to validate the analysis tool. Data were developed to understand the gas and solid phase fuel exhaust characteristics at the propellant surface, exiting the gas generator injector, and following secondary combustion with air. Particles were collected and analyzed from the fuel generator exhaust. While exhibiting some variation with time in the firing, they were roughly an average of 20 microns in diameter, in line with prior experience with pulverized coal combustion experiments. A computational model was developed based on coal combustion parameters using FLUENT. However, despite considerable effort, the CFD analysis was not able to predict effective burning of the carbon particles to the degree seen in testing. In addition, using equilibrium thermochemistry as a basis for determining the carbon particle content in the fuel exhaust, the CFD analysis resulted in trends in performance opposite to the test results. These facts led to a hypothesis that there was actually a significant fraction of small particles or much less carbon produced than equilibrium thermochemistry would predict. A parametric analysis was performed replacing the 20 micron soot particles with fine fraction particles, representing a fraction of the predicted equilibrium carbon soot being still in the gas phase as higher molecular weight hydrocarbons, or in the form of sub-micron particles. When almost all particles were replaced with fine fraction particles, the model was able to correctly predict absolute values of combustion efficiency as well as trends for different injector geometries. The presence of particles was apparent from the visible exhaust and collection data, however they were found not to play a significant role in the combustion process for this fuel and engine configuration. The robustness of the computational model was also evaluated by examining the effects of turbulence model, order of discretization, and grid size. Comparable trends and results were seen for all cases examined. With the successful development of this modeling tool and an improved understanding of the combustion process, future work is enabled to develop improved combustor flow management and fuel injection schemes to improve existing designs and develop new configurations. This research has served to advance the field of combustion modeling by providing: 1) a solid ducted rocket combustion modeling tool considering solid and gas phase combustion, 2) a correlation between primary combustion theory and particulate exhaust sampling, 3) low length/diameter ratio ducted rocket combustor modeling, and 4) combustor CFD coupled with solid particle tracking and combustion models. / Ph. D.

The next generation of wireless communications will demand the use of software radio technology as the basic architecture to support multi-standard, multi-mode and future-proof radio designs. Software-defined radios are configurable devices in which the physical layer can be reprogrammed to support various standards. Field programmable architectures provide a suitable platform to achieve such run-time reconfigurations of the physical layer of the radio. This thesis explores the use of FPGAs in the design of reconfigurable radios. The results presented here demonstrate how FPGAs can be used to provide the flexibility, performance, efficiency and better resource utilization while meeting the speed and area constraints set by a particular design. The partial reconfiguration feature available in the state-of-the art FPGAs has been exploited to implement the baseband physical layer of reconfigurable radio which can be altered to support various modulations schemes for different wireless standards. The design flow for partial reconfiguration along with the implementation results on two different FPGA platforms is presented. The experiments presented in this thesis make use of System Generator for DSP, a productivity tool from Xilinx, to design and to simulate system-level models in a MATLAB/Simulink environment, and to obtain timing and resource utilization results before implementing the design on actual hardware. / Master of Science

The design of digital systems is getting more complex with rapid improvements in VLSI design which can accommodate many millions of gates in one integrated chip (IC). Additionally, the speed with which the design is completed is also becoming significant due to the demands of the market for the ICs. Tools to automate the initial design process can make the designer's task simpler and more accurate. The ASPIN system being built at Virginia Polytechnic Institute and State University focuses on deriving a synthesizable model for a digital system from various kinds of informal specifications( e.g. natural language descriptions, flowcharts, block diagrams, timing diagrams). This thesis describes an interactive tool for validating and correcting formal models acquired from natural language specifications of digital system. Validation is important since the formal models have to be devoid of any ambiguities which might be present in the natural language specifications. The information acquired from the specifications is stored in an intermediate graphical notation called conceptual graphs. A preliminary tool called the Model Generator can produce a graphical display from conceptual graphs which helps the user visualize the model contained in the conceptual graph. The Back Annotator which is described in this thesis lets the user correct any misinterpretations by making changes to the graphical display such as additions, deletions, modifications, and movement / Master of Science

