Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 57 for “"uncertainty propagation"”.
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Inference for Populations: Uncertainty Propagation via Bayesian Population Synthesis
In this dissertation, we develop a new type of prior distribution, specifically for populations themselves, which we denote the Dirichlet Spacing prior. This prior solves a specific problem that arises when attempting to create synthetic populations from a known subset: the unfortunate reality that …
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High dimensional uncertainty propagation for hypersonic flows and entry propagation
… this work, two approaches for a high dimensional uncertainty quantification (UQ) are developed. The first approach performs a single-fidelity non-intrusive forward UQ, while the second one performs a multi fidelity UQ, as an extension of the first approach. Both methods are focused on real …
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Assessing uncertainty propagation of precipitation input in hydrometeorological ensemble forecasting systems
… thesis is the assessment of precipitation input uncertainty into hydrological response in hydrometeorological ensemble systems for flood prediction. The study has been preliminary focused on the development of a hydrometeorological system that couples a statistical precipitation downscaling …
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Efficient development and uncertainty propagation of aviation fuel chemical kinetic models
… To efficiently propagate and reduce model uncertainty, a hybrid response surface network and stochastic gradient descent ensemble (HRSN-SGDE) technique is developed, enabling the rapid generation and analysis of a large distribution of optimized mechanisms. An approach is then introduced to …
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A reduced-basis method for input-output uncertainty propagation in stochastic PDEs
… vibrations, flow through porous media, and wave propagation through random media. Monte-Carlo based sampling methods, generalized polynomial chaos and stochastic collocation methods are some of the popular approaches that have been used in the analysis of such problems. This work proposes a …
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Nonlinear Uncertainty Quantification, Sensitivity Analysis, and Uncertainty Propagation of a Dynamic Electrical Circuit
… The process can be used to identify sources of uncertainty, quantify magnitudes of uncertainty, and propagate uncertainty through a model. Model form error was identified through prototype experiments with the system and subsystem, and methods for reducing model form error are presented. …
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A Monte Carlo framework for nuclear data uncertainty propagation via the windowed multipole formalism
… framework has been developed that calculates the uncertainty in calculated quantities, such as K[subscript eff], reactivity coefficients, multigroup cross sections, and reaction rate ratios, that arise due to uncertainties in the underlying nuclear data. This framework relies on first order …
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Fluoride-salt-cooled high-temperature test reactor thermal-hydraulic licensing and uncertainty propagation analysis
… a newly developed methodology to incorporate uncertainty propagation in a thermal-hydraulic safety analysis for test reactor licensing. A hot channel model, Monte Carlo statistical sampling uncertainty propagation, and limiting safety systems settings (LSSS) approach are uniquely combined to …
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Flux-Independent Uncertainty Propagation of Nuclear Cross Section Data Using the Windowed Multipole Formalism
This thesis encompasses work in the propagation of resolved resonance range nuclear cross section uncertainties, primarily for eigenvalue calculations. The first portion explores the use of resonance parameter uncertainty data in the generation of multi-group cross section libraries. Multigroup …
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Fatigue Damage Prognosis of Internal Delamination in Composite Plates Under Cyclic Compression Loadings Using Affine Arithmetic as Uncertainty Propagation Tool
… but most importantly the quantification of uncertainty in all these areas.</p> <p>In this study, Affine Arithmetic is used as a method for incorporating the uncertainties due to the material properties into the fatigue life prognosis of composite plants subjected to cyclic compressive …
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Learning for informative path planning
… techniques, we will learn models of the uncertainty propagation efficiently and accurately to replace computationally intensive Monte- Carlo simulations in informative path planning. This will enable us to decrease the uncertainty of the weather estimates more than current methods by …
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Uncertainty Analysis of Computational Fluid Dynamics Via Polynomial Chaos
The main limitations in performing uncertainty analysis of CFD models using conventional methods are associated with cost and effort. For these reasons, there is a need for the development and implementation of efficient stochastic CFD tools for performing uncertainty analysis. One of the main …
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Uncertainty analysis in automatic reaction mechanism generation : neopentyl + O₂
… these programs did not include tools for the propagation of uncertainty. Rate constants and thermodynamic properties are not known precisely, and this can lead to large errors in model predictions. This work presents tools for sensitivity analysis and uncertainty propagation within an …
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Uncertainty management in prognosis of electric vehicle energy system
… and propagate them, and to manage or shrink uncertainty distribution bounds under long-term and usage-based prognosis for accurate and precise results. Uncertainty is an inherent attribute of prognostic technologies, in which we estimate the End-Of-Life (EOL) and Remaining-Useful-Life (RUL) …
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Technology assessment of biomass ethanol : a multi-objective, life cycle approach under uncertainty
… Pareto curves, 3) explicit incorporation of uncertainty analysis using Bayesian updating, and 4) integration of multiple feedstocks, processes, and products, in a network optimization framework, with subsequent decomposition to more refined models, for an improvement assessment of specific …
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Decision support tools for environmentally conscious chemical process design
… performance do not necessarily imply uncertainty in decision-making. A series of computer-aided decision making tools have been developed to decrease the barriers to the use of environmental valuation functions in routine design activities. These tools include: uncertainty propagation …
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UNCERTAINTY QUANTIFICATION OF LANDSLIDE SUSCEPTIBILITY MAPPING USING BAYESIAN NETWORK
… strategies. To enhance the reliability of LSM, uncertainty in landslides characterization must be identified and quantified. There are longstanding and systematic uncertainties in LSM that remain unaddressed or inadequately resolved in the literature, including (1) the impact of boundary …
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Quantifying uncertainty in reliability block diagrams
… sources decrease and allow analysts to estimate uncertainty in model parameters describing driving component performance. Bayesian analysis accumulates these data into posterior distributions summarizing all available performance knowledge about driving components. Sampling-based uncertainty …
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Mass and Distance Estimation Simulations for the Nancy Grace Roman Space Telescope Using PyLIMASS and a Case Study on Intellectual Property Frameworks in Space Collaborations
… 40% of planetary events with better than 20% uncertainty, targeted simulations are essential. Using the pyLIMASS inference framework and Fisher matrix-based uncertainty propagation, I demonstrate that for the well-characterized event OGLE-2013-BLG-0132Lb, the lens mass can be constrained to …
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