Browsing by Subject "uncertainty quantification"
Now showing items 1-18 of 18
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(2022-12-08)The simulation of radiation neutron transport involves a complex system of partial differential equations. Methods in solving these systems of equations can be categorized into two areas of concern, stochastic and ...
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(2013-04-09)Identification of material properties has been highly discussed in recent times thanks to better technology availability and its application to the field of experimental mechanics. Bayesian approaches as Markov-chain Monte ...
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(2020-11-13)Alpha-beta network is a mixture of deep neural networks, implementing a mixture of experts, where each component is a neural network. It is trained using the expectation-maximization algorithm. It enables context-awareness ...
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(2013-07-26)Recent developments in instrumentation, communication and software have enabled the integration of real-time data into the decision-making process of hydrocarbon production. Applications of real-time data integration in ...
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(2019-05-02)Uncertainty propagation through coupled multiphysics systems is often intractable due to computational expense. In this work, we present a novel methodology to enable uncertainty analysis of expensive coupled systems. The ...
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(2016-06-17)The one megawatt TRIGA reactor at Texas A&M has various methods of irradiating samples, but one of the most unique dose positions is severely underutilized. This irradiation cell is a large space where samples may be placed ...
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(2019-04-09)One of the most commonly used methods for quantifying fluid velocity profiles is particle image velocimetry (PIV). This non-invasive measurement technique employs seeding particles in a transparent simulant fluid flowing ...
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(2015-05-04)Hydraulic stimulation of low permeability rocks in unconventional reservoirs has been observed to trigger microearthquakes (MEQs). Triggering of the MEQ events has been linked to the pore pressure, temperature, and in-situ ...
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(2016-04-18)The study was initiated to develop more accurate well cost estimations for drilling and completion Authorization for Expenditures (AFE). Specifically, a privately funded company (Company A) is interested in analyzing ...
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(2022-08-18)Artificial Intelligent and Machine Learning (AI/ML) systems have been widely adopted with the increasing availability of data in a variety of applications such as computer vision, activity recognition, autonomous driving, ...
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(2012-10-19)Recently there has been growing interest to characterize and reduce uncertainty in stochastic dynamical systems. This drive arises out of need to manage uncertainty in complex, high dimensional physical systems. Traditional ...
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(2019-10-31)Nuclear thermal propulsion (NTP) designs include large margins for manufacturing, thermal, and neutronic uncertainties. In the past these uncertainties could be better understood through rapid design and experimental ...
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(2021-12-08)Proteins are the workhorse molecules of lives. Understanding how proteins function is one of the most fundamental problems in molecular biology, which can drive a plethora of biological and pharmaceutical applications. ...
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(2013-12-06)The thermal neutron scattering cross sections of ZrHx are heavily affected by the solid frequency distributions, also called “phonon spectra”, of Zr and H in ZrHx. The phonon spectra are different for ZrHx with different ...
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(2016-05-19)The importance of uncertainty quantification and risks assessment in the petroleum industry cannot be overstated. Uncertainty will always be present in production forecasts and reserves estimates. Underestimation of ...
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(2018-05-04)Laser Powder-Bed Fusion processes capable of processing metallic materials are a set of relatively new and emerging Additive Manufacturing technologies that offer attractive potential and capabilities (e.g., design freedom, ...
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(2012-10-19)In this dissertation, we focus on the uncertainty quantification problems where the goal is to sample the porous media properties given integrated responses. We first introduce a reduced order model using the level set ...
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(2015-08-10)Classical statistical models encounter the computational bottleneck for large spatial/spatio-temporal datasets. This dissertation contains three articles describing computationally efficient approximation methods for ...