Timothy Michael Wildey

Anh Tran, Pieterjan Magda M Robbe, Timothy Michael Wildey, David Montes de Oca Zapiain, Hojun Lim, (2022). The multifaceted uncertainty nature of structure-property linkage with crystal plasticity finite element model AIAA SciTech Forum Document ID: 1677522

Tian Yu NMN Yen, Timothy Michael Wildey, (2022). Leveraging Physics-based Surrogates for Efficient Density Estimation of Sparse Observable Data on Low-dimensional Manifolds SIAM Texas-Lousiana Section Meeting Document ID: 1675224

Kelsey DiPietro, Timothy Michael Wildey, Denis Ridzal, (2022). Extreme-scale Electromagnetics for Design and Control of Metamaterials Trilinos User-Developer Meeting Document ID: 1663906

Gianluca Geraci, Timothy Michael Wildey, Tian Yu NMN Yen, Daniele Schiavazzi, Mahammad Motamed, (2022). Multi-fidelity information fusion with data-driven models in computational applications 17th U.S. National Congress on Computational Mechanics Document ID: 1653176

Anh Tran, Timothy Michael Wildey, Hojun Lim, (2022). Uncertainty Quantification of Constitutive Models in Crystal Plasticity Finite Element Method TMS Materials Science & Technology Document ID: 1652576

Timothy Michael Wildey, (2022). Estimating Aleatoric and Epistemic Uncertainty in Solutions to Stochastic Inverse Problems Using Machine Learning Surrogate Models SIAM Conference on the Mathematics of Data Science Document ID: 1641279

Tian Yu NMN Yen, Timothy Michael Wildey, (2022). Constructing Data-consistent Solutions to Stochastic Inverse Problems with Sparse Observable Data SIAM Conference on Mathematics of Data Science Document ID: 1641439

Graham Bennett Harper, Timothy Michael Wildey, (2022). Data Compression Techniques for Large-Scale Memory-Bound Finite Element Applications SIAM Mathematics of Data Science 2022 Document ID: 1630735

Michael S. Eldred, Brian M. Adams, Gianluca Geraci, Teresa Portone, Elliott Marshall Ridgway, John Adam Stephens, Timothy Michael Wildey, (2022). Deployment of Multifidelity Uncertainty Quantification for Thermal Battery Assessment; Part I: Algorithms and Single Cell Results https://www.osti.gov/search/identifier:1885882 Document ID: 1618639

Anh Tran, Timothy Michael Wildey, Hojun Lim, (2022). Microstructure-Sensitive UQ for Materials Constitutive Models in Crystal Plasticity Finite Element Method USACM Thematic Conference on Uncertainty Quantification for Machine Learning Integrated Physics Modeling (UQ-MLIP) Document ID: 1595518

Bryan William Reuter, Timothy Michael Wildey, (2022). Synchronous and Asynchronous Time Integration for Multiscale Simulations Using Hybridized Finite Element Methods 15th World Congress on Computational Mechanics Document ID: 1573853

Tian Yu NMN Yen, Timothy Michael Wildey, (2022). Using Manifold Learning to Enable Computationally Efficient Stochastic Inversion with High-dimensional Data Wccm-apcom 2022 Document ID: 1573846

Timothy Michael Wildey, Gianluca Geraci, Michael S. Eldred, John Davis Jakeman, Owen Davis, Teresa Portone, Tian Yu NMN Yen, Bryan William Reuter, Alex Gorodetsky, Ahmad Rushdi, Daniele Schiavazzi, Lauren Partin, (2022). Embedded uncertainty estimation for data-driven surrogates to enable trustworthy ML for UQ Machine Learning and Deep Learning Conference Document ID: 1573362

Anh Tran, Timothy Michael Wildey, Hojun Lim, (2022). Microstructure-sensitive uncertainty quantification for crystal plasticity finite element constitutive models using stochastic collocation methods Frontiers in Materials Document ID: 1540494

Bryan William Reuter, Gianluca Geraci, Timothy Michael Wildey, Michael S. Eldred, (2022). Multifidelity Uncertainty Quantification For Non-Deterministic Models ECCOMAS Congress 2022 Document ID: 1539856

Anh Tran, Pieterjan Magda M Robbe, Timothy Michael Wildey, Guy Leshem Bergel, David Montes de Oca Zapiain, Hojun Lim, (2022). Multifaceted uncertainty quantification in crystal plasticity finite element model AIAA Science and Technology Forum and Exposition Document ID: 1539527

Bryan William Reuter, Gianluca Geraci, Timothy Michael Wildey, (2022). Efficient Multifidelity Strategies for Uncertainty Quantification of Non-Deterministic Models Siam Uq 2022 Document ID: 1494559

