The noise emitted from tactical supersonic aircraft presents a dangerous risk of noise-induced hearing loss for personnel who work near these jets. Although jet noise has many interacting features, large-scale turbulent structures are believed to dominate the noise produced by heated supersonic jets. To characterize the unsteady behavior of these large-scale turbulent structures, which can be correlated over several jet diameters, a velocimetry technique resolving a large region of the flow spatially and temporally is desired. This work details the development of time-resolved Doppler global velocimetry (TRDGV) for the study of large-scale turbulence in high-speed flows. The technique has been used to demonstrate three-component velocity measurements acquired at 250 kHz, and an analysis is presented to explore the implications of scaling the technique for studying large-scale turbulent behavior. The work suggests that the observation of low-wavenumber structures will not be affected by the large-scale measurement. Finally, a spatiotemporally-resolved measurement of a heated supersonic jet is achieved using large-scale TRDGV. By measuring a region spanning several jet diameters, the lifetime of turbulent features can be observed. The work presented in this dissertation suggests that TRDGV can be an invaluable tool for the discussion of turbulence with respect to aeroacoustics, providing a path for linking the flow to far-field noise. / Doctor of Philosophy / During takeoff, the intense noise emitted from tactical supersonic aircraft exposes personnel to dangerous risks of noise-induced hearing loss. In order to develop noise-reduction techniques which can be applied to these aircraft, a better understanding of the links between the jet flow and sound is needed. Laser-based diagnostics present an opportunity for studying the flow-field through time and space; however, achieving both temporal and spatial resolution is a technically challenging task. The research presented herein seeks to develop a diagnostic technique which is optimized for the study of turbulent structures which dominate jet noise production. The technique, Doppler global velocimetry (DGV), uses the Doppler shift principle to measure the velocity of the flow. First, the ability of DGV to measure the three orthogonal components of velocity is demonstrated, acquiring data at 250 kHz. Since turbulent structures in heated jets can be correlated over long distances, the effects on measurement error due to a large field-of-view measurement are investigated. The work suggests that DGV can be an invaluable tool for the discussion of turbulence and aeroacoustics, particularly for the consideration of full-scale measurements. Finally, a large-scale velocity measurement resolved in time and space is demonstrated on a heated supersonic jet and used to make observations about the turbulence structure of the flow field.

An improved algorithm for the automatic generation of test vectors from chip-level descriptions written in VHDL is described. The method offers an order of magnitude speed improvement over earlier test generation algorithms. The algorithm accepts data flow circuit descriptions written in a subset of VHDL. A fault model which defines faults for the VHDL statements is applied to determine fault cases. Test generation requirements of fault sensitization, value justification, and fault effect propagation are expressed in terms of justification, propagation, and execution goals, rather than in terms of low-level operations. Prolog rules define the way in which the goals are satisfied, using backtracking to select alternative solutions. A method for handling time in absolute, rather than relative, terms is discussed. Comparison of run times for the improved algorithm against those obtained by the previous method is made to demonstrate the speedup. Suggestions for incorporating the algorithm into a test generation system are discussed. A user’s guide is given for the current implementation of the method. / Master of Science

VLSI technology is continually fueling the need for more efficient computer aided design tools. Parallel or distributed processing is a possible solution to this problem. Advances in computer networking have made distributed processing over a local area network very attractive and cost-effective. This research investigates the application of such a large-grained parallel processing method to the task of checking geometric constraints or design rules that are imposed on the layout of VLSI circuits to ensure a correct implementation of the design despite imperfections in the fabrication process. The thesis begins with a study of design rule checking algorithms including algorithms for parallel processing as applied to design rule checking. Then, the algorithms for a technology independent design rule verification tool are developed. For distributed processing, two separate approaches are examined. One approach, called the data partitioning method, divides a fully instantiated or non-hierarchical layout into several sections and then processes each section on a different computer. The second approach looks for smaller tasks within the design rule checking process that can be executed in parallel and is called the task partitioning method. A dynamic task-scheduling algorithm is used to assign the tasks to the available processors. Implementations of both of these parallel processing schemes on a local area network of workstations are described. Experiments are performed to assess the performance of the programs and the results of testing a few layouts are presented. / Master of Science

