Matching Items (50)
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- Genre: Masters Thesis
- Creators: Holbert, Keith E.
Description
Microprocessors are the processing heart of any digital system and are central to all the technological advancements of the age including space exploration and monitoring. The demands of space exploration require a special class of microprocessors called radiation hardened microprocessors which are less susceptible to radiation present outside the earth's atmosphere, in other words their functioning is not disrupted even in presence of disruptive radiation. The presence of these particles forces the designers to come up with design techniques at circuit and chip levels to alleviate the errors which can be encountered in the functioning of microprocessors. Microprocessor evolution has been very rapid in terms of performance but the same cannot be said about its rad-hard counterpart. With the total data processing capability overall increasing rapidly, the clear lack of performance of the processors manifests as a bottleneck in any processing system. To design high performance rad-hard microprocessors designers have to overcome difficult design problems at various design stages i.e. Architecture, Synthesis, Floorplanning, Optimization, routing and analysis all the while maintaining circuit radiation hardness. The reference design `HERMES' is targeted at 90nm IBM G process and is expected to reach 500Mhz which is twice as fast any processor currently available. Chapter 1 talks about the mechanisms of radiation effects which cause upsets and degradation to the functioning of digital circuits. Chapter 2 gives a brief description of the components which are used in the design and are part of the consistent efforts at ASUVLSI lab culminating in this chip level implementation of the design. Chapter 3 explains the basic digital design ASIC flow and the changes made to it leading to a rad-hard specific ASIC flow used in implementing this chip. Chapter 4 talks about the triple mode redundant (TMR) specific flow which is used in the block implementation, delineating the challenges faced and the solutions proposed to make the flow work. Chapter 5 explains the challenges faced and solutions arrived at while using the top-level flow described in chapter 3. Chapter 6 puts together the results and analyzes the design in terms of basic integrated circuit design constraints.
ContributorsRamamurthy, Chandarasekaran (Author) / Clark, Lawrence T (Thesis advisor) / Holbert, Keith E. (Committee member) / Barnaby, Hugh J (Committee member) / Mayhew, David (Committee member) / Arizona State University (Publisher)
Created2013
Description
With ever increasing use of natural gas to generate electricity, installed natural gas fired microturbines are found in residential areas to generate electricity locally. This research work discusses a generalized methodology for assessing optimal capacity and locations for installing natural gas fired microturbines in a distribution residential network. The overall objective is to place microturbines to minimize the system power loss occurring in the electrical distribution network; in such a way that the electric feeder does not need any up-gradation. The IEEE 123 Node Test Feeder is selected as the test bed for validating the developed methodology. Three-phase unbalanced electric power flow is run in OpenDSS through COM server, and the gas distribution network is analyzed using GASWorkS. The continual sensitivity analysis methodology is developed to select multiple DG locations and annual simulation is run to minimize annual average losses. The proposed placement of microturbines must be feasible in the gas distribution network and should not result into gas pipeline reinforcement. The corresponding gas distribution network is developed in GASWorkS software, and nodal pressures of the gas system are checked for various cases to investigate if the existing gas distribution network can accommodate the penetration of selected microturbines. The results indicate the optimal locations suitable to place microturbines and capacity that can be accommodated by the system, based on the consideration of overall minimum annual average losses as well as the guarantee of nodal pressure provided by the gas distribution network. The proposed method is generalized and can be used for any IEEE test feeder or an actual residential distribution network.
ContributorsKamdar, Krutak (Author) / Karady, George G. (Thesis advisor) / Ayyanar, Raja (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2014
Description
t temperature (HST) and top-oil temperature (TOT) are reliable indicators of the insulation temperature. The objective of this project is to use thermal models to estimate the transformer's maximum dynamic loading capacity without violating the HST and TOT thermal limits set by the operator. In order to ensure the optimal loading, the temperature predictions of the thermal models need to be accurate. A number of transformer thermal models are available in the literature. In present practice, the IEEE Clause 7 model is used by the industry to make these predictions. However, a linear regression based thermal model has been observed to be more accurate than the IEEE model. These two models have been studied in this work.
This document presents the research conducted to discriminate between reliable and unreliable models with the help of certain metrics. This was done by first eyeballing the prediction performance and then evaluating a number of mathematical metrics. Efforts were made to recognize the cause behind an unreliable model. Also research was conducted to improve the accuracy of the performance of the existing models.
A new application, described in this document, has been developed to automate the process of building thermal models for multiple transformers. These thermal models can then be used for transformer dynamic loading.
This document presents the research conducted to discriminate between reliable and unreliable models with the help of certain metrics. This was done by first eyeballing the prediction performance and then evaluating a number of mathematical metrics. Efforts were made to recognize the cause behind an unreliable model. Also research was conducted to improve the accuracy of the performance of the existing models.
A new application, described in this document, has been developed to automate the process of building thermal models for multiple transformers. These thermal models can then be used for transformer dynamic loading.