Timothy Michael Wildey, Troy Butler, Tian Yu NMN Yen, (2022). A Probabilistic Characterization of Aleatoric and Epistemic Uncertainty in Solutions to Stochastic Inverse Problems Using Machine Learning Surrogate Models SIAM Conference on Uncertainty Quantification Document ID: 1504576

Tian Yu NMN Yen, Timothy Michael Wildey, Troy Butler, (2022). Quantifying Aleatoric and Epistemic Uncertainties in RLC Circuits with Data-consistent Inversion SIAM Conference on Uncertainty Quantification Document ID: 1504683

Anh Tran, Timothy Michael Wildey, (2022). Solving inverse problems in process-structure-property linkage with Gaussian process regression TMS World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022) Document ID: 1493809

Anh Tran, Jing Sun, Dehao Liu, Yan Wang, Timothy Michael Wildey, (2022). A stochastic reduced-order model for statistical microstructure descriptors evolution ASME Journal of Computing and Information Science in Engineering Document ID: 1481862

Bryan William Reuter, Timothy Michael Wildey, (2022). Efficient Implicit-Explicit Time Integration for Multiscale Simulations Using Hybridized Finite Element Methods 15th World Congress on Computational Mechanics Document ID: 1426500

Bryan William Reuter, Gianluca Geraci, Timothy Michael Wildey, Michael S. Eldred, (2021). Multifidelity Uncertainty Quantification For Non-Deterministic Models ECCOMAS Congress 2022 Document ID: 1405431

Timothy Michael Wildey, (2021). Adaptive Concurrent Multiscale Modelling Using Hybridized Discretizations, Error Estimation and Machine Learning 15th World Congress on Computational Mechanics Document ID: 1392929

Anh Tran, Michael S. Eldred, Timothy Michael Wildey, Scott McCann, Jing Sun, Robert Visintainer, (2021). aphBO-2GP-3B: A budgeted asynchronous parallel multi-acquisition functions for constrained Bayesian optimization on high-performing computing architecture Structural and Multidisciplinary Optimization Document ID: 1370404

Tian Yu NMN Yen, Timothy Michael Wildey, (2021). Using Manifold Learning to Enable Computationally Efficient Stochastic Inversion with High-dimensional Data 15th World Congress on Computational Mechanics Document ID: 1392127

Bryan William Reuter, Gianluca Geraci, Timothy Michael Wildey, (2021). Efficient Multifidelity Strategies for Uncertainty Quantification of Non-Deterministic Models SIAM Conference on Uncertainty Quantification (UQ22) Document ID: 1369347

Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman, Teresa Portone, Timothy Michael Wildey, Ahmad Rushdi, Daniel Thomas Seidl, (2021). The Dakota Project: Connecting the Pipeline from Uncertainty Quantification R&D to Mission Impact NASA Langley HPC Seminar Series Document ID: 1369333

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, Anh Tran, (2021). Solving Stochastic Inverse Problems for Property-Structure Relationships in Computational Materials Science US National Congress on Computational Mechanics Document ID: 1342636

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, (2021). Combining Measure Theory and Bayes? Rule to Solve a Stochastic Inverse Problem Emi/pmc 2021 https://www.osti.gov/search/identifier:1877851 Document ID: 1294038

Anh Tran, Timothy Michael Wildey, (2021). Solving inverse problems for process-structure linkages using asynchronous parallel Bayesian optimization TMS 2021 Annual Meeting & Exhibition https://www.osti.gov/search/identifier:1854075 Document ID: 1279877

Anh Tran, Julien Guy Tranchida, Timothy Michael Wildey, Aidan P. Thompson, (2021). Multi-fidelity ML/UQ and Bayesian Optimization for Materials Design: Application to Ternary Random Alloys TMS 2021 Annual Meeting & Exhibition (TMS2021) https://www.osti.gov/search/identifier:1853874 Document ID: 1280006

Anh Tran, Timothy Michael Wildey, (2021). Solving stochastic inverse problems for property-structure linkage using data-consistent inversion and ML TMS 2021 Annual Meeting & Exhibition https://www.osti.gov/search/identifier:1848050 Document ID: 1279878

Timothy Michael Wildey, Lukas Bruder, Michael Gee, (2021). Data-consistent Solutions To Stochastic Inverse Problems Using A Probabilistic Multi-fidelity Method Based On Conditional Densities International Journal for Uncertainty Quantification https://www.osti.gov/search/identifier:1769923 Document ID: 1279530

Anh Tran, Timothy Michael Wildey, (2020). Solving stochastic inverse problems for property-structure linkages using data-consistent inversion and machine learning Jom https://www.osti.gov/search/identifier:1760459 Document ID: 1208830