This is an investigation into the possibilities of using repeated members to generate complex geometry, specifically using alternating beams of uniform dimension to create both structure and building envelope. These beams are placed according to a single, custom-built "generator" element and then clad using as few custom shapes as possible. In many cases, the generator element is the ridge beam of the roof - but it is not always part of the permanent construction. / Master of Architecture

In this work, a thermoelectric energy harvester system aimed at harvesting energy for locally powering sensor nodes in nuclear power plant coolant loops has been designed, fabricated and tested. Different mathematical modeling methods have been validated by comparing with experimental results. The model developed by this work has the best accuracy in low temperature range and can be adapted and used with any heat sink, heat pipe, or thermoelectric system, and have proven to provide results closely matching experimental data. Using the models, an optimization of the thermoelectric energy harvesting system has been performed which is applicable to any energy harvester of this variety. With experimental validation, the system is capable of generating sufficient energy to power all the sensors and electronical circuits designed for this application. The effect of gamma radiation on this thermoelectric harvester has also been proved to be small enough through radiation experiment. / Master of Science

Energy harvesting is a technology for generating electrical power from ambient or wasted energy. It has been investigated extensively as a means of powering small electronic devices. The recent proliferation of devices with ultra-low power consumption - devices such as RF transmitters, sensors, and integrated chipsets - has created new opportunities for energy harvesters. There is a variety of ambient energies such as vibration, thermal, solar, stray current, etc. Depending on energy sources, different kinds of energy conversion mechanism should be employed. For energy harvesters to become practical, their energy conversion efficiency must improve. This efficiency depends upon advances in two areas: the system or structural design of the energy harvester, and the properties of the materials employed in energy conversion. This dissertation explores developments in both areas. In the first area, the role of nano-, micro-, and bulk structure of the energy conversion materials were investigated. In the second area, piezoelectric energy harvesters and a magneto-thermoelectric generator are treated from the perspective of system design. In the area of materials development, PbTiO3 (PTO) nanostructures consisting of nanofibers and three-dimensional (3-D) nanostructure arrays were hydrothermally synthesized. The growth mechanism of the PTO nanofibers and 3-D nanostructures were investigated experimentally and theoretically. The PTO nanostructures were composed of oriented PTO crystals with high tetragonality; these arrays could be promising candidates for nanogenerators. Different designs for energy harvesters were explored as a means of improving energy conversion efficiency. Piezoelectric energy harvesters were designed and constructed for applications with a low frequency vibrational energy and for applications with a broadband energy spectrum. A spiral MEMS piezoelectric energy harvester design was fabricated using a silicon MEMS process and demonstrated to extract high power density at ultra-low resonance frequencies and low acceleration conditions. For a broadband energy harvester, a magnetically-coupled array of oscillators was designed and built that broadened the harvester's effective resonance frequency with considerably improved output power. A new design concept for thermal energy harvesting that employs a magneto-thermoelectric generator (MTG) design was proposed. The MTG exploits a thermally-induced second order phase transition in a soft magnetic material near the Curie temperature. The MTG harvested electric power from oscillations of the soft magnet between hot and cold sources. For the MTG design, suitable soft magnetic materials were selected and developed using La0.85Sr0.15MnO3-Ni0.6Cu0.2Zn0.2Fe2O4 magnetic composites. The MTG was fabricated from a PVDF cantilever and a gadolinium (Gd) soft magnetic material. The feasibility of the design for harvesting energy from the waste heat was demonstrated by attaching an MTG array to a computer CPU. / PHD / Energy harvesting is a technology for generating electrical power from ambient or wasted energy. It has been investigated extensively as a means of powering small electronic devices. The recent proliferation of devices with ultra-low power consumption – devices such as RF transmitters, sensors, and integrated chipsets – has created new opportunities for energy harvesters. There is a variety of ambient energies such as vibration, thermal, solar, stray current, etc. Depending on energy sources, different kinds of energy conversion mechanism should be employed. For energy harvesters to become practical, their energy conversion efficiency must improve. This efficiency depends upon advances in two areas: the system or structural design of the energy harvester and the properties of the materials employed in energy conversion. This dissertation explores developments in both areas. In the first area, the role of nano-, micro-, and bulk structure of the energy conversion materials were investigated. In the second area, vibration energy harvesters using piezoelectric materials (mechanical to electrical energy conversion) and thermoelectric generator employing magnetic phase transition are treated from the perspective of system design.

