Matching Items (7)
Filtering by
- All Subjects: Simulation
- Creators: Goodnick, Stephen
Description
New technologies enable the exploration of space, high-fidelity defense systems, lighting fast intercontinental communication systems as well as medical technologies that extend and improve patient lives. The basis for these technologies is high reliability electronics devised to meet stringent design goals and to operate consistently for many years deployed in the field. An on-going concern for engineers is the consequences of ionizing radiation exposure, specifically total dose effects. For many of the different applications, there is a likelihood of exposure to radiation, which can result in device degradation and potentially failure. While the total dose effects and the resulting degradation are a well-studied field and methodologies to help mitigate degradation have been developed, there is still a need for simulation techniques to help designers understand total dose effects within their design. To that end, the work presented here details simulation techniques to analyze as well as predict the total dose response of a circuit. In this dissertation the total dose effects are broken into two sub-categories, intra-device and inter-device effects in CMOS technology. Intra-device effects degrade the performance of both n-channel and p-channel transistors, while inter-device effects result in loss of device isolation. In this work, multiple case studies are presented for which total dose degradation is of concern. Through the simulation techniques, the individual device and circuit responses are modeled post-irradiation. The use of these simulation techniques by circuit designers allow predictive simulation of total dose effects, allowing focused design changes to be implemented to increase radiation tolerance of high reliability electronics.
ContributorsSchlenvogt, Garrett (Author) / Barnaby, Hugh (Thesis advisor) / Goodnick, Stephen (Committee member) / Vasileska, Dragica (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2014
Description
The measurement of competency in nursing is critical to ensure safe and effective care of patients. This study had two purposes. First, the psychometric characteristics of the Nursing Performance Profile (NPP), an instrument used to measure nursing competency, were evaluated using generalizability theory and a sample of 18 nurses in the Measuring Competency with Simulation (MCWS) Phase I dataset. The relative magnitudes of various error sources and their interactions were estimated in a generalizability study involving a fully crossed, three-facet random design with nurse participants as the object of measurement and scenarios, raters, and items as the three facets. A design corresponding to that of the MCWS Phase I data--involving three scenarios, three raters, and 41 items--showed nurse participants contributed the greatest proportion to total variance (50.00%), followed, in decreasing magnitude, by: rater (19.40%), the two-way participant x scenario interaction (12.93%), and the two-way participant x rater interaction (8.62%). The generalizability (G) coefficient was .65 and the dependability coefficient was .50. In decision study designs minimizing number of scenarios, the desired generalizability coefficients of .70 and .80 were reached at three scenarios with five raters, and five scenarios with nine raters, respectively. In designs minimizing number of raters, G coefficients of .72 and .80 were reached at three raters and five scenarios and four raters and nine scenarios, respectively. A dependability coefficient of .71 was attained with six scenarios and nine raters or seven raters and nine scenarios. Achieving high reliability with designs involving fewer raters may be possible with enhanced rater training to decrease variance components for rater main and interaction effects. The second part of this study involved the design and implementation of a validation process for evidence-based human patient simulation scenarios in assessment of nursing competency. A team of experts validated the new scenario using a modified Delphi technique, involving three rounds of iterative feedback and revisions. In tandem, the psychometric study of the NPP and the development of a validation process for human patient simulation scenarios both advance and encourage best practices for studying the validity of simulation-based assessments.
ContributorsO'Brien, Janet Elaine (Author) / Thompson, Marilyn (Thesis advisor) / Hagler, Debra (Thesis advisor) / Green, Samuel (Committee member) / Arizona State University (Publisher)
Created2014
Description
Thermal effects in nano-scaled devices were reviewed and modeling methodologies to deal with this issue were discussed. The phonon energy balance equations model, being one of the important previous works regarding the modeling of heating effects in nano-scale devices, was derived. Then, detailed description was given on the Monte Carlo (MC) solution of the phonon Boltzmann Transport Equation. The phonon MC solver was developed next as part of this thesis. Simulation results of the thermal conductivity in bulk Si show good agreement with theoretical/experimental values from literature.
ContributorsYoo, Seung Kyung (Author) / Vasileska, Dragica (Thesis advisor) / Ferry, David (Committee member) / Goodnick, Stephen (Committee member) / Arizona State University (Publisher)
Created2015
Description
In recent years, there has been increased interest in the Indium Gallium Nitride (InGaN) material system for photovoltaic (PV) applications. The InGaN alloy system has demonstrated high performance for high frequency power devices, as well as for optical light emitters. This material system is also promising for photovoltaic applications due to broad range of bandgaps of InxGa1-xN alloys from 0.65 eV (InN) to 3.42 eV (GaN), which covers most of the electromagnetic spectrum from ultraviolet to infrared wavelengths. InGaN’s high absorption coefficient, radiation resistance and thermal stability (operating with temperature > 450 ℃) makes it a suitable PV candidate for hybrid concentrating solar thermal systems as well as other high temperature applications. This work proposed a high efficiency InGaN-based 2J tandem cell for high temperature (450 ℃) and concentration (200 X) hybrid concentrated solar thermal (CSP) application via numerical simulation. In order to address the polarization and band-offset issues for GaN/InGaN hetero-solar cells, band-engineering techniques are adopted and a simple interlayer is proposed at the hetero-interface rather than an Indium composition grading layer which is not practical in fabrication. The base absorber thickness and doping has been optimized for 1J cell performance and current matching has been achieved for 2J tandem cell design. The simulations also suggest that the issue of crystalline quality (i.e. short SRH lifetime) of the nitride material system to date is a crucial factor limiting the performance of the designed 2J cell at high temperature. Three pathways to achieve ~25% efficiency have been proposed under 450 ℃ and 200 X. An anti-reflection coating (ARC) for the InGaN solar cell optical management has been designed. Finally, effective mobility model for quantum well solar cells has been developed for efficient quasi-bulk simulation.