Anh Tran, Timothy Michael Wildey, (2020). Solving stochastic inverse problems for structure-property linkages using data-consistent inversion TMS 2021 Annual Meeting & Exhibition https://www.osti.gov/search/identifier:1825594 Document ID: 1208926

Anh Tran, Timothy Michael Wildey, (2020). Solving inverse problems for process-structure linkages using asynchronous parallel Bayesian optimization TMS 2021 Annual Meeting & Exhibition https://www.osti.gov/search/identifier:1825595 Document ID: 1208927

Anh Tran, Theron Rodgers, Timothy Michael Wildey, (2020). Reification of latent microstructures: On supervised, unsupervised, and semi-supervised deep learning applications for microstructures in materials informatics https://www.osti.gov/search/identifier:1673174 Document ID: 1207587

Julien Guy Tranchida, Anh Tran, Timothy Michael Wildey, Aidan P. Thompson, (2020). Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloys The Journal of Chemical Physics Document ID: 1184315

Anh Tran, Timothy Michael Wildey, Theron Rodgers, (2020). On supervised and unsupervised deep learning applications for materials informatics Sandia Machine Learning and Deep Learning Workshop https://www.osti.gov/search/identifier:1812467 Document ID: 1183452

Julien Guy Tranchida, Aidan P. Thompson, Anh Tran, Timothy Michael Wildey, (2020). Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloys Sandia MLDL Workshop Document ID: 1172695

Anh Tran, Timothy Michael Wildey, Julien Guy Tranchida, Aidan P. Thompson, (2020). Multi-fidelity machine-learning with uncertainty quantification for materials design: Application to ternary random alloys arXiv https://www.osti.gov/search/identifier:1670182 Document ID: 1138817

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, (2020). Optimal Experimental Design for Prediction Based on Push-forward Probability Measures Journal of Computational Physics https://www.osti.gov/search/identifier:1630281 Document ID: 1127990

Timothy Michael Wildey, Nathan Garland, Hyun-Kyung Chung, Christopher Fontes, Mark Zammit, James Colgan, Todd Elder, Christopher McDevitt, Xian-Zhu Tang, (2020). Impact of a minority relativistic electron tail interacting with a thermal plasma containing high-atomic-number impurities Physics Review Letters Document ID: 1126935

Anh Tran, John A. Mitchell, Laura Painton Swiler, Timothy Michael Wildey, (2020). An active learning high-throughput microstructure calibration framework for solving inverse structure-process problems in materials informatics Acta Materialia https://www.osti.gov/search/identifier:1634790 Document ID: 1126840

Anh Tran, Jing Sun, Yan Wang, Dehao Liu, Timothy Michael Wildey, (2020). Multiscale stochastic reduced-order model for uncertainty propagation using Fokker-Planck equation with microstructure evolution applications arXiv preprint https://www.osti.gov/search/identifier:1834331 Document ID: 1115314

Anh Tran, Timothy Michael Wildey, John Furlan, Pagalthivarthi Krishnan, Robert Visintainer, Scott McCann, (2020). aphBO-2GP-3B: A budgeted asynchronously-parallel multi-acquisition for known/unknown constrained Bayesian optimization on high-performing computing architecture arXiv https://www.osti.gov/search/identifier:1834333 Document ID: 1104752

Timothy Michael Wildey, Troy Butler, Tian Yu Yen, (2020). Data-consistent Inversion For Stochastic Input-to-output Maps Inverse Problems https://www.osti.gov/search/identifier:1619228 Document ID: 1104293

Anh Tran, Timothy Michael Wildey, Scott McCann, (2020). sMF-BO-2CoGP: A sequential multi-fidelity constrained Bayesian optimization framework for design applications ASME Journal of Computing and Information Science in Engineering https://www.osti.gov/search/identifier:1605731 Document ID: 1104117

Timothy Michael Wildey, Troy Butler, Wenjuan Zhang, (2020). Convergence of Probability Densities using Approximate Models for Forward and Inverse Problems in Uncertainty Quantification: Extensions to Lp SIAM/ASA Journal on Uncertainty Quantification https://www.osti.gov/search/identifier:1595429 Document ID: 1078791

Anh Tran, Timothy Michael Wildey, (2019). Materials informatics: data-driven, materials design, and uncertainty quantification perspectives SNL 13th annual postdoc technical showcase https://www.osti.gov/search/identifier:1643479 Document ID: 1067454

Timothy Michael Wildey, Lukas Bruder, Tan Bui-Thanh, Troy Butler, John Davis Jakeman, Brad Marvin, Anh Tran, Scott Walsh, (2019). Moving Beyond Forward Simulation to Enable Data-informed Physics-based Predictions Colloquium at University of Colorado – Denver https://www.osti.gov/search/identifier:1646273 Document ID: 1055964