This thesis project is complex because of its crystalline form. It is ordered through structural hierarchy and modularity. The presence of both complexity and order gives articulation to all scales of the project, allows for variety without chaos, and repetition without monotony. All of these characteristics are essential for the program of a high-rise residential building that accommodates 1,500 people. / Master of Architecture

An efficient test generation algorithm for behavioral descriptions is discussed. It generates tests for behavioral dataflow descriptions of digital circuits written in VHDL. The algorithm accepts input descriptions containing multiple process statements and concurrent signal assignment statements. The fault model based on previous research includes micro-operation and control faults. The test generation algorithm uses artificial intelligence techniques of goal trees and rule databases and it can make use of human understanding of the device model to generate more efficient tests. An improved timing model helps detect conflicts more quickly and improves the speed performance of the algorithm. The test generation algorithm has been used to generate tests for complex circuits. Results of fault coverage experiments for some of these circuits is presented. / Master of Science

As the dimension and the complexity of large interconnected systems grow, so does the necessity for decentralized control. One of the interesting challenges in the field of decentralized control is the arbitrary pole placement using output feedback. The feasibility of this problem depends solely on the identification of the decentralized fixed modes. As a matter of fact, if the system is free of fixed modes, then by increasing the controller’s order, any arbitrary closed loop poles can always be assigned. Due to this fact, reducing the controller’s order constitutes another interesting challenge when dealing with decentralization. This research describes the decentralized pole placement of linear systems. It is assumed that the internal structure of the system is unknown. The only access to the system is from a number of control stations. The decentralized controller consists of output feedback controllers each built at a control station. The research can be divided into two parts. In the first part, conditions for fixed modes existence as well as realization and stability of the overall system under decentralization are established using polynomial matrix algebra. The second part deals with the solution of decentralized pole placement problem, in particular, finding a decentralized controller which assigns some set of desired poles. The solution strategy is to reduce the controller’s order as much as possible using mathematical programming techniques. The idea behind this method is to start with a low order controller and then attempt to shift the poles of the closed loop system to the desired poles. / Ph. D. / incomplete_metadata

Intelligent Transportation Systems (ITSs) are key components of the transportation systems within future smart cities, in which information and communication technologies interact to enhance the transportation system. By collecting and analyzing real-time data, and applying advanced data analytics techniques, ITS can make better-informed decisions, that are sent back to the network actuators (cars, drivers, traffic signals, travelers,... etc.) to solve or at least mitigate the ongoing transportation problems. In such feedback systems, the communication network is a major component that interacts with the transportation applications. Consequently, it is imperative to study the mutual interactions and effects between the communication and the transportation networks. The key enabler for such studies is the large-scale modeling of communication and transportation systems. However, developing such models is challenging, not only because of the intricate interdependency between the communication and transportation systems but also because of the scale of such systems that usually covers a city-level network with hundreds of thousands of travelers concurrently moving and communicating in the network. Consequently, in our research, we are interested in studying the mutual impact of the communication and transportation systems in large-scale networks while focusing on eco-routing navigation applications that attempt to minimize the transportation network carbon footprint. Our objectives are: 1) enabling the large-scale modeling of transportation systems in smart cities including both transportation and communication systems and 2) studying the mutual interactions between the communication and the transportation systems in real-world networks. Under this umbrella, we introduced two simulation frameworks to realistically model the communication in vehicular systems. Subsequently, we use them to study the mutual influence of the communication and transportation system. Moreover, we designed, developed, and tested a multi-modal agent-based simulation platform which can simulate large-scale transportation systems. The results show that, in congested road networks, the communication performance has a significant impact on the transportation system performance. Moreover, the results show that there is a negative mutual impact loop that may lead to a degrading performance of both systems. Thus, it is important to consider this impact when deploying new ITS technologies that utilize vehicular wireless communication. / PHD / In future smart cities, communication network is a major component that interacts with the transportation applications. Consequently, it is imperative to study the mutual interactions and effects between the communication and the transportation networks. Studying these systems is challenging, not only because of the intricate interdependency between the communication and transportation but also because of the scale of these systems that usually covers a city-level network with hundreds of thousands of travelers concurrently moving and communicating in the network. Therefore, in this dissertation, our main objectives are: 1) to enable the large-scale modeling of transportation systems in smart cities including both transportation and communication systems and 2) to study the mutual interactions between the communication and the transportation systems in real-world networks. Under this umbrella, we introduced two simulation frameworks to realistically model the communication in vehicular systems. Subsequently, we used them to study the mutual influence of the communication and transportation system. Moreover, we designed, developed, and tested a multi-modal agent-based simulation platform which can simulate large-scale transportation systems. The results show that, in congested road networks, the communication performance has a significant impact on the transportation system performance. Moreover, they show that there is a negative mutual impact loop that may lead to a degrading performance of both systems. Thus, it is important to consider this impact when deploying new ITS technologies that utilize vehicular wireless communication.

