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Browsing by Subject "Computer simulation"
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Item Automatic Modeling and Simulation of Networked Components(2011) Bruce, Nathaniel William; Koskie, Sarah; Chen, Yaobin; Li, LingxiTesting and verification are essential to safe and consistent products. Simulation is a widely accepted method used for verification and testing of distributed components. Generally, one of the major hurdles in using simulation is the development of detailed and accurate models. Since there are time constraints on projects, fast and effective methods of simulation model creation emerge as essential for testing. This thesis proposes to solve these issues by presenting a method to automatically generate a simulation model and run a random walk simulation using that model. The method is automated so that a modeler spends as little time as possible creating a simulation model and the errors normally associated with manual modeling are eliminated. The simulation is automated to allow a human to focus attention on the device that should be tested. The communications transactions between two nodes on a network are recorded as a trace file. This trace file is used to automatically generate a finite state machine model. The model can be adjusted by a designer to add missing information and then simulated in real-time using a software-in-the-loop approach. The innovations in this thesis include adaptation of a synthesis method for use in simulation, introduction of a random simulation method, and introduction of a practical evaluation method for two finite state machines. Test results indicate that nodes can be adequately replaced by models generated automatically by these methods. In addition, model construction time is reduced when comparing to the from scratch model creation method.Item Bayesian Optimization of Active Materials for Lithium-Ion Batteries(SAE, 2021-04) Valladares, Homero; Li, Tianyi; Zhu, Likun; El-Mounayri, Hazim; Tovar, Andres; Hashem, Ahmed; Abdel-Ghany, Ashraf E.; Mechanical Engineering, School of Engineering and TechnologyThe design of better active materials for lithium-ion batteries (LIBs) is crucial to satisfy the increasing demand of high performance batteries for portable electronics and electric vehicles. Currently, the development of new active materials is driven by physical experimentation and the designer’s intuition and expertise. During the development process, the designer interprets the experimental data to decide the next composition of the active material to be tested. After several trial-and-error iterations of data analysis and testing, promising active materials are discovered but after long development times (months or even years) and the evaluation of a large number of experiments. Bayesian global optimization (BGO) is an appealing alternative for the design of active materials for LIBs. BGO is a gradient-free optimization methodology to solve design problems that involve expensive black-box functions. An example of a black-box function is the prediction of the cycle life of LIBs. The cycle life cannot be predicted using a simple closed-form expression but only through the cycling performance test or a numerical simulation. BGO has two main components: a surrogate probabilistic model of the black-box function and an acquisition function that guides the optimization. This research employs BGO in the design of cathode active materials for LIB cells. The training data corresponds to the initial capacity and cycle life of five coin cells with different compositions of LiNixMn2 − xO4 in their cathode, where x is the content of Ni. BGO utilizes the experimental data to identify five new compositions that can produce cells with high initial capacity and\or large cycle life. The surrogate models of the initial capacity and cycle life are Gaussian Processes. The acquisition function is the constrained multi-objective expected improvement. The results show that BGO can identify high-performance active materials for LIBs. Designers can use the data generated during the optimization to decide the composition of the next batch of active materials to be tested, i.e., guide the physical experimentation.Item Computational Methods and Models in Circulatory and Reproductive Systems(Hindawi, 2016) Tian, Fang-Bao; Sui, Yi; Zhu, Luoding; Shu, Chang; Sung, Hyung J.; Department of Mathematical Sciences, School of ScienceItem A Computational Study of the Mechanism for F1-ATPase Inhibition by the Epsilon Subunit(2013) Thomson, Karen J.; Pu, Jingzhi; Ge, Haibo; Sardar, Rajesh; Long, Eric C. (Eric Charles)The multi-protein complex of F0F1 ATP synthase has been of great interest in the fields of microbiology and biochemistry, due to the ubiquitous use of ATP as a biological energy source. Efforts to better understand this complex have been made through structural determination of segments based on NMR and crystallographic data. Some experiments have provided useful data, while others have brought up more questions, especially when structures and functions are compared between bacteria and species with chloroplasts or mitochondria. The epsilon subunit is thought to play a signi cant role in the regulation of ATP synthesis and hydrolysis, yet the exact pathway is unknown due to the experimental difficulty in obtaining data along the transition pathway. Given starting and end point protein crystal structures, the transition pathway of the epsilon subunit was examined through computer simulation.The purpose of this investigation is to determine the likelihood of one such proposed mechanism for the involvement of the epsilon subunit in ATP regulation in bacterial species such as E. coli.Item Decentralized and Partially Decentralized Multi-Agent Reinforcement Learning(2013-08-22) Tilak, Omkar Jayant; Mukhopadhyay, Snehasis; Si, Luo; Neville, Jennifer; Raje, Rajeev; Tuceryan, Mihran; Gorman, William J.Multi-agent systems consist of multiple agents that interact and coordinate with each other to work towards to certain goal. Multi-agent systems naturally arise in a variety of domains such as robotics, telecommunications, and economics. The dynamic and complex nature of these systems entails the agents to learn the optimal solutions on their own instead of following a pre-programmed strategy. Reinforcement learning provides a framework in which agents learn optimal