ContributorsRao, Shruti Dwarkanath (Author) / Tylavsky, Daniel J (Thesis advisor) / Holbert, Keith E. (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2014
Description
This work describes the development of automated flows to generate pad rings, mixed signal power grids, and mega cells in a multi-project test chip. There were three major design flows that were created to create the test chip. The first was the pad ring which was used as the staring block for creating the test chip. This flow put all of the signals for the chip in the order that was wanted along the outside of the die along with creation of the power ring that is used to supply the chip with a robust power source.
The second flow that was created was used to put together a flash block that is based off of a XILIX XCFXXP. This flow was somewhat similar to how the pad ring flow worked except that optimizations and a clock tree was added into the flow. There was a couple of design redoes due to timing and orientation constraints.
Finally, the last flow that was created was the top level flow which is where all of the components are combined together to create a finished test chip ready for fabrication. The main components that were used were the finished flash block, HERMES, test structures, and a clock instance along with the pad ring flow for the creation of the pad ring and power ring.
Also discussed is some work that was done on a previous multi-project test chip. The work that was done was the creation of power gaters that were used like switches to turn the power on and off for some flash modules. To control the power gaters the functionality change of some pad drivers was done so that they output a higher voltage than what is seen in the core of the chip.
The second flow that was created was used to put together a flash block that is based off of a XILIX XCFXXP. This flow was somewhat similar to how the pad ring flow worked except that optimizations and a clock tree was added into the flow. There was a couple of design redoes due to timing and orientation constraints.
Finally, the last flow that was created was the top level flow which is where all of the components are combined together to create a finished test chip ready for fabrication. The main components that were used were the finished flash block, HERMES, test structures, and a clock instance along with the pad ring flow for the creation of the pad ring and power ring.
Also discussed is some work that was done on a previous multi-project test chip. The work that was done was the creation of power gaters that were used like switches to turn the power on and off for some flash modules. To control the power gaters the functionality change of some pad drivers was done so that they output a higher voltage than what is seen in the core of the chip.
ContributorsLieb, Christopher (Author) / Clark, Lawrence (Thesis advisor) / Holbert, Keith E. (Committee member) / Seo, Jae-Sun (Committee member) / Arizona State University (Publisher)
Created2015
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
Description
The subject of this thesis is distribution level load management using a pricing signal in a smart grid infrastructure. The project relates to energy management in a spe-cialized distribution system known as the Future Renewable Electric Energy Delivery and Management (FREEDM) system. Energy management through demand response is one of the key applications of smart grid. Demand response today is envisioned as a method in which the price could be communicated to the consumers and they may shift their loads from high price periods to the low price periods. The development and deployment of the FREEDM system necessitates controls of energy and power at the point of end use.
In this thesis, the main objective is to develop the control model of the Energy Management System (EMS). The energy and power management in the FREEDM system is digitally controlled therefore all signals containing system states are discrete. The EMS is modeled as a discrete closed loop transfer function in the z-domain. A breakdown of power and energy control devices such as EMS components may result in energy con-sumption error. This leads to one of the main focuses of the thesis which is to identify and study component failures of the designed control system. Moreover, H-infinity ro-bust control method is applied to ensure effectiveness of the control architecture. A focus of the study is cyber security attack, specifically bad data detection in price. Test cases are used to illustrate the performance of the EMS control design, the effect of failure modes and the application of robust control technique.
The EMS was represented by a linear z-domain model. The transfer function be-tween the pricing signal and the demand response was designed and used as a test bed. EMS potential failure modes were identified and studied. Three bad data detection meth-odologies were implemented and a voting policy was used to declare bad data. The run-ning mean and standard deviation analysis method proves to be the best method to detect bad data. An H-infinity robust control technique was applied for the first time to design discrete EMS controller for the FREEDM system.
In this thesis, the main objective is to develop the control model of the Energy Management System (EMS). The energy and power management in the FREEDM system is digitally controlled therefore all signals containing system states are discrete. The EMS is modeled as a discrete closed loop transfer function in the z-domain. A breakdown of power and energy control devices such as EMS components may result in energy con-sumption error. This leads to one of the main focuses of the thesis which is to identify and study component failures of the designed control system. Moreover, H-infinity ro-bust control method is applied to ensure effectiveness of the control architecture. A focus of the study is cyber security attack, specifically bad data detection in price. Test cases are used to illustrate the performance of the EMS control design, the effect of failure modes and the application of robust control technique.
The EMS was represented by a linear z-domain model. The transfer function be-tween the pricing signal and the demand response was designed and used as a test bed. EMS potential failure modes were identified and studied. Three bad data detection meth-odologies were implemented and a voting policy was used to declare bad data. The run-ning mean and standard deviation analysis method proves to be the best method to detect bad data. An H-infinity robust control technique was applied for the first time to design discrete EMS controller for the FREEDM system.
