Uncertainty Quantification in the Community Land Model
Abstract not provided.
Publications
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Jump to search filtersINFERENCE OF UNCERTAIN PARAMETERS IN CHEMICALMODELS
Proposed for publication in International Journal for Uncertainty Quantification.
Abstract not provided.
Bayesian Parameter Estimation with Partial Information
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Reacting Flow Modeling with Detailed Chemical Kinetics
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Challenges in Uncertainty Quantification and Model Validation
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Quantification of Uncertainty in Extreme Scale Computations (QUEST)
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Quantification of Uncertainty in Extreme Scale Computations (QUEST) - Handout
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Coupled Chemical Master Equation - Fokker Planck Solver for Stochastic Reaction Networks
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Efficient Surrogate Construction for High-Dimensional Climate Model
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Introductory slides for presentation to seminar: Quantification of Uncertainty in Extreme Scale Computations
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Quantification of Uncertainty in Extreme Scale Computations
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Quantification of Uncertainty in Extreme Scale Computations (QUEST)
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Uncertainty Quantification in Computational Models
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Quantifying Sampling Noise and Parametric Uncertainty in Coupled Atomistic-Continuum Simulations
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Analysis and Reduction of Power Grid Models under Uncertainty
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Data Free Inference in Computational Models
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Uncertainty Quantification in ClimateModeling
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Efficient Source Inversion Methodologies using Regional Transport Models
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Analysis of Uncertainty in Dynamical Systems
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Asymptotic Eigenvalue Distribution of Block Toeplitz Matrices Associated with Orthogonal Polynomials
Linear Algebra and its Applications
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Quantification of Uncertainty in Extreme Scale Computations (QUEST)
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Efficient uncertainty quantification methodologies for high-dimensional climate land models
In this report, we proposed, examined and implemented approaches for performing efficient uncertainty quantification (UQ) in climate land models. Specifically, we applied Bayesian compressive sensing framework to a polynomial chaos spectral expansions, enhanced it with an iterative algorithm of basis reduction, and investigated the results on test models as well as on the community land model (CLM). Furthermore, we discussed construction of efficient quadrature rules for forward propagation of uncertainties from high-dimensional, constrained input space to output quantities of interest. The work lays grounds for efficient forward UQ for high-dimensional, strongly non-linear and computationally costly climate models. Moreover, to investigate parameter inference approaches, we have applied two variants of the Markov chain Monte Carlo (MCMC) method to a soil moisture dynamics submodel of the CLM. The evaluation of these algorithms gave us a good foundation for further building out the Bayesian calibration framework towards the goal of robust component-wise calibration.
Bayesian Quantification of Uncertainty in Systems with Intrinsic Noise
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Bayesian Quantification of Uncertainty in Systems with Intrinsic Noise
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Propagating Uncertainty from Simulation Parameters and Sampling Noise through Coupled Atomistic-to-Continuum Systems
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Uncertainty Quantification
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Quantification of Uncertainty in Extreme Scale Computations (QUEST)
Abstract not provided.
Quantification of Uncertainty in Extreme Scale Computations (QUEST)
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Uncertainty Quantification in Reacting Flow
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Uncertainty Quantication in Climate Modeling
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Uncertainty Quantification in Computational Models
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Uncertainty Quantification given Discontinuities Long-tailed Distributions and Computationally Intensive Models
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Role and Impact of Uncertainty Quantification in the Coming Decade
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Uncertainty Quantification in Reacting Flow
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Computational Singular Perturbation with Non-Parametric Tabulation of Slow Manifolds for Time Integration of Stiff Chemical Kinetics
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A high-order AMR algorithm for chemically reacting flows
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Uncertainty Quantification in Multiscale Atomistic-Continuum Models
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TChem - A Software Toolkit for the Analysis of Complex Kinetic Models
The TChem toolkit is a software library that enables numerical simulations using complex chemistry and facilitates the analysis of detailed kinetic models. The toolkit provide capabilities for thermodynamic properties based on NASA polynomials and species production/consumption rates. It incorporates methods that can selectively modify reaction parameters for sensitivity analysis. The library contains several functions that provide analytically computed Jacobian matrices necessary for the efficient time advancement and analysis of detailed kinetic models.
Uncertainty Quantification in Computational Models
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Uncertainty Quantification in Reacting Flow
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Analysis and Reduction of a Simplified Stochastic Chemical System via CSP
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Analysis of Chemical Structure using CSP applied to Triple Flames of Methane and n-Heptane
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SciDAC Institute QUEST (Quantification of Uncertainty in Extreme Scale Computations)
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Uncertainty Quantification in Reacting Flow
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High-order AMR computations of chemically reacting flows
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Uncertainty Quantification given Discontinuities Long-tailed Distributions and Computationally Intensive Models
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Stochastic Atomistic-to-Continuum Coupling using Bayesian inference
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High-order AMR computations of chemically reacting flows
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Analysis of Uncertain Dynamical Network Models
Abstract not provided.
Uncertainty Quantification in Reacting Flow
Abstract not provided.
Results 301–350 of 433