behavior based on the response obtained from the environment. In this thesis, we propose various novel de- centralized, learning automaton based algorithms which can be employed by a group of interacting learning automata. We propose a completely decentralized version of the estimator algorithm. As compared to the completely centralized versions proposed before, this completely decentralized version proves to be a great improvement in terms of space complexity and convergence speed. The decentralized learning algorithm was applied; for the first time; to the domains of distributed object tracking and distributed watershed management. The results obtained by these experiments show the usefulness of the decentralized estimator algorithms to solve complex optimization problems. Taking inspiration from the completely decentralized learning algorithm, we propose the novel concept of partial decentralization. The partial decentralization bridges the gap between the completely decentralized and completely centralized algorithms and thus forms a comprehensive and continuous spectrum of multi-agent algorithms for the learning automata. To demonstrate the applicability of the partial decentralization, we employ a partially decentralized team of learning automata to control multi-agent Markov chains. More flexibility, expressiveness and flavor can be added to the partially decentralized framework by allowing different decentralized modules to engage in different types of games. We propose the novel framework of heterogeneous games of learning automata which allows the learning automata to engage in disparate games under the same formalism. We propose an algorithm to control the dynamic zero-sum games using heterogeneous games of learning automata.Item Developing a Neural Signal Processor Using the Extended Analog Computer(2013-08-21) Soliman, Muller Mark; Yoshida, Ken; Eberhart, Russell C.; Mills, Jonathan W. (Jonathan Wayne); Berbari, Edward J.Neural signal processing to decode neural activity has been an active research area in the last few decades. The next generation of advanced multi-electrode neuroprosthetic devices aim to detect a multiplicity of channels from multiple electrodes, making the relatively time-critical processing problem massively parallel and pushing the computational demands beyond the limits of current embedded digital signal processing (DSP) techniques. To overcome these limitations, a new hybrid computational technique was explored, the Extended Analog Computer (EAC). The EAC is a digitally confgurable analog computer that takes advantage of the intrinsic ability of manifolds to solve partial diferential equations (PDEs). They are extremely fast, require little power, and have great potential for mobile computing applications. In this thesis, the EAC architecture and the mechanism of the formation of potential/current manifolds was derived and analyzed to capture its theoretical mode of operation. A new mode of operation, resistance mode, was developed and a method was devised to sample temporal data and allow their use on the EAC. The method was validated by demonstration of the device solving linear diferential equations and linear functions, and implementing arbitrary finite impulse response (FIR) and infinite impulse response (IIR) linear flters. These results were compared to conventional DSP results. A practical application to the neural computing task was further demonstrated by implementing a matched filter with the EAC simulator and the physical prototype to detect single fiber action potential from multiunit data streams derived from recorded raw electroneurograms. Exclusion error (type 1 error) and inclusion error (type 2 error) were calculated to evaluate the detection rate of the matched filter implemented on the EAC. The detection rates were found to be statistically equivalent to that from DSP simulations with exclusion and inclusion errors at 0% and 1%, respectively.Item A Dynamically Configurable Discrete Event Simulation Framework for Many-Core System-on-Chips(2010) Barnes, Christopher J.; Lee, Jaehwan John; King, Brian S.; Chien, Yung Ping StanleyIndustry trends indicate that many-core heterogeneous processors will be the next-generation answer to Moore's law and reduced power consumption. Thus, both academia and industry are focused on the challenges presented by many-core heterogeneous processor designs. In many cases, researchers use discrete event simulators to research and validate new computer architecture innovations. However, there is a lack of dynamically configurable discrete event simulation environments for the testing and development of many-core heterogeneous processors. To fulfill this need we present Mhetero, a retargetable framework for cycle-accurate simulation of heterogeneous many-core processors along with the cycle-accurate simulation of their associated network-on-chip communication infrastructure. Mhetero is the result of research into dynamically configurable and highly flexible simulation tools with which users are free to produce custom instruction sets and communication methods in a highly modular design environment. In this thesis we will discuss our approach to dynamically configurable discrete event simulation and present several experiments performed using the framework to exemplify how Mhetero, and similarly constructed simulators, may be used for future innovations.Item Injector Waveform Monitoring of a Diesel Engine in Real-Time on a Hardware in the Loop Bench(2011-12) Farooqi, Quazi Mohammed Rushaed; Anwar, Sohel; Wasfy, Tamer; Lee, Jaehwan (John)This thesis presents the development, experimentation and validation of a reliable and robust system to monitor the injector pulse generated by an Engine Control Module (ECM) and send the corresponding fueling quantity to the real-time computer in a closed loop Hardware In the Loop (HIL) bench. The system can be easily calibrated for different engine platforms as well. The fueling quantity that is being injected by the injectors is a crucial variable to run closed loop HIL simulation to carry out the performance testing of engine, aftertreatment and other components of the vehicle. This research utilized Field Programmable Gate Arrays (FPGA) and Direct Memory Access (DMA) transfer capability offered by National Instruments (NI) Compact Reconfigurable Input-Output (cRIO) to achieve high speed data acquisition and delivery. The