Master of Science (M.S.), University of Dayton, 2024, Mechanical Engineering

This work discusses the experimental testing of a nominal six-inch diameter single airstream rotating detonation engine that utilizes a hollow core to split the airstream into two separate flow paths and causes the test article to self-balance. Hydrogen and air were selected as the fuel/oxidizer combination for this test. The hollow core is designed to mimic a venturi nozzle, enabling the collection of pressure and temperature at the throat of nozzle to determine the mass flow rate through each flow path. Two Laval nozzles with varying contraction ratios, 7.5 and 11, and three fuel rings of varying injection are experimentally examined and their impact on the operability of the self-balancing RDE is investigated. This work highlights the calculation and determination of the mass flow split between the flow paths during cold flow and hot flow conditions, the operating map across six experimental configurations, and the impact of fuel injection penetration and momentum flux on the operability of the test article.

Committee: Matthew Fotia (Advisor); Taber Wanstall (Committee Member); Carson Running (Committee Member) Subjects: Mechanical Engineering

Master of Science (M.S.), University of Dayton, 2020, Aerospace Engineering

Velocity measurement inside of a wind tunnel is an extremely useful quantitative data for a multitude of reasons. One major reason is that velocity has a mathematical relationship with dynamic pressure which in turn influences all the aerodynamic forces on the test model. Many devices and methods exist for measuring velocity inside wind tunnels. At the same time, Doppler wind lidar (light detection and ranging) has been used for decades to make air speed measurements outdoors at long ranges. Lidar has been proven effective for many applications, and it has the potential to solve many of the problems faced by current velocimetry techniques inside wind tunnels. Despite this, minimal research has been performed with Doppler wind lidars inside wind tunnels. While multiple commercial systems exist for making air speed measurements at longer ranges, there are currently no widely available commercial devices designed to work well inside wind tunnels. In this research, initial work is described for the design and development of a continuous wave (CW), coherent wind lidar system. The system is for use as an alternative non-intrusive velocimetry method inside wind tunnels relying on the Doppler effect. A scaled down wind lidar designed to operate at much shorter ranges than current commercial wind lidars can be simpler, less expensive, and require less power. A first iteration of the design was constructed for proof of concept testing with a small-scale wind tunnel at low speeds (7.5-9 m/s). Testing showed that the lidar system could take one-dimensional speed measurements of seeded flow that closely matched Pitot static tube data. When not adding tracer particles to the flow, the lidar return signal was not strong enough for the photodetector used to measure the beat frequency. This research is focused on the process for designing the Doppler wind lidar system, constructing the experimental setup, and studying methods for data analysis. Results of testing presente (open full item for complete abstract)

Committee: Sidaard Gunasekaran (Advisor); Aaron Altman (Committee Member); Paul McManamon (Committee Member) Subjects: Aerospace Engineering; Atmosphere; Atmospheric Sciences; Engineering; Optics; Technology

Master of Science in Engineering, University of Akron, 2018, Electrical Engineering

This thesis discusses a detailed study of the design and performance analysis of patch antenna arrays at different frequencies. A linear hybrid array of 16 elements is built using patch antennas integrated with an RF front-end using commercial off-the-shelf (COTS) components. A well organized receiver chain that can work at a frequency in the range of 5 - 6 GHz is built using chip level components on a printed circuit board (PCB). This study mainly emphasizes the design and implementation of the comprehensive receiver beamforming systems using fast Fourier transform (FFT) algorithm and approximate - discrete Fourier transform (a-DFT). A low complexity 32-beam multi-beamformer at 5.8 GHz is designed, built and implemented in real time using optimized digital FPGA cores as the digital back-end which is collaborated work with Viduneth Ariyarathna. The emanating beams were measured and verified using the FPGA - based 32-element 5.8 GHz array setup which can generate 120 MHz bandwidth per channel. The beams corresponding to the approximate DFT are in good agreement with the beams corresponding to the FFT with negligible error approximately less than -14 dB. This setup can be used as a test bed to measure and evaluate various signal processing algorithms up to 32 linear array elements.

Committee: Arjuna Madanayake Dr (Advisor); Nghi Tran Dr (Committee Member); Ryan Christopher Toonen Dr (Committee Member) Subjects: Computer Engineering; Electrical Engineering

MA, Kent State University, 2018, College of Arts and Sciences / Department of Sociology and Criminology

Sociologists have been unable to determine whether online communication supports the development of communities, or perhaps ironically, encourages increased isolation. The important question arises: can solidarity be established and maintained electronically (i.e., online). To address this question, I conducted an experiment that utilizes Fast Fourier Transform (FFT) methods to determine whether individuals can experience interpersonal synchronization and solidarity while interacting through different mediums. Results from this study show that face-to-face interaction produces greater feelings of solidarity than audio-only and audio/video forms of mediated communication, that audio/video produces less solidarity than audio-only interaction, and that the impact of communication medium on solidarity grows stronger over time. Further research is needed to fully understand the problems of solidarity in modern society, including the examination of other solidarity-producing forms of distance media.

