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Description
Ever reducing time to market, along with short product lifetimes, has created a need to shorten the microprocessor design time. Verification of the design and its analysis are two major components of this design cycle. Design validation techniques can be broadly classified into two major categories: simulation based approaches and formal techniques. Simulation based microprocessor validation involves running millions of cycles using random or pseudo random tests and allows verification of the register transfer level (RTL) model against an architectural model, i.e., that the processor executes instructions as required. The validation effort involves model checking to a high level description or simulation of the design against the RTL implementation. Formal techniques exhaustively analyze parts of the design but, do not verify RTL against the architecture specification. The focus of this work is to implement a fully automated validation environment for a MIPS based radiation hardened microprocessor using simulation based approaches. The basic framework uses the classical validation approach in which the design to be validated is described in a Hardware Definition Language (HDL) such as VHDL or Verilog. To implement a simulation based approach a number of random or pseudo random tests are generated. The output of the HDL based design is compared against the one obtained from a "perfect" model implementing similar functionality, a mismatch in the results would thus indicate a bug in the HDL based design. Effort is made to design the environment in such a manner that it can support validation during different stages of the design cycle. The validation environment includes appropriate changes so as to support architecture changes which are introduced because of radiation hardening. The manner in which the validation environment is build is highly dependent on the specifications of the perfect model used for comparisons. This work implements the validation environment for two MIPS simulators as the reference model. Two bugs have been discovered in the RTL model, using simulation based approaches through the validation environment.
ContributorsSharma, Abhishek (Author) / Clark, Lawrence (Thesis advisor) / Holbert, Keith E. (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2011
Description
The high penetration of photovoltaic (PV) both at the utility and at the distribu-tion levels, has raised concerns about the reliability of grid-tied inverters of PV power systems. Inverters are generally considered as the weak link in PV power systems. The lack of a dedicated qualification/reliability standard for PV inverters is a main barrier in realizing higher level of confidence in reliability. Development of a well-accepted design qualification standard specifically for PV inverters will help pave the way for significant improvement in reliability and performance of inverters across the entire industry. The existing standards for PV inverters such as UL 1741 and IEC 62109-1 primarily focus on safety. IEC 62093 discusses inverter qualification but it includes all the balance of sys-tem components and therefore not specific to PV inverters. There are other general stan-dards for distributed generators including the IEEE1547 series of standards which cover major concerns like utility integration but they are not dedicated to PV inverters and are not written from a design qualification point of view. In this thesis, some of the potential requirements for a design qualification standard for PV inverters are addressed. The IEC 62093 is considered as a guideline and the possible inclusions in the framework for a dedicated design qualification standard of PV inverter are discussed. The missing links in existing PV inverter related standards are identified by performing gap analysis. Dif-ferent requirements of small residential inverters compared to large utility-scale systems, and the emerging requirements on grid support features are also considered. Electric stress test is found to be the key missing link and one of the electric stress tests, the surge withstand test is studied in detail. The use of the existing standards for surge withstand test of residential scale PV inverters is investigated and a method to suitably adopt these standards is proposed. The proposed method is studied analytically and verified using simulation. A design criterion for choosing the switch ratings of the inverter that can per-form reliably under the surge environment is derived.
ContributorsAlampoondi Venkataramanan, Sai Balasubramanian (Author) / Ayyanar, Raja (Thesis advisor) / Vittal, Vijay (Committee member) / Heydt, Gerald (Committee member) / Arizona State University (Publisher)
Created2011
Description
In modern electric power systems, energy management systems (EMSs) are responsi-ble for monitoring and controlling the generation system and transmission networks. State estimation (SE) is a critical `must run successful' component within the EMS software. This is dictated by the high reliability requirements and need to represent the closest real time model for market operations and other critical analysis functions in the EMS. Tradi-tionally, SE is run with data obtained only from supervisory control and data acquisition (SCADA) devices and systems. However, more emphasis on improving the performance of SE drives the inclusion of phasor measurement units (PMUs) into SE input data. PMU measurements are claimed to be more accurate than conventional measurements and PMUs `time stamp' measurements accurately. These widely distributed devices meas-ure the voltage phasors directly. That is, phase information for measured voltages and currents are available. PMUs provide data time stamps to synchronize measurements. Con-sidering the relatively small number of PMUs installed in contemporary power systems in North America, performing SE with only phasor measurements is not feasible. Thus a hy-brid SE, including both SCADA and PMU measurements, is the reality for contemporary power system SE. The hybrid approach is the focus of a number of research papers. There are many practical challenges in incorporating PMUs into SE input data. The higher reporting rates of PMUs as compared with SCADA measurements is one of the salient problems. The disparity of reporting rates raises a question whether buffering the phasor measurements helps to give better estimates of the states. The research presented in this thesis addresses the design of data buffers for PMU data as used in SE applications in electric power systems. The system theoretic analysis is illustrated using an operating electric power system in the southwest part of the USA. Var-ious instances of state estimation data have been used for analysis purposes. The details of the research, results obtained and conclusions drawn are presented in this document.