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, (2019). Convergence of Probability Densities using Approximate Models for Forward and Inverse Problems in Uncertainty Quantification AMS Fall Southeastern Sectional Meeting https://www.osti.gov/search/identifier:1641989 Document ID: 1020264

Anh Tran, Timothy Michael Wildey, Scott McCann, (2019). sBF-BO-2CoGP: A sequential bi-fidelity constrained Bayesian optimization for design applications International Design Engineering Technical Conferences & Computers and Information in Engineering Conference https://www.osti.gov/search/identifier:1641650 Document ID: 998371

Anh Tran, Timothy Michael Wildey, Scott McCann, (2019). A sequential bi-fidelity constrained Bayesian optimization for design applications ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference https://www.osti.gov/search/identifier:1641565 Document ID: 997895

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, Lukas Bruder, (2019). Solving Stochastic Inverse Problems using Approximate Push-forward Densities based on a Multi-fidelity Monte Carlo Method 9th International Congress on Industrial and Applied Mathematics https://www.osti.gov/search/identifier:1641047 Document ID: 985120

Timothy Michael Wildey, Anh Tran, (2019). Using High Performance Computing to Enable Data-informed Multiscale Modeling with Applications to Additive Materials Engineering Mechanics Institute Conference https://www.osti.gov/search/identifier:1640837 Document ID: 974059

Anh Tran, Yan Wang, Timothy Michael Wildey, (2019). A step towards a versatile Bayesian optimization: constrained, asynchronous batch-parallel, multi-fidelity, and mixed-integer extensions MUMS Transition Workshop and SPUQ https://www.osti.gov/search/identifier:1640079 Document ID: 961404

Daniel Thomas Seidl, Bart G van Bloemen Waanders, Timothy Michael Wildey, (2019). Simultaneous Inversion of Shear Modulus and Traction Boundary Conditions in Biomechanical Imaging Inverse Problems in Science and Engineering https://www.osti.gov/search/identifier:1515211 Document ID: 948096

Timothy Michael Wildey, Alex Gorodetsky, Anca Belme, John N. Shadid, (2019). Robust Uncertainty Quantification Using Response Surface Approximations Of Discontinuous Functions International Journal for Uncertainty Quantification https://www.osti.gov/search/identifier:1559480 Document ID: 948910

Timothy Michael Wildey, (2019). Exploiting Low-dimensional Structure to Efficiently Perform Stochastic Inference for Prediction SIAM Conference on Computational Science and Engineering https://www.osti.gov/search/identifier:1601938 Document ID: 925364

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, Tan Bui-Thanh, Brad Marvin, Lukas Bruder, (2019). Developing Scalable and Multi-fidelity Approaches for Push-forward Based Inference DOE ASCR Applied Mathematics PI Meeting https://www.osti.gov/search/identifier:1596420 Document ID: 913330

Anh Tran, John M. Furlan, Krishnan V. Pagalthivarthi, Robert J. Visintainer, Timothy Michael Wildey, Yan Wang, (2019). WearGP: A computationally efficient machine learning framework for local erosive wear predictions via nodal Gaussian processes Wear https://www.osti.gov/search/identifier:1492797 Document ID: 902478

Daniel Thomas Seidl, Bart G van Bloemen Waanders, Timothy Michael Wildey, (2018). Simultaneous Inversion of Heterogeneous Traction Boundary Conditions and Shear Modulus in Soft Biomaterials Annual Conference and Exposition on Experimental and Applied Mechanics Document ID: 888804

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, (2018). The Consistent Bayesian Approach for Stochastic Inverse Problems AMS Fall Southeastern Sectional Meeting https://www.osti.gov/search/identifier:1592669 Document ID: 888504

Timothy Michael Wildey, Brad Marvin, Tan Bui-Thanh, (2018). Scalable Approximations for the Consistent Bayes Method SIAM TX-LA Section Meeting https://www.osti.gov/search/identifier:1594647 Document ID: 876493

Timothy Michael Wildey, SRIRAMKRISHNAN MURALIKRISHNAN, Tan Bui-Thanh, (2018). Unified Geometric Multigrid Algorithm For Hybridized High-order Finite Element Methods SIAM Journal on Scientific Computing https://www.osti.gov/search/identifier:1595039 Document ID: 854326

Timothy Michael Wildey, (2018). Overview of Forward and Inverse Uncertainty Quantification Methods BOUT++ Workshop https://www.osti.gov/search/identifier:1581941 Document ID: 842966