Committee: Will Kalkhoff (Advisor) Subjects: Sociology

Doctor of Philosophy, Case Western Reserve University, 2017, Applied Mathematics

Image segmentation and registration play active roles in machine vision and medical image analysis of historical data. Individually, the two has seen important research contributions, and the joint treatment of the two problems has become an active area of research. In this thesis we will explore the joint problem of segmenting and registering a template image given a reference image. We formulate the joint problem through an energy functional that integrates two well studied approaches in segmentation and registration: Geodesic Active Contours and nonlinear elastic registration. In the registration regime, the domain is modeled as a St. Venant-Kirchhoff material. We minimize the potential energy of this elastic system using variational methods, and derive an evolution equation which we solve using implicit-explicit integration methods. The numerical discretization of the problem allows us to take advantage of the Fast Fourier Transform. In the segmentation regime, we will adopt an active contours based energy with a weighted total variation penalty on the segmenting front. This particular choice allows for fast solution using the dual formulation of the total variation. The weight of the total variation penalty is an edge stopping function which depends on the deforming template. This allows the segmenting front to accurately track spontaneous changes in the shape of objects embedded in the template image as it deforms.

Committee: Weihong Guo (Committee Chair); Daniela Calvetti (Committee Member); Julia Dobrotsoskya (Committee Member); Erkki Somersalo (Committee Member); Michael Lewicki (Committee Member) Subjects: Applied Mathematics; Biomedical Engineering

Master of Science (MS), Wright State University, 2015, Computer Science

Convolutional neural networks (CNNs) are currently state-of-the-art for various classification tasks, but are computationally expensive. Propagating through the convolutional layers is very slow, as each kernel in each layer must sequentially calculate many inner products for a single forward and backward propagation which equates to O(N^2 n^2) per kernel per layer where the inputs are N x N arrays and the kernels are n x n arrays. Convolution can be efficiently performed as a Hadamard product in the frequency domain. The bottleneck is the transformation which has a cost of O(N^2 log_2 N) using the fast Fourier transform (FFT). However, the increase in efficiency is less significant when N >> n as is the case in CNNs. We mitigate this by using the ``overlap-and-add'' technique reducing the computational complexity to O(N^2 log_2 n) per kernel. This method increases the algorithm's efficiency in both the forward and backward propagation, significantly reducing the training and testing time for CNNs. Our empirical results show our method reduces computational time by a factor of up to 50.4 times the traditional convolution implementation.

Committee: Mateen Rizki Ph.D. (Advisor); John Gallagher Ph.D. (Committee Member); Michael Raymer Ph.D. (Committee Member); Andres Rodriguez Ph.D. (Committee Member) Subjects: Computer Science; Electrical Engineering

MS, University of Cincinnati, 2014, Engineering and Applied Science: Mechanical Engineering

The current set up is an improvement of a previous set up designed and fabricated to study pulsating flow through blockages[1]. The ultimate objective of such an experiment is to non-invasively be able to detect blockages in a pipe line with such theory and results then extended to detecting blockages in arteries. This facility additionally has the capability of pulsing both upstream as well as downstream of the flow, that is, in the direction as well as the opposite to the direction of the flow to be able to study the effect of pulsing flow better and reach the ultimate goal of a near perfect facility in the future with improvements. The facility has been designed such that pressure measurements can be made at different axial locations along the pipeline. Parameters such as pressure head, frequency of pulsation blockage size and location of pulsation are varied to study the various cases. In addition to this, the duty cycle of the pulse can be changed depending on the systole and diastole ratios. Different wheels have been designed to change the pattern of pulsing for a set specific frequency. The results are looked at in the light of these parameter changes. The fast fourier transforms and pressure time traces are studied. The FFTs show typical fundamental tones at the pulsing frequencies with subsequent harmonics and a gradual roll off after about 20-30Hz. The pressure time traces give us a picture of the pressure cycle during the systole and diastole periods and the fluctuation during those periods. From these basic plots the fundamental pressures are obtained and pressure drops and percentage pressure drops across various blockages and for various pressure heads. As a general observation, the pressure drops are higher with higher pressure heads and greater extent of blockage. With a higher frequency of pulsation the percentage pressure drop reduces and with a more accurate systole diastole ratio the percentage drop is even lower. Upstream pulsing shows (open full item for complete abstract)

Committee: Ephraim Gutmark Ph.D. D.Sc. (Committee Chair); Urmila Ghia Ph.D. (Committee Member); Milind Jog Ph.D. (Committee Member); Jeffrey Kastner Ph.D. (Committee Member) Subjects: Engineering