ContributorsMurugesan, Veerakumar (Author) / Vittal, Vijay (Committee member) / Heydt, Gerald (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
Description
The action/adventure game Grad School: HGH is the final, extended version of a BME Prototyping class project in which the goal was to produce a zombie-themed game that teaches biomedical engineering concepts. The gameplay provides fast paced, exciting, and mildly addicting rooms that the player must battle and survive through, followed by an engineering puzzle that must be solved in order to advance to the next room. The objective of this project was to introduce the core concepts of BME to prospective students, rather than attempt to teach an entire BME curriculum. Based on user testing at various phases in the project, we concluded that the gameplay was engaging enough to keep most users' interest through the educational puzzles, and the potential for expanding this project to reach an even greater audience is vast.
ContributorsNitescu, George (Co-author) / Medawar, Alexandre (Co-author) / Spano, Mark (Thesis director) / LaBelle, Jeffrey (Committee member) / Guiang, Kristoffer (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
Overhead high voltage transmission lines are widely used around the world to deliver power to customers because of their low losses and high transmission capability. Well-coordinated insulation systems are capable of withstanding lightning and switching surge voltages. However, flashover is a serious issue to insulation systems, especially if the insulator is covered by a pollution layer. Many experiments in the laboratory have been conducted to investigate this issue. Since most experiments are time-consuming and costly, good mathematical models could contribute to predicting the insulator flashover performance as well as guide the experiments. This dissertation proposes a new statistical model to calculate the flashover probability of insulators under different supply voltages and contamination levels. An insulator model with water particles in the air is simulated to analyze the effects of rain and mist on flashover performance in reality. Additionally, insulator radius and number of sheds affect insulator surface resistivity and leakage distance. These two factors are studied to improve the efficiency of insulator design. This dissertation also discusses the impact of insulator surface hydrophobicity on flashover voltage.
Because arc propagation is a stochastic process, an arc could travel on different paths based on the electric field distribution. Some arc paths jump between insulator sheds instead of travelling along the insulator surfaces. The arc jumping could shorten the leakage distance and intensify the electric field. Therefore, the probabilities of arc jumping at different locations of sheds are also calculated in this dissertation.
The new simulation model is based on numerical electric field calculation and random walk theory. The electric field is calculated by the variable-grid finite difference method. The random walk theory from the Monte Carlo Method is utilized to describe the random propagation process of arc growth. This model will permit insulator engineers to design the reasonable geometry of insulators, to reduce the flashover phenomena under a wide range of operating conditions.
Because arc propagation is a stochastic process, an arc could travel on different paths based on the electric field distribution. Some arc paths jump between insulator sheds instead of travelling along the insulator surfaces. The arc jumping could shorten the leakage distance and intensify the electric field. Therefore, the probabilities of arc jumping at different locations of sheds are also calculated in this dissertation.
The new simulation model is based on numerical electric field calculation and random walk theory. The electric field is calculated by the variable-grid finite difference method. The random walk theory from the Monte Carlo Method is utilized to describe the random propagation process of arc growth. This model will permit insulator engineers to design the reasonable geometry of insulators, to reduce the flashover phenomena under a wide range of operating conditions.
ContributorsHe, Jiahong (Author) / Gorur, Ravi (Thesis advisor) / Ayyanar, Raja (Committee member) / Holbert, Keith E. (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2016
Description
Underground transmission cables in power systems are less likely to experience electrical faults, however, resulting outage times are much greater in the event that a failure does occur. Unlike overhead lines, underground cables are not self-healing from flashover events. The faulted section must be located and repaired before the line can be put back into service. Since this will often require excavation of the underground duct bank, the procedure to repair the faulted section is both costly and time consuming. These added complications are the prime motivators for developing accurate and reliable ratings for underground cable circuits.
This work will review the methods by which power ratings, or ampacity, for underground cables are determined and then evaluate those ratings by making comparison with measured data taken from an underground 69 kV cable, which is part of the Salt River Project (SRP) power subtransmission system. The process of acquiring, installing, and commissioning the temperature monitoring system is covered in detail as well. The collected data are also used to evaluate typical assumptions made when determining underground cable ratings such as cable hot-spot location and ambient temperatures.
Analysis results show that the commonly made assumption that the deepest portion of an underground power cable installation will be the hot-spot location does not always hold true. It is shown that distributed cable temperature measurements can be used to locate the proper line segment to be used for cable ampacity calculations.