John Davis Jakeman, Troy Butler (University of Colorado Denver), Michael S. Eldred, Gianluca Geraci, Alex Gorodetsky (University of Michigan), Timothy Michael Wildey, (2018). Adaptive multi-index collocation for quantifying uncertainty 5th Workshop on Sparse Grids and Applications https://www.osti.gov/search/identifier:1806541 Document ID: 831137

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, Brad Marvin, (2018). Consistent Bayesian Inference with Push-forward Measures: Scalable Implementations and Applications SIAM Annual Meeting https://www.osti.gov/search/identifier:1567818 Document ID: 830217

Troy Butler, John Davis Jakeman, Timothy Michael Wildey, (2018). Convergence of Probability Densities using Approximate Models for Forward and Inverse Problems in Uncertainty Quantification SIAM Journal on Scientific Computing https://www.osti.gov/search/identifier:1479491 Document ID: 819775

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, (2018). Combining Measure Theory and Bayes Rule to Solve a Stochastic Inverse Problem Center for Computing Research, Summer Seminar Series Document ID: 808781

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, Daniel Thomas Seidl, Bart G van Bloemen Waanders, (2018). Data-informed Multiscale Modeling of Additive Materials Engineering Mechanics Institute Conference 2018 https://www.osti.gov/search/identifier:1523778 Document ID: 807805

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, Scott Walsh, (2018). Optimal Experimental Design for Prediction Using a Consistent Bayesian Approach SIAM Conference on Uncertainty Quantification https://www.osti.gov/search/identifier:1507835 Document ID: 784746

Daniel Thomas Seidl, Bart G van Bloemen Waanders, Timothy Michael Wildey, (2018). Multiscale Interfaces for Large Scale Optimization SIAM Conference on Uncertainty Quantification https://www.osti.gov/search/identifier:1525680 Document ID: 784306

Pavel B. Bochev, Peter Andrew Bosler, Karen D. Devine, Mauro Perego, Kara J. Peterson, Andrew G. Salinger, John N. Shadid, Erik Gunnar Boman, Scott A. Mitchell, Timothy Michael Wildey, (2018). Slides for Presentation to Steve Lee Visit to SNL by Steve Lee Document ID: 772191

R. Allen Roach, Bradley Howell Jared, Adam Cook, David M Keicher, Bart G van Bloemen Waanders, Laura Painton Swiler, Daniel Thomas Seidl, Timothy Michael Wildey, Shaun R Whetten, (2018). Born Qualified EAB Telecon BQ EAB Telecon https://www.osti.gov/search/identifier:1514821 Document ID: 739323

Timothy Michael Wildey, (2017). Challenges and Opportunities for Predictive Multi-scale Modeling on Exascale Computing Systems Invited Presentation in Colorado State Math Department Document ID: 725967

Timothy Michael Wildey, Troy Butler, (2017). Utilizing Adjoint-Based Error Estimates for Surrogate Models to Accurately Predict Probabilities of Events International Journal for Uncertainty Quantification https://www.osti.gov/search/identifier:1429672 Document ID: 703844

Daniel Thomas Seidl, Paul (BU) Barbone, Assad (RPI) Oberai, Timothy Michael Wildey, Bart G van Bloemen Waanders, (2017). PDE-Constrained Optimization for Heterogeneous Mechanical Property Estimation of Biomaterials International Digital Image Correlation Society 2017 Conference & Workshop Document ID: 671953

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, (2017). A Consistent Bayesian Approach for Solving Stochastic Inverse Problems ASCR Applied Math PI Meeting https://www.osti.gov/search/identifier:1469097 Document ID: 671501

Timothy Michael Wildey, John Davis Jakeman, Troy Butler, (2017). Advancing Beyond Interpretive Simulation to Inference for Prediction ASCR Applied Math PI Meeting https://www.osti.gov/search/identifier:1467988 Document ID: 670692

Timothy Michael Wildey, Bart G van Bloemen Waanders, Daniel Thomas Seidl, (2017). Adaptive Multiscale Modeling Using Generalized Mortar Methods US National Congress on Computational Mechanics https://www.osti.gov/search/identifier:1513505 Document ID: 637802

Matthias Mayr, Eric Christopher Cyr, John N. Shadid, Roger P. Pawlowski, Timothy Michael Wildey, Guglielmo Scovazzi, Xianyi Zeng, Edward Geoffrey Phillips, Sidafa Conde, (2017). Implicit-Explicit (IMEX) Time Integration for CFD & Multi-Physics Problems Mechanics & High Performance Computing Seminar https://www.osti.gov/search/identifier:1458227 Document ID: 625704