ContributorsMusani, Aatif (Author) / Heydt, Gerald (Thesis advisor) / Ayyanar, Raja (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2014
Description
Due to increasing integration of renewable resources in the power grid, an efficient high power transmission system is needed in the near future to transfer energy from remote locations to the load centers. Gas Insulated Transmission Line (GIL) is a specialized high power transmission system, designed by Siemens, for applications requiring direct burial or vertical installation of the transmission line. GIL uses SF6 as an insulating medium. Due to unavoidable gas leakages and high global warming potential of SF6, there is a need to replace this insulating gas by some other possible alternative. Insulating foam materials are characterized by excellent dielectric properties as well as their reduced weight. These materials can find their application in GIL as high voltage insulators. Syntactic foam is a polymer based insulating foam. It consists of a large number of microspheres embedded in a polymer matrix.
The work in this thesis deals with the development of the selection proce-dure for an insulating foam for its application in GIL. All the steps in the process are demonstrated considering syntactic foam as an insulator. As the first step of the procedure, a small representative model of the insulating foam is built in COMSOL Multiphysics software with the help of AutoCAD and Excel VBA to analyze electric field distribution for the application of GIL. The effect of the presence of metal particles on the electric field distribution is also observed. The AC voltage withstand test is performed on the insulating foam samples according to the IEEE standards. The effect of the insulating foam on electrical parameters as well as transmission characteristics of the line is analyzed as the last part of the thesis. The results from all the simulations and AC voltage withstand test are ob-served to predict the suitability of the syntactic foam as an insulator in GIL.
The work in this thesis deals with the development of the selection proce-dure for an insulating foam for its application in GIL. All the steps in the process are demonstrated considering syntactic foam as an insulator. As the first step of the procedure, a small representative model of the insulating foam is built in COMSOL Multiphysics software with the help of AutoCAD and Excel VBA to analyze electric field distribution for the application of GIL. The effect of the presence of metal particles on the electric field distribution is also observed. The AC voltage withstand test is performed on the insulating foam samples according to the IEEE standards. The effect of the insulating foam on electrical parameters as well as transmission characteristics of the line is analyzed as the last part of the thesis. The results from all the simulations and AC voltage withstand test are ob-served to predict the suitability of the syntactic foam as an insulator in GIL.
ContributorsPendse, Harshada Ganesh (Author) / Karady, George G. (Thesis advisor) / Holbert, Keith E. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2014
Description
Radiation-induced gain degradation in bipolar devices is considered to be the primary threat to linear bipolar circuits operating in the space environment. The damage is primarily caused by charged particles trapped in the Earth's magnetosphere, the solar wind, and cosmic rays. This constant radiation exposure leads to early end-of-life expectancies for many electronic parts. Exposure to ionizing radiation increases the density of oxide and interfacial defects in bipolar oxides leading to an increase in base current in bipolar junction transistors. Radiation-induced excess base current is the primary cause of current gain degradation. Analysis of base current response can enable the measurement of defects generated by radiation exposure. In addition to radiation, the space environment is also characterized by extreme temperature fluctuations. Temperature, like radiation, also has a very strong impact on base current. Thus, a technique for separating the effects of radiation from thermal effects is necessary in order to accurately measure radiation-induced damage in space. This thesis focuses on the extraction of radiation damage in lateral PNP bipolar junction transistors and the space environment. It also describes the measurement techniques used and provides a quantitative analysis methodology for separating radiation and thermal effects on the bipolar base current.
ContributorsCampola, Michael J (Author) / Barnaby, Hugh J (Thesis advisor) / Holbert, Keith E. (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2011
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
Power generation in remote isolated places is a tough problem. Presently, a common source for remote generation is diesel. However, diesel generation is costly and environmental unfriendly. It is promising to replace the diesel generation with some clean and economical generation sources. The concept of renewable generation offers a solution to remote generation. This thesis focuses on evaluation of renewable generation penetration in the remote isolated grid. A small town named Coober Pedy in South Australia is set as an example. The first task is to build the stochastic models of solar irradiation and wind speed based on the local historical data. With the stochastic models, generation fluctuations and generation planning are further discussed. Fluctuation analysis gives an evaluation of storage unit size and costs. Generation planning aims at finding the relationships between penetration level and costs under constraint of energy sufficiency. The results of this study provide the best penetration level that makes the minimum energy costs. In the case of Coober Pedy, cases of wind and photovoltaic penetrations are studied. The additional renewable sources and suspended diesel generation change the electricity costs. Results show that in remote isolated grid, compared to diesel generation, renewable generation can lower the energy costs.
ContributorsZhu, Yujia (Author) / Holbert, Keith E. (Thesis advisor) / Karady, George G. (Committee member) / Tylavsky, Daniel J (Committee member) / Arizona State University (Publisher)
Created2012