Interest in BiCMOS technology has been generated recently due to the potential advantages this technology offers over conventional CMOS which enjoys widespread use in today’s semiconductor industry. However, before BiCMOS can be readily adopted by the VLSI community, an understanding of the design issues and tradeoffs involved when utilizing it, must be achieved. The principal focus of this research is to move towards such an understanding through the means of analytical modeling and circuit simulation using PSPICE [1]. The device chosen for the modeling approach is the basic BiCMOS Inverting Buffer Driver. The model yields equations that characterize output rise and fall transients and quantify the delays incurred therein. At the end of the analysis, we have a composite set of delay equations that are a measure of the total gate delay and reflect the importance of individual device and circuit parameters in determining this delay. Further investigations conducted to determine the influence of device, circuit and process parameters on BiCMOS, indicate that this technology is far more resilient to variations in such parameters than CMOS. At the end of this research, we are able to make a definitive judgement about BiCMOS performance and its superiority over CMOS in the switching speed domain. / Master of Science

A number of errors occur in digital systems operating in a harsh radiation environment. These errors are due to transient faults which may cause a temporary change in the state of the system without any permanent damage. These transient faults are referred to as Single Event Upsets (SEUs). Because of their random and non-recurring nature, such faults are very difficult to detect and hence are of source of great concern. This thesis examines the logical response of combinational logic circuits to SEUs. Time domain analyses of a large number of circuits attempts to determine the affect of an SEU on a flip-flop which might lay at the end of a chain of combinational logic gates. In this way, the concept of an upset window, as it pertains to different types of logic gates is introduced. The results of the simulations carried out on various blocks of combinational logic are discussed. A program called SUPER (SUsceptibility PrEdiction pRogram) is developed. SUPER predicts the probability of a circuit fault occurring given that a cosmic ray with certain energy characteristics impinges on an arbitrary point within an IC. IC. The input variables to SUPER include the radiation level, the duration of the radiation, the types of gates the radiation affects, the signal path, the type of voltage pulse that the radiation produces (rising or falling) and the time (with respect to the clock pulse) that the radiation is incident on the circuit. The output of SUPER consists of a prediction as to whether or not the incident radiation causes a change in the output of a flip-flop. / Master of Science

Managing large-scale dynamical systems (e.g., transportation systems, complex information systems, and power networks, etc.) in real-time is very challenging considering their complicated system dynamics, intricate network interactions, large scale, and especially the existence of various uncertainties. To address this issue, intelligent techniques which can quickly design decision-making strategies that are robust to uncertainties are needed. This dissertation aims to conquer these challenges by exploring a data-driven decision-making framework, which leverages big-data techniques and scalable uncertainty evaluation approaches to quickly solve optimal control problems. In particular, following techniques have been developed along this direction: 1) system modeling approaches to simplify the system analysis and design procedures for multiple applications; 2) effective simulation and analytical based approaches to efficiently evaluate system performance and design control strategies under uncertainty; and 3) big-data techniques that allow some computations of control strategies to be completed offline. These techniques and tools for analysis, design and control contribute to a wide range of applications including air traffic flow management, complex information systems, and airborne networks.