Matthias Mayr, Eric Christopher Cyr, John N. Shadid, Roger P. Pawlowski, Timothy Michael Wildey, Guglielmo Scovazzi, Xianyi Zeng, Edward Geoffrey Phillips, Sidafa Conde, (2017). Implicit-Explicit (IMEX) Time Integration for Multi-Physics: Application to ALE-based CFD Simulations VII International Conference on Coupled Problems in Science and Engineering https://www.osti.gov/search/identifier:1458228 Document ID: 625705

Timothy Michael Wildey, Bart G van Bloemen Waanders, Daniel Thomas Seidl, (2017). Multiscale Modeling Using Mortar Methods Engineering Mechanics Institute Conference https://www.osti.gov/search/identifier:1458195 Document ID: 625646

Scott Walsh (UC Denver), Timothy Michael Wildey, John Davis Jakeman, (2017). OptimalExperimental Design Using A Consistent Bayesian Approach ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part BMechanical Engineering https://www.osti.gov/search/identifier:1478379 Document ID: 623516

Daniel Thomas Seidl, Bart G van Bloemen Waanders, Timothy Michael Wildey, (2017). Multiscale Interfaces for Large Scale Optimization Optimization Under Uncertainty and Data-Driven Science and Engineering Workshop https://www.osti.gov/search/identifier:1456522 Document ID: 612151

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, Scott Walsh, (2017). A Consistent Bayesian Approach for Stochastic Inverse Problems Based on Push-forward Measures CCM Seminar – Department of Mathematical and Statistical Science – UC-Denver Document ID: 611679

Timothy Michael Wildey, Troy Butler, John Davis Jakeman, (2017). A Consistent Bayesian Formulation for Stochastic Inverse Problems Based on Push-forward Measures SIAM Journal on Scientific Computing https://www.osti.gov/search/identifier:1469654 Document ID: 611451

Eric Christopher Cyr, John N. Shadid, Timothy Michael Wildey, Edward Geoffrey Phillips, Allen C. Robinson, Roger P. Pawlowski, (2017). A Monolithic Arbitrary Lagrangian Eulerian Implicit-Explicit (IMEX) Method Multimat Document ID: 599626

Bart G van Bloemen Waanders, Timothy Michael Wildey, Daniel Thomas Seidl, Harriet Li, (2017). Multiscale optimization under uncertainty for additive manufacturing SIAM Conference on Computational Science and Engineering https://www.osti.gov/search/identifier:1426379 Document ID: 599475

Timothy Michael Wildey, John Davis Jakeman, Troy Butler, (2017). Efficient Sampling Strategies for the Consistent Bayesian Approach for Solving Stochastic Inverse Problems SIAM Conference on Computational Science and Engineering https://www.osti.gov/search/identifier:1425298 Document ID: 589385

Bart G van Bloemen Waanders, Timothy Michael Wildey, Daniel Thomas Seidl, Harriet Li, (2017). Multiscale optimization under uncertainty Pioneer Natural Resources, Oak Ridge National Laboratories, and Sandia National Laboratories Workshop https://www.osti.gov/search/identifier:1458249 Document ID: 589318

Daniel Thomas Seidl, Bart G van Bloemen Waanders, Timothy Michael Wildey, (2017). Simultaneous Estimation of Material Parameters and Neumann Boundary Conditions in a Linear Elastic Model by PDE-Constrained Optimization Siam Cse 2017 https://www.osti.gov/search/identifier:1458297 Document ID: 577926

Thomas M. Smith, John N. Shadid, Eric Christopher Cyr, Roger P. Pawlowski, Timothy Michael Wildey, (2016). Stabilized FE Simulation of Prototype Thermal-Hydraulics Problems with Integrated Adjoint-based Capabilities for %Error-estimation, Sensitivity Analysis and UQ Journal of Computational Physics https://www.osti.gov/search/identifier:1338379 Document ID: 207904

Eric Christopher Cyr, John N. Shadid, Timothy Michael Wildey, Edward Geoffrey Phillips, Allen C. Robinson, Sean Miller, Roger P. Pawlowski, (2016). Implicit-Explicit (IMEX) Time Integration for Multi-Physics: Application to ALE and Plasma Simulation Necdc https://www.osti.gov/search/identifier:1401944 Document ID: 531600

Timothy Michael Wildey, John Davis Jakeman, Troy Butler, (2016). A Consistent Bayesian Approach for Stochastic Inverse Problems ICES Seminar Document ID: 531497

Timothy Michael Wildey, John N. Shadid, Eric Christopher Cyr, Jehanzeb Chaudry, (2016). Adjoint Enhanced Methods for Uncertainty Quantification of Multiphysics Applications Nuclear Explosive Code Developers Conference (NECDC) https://www.osti.gov/search/identifier:1400047 Document ID: 531530