This work will review the methods by which power ratings, or ampacity, for underground cables are determined and then evaluate those ratings by making comparison with measured data taken from an underground 69 kV cable, which is part of the Salt River Project (SRP) power subtransmission system. The process of acquiring, installing, and commissioning the temperature monitoring system is covered in detail as well. The collected data are also used to evaluate typical assumptions made when determining underground cable ratings such as cable hot-spot location and ambient temperatures.
Analysis results show that the commonly made assumption that the deepest portion of an underground power cable installation will be the hot-spot location does not always hold true. It is shown that distributed cable temperature measurements can be used to locate the proper line segment to be used for cable ampacity calculations.
ContributorsStowers, Travis (Author) / Tylavsky, Daniel (Thesis advisor) / Karady, George G. (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2015
Description
With the growing importance of underground power systems and the need for greater reliability of the power supply, cable monitoring and accurate fault location detection has become an increasingly important issue. The presence of inherent random fluctuations in power system signals can be used to extract valuable information about the condition of system equipment. One such component is the power cable, which is the primary focus of this research.
This thesis investigates a unique methodology that allows online monitoring of an underground power cable. The methodology analyzes conventional power signals in the frequency domain to monitor the condition of a power cable.
First, the proposed approach is analyzed theoretically with the help of mathematical computations. Frequency domain analysis techniques are then used to compute the power spectral density (PSD) of the system signals. The importance of inherent noise in the system, a key requirement of this methodology, is also explained. The behavior of resonant frequencies, which are unique to every system, are then analyzed under different system conditions with the help of mathematical expressions.
Another important aspect of this methodology is its ability to accurately estimate cable fault location. The process is online and hence does not require the system to be disconnected from the grid. A single line to ground fault case is considered and the trend followed by the resonant frequencies for different fault positions is observed.
The approach is initially explained using theoretical calculations followed by simulations in MATLAB/Simulink. The validity of this technique is proved by comparing the results obtained from theory and simulation to actual measurement data.
This thesis investigates a unique methodology that allows online monitoring of an underground power cable. The methodology analyzes conventional power signals in the frequency domain to monitor the condition of a power cable.
First, the proposed approach is analyzed theoretically with the help of mathematical computations. Frequency domain analysis techniques are then used to compute the power spectral density (PSD) of the system signals. The importance of inherent noise in the system, a key requirement of this methodology, is also explained. The behavior of resonant frequencies, which are unique to every system, are then analyzed under different system conditions with the help of mathematical expressions.
Another important aspect of this methodology is its ability to accurately estimate cable fault location. The process is online and hence does not require the system to be disconnected from the grid. A single line to ground fault case is considered and the trend followed by the resonant frequencies for different fault positions is observed.
The approach is initially explained using theoretical calculations followed by simulations in MATLAB/Simulink. The validity of this technique is proved by comparing the results obtained from theory and simulation to actual measurement data.
ContributorsGovindarajan, Sudarshan (Author) / Holbert, Keith E. (Thesis advisor) / Heydt, Gerald (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2016
Description
Flash memories are critical for embedded devices to operate properly but are susceptible to radiation effects, which make flash memory a key factor to improve the reliability of circuitry. This thesis describes the simulation techniques used to analyze and predict total ionizing dose (TID) effects on 90-nm technology Silicon Storage Technology (SST) SuperFlash Generation 3 devices. Silvaco Atlas is used for both device level design and simulation purposes.
The simulations consist of no radiation and radiation modeling. The no radiation modeling details the cell structure development and characterizes basic operations (read, erase and program) of a flash memory cell. The program time is observed to be approximately 10 μs while the erase time is approximately 0.1 ms.
The radiation modeling uses the fixed oxide charge method to analyze the TID effects on the same flash memory cell. After irradiation, a threshold voltage shift of the flash memory cell is observed. The threshold voltages of a programmed cell and an erased cell are reduced at an average rate of 0.025 V/krad.
The use of simulation techniques allows designers to better understand the TID response of a SST flash memory cell and to predict cell level TID effects without performing the costly in-situ irradiation experiments. The simulation and experimental results agree qualitatively. In particular, simulation results reveal that ‘0’ to ‘1’ errors but not ‘1’ to ‘0’ retention errors occur; likewise, ‘0’ to ‘1’ errors dominate experimental testing, which also includes circuitry effects that can cause ‘1’ to ‘0’ failures. Both simulation and experimental results reveal flash memory cell TID resilience to about 200 krad.
The simulations consist of no radiation and radiation modeling. The no radiation modeling details the cell structure development and characterizes basic operations (read, erase and program) of a flash memory cell. The program time is observed to be approximately 10 μs while the erase time is approximately 0.1 ms.
The radiation modeling uses the fixed oxide charge method to analyze the TID effects on the same flash memory cell. After irradiation, a threshold voltage shift of the flash memory cell is observed. The threshold voltages of a programmed cell and an erased cell are reduced at an average rate of 0.025 V/krad.