Master of Science (M.S.), University of Dayton, 2014, Electrical Engineering

An analytic examination of 3-D holography under a recording geometry was carried out earlier in which 2-D spatial Laplace transforms were introduced in order to develop transfer functions for the scattered outputs under readout [1]. Thereby, the resulting reconstructed output was obtained in the 2-D Laplace domain whence the spatial information would be found only by performing a 2-D Laplace inversion. Laplace inversion in 2-D was attempted by testing a prototype function for which the analytic result was known using two known inversion algorithms via the Brancik and the Abate [2]. The results indicated notable differences in the 3-D plots between the algorithms and the analytic result, and hence were somewhat inconclusive. In this research, we take a close look at the Brancik algorithm in order to understand better the implications of the choices of key parameters such as the real and imaginary parts of the Bromwich contour and the grids sizes of the summation operations [3]. To assess the inversion findings, three prototype test cases are considered for which the analytic solutions are known. For specific choices of the algorithm parameters, optimal values are determined that would minimize errors in general. It is found that even though errors accumulate near the edges of the grid, overall reasonably accurate inversions are possible to obtain with optimal parameter choices that are verifiable via cross-sectional views. For a holographic problem, a 90-deg geometry recording model is established to derive two important coupled equations [4]. The optimum parameters are used to find the output field profiles under readout for a uniform plane wave, a point source wave and a Gaussian profile input. To understand the results better, a convolutional approach and a holistic approach are compared. Further work may include recording and reconstructing a dynamic object wave whose wave representations are more complicated. Also, the observed “right shift” phenomeno (open full item for complete abstract)

Committee: Monish Chatterjee (Advisor) Subjects: Optics

Doctor of Philosophy (PhD), Wright State University, 2009, Engineering PhD

The fast Fourier transform (FFT) plays a critical role in many modern applications, such as acoustics, optics, telecommunications, wireless sensor networks, location sensing, patient monitoring, speech, signal detection, and image processing. The input dynamic range, data throughput rate, frequency resolution, bandwidth, design flexibility, hardware consumption, and power requirements for the various applications are vastly different, leading to significant research focusing on different aspects of FFT performance improvement.The proposed dynamic kernel function uses an efficient fixed-point numerical representation of the twiddle factor and replaces the cumbersome multipliers with simple shift-and-add operations to enhance the data throughput rate for high-speed wideband signal detection. Numerical representation in hardware plays a role in determining the dynamic range and bit precision of FFT processors. Variable truncation scheme dynamically scales the computation data and maximizes the use of fixed-input and inter-stage wordlength in existing hardware efficient fixed-point FFT. The above data scaling algorithm enhances the dynamic range of fixed-point fixed-precision FFT designs and emulates the precision benefits of floating-point representation without complicated design additions. Novel algorithms and performance analysis for hardware efficient representation of twiddle factors are studied for multi-tone signal detection with dynamic kernel function FFT processors. The development of hardware performance estimation models based on different number of bits used for dynamic kernel function shows the relative trade-off between kernel bits to FFT spurious-free dynamic range (SFDR) and phase performance. A 2.048 GSPS fixed-point fixed-precision dynamic kernel function FFT processor with variable truncation scheme is proposed, developed and implemented for real-time wideband signal detection. Using an Atmel 10-bit ADC, two-tone real-time signal detection is demons (open full item for complete abstract)

Committee: Chien-In Henry Chen Ph.D. (Advisor); Raymond E. Siferd Ph.D. (Committee Member); Zhiqiang John Wu Ph.D. (Committee Member); Bin Wang Ph.D. (Committee Member); Wen-Ben Jone Ph.D. (Committee Member) Subjects: Electrical Engineering

Master of Science in Engineering (MSEgr), Wright State University, 2007, Electrical Engineering

The advent of field-programmable gate array (FPGA) has provided an excellent platform to market prototyping of full receiver-on-chip designs in a short time. The design of multi-tone wideband receiver has always been a challenge because of the difficulty to detect weak signals in the presence of noise in the frequency spectrum and also the presence of general spurs generated by the receiver. In this research, architecture for a FPGA-based 2.56-GSPS digital wideband receiver with multi-tone signal detection and tracking is designed to demonstrate the capability of replacing more expensive analog components into their cheaper digital design counterparts. Novel hardware implementations of a Hamming window function, a fast Fourier transform (FFT), and an encoder algorithm is presented. This receiver can distinguish four-tone signals for a bandwidth of 1.20 GHz at a 20 MHz interval, has an average of four-tone signal spurious-free dynamic range (SFDR) of 22 dB, two-tone signal SFDR of 39 dB, and single signal SFDR of 45.5 dB. The digital receiver can also track the input signals and distinguish if they are continuous or a pulse wave signals.