Eric Christopher Cyr, John N. Shadid, Timothy Michael Wildey, Allen C. Robinson, Edward Geoffrey Phillips, Roger P. Pawlowski, (2016). Implicit-Explicit (IMEX) Time Integration for Multi-Physics: Application to ALE and Plasma Simulation Necdec Document ID: 475406

Timothy Michael Wildey, John N. Shadid, Eric Christopher Cyr, (2016). Adjoint Enhanced Methods for Uncertainty Quantification of Multiphysics Applications Nuclear Explosive Code Developers Conference (NECDC) https://www.osti.gov/search/identifier:1367627 Document ID: 475446

Eric Christopher Cyr, John N. Shadid, Timothy Michael Wildey, Allen C. Robinson, (2016). Implicit-Explicit (IMEX) Time Integration for Multi-Physics: Application to ALE and Plasma Simulation Necdec Document ID: 475341

Timothy Michael Wildey, John Davis Jakeman, Troy Butler, (2016). A Consistent Bayesian Approach for Stochastic Inverse Problems European Congress on Computational Methods in Applied Sciences and Engineering https://www.osti.gov/search/identifier:1368940 Document ID: 464115

Timothy Michael Wildey, Bart G van Bloemen Waanders, Daniel Thomas Seidl, (2016). Uncertainty Quantification for Multiscale Mortar Methods Probabilistic Mechanics and Reliability Conference https://www.osti.gov/search/identifier:1368791 Document ID: 453711

Brian Carnes, Steven W. Bova, Travis C. Fisher, V. Gregory Weirs, Timothy Michael Wildey, (2016). Discretization error transport for unstructured CFD ASME Verification and Validation Symposium https://www.osti.gov/search/identifier:1422082 Document ID: 443400

Timothy Michael Wildey, Bart G van Bloemen Waanders, Daniel Thomas Seidl, Todd Arbogast, Ben Ganis, Vivette Girault, Gergina Pencheva, Mary F Wheeler, Guangri Xue, Ivan Yotov, Simon Tavener, Martin Vohralik, (2016). Multiscale Mortar Methods: Theory, Applications and Future Directions Semiar at UNM https://www.osti.gov/search/identifier:1365248 Document ID: 432061

Bart G van Bloemen Waanders, Timothy Michael Wildey, Daniel Thomas Seidl, Harriet Li, (2016). Multiscale Optimization Under Uncertainty 14th Copper Mountain Conference on Iterative Methods https://www.osti.gov/search/identifier:1348106 Document ID: 430232

Timothy Michael Wildey, Eric Christopher Cyr, John N. Shadid, Bart G van Bloemen Waanders, Drew Philip Kouri, Joseph E. Bishop, Simon Tavener, Troy Butler, Serge Prudhomme, Clint Dawson, (2016). Utilizing Adjoint-Based Techniques to Improve the Accuracy and Reliability in Uncertainty Quantification Research Collaboration WorkshopOptimization and Uncertainty Quantification in Energy and Industrial Applications https://www.osti.gov/search/identifier:1345103 Document ID: 408643

Timothy Michael Wildey, John Davis Jakeman, (2015). Adaptive Bayesian Inference for Prediction https://www.osti.gov/search/identifier:1221574 Document ID: 321653

Timothy Michael Wildey, John N. Shadid, Eric Christopher Cyr, John Davis Jakeman, Troy Butler, (2015). Adjoint-Based a Posteriori Error Estimation and Uncertainty Quantification for Transient Nonlinear Problems with Discontinuous Solutions Numerical Methods for Large-Scale Nonlinear Problems and Their Applications https://www.osti.gov/search/identifier:1323036 Document ID: 320824

Eric T. Phipps, John R. Red-Horse, Timothy Michael Wildey, Paul Constantine, Roger Ghanem, Maarten Arnst, (2015). Stochastic Dimension Reduction of Multiphysics Systems through Measure Transformation ICERM Workshop on Numerical Methods for Large-Scale Nonlinear Problems and Their Applications https://www.osti.gov/search/identifier:1321810 Document ID: 320891

Timothy Michael Wildey, John Davis Jakeman, Troy Butler, Eric Christopher Cyr, John N. Shadid, (2015). Adjoint-Based a Posteriori Error Estimation and Uncertainty Quantification for Shock-Hydrodynamic Applications US National Congress on Computational Mechanics https://www.osti.gov/search/identifier:1279685 Document ID: 318828

Timothy Michael Wildey, John Davis Jakeman, Troy Butler, (2015). Utilizing Adjoint-based Error Estimates to Adaptively Resolve Response Surface Approximations International Conference on Adaptive Modeling and Simulation https://www.osti.gov/search/identifier:1256570 Document ID: 286409

