Matching Items (17)
Filtering by
- All Subjects: engineering
- Status: Published
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
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
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
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
Concrete is relatively brittle, and its tensile strength is typically only about one-tenth of its compressive strength. Regular concrete is therefore normally uses reinforcement steel bars to increase the tensile strength. It is becoming increasingly popular to use random distributed fibers as reinforcement and polymeric fibers is once such kind. In the case of polymeric fibers, due to hydrophobicity and lack of any chemical bond between the fiber and matrix, the weak interface zone limits the ability of the fibers to effectively carry the load that is on the matrix phase. Depending on the fiber’s surface asperity, shape, chemical nature, and mechanical bond characteristic of the load transfer between matrix and fiber can be altered so that the final composite can be improved. These modifications can be carried out by means of thermal treatment, mechanical surface modifications, or chemical changes The objective of this study is to measure and document the effect of gamma ray irradiation on the mechanical properties of macro polymeric fibers. The objective is to determine the mechanical properties of macro-synthetic fibers and develop guidelines for treatment and characterization that allow for potential positive changes due to exposure to irradiation. Fibers are exposed to various levels of ionizing radiation and the tensile, interface and performance in a mortar matrix are documented. Uniaxial tensile tests were performed on irradiated fibers to study fiber strength and failure pattern. SEM tests were carried out in order to study the surface characteristic and effect of different radiation dose on polymeric fiber. The interaction of the irradiated fiber with the cement composite was studied by a series of quasi-static pullout test for a specific embedded length. As a final task, flexural tests were carried out for different irradiated fibers to sum up the investigation. An average increase of 13% in the stiffness of the fiber was observed for 5 kGy of radiation. Flexural tests showed an average increase of 181% in the Req3 value and 102 % in the toughness of the sample was observed for 5 kGy of dose.
ContributorsTiwari, Sanchay Sushil (Author) / Mobasher, Barzin (Thesis advisor) / Neithalath, Narayanan (Thesis advisor) / Dharmarajan, Subramaniam (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2018
Description
This report provides information concerning qualities of methylcellulose and how those properties affect further experimentation within the biomedical world. Utilizing the compound’s biocompatibility many issues, ranging from surgical to cosmetic, can be solved. As of recent, studies indicate, methylcellulose has been used as a physically cross-linked gel, which cannot sustain a solid form within the body. Therefore, this report will ultimately explore the means of creating a non-degradable, injectable, chemically cross-linking methylcellulose- based hydrogel. Methylcellulose will be evaluated and altered in experiments conducted within this report and a chemical cross-linker, developed from Jeffamine ED 2003 (O,O′-Bis(2-aminopropyl) polypropylene glycol-block-polyethylene glycol-block-polypropylene glycol), will be created. Experimentation with these elements is outlined here, and will ultimately prompt future revisions and analysis.
ContributorsBundalo, Zoran Luka (Author) / Vernon, Brent (Thesis director) / LaBelle, Jeffrey (Committee member) / Overstreet, Derek (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05
Description
Cardiac tissue engineering has major applications in regenerative medicine, disease modeling and fundamental biological studies. Despite the significance, numerous questions still need to be explored to enhance the functionalities of the engineered tissue substitutes. In this study, three dimensional (3D) cardiac micro-tissues were developed through encapsulating co-culture of cardiomyocytes and cardiac fibroblasts, as the main cellular components of native myocardium, within photocrosslinkable gelatin-based hydrogels. Different co-culture ratios were assessed to optimize the functional properties of constructs. The geometry of the micro-tissues was precisely controlled using micro-patterning techniques in order to evaluate their role on synchronous contraction of the cells. Cardiomyocytes exhibited a native-like phenotype when co-cultured with cardiac fibroblasts as compared to the mono-culture condition. Particularly, elongated F-actin fibers with abundance of sarcomeric α-actinin and troponin-I were observed within all layers of the hydrogel constructs. Higher expressions of connexin-43 and integrin β1 indicated improved cell-cell and cell-matrix interactions. Amongst co-culture conditions, 2:1 (cardiomyocytes: cardiac fibroblasts) ratio exhibited enhanced functionalities, whereas decreasing the construct size adversely affected the synchronous contraction of the cells. Therefore, this study indicated that cell-cell ratio as well as the geometrical features of the micropatterned constructs are among crucial parameters, which need to be optimized in order to enhance the functionalities of engineered tissue substitutes and cardiac patches.
ContributorsSaini, Harpinder (Author) / Nikkhah, Mehdi (Thesis advisor) / Vernon, Brent (Committee member) / Towe, Bruce (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