research was conducted in three stages. The first stage was to develop the HIL bench for the research. The second stage was to determine the performance of the system with different threshold methods and different sampling speeds necessary to satisfy the required accuracy of the fueling quantity being monitored. The third stage was to study the error and its variability involved in the injected fueling quantity from pulse to pulse, from injector to injector, between real injector stators and cheaper inductor load cells emulating the injectors, over different operating conditions with full factorial design of experimentation and mixed model Analysis Of Variance (ANOVA). Different thresholds were experimented to find out the best thresholds, the Start of Injection (SOI) threshold and the End of Injection (EOI) threshold that captured the injector “ontime” with best reliability and accuracy. Experimentation has been carried out at various data acquisition rates to find out the optimum speed of data sampling rate, trading off the accuracy of fueling quantity. The experimentation found out the expected error with a system with cheaper solution as well, so that, if a test application is not sensitive to error in fueling quantity, a cheaper solution with lower sampling rate and inductors as load cells can be used. The statistical analysis was carried out at highest available sampling rate on both injectors and inductors with the best threshold method found in previous studies. The result clearly shows the factors that affect the error and the variability in the standard deviations in error; it also shows the relation with the fixed and random factors. The real-time application developed for the HIL bench is capable of monitoring the injector waveform, using any fueling ontime table corresponding to the platform being tested, and delivering the fueling quantity in real-time. The test bench made for this research is also capable of studying injectors of different types with the automated test sequence, without occupying the resource of fully capable closed loop test benches for testing the ECM unctionality.Item INVESTIGATION OF QUANTUM FLUCTUATIONS IN A NONLINEAR INTERFEROMETER WITH HARMONIC GENERATION AND COHERENT INTERACTION OF LIGHT AND CS ATOMS(2013-08-23) Srinivasan, Prashant; Ou, Zhe-Yu Jeff; Decca, Ricardo; Vemuri, Gautam; Petrache, HoriaIn the first part of this thesis, we investigate the propagation of quantum fluctuations in a nonlinear interferometer comprising under conditions of harmonic generation by computer simulations. This investigation assumes idealized conditions such as lossless and uniform nonlinear media, an ideal cavity and ideal photodetectors. After linearizing wave equations for harmonic generation with a coherent state input, we obtain equations for one dimensional spatial propagation of the mean field and quantum fluctuations for initial conditions set by arbitrary interferometer phase. We discover that fluctuations are de-squeezed in the X and Y quadratures as the interferometer phase is tuned. However, we discover that there is are quadratures P-Q obtained by rotating the X-Y quadratures for which squeezing is improved by factors of 10^9. We present a practical idea to implement rotation of X quadrature fluctuations to the Q quadrature by using an ideal empty optical cavity. Signal-to-Noise ratio of the nonlinear interferometer was calculated and compared with that of a linear interferometer with coherent state input. We calculated a maximum performance improvement of a factor of 60 for a normalized propagation length ζ0 = 3 under ideal conditions. In the second part of this thesis, we investigate experimentalarrangements to transfer atomic coherence from light to cesium atoms. We discuss the experimental arrangement to generate coherence under conditions of electromagnetically induced transparency (EIT). We measure a continuous wave EIT width of 7.18 MHz and present results for pulsed arrangements.Item Mathematical analysis of the lithium ion transport in lithium ion batteries using three dimensional reconstructed electrodes(2012-05) Lim, Cheol Woong; Zhu, Likun; Xie, Jian; Kim, Youngsik; Anwar, SohelComputational analysis of lithium ion batteries has been improved since Newman and et al. suggested the porous electrode theory. It assumed the electrode as a simple structure of homogeneous spherical particles. Bruggeman relationship which characterizes porous material by a simple equation was adopted in the homogeneous electrode model instead of the electrode morphology. To improve the prediction of a cell performance, the numerical analysis requires the realistic microstructure of the cell. Based on the experimentally determined microstructure of the positive and negative electrodes of a lithium ion battery (LIB) using x-ray micro/nano-CT technology, three dimensional (3D) simulations have been presented in this research. Tortuosity of the microstructures has been calculated by a linear diffusion equation to characterize the 3D morphology. The obtained tortuosity and porosity results pointed out that the Bruggeman relationship is not sufficiently estimate the tortuosity by the porosity of electrodes. We studied the diffusion-induced stress numerically based on realistic morphology of reconstructed particles during the lithium ion intercalation process. Diffusion-induced stresses were simulated at different C rates under galvonostatic conditions and compared with spherical particles. The simulation results showed that the intercalation stresses of particles depend on their geometric characteristics. The highest von Mises stress and tresca stress in a real particle are several times higher than the stresses in a spherical particle with the same volume. With the reconstructed positive electrode structure, local effects in the LIB cathode electrode during galvanostatic discharge process have been studied. The simulation results reported that large current density usually occurs at the joints between cathode active material particles and in the small channels in electrolyte, which will generate high electric joule power. By using the 3D real image of a LIB cathode electrode, numerical simulation results revealed that the spatial distribution of variable fields such as concentration, voltage, reaction rate, overpotential, and etc. in the cathode electrode are complicated and non-uniform, especially at high discharge rates.