ContributorsFang, Yi, Ph.D (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Thesis advisor) / Ponce, Fernando (Committee member) / Nemanich, Robert (Committee member) / Arizona State University (Publisher)
Created2017
Description
Investigation of measurement invariance (MI) commonly assumes correct specification of dimensionality across multiple groups. Although research shows that violation of the dimensionality assumption can cause bias in model parameter estimation for single-group analyses, little research on this issue has been conducted for multiple-group analyses. This study explored the effects of mismatch in dimensionality between data and analysis models with multiple-group analyses at the population and sample levels. Datasets were generated using a bifactor model with different factor structures and were analyzed with bifactor and single-factor models to assess misspecification effects on assessments of MI and latent mean differences. As baseline models, the bifactor models fit data well and had minimal bias in latent mean estimation. However, the low convergence rates of fitting bifactor models to data with complex structures and small sample sizes caused concern. On the other hand, effects of fitting the misspecified single-factor models on the assessments of MI and latent means differed by the bifactor structures underlying data. For data following one general factor and one group factor affecting a small set of indicators, the effects of ignoring the group factor in analysis models on the tests of MI and latent mean differences were mild. In contrast, for data following one general factor and several group factors, oversimplifications of analysis models can lead to inaccurate conclusions regarding MI assessment and latent mean estimation.
ContributorsXu, Yuning (Author) / Green, Samuel (Thesis advisor) / Levy, Roy (Committee member) / Thompson, Marilyn (Committee member) / Arizona State University (Publisher)
Created2018
Description
Gallium Nitride (GaN) based Current Aperture Vertical Electron Transistors (CAVETs) present many appealing qualities for applications in high power, high frequency devices. The wide bandgap, high carrier velocity of GaN make it ideal for withstanding high electric fields and supporting large currents. The vertical topology of the CAVET allows for more efficient die area utilization, breakdown scaling with the height of the device, and burying high electric fields in the bulk where they will not charge interface states that can lead to current collapse at higher frequency.
Though GaN CAVETs are promising new devices, they are expensive to develop due to new or exotic materials and processing steps. As a result, the accurate simulation of GaN CAVETs has become critical to the development of new devices. Using Silvaco Atlas 5.24.1.R, best practices were developed for GaN CAVET simulation by recreating the structure and results of the pGaN insulated gate CAVET presented in chapter 3 of [8].
From the results it was concluded that the best simulation setup for transfer characteristics, output characteristics, and breakdown included the following. For methods, the use of Gummel, Block, Newton, and Trap. For models, SRH, Fermi, Auger, and impact selb. For mobility, the use of GANSAT and manually specified saturation velocity and mobility (based on doping concentration). Additionally, parametric sweeps showed that, of those tested, critical CAVET parameters included channel mobility (and thus doping), channel thickness, Current Blocking Layer (CBL) doping, gate overlap, and aperture width in rectangular devices or diameter in cylindrical devices.
Though GaN CAVETs are promising new devices, they are expensive to develop due to new or exotic materials and processing steps. As a result, the accurate simulation of GaN CAVETs has become critical to the development of new devices. Using Silvaco Atlas 5.24.1.R, best practices were developed for GaN CAVET simulation by recreating the structure and results of the pGaN insulated gate CAVET presented in chapter 3 of [8].
From the results it was concluded that the best simulation setup for transfer characteristics, output characteristics, and breakdown included the following. For methods, the use of Gummel, Block, Newton, and Trap. For models, SRH, Fermi, Auger, and impact selb. For mobility, the use of GANSAT and manually specified saturation velocity and mobility (based on doping concentration). Additionally, parametric sweeps showed that, of those tested, critical CAVET parameters included channel mobility (and thus doping), channel thickness, Current Blocking Layer (CBL) doping, gate overlap, and aperture width in rectangular devices or diameter in cylindrical devices.
ContributorsWarren, Andrew (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Committee member) / Zhao, Yuji (Committee member) / Arizona State University (Publisher)
Created2019
Description
Currently, autonomous vehicles are being evaluated by how well they interact with humans without evaluating how well humans interact with them. Since people are not going to unanimously switch over to using autonomous vehicles, attention must be given to how well these new vehicles signal intent to human drivers from the driver’s point of view. Ineffective communication will lead to unnecessary discomfort among drivers caused by an underlying uncertainty about what an autonomous vehicle is or isn’t about to do. Recent studies suggest that humans tend to fixate on areas of higher uncertainty so scenarios that have a higher number of vehicle fixations can be reasoned to be more uncertain. We provide a framework for measuring human uncertainty and use the framework to measure the effect of empathetic vs non-empathetic agents. We used a simulated driving environment to create recorded scenarios and manipulate the autonomous vehicle to include either an empathetic or non-empathetic agent. The driving interaction is composed of two vehicles approaching an uncontrolled intersection. These scenarios were played to twelve participants while their gaze was recorded to track what the participants were fixating on. The overall intent was to provide an analytical framework as a tool for evaluating autonomous driving features; and in this case, we choose to evaluate how effective it was for vehicles to have empathetic behaviors included in the autonomous vehicle decision making. A t-test analysis of the gaze indicated that empathy did not in fact reduce uncertainty although additional testing of this hypothesis will be needed due to the small sample size.
ContributorsGreenhagen, Tanner Patrick (Author) / Yang, Yezhou (Thesis director) / Jammula, Varun C (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05