As the broad implementation and use of wireless sensor nodes in Internet of Things (IOT) devices increase over the years, securing personal data becomes a growing issue. Physical unclonable functions (PUFs) and random number generators (RNGs) provide methods to generate security keys for data encryption. Transducers used in the energy harvesting systems of wireless sensor nodes, can generate the PUFs and RNGs. These transducers include piezoelectric devices (piezo), thermoelectric generators (TEG) and solar cells. This research studies the electrical properties of transducers at normal and low operating levels for electrical responses that can be used in PUF generation and random number generation respectively. The PUF generation discussed in this study analyzes the resonance frequency of 10 piezos, and the open-circuit voltages of 5 TEGs and 5 solar cells. The transducers are tested multiple times over a 10-day period to evaluate PUF reproducibility and reliability characteristics. The random number generation is accomplished by applying a low-level vibration, thermal or light excitation to each respective transducer. The generated electrical signals are amplified and digitally processed and analyzed using the National Institute of Standards and Technology (NIST) Statistical Test Suite. The experiment results for the PUF generation are promising and indicate that the piezos are the better choice due to their stable frequency output. Each transducer was able to produce random numbers and pass the NIST tests, but the TEGs passed the NIST tests more often than the other transducers. These results offer a preliminary basis for transducers to be used directly in security applications. / Master of Science / As the broad implementation and use of wireless sensor nodes in Internet of Things (IOT) devices increase over the years, securing personal data becomes a growing issue. Physical unclonable functions (PUFs) and random number generators (RNGs) provide methods for securing data. Transducers used in the energy harvesting systems of wireless sensor nodes, can be used to generate the PUFs and RNGs. These transducers convert vibrations, light and heat into electricity. This research studies the electrical properties of transducers at normal and low operating levels for responses that can be used in PUF generation and random number generation respectively. The PUF generation discussed in this study analyzes the different electrical properties of each transducer. The transducers are tested multiple times over a 10-day period to gather an adequate amount of data. Producing the same output every single time is imperative for PUFs. The random number generation is accomplished by applying a low input vibration, heat or light to each respective transducer. The generated electrical signals are amplified and digitally processed to be analyzed using software. The experiment results for the PUF generation are promising and indicate that the transducers that convert vibrations to electrical energy are the better choice due to their consistent output. Each transducer was able to produce random numbers and pass the required tests. These results offer a preliminary basis for transducers to be used directly in security applications.

Considerable attention has been paid to the design of low-power, high-performance SRAMs (Static Random Access Memories) since they are a critical component in both hand-held devices and high-performance processors. A key in improving the performance of the system is to use an optimum sized SRAM. In this thesis, an SRAM compiler has been developed for the automatic layout of memory elements in the ASIC environment. The compiler generates an SRAM layout based on a given SRAM size, input by the user, with the option of choosing between fast vs. low-power SRAM. Array partitioning is used to partition the SRAM into blocks in order to reduce the total power consumption. Experimental results show that the low-power SRAM is capable of functioning at a minimum operating voltage of 2.1 V and dissipates 17.4 mW of average power at 20 MHz. In this report, we discuss the implementation of the SRAM compiler from the basic component to the top-level SKILL code functions, as well as simulation results and discussion. / Master of Science

Yes / This paper proposes a formal methodology to analyse bio-systems, in particular synthetic biology systems. An integrative analysis perspective combining different model checking approaches based on different property categories is provided. The methodology is applied to the synthetic pulse generator system and several verification experiments are carried out to demonstrate the use of our approach to formally analyse various aspects of synthetic biology systems. / EPSRC