Browsing by Subject "Uncertainty Quantification"
Now showing items 1-20 of 26
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Adjoint-Based Uncertainty Quantification and Sensitivity Analysis for Reactor Depletion Calculations (2013-08-02)Depletion calculations for nuclear reactors model the dynamic coupling between the material composition and neutron flux and help predict reactor performance and safety characteristics. In order to be trusted as reliable ...
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(2016-07-28)The accurate modeling of complex physical phenomena, such as radiation transport in a laboratory experiment or a nuclear reactor, challenges the limits of modern computing resources and helps drive the requirement for ...
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Counting the number of objects from images has become an increasingly important topic in different applications, such as crowd counting, cell microscopy image analyses in biomedical imaging, and horticulture monitoring and ...
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(2022-04-19)Additive manufacturing (AM) is a disruptive technology leveraging innovations of the past and present to enable the design and fabrication of the new standard for components across industries. However, the successful ...
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(2013-08-08)This study presents different aspects on the use of deterministic methods including Artificial Neural Networks (ANNs), and linear and nonlinear regression, as well as probabilistic methods including Bayesian inference and ...
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Distribution Optimal Importance Weights For Efficient Uncertainty Propagation Through Model Chains (2019-11-12)This thesis proposes a least squares formulation to determine a set of empirical importance weights to achieve a change of probability measure. The objective of the thesis is to estimate statistics from a target distribution ...
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(2022-04-01)Uncertainty Quantification (UQ) and its subsequent propagation are powerful tools for estimating material property and performance distributions. As the paradigm of materials discovery within an Integrated Computational ...
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(2017-12-01)The Consortium for Advanced Simulation of LightWater Reactors (CASL) is working towards developing a virtual reactor called the Virtual Environment for Reactor Application (VERA). As part of this work, computational fluid ...
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(2012-02-14)Modern reservoir management typically involves simulations of geological models to predict future recovery estimates, providing the economic assessment of different field development strategies. Integrating reservoir data ...
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(2016-05-24)The study of thermal radiative transfer in the high energy density regime is important to the National Nuclear Security Administration, and experiments are an important component of such studies. Strong non-linear coupling ...
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(2009-05-15)Uncertainty quantification involves sampling the reservoir parameters correctly from a posterior probability function that is conditioned to both static and dynamic data. Rigorous sampling methods like Markov Chain Monte ...
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(2020-10-13)Current interest in verification, validation, and uncertainty quantification (VVUQ) has increased substantially over the past 30 years with increased awareness of potential inaccuracies of numerical simulations. This ...
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(2011-02-22)The Method of Manufactured Universes is presented as a validation framework for uncertainty quantification (UQ) methodologies and as a tool for exploring the effects of statistical and modeling assumptions embedded in ...
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(2016-08-01)An energy producer must determine optimal energy investment strategies in order to maximize the value of its energy portfolio. Determining optimal investment strategies is challenging. One of the main challenges is the ...
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(2017-05-09)While the growing number of computational models available to designers can solve a lot of problems, it complicates the process of properly utilizing the information provided by each simulator. It may seem intuitive to ...
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(2015-11-05)In this dissertation, we focus on the uncertainty quantification problems in sub-surface flow models which can be computationally demanding because of the large number of unknowns in forward simulations. First, we propose a ...
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(2021-06-29)This work presents a model-order reduction approach for parametric multiphysics problems. The developed method utilizes the intrusive Proper Orthogonal Decomposition aided Reduced Basis technique (POD-RB) which builds ...
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(Springer, 2018-03-19)Metal additive manufacturing (AM) typically suffers from high degrees of variability in the properties/performance of the fabricated parts, particularly due to the lack of understanding and control over the physical ...
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(2014-12-15)Codes for accurately simulating the core composition changes for nuclear reactors have developed as computing technology developed. The desire to understand neutronics, material compositions, and reactor parameters as a ...
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(2023-03-23)Climate disasters have severely impacted our built environment, infrastructure, and way of life, causing significant economic and fatal losses. In the immediate aftermath of a disaster, preliminary damage assessment (PDA) ...