The use of simulation techniques allows designers to better understand the TID response of a SST flash memory cell and to predict cell level TID effects without performing the costly in-situ irradiation experiments. The simulation and experimental results agree qualitatively. In particular, simulation results reveal that ‘0’ to ‘1’ errors but not ‘1’ to ‘0’ retention errors occur; likewise, ‘0’ to ‘1’ errors dominate experimental testing, which also includes circuitry effects that can cause ‘1’ to ‘0’ failures. Both simulation and experimental results reveal flash memory cell TID resilience to about 200 krad.
ContributorsChen, Yitao (Author) / Holbert, Keith E. (Thesis advisor) / Clark, Lawrence T. (Committee member) / Allee, David R. (Committee member) / Arizona State University (Publisher)
Created2016
Description
The Solid State Transformer (SST) is an essential component in the FREEDM system. This research focuses on the modeling of the SST and the controller hardware in the loop (CHIL) implementation of the SST for the support of the FREEDM system demonstration. The energy based control strategy for a three-stage SST is analyzed and applied. A simplified average model of the three-stage SST that is suitable for simulation in real time digital simulator (RTDS) has been developed in this study. The model is also useful for general time-domain power system analysis and simulation. The proposed simplified av-erage model has been validated in MATLAB and PLECS. The accuracy of the model has been verified through comparison with the cycle-by-cycle average (CCA) model and de-tailed switching model. These models are also implemented in PSCAD, and a special strategy to implement the phase shift modulation has been proposed to enable the switching model simulation in PSCAD. The implementation of the CHIL test environment of the SST in RTDS is described in this report. The parameter setup of the model has been discussed in detail. One of the dif-ficulties is the choice of the damping factor, which is revealed in this paper. Also the grounding of the system has large impact on the RTDS simulation. Another problem is that the performance of the system is highly dependent on the switch parameters such as voltage and current ratings. Finally, the functionalities of the SST have been realized on the platform. The distributed energy storage interface power injection and reverse power flow have been validated. Some limitations are noticed and discussed through the simulation on RTDS.
ContributorsJiang, Youyuan (Author) / Ayyanar, Raja (Thesis advisor) / Holbert, Keith E. (Committee member) / Chowdhury, Srabanti (Committee member) / Arizona State University (Publisher)
Created2014
Description
Parkinson's disease is a neurodegenerative condition diagnosed on patients with
clinical history and motor signs of tremor, rigidity and bradykinesia, and the estimated
number of patients living with Parkinson's disease around the world is seven
to ten million. Deep brain stimulation (DBS) provides substantial relief of the motor
signs of Parkinson's disease patients. It is an advanced surgical technique that is used
when drug therapy is no longer sufficient for Parkinson's disease patients. DBS alleviates the motor symptoms of Parkinson's disease by targeting the subthalamic nucleus using high-frequency electrical stimulation.
This work proposes a behavior recognition model for patients with Parkinson's
disease. In particular, an adaptive learning method is proposed to classify behavioral
tasks of Parkinson's disease patients using local field potential and electrocorticography
signals that are collected during DBS implantation surgeries. Unique patterns
exhibited between these signals in a matched feature space would lead to distinction
between motor and language behavioral tasks. Unique features are first extracted
from deep brain signals in the time-frequency space using the matching pursuit decomposition
algorithm. The Dirichlet process Gaussian mixture model uses the extracted
features to cluster the different behavioral signal patterns, without training or
any prior information. The performance of the method is then compared with other
machine learning methods and the advantages of each method is discussed under
different conditions.
clinical history and motor signs of tremor, rigidity and bradykinesia, and the estimated
number of patients living with Parkinson's disease around the world is seven
to ten million. Deep brain stimulation (DBS) provides substantial relief of the motor
signs of Parkinson's disease patients. It is an advanced surgical technique that is used
when drug therapy is no longer sufficient for Parkinson's disease patients. DBS alleviates the motor symptoms of Parkinson's disease by targeting the subthalamic nucleus using high-frequency electrical stimulation.
This work proposes a behavior recognition model for patients with Parkinson's
disease. In particular, an adaptive learning method is proposed to classify behavioral
tasks of Parkinson's disease patients using local field potential and electrocorticography
signals that are collected during DBS implantation surgeries. Unique patterns
exhibited between these signals in a matched feature space would lead to distinction
between motor and language behavioral tasks. Unique features are first extracted
from deep brain signals in the time-frequency space using the matching pursuit decomposition
algorithm. The Dirichlet process Gaussian mixture model uses the extracted
features to cluster the different behavioral signal patterns, without training or
any prior information. The performance of the method is then compared with other
machine learning methods and the advantages of each method is discussed under
different conditions.
ContributorsDutta, Arindam (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Holbert, Keith E. (Committee member) / Bliss, Daniel W. (Committee member) / Arizona State University (Publisher)
Created2015