Committee: Chien-In Chen (Advisor) Subjects:

Master of Science in Engineering (MSEgr), Wright State University, 2006, Electrical Engineering

The Global Positioning System or GPS is a satellite based technology that has gained widespread use worldwide in civilian and military applications. Direct Sequence Spread spectrum (DSSS) is the method whereby the data transmitted by the satellite and received by user is kept secure, low power and relatively noise-immune. The first step required in the GPS operation is to perform a lock on the incoming signal, both with respect to time synchronization and frequency resolution. Because of the need for reduced time to lock and also reduced hardware, algorithms based in the frequency domain have been developed. These algorithms take advantage of the time to frequency matrix operation known as the fast Fourier transform or FFT. For this thesis, a Direct Sequence Spread Spectrum Coarse Acquisition code processor based on the FFT was implemented in VHDL and targeted to a Xilinx Virtex –II Pro Field Programmable Gate Array (FPGA). The use of the FFT allows simultaneous lock on coarse acquisition (C/A) code and carrier frequency. Because of hardware limitations, a novel technique of sub-sampling is used in this system to obtain data block sizes that match hardware limitations. In addition, design challenges related to scheduling and timing were addressed, allowing a system with 19 pipeline stages to be built. The system, which fits on a Xilinx Virtex-II pro XC2VP70 FPGA, uses 10 ms of data to perform the lock with 5.5 ms of processing time at 100 MHz and theoretically can operate on signals 20 db below the noise floor.

Committee: Henry Chen (Advisor) Subjects:

MS, University of Cincinnati, 2003, Arts and Sciences : Physics

The principle goal of the present research is to understand the process of crystal dendrite growth. The main interest is to map the concentration and the temperature profile in the environment surrounding a crystal that is growing in the melt, using algorithms developed in MATLAB. Using optical interferometric techniques, it is clear that during the growth of dendrite crystals, a concentration gradient in the solution drives molecules toward the crystal. This results in the release of heat that is fed back into the temperature field of the melt. Solidification proceeds by driving the liquid/solid interface through a temperature gradient, at a specific velocity. Recent experimental advances have made it possible to map the index of refraction of the solution in the vicinity of the growing crystal through Fourier Interferometric techniques. Of particular interest are the calculations of the temperature dependence on the index of refraction. These calculations make the mapping of a field surrounding the crystal possible using a Fast Fourier Transform Technique.

Committee: DR. HENRY FENICHEL (Advisor) Subjects: Physics, General

Master of Science (MS), University of Toledo, 2004, School of Nursing

This study sought to establish the utility of heart rate variability measurement as a tool to assess pain in low birth weight premature infants. It used a repeated measures design with secondary analysis and paired samples. Subjects were a subset of 10 infants who were less than 28 weeks gestational age. Heart rate increased significantly following a heel stick and remained unchanged following an axillary temperature measurement. There was a significant increase in heart rate during what is thought to be pain that did not occur following a presumably non-painful stimulus. Heart rate was shown to be a sensitive indicator of pain in this sample of infants. No support was found for the use of heart rate variability as a pain measure in this age group and post-conception age range.

Committee: Jane Evans (Advisor) Subjects: Health Sciences, Nursing

Master of Science in Engineering, University of Akron, 2010, Biomedical Engineering

The Fourier Transform is a mathematical operation used widely in many fields. In medical imaging it is used for many applications such as image filtering, image reconstruction and image analysis. It is an important image processing tool which is used to decompose an image into its sine and cosine components. The output of the transformation represents the image in the frequency domain, while the input image is the spatial domain equivalent. In the frequency domain image, each point represents a particular frequency contained in the spatial domain image [8]. The objective of the research is to develop an algorithm for the Fast Fourier Transform so that it will compute the Fourier Transform much faster for input data with fixed length. The algorithm is developed in the c language and MATLAB. The goal of this research work basically revolves around the use of the Fourier Transform for reconstruction of an image in MRI and CT scan machines. As we know, when MRI machines take an image of the human body, the output is in the form of raw data. The Fourier Transform is used to reconstruct the image from this raw data. When the raw data size is relatively small, it takes moderate time to reconstruct an image. But, as the raw data size continue increasing, the time for processing the reconstruction increases as well. That triggers the quest for a faster way to compute the Fourier Transform. The Fast Fourier Transform is an efficient algorithm available since 1965 to calculate computationally intensive Fourier Transforms. Our goal in this entire work is to develop a strategy to compute the Fast Fourier Transform more efficiently and to reduce the time it takes for calculation. This mathematical transform makes reconstruction of images with larger data size practical.

Committee: Dale Mugler Dr (Advisor); Wolfgang Pelz Dr (Advisor); Daniel Sheffer Dr (Committee Member) Subjects: Biomedical Research; Engineering