Eric Christopher Cyr, John N. Shadid, Timothy Michael Wildey, David M. Hensinger, Allen C. Robinson, William J. Rider, Guglielmo (Duke) Scovazzi, (2015). IMEX Lagrangian Methods Coupled Problems 2015 https://www.osti.gov/search/identifier:1253301 Document ID: 275497

Timothy Michael Wildey, John N. Shadid, Eric Christopher Cyr, Paul Constantine, (2015). Enabling Efficient Uncertainty Quantification Using Adjoint-based Techniques https://www.osti.gov/search/identifier:1179153 Document ID: 264484

Travis C. Fisher, Steven W. Bova, V. Gregory Weirs, Timothy Michael Wildey, (2015). Propagating Discretization Error Estimates in Compressible Turbulent Flow Simulations Engineering Sciences External Review Poster Session https://www.osti.gov/search/identifier:1246879 Document ID: 243637

Timothy Michael Wildey, Eric Christopher Cyr, John N. Shadid, (2015). Utilizing Adjoint-Based Techniques to Effectively Perform UQ on Discontinuous Responses SIAM Conference on Computational Science and Engineering https://www.osti.gov/search/identifier:1246277 Document ID: 232332

Timothy Michael Wildey, Michael S. Eldred, Roy Edward Hogan, Kevin J. Dowding, (2014). Advanced UQ/QMU Methods for Abnormal Thermal Safety Studies Document ID: 155757

William J. Rider, Edward Love, Timothy Michael Wildey, (2014). Replacing Discon.nuous Functions in Limiters with Smooth Ones Nuclear Explosive Code Development Conference https://www.osti.gov/search/identifier:1241667 Document ID: 155600

Brian M. Adams, Lara E Bauman, William J. Bohnhoff, Keith Dalbey, John P. Eddy, Mohamed Salah Ebeida, Michael S. Eldred, Patricia D. Hough, Kenneth Hu, John Davis Jakeman, Laura Painton Swiler, John Adam Stephens, Dena Vigil, Timothy Michael Wildey, (2014). Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis Version 6.0 Users ManualVersion 6.0 Users Manual https://www.osti.gov/search/identifier:1177077 Document ID: 5336051

Timothy Michael Wildey, John N. Shadid, Eric Christopher Cyr, (2014). Adjoint Based a posteriori Error Estimates for CFD Using Data Compression SIAM Annual Meeting Document ID: 112427

Timothy Michael Wildey, Eric Christopher Cyr, John N. Shadid, (2014). Evaluation of Continuous Adjoint Approaches for Error Estimations for Numerical Approximations of Hyperbolic PDEs with Shocks SIAM Annual Meeting Document ID: 112538

Timothy Michael Wildey, John Davis Jakeman, Troy Butler, (2014). Effective Uncertainty Quantification Using Adjoint-Based Error Estimates and Surrogate Models World Congress on Computational Mechanics Document ID: 132780

Brian M. Adams, Lara E Bauman, William J. Bohnhoff, Keith Dalbey, John P. Eddy, Mohamed Salah Ebeida, Michael S. Eldred, Patricia D. Hough, Kenneth Hu, John Davis Jakeman, Laura Painton Swiler, John Adam Stephens, Dena Vigil, Timothy Michael Wildey, (2014). Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis Version 6.0 Theory ManualVersion 6.0 Theory Manual https://www.osti.gov/search/identifier:1177048 Document ID: 5336050

Donald F. Susan, Timothy Michael Wildey, Kevin J. Dowding, (2014). Advanced UQ/QMU Methods for Abnormal Thermal Safety Studies Predictive Engineering Sciences Panel Review https://www.osti.gov/search/identifier:1692314 Document ID: 5334344

Laura Painton Swiler, Timothy Michael Wildey, Gardar Johannesson, Donald Lucas, Yun Qian, (2014). Sensitivity of Precipitation to Parameter Values in the Community Atmosphere Model Version 5 https://www.osti.gov/search/identifier:1204103 Document ID: 5332198

John N. Shadid, Roger P. Pawlowski, Eric Christopher Cyr, Timothy Michael Wildey, (2014). Thermal Hydraulic Simulations, Error Estimation and Parameter Sensitivity Studies in Drekar::CFDStudies in Drekar::CFD https://www.osti.gov/search/identifier:1204072 Document ID: 5331814

John Davis Jakeman, Timothy Michael Wildey, (2013). Enhancing adaptive sparse grid approximations and improving refinement streategies using adjoint-based a posteriori error estimates Journal of Computational Physics https://www.osti.gov/search/identifier:1123534 Document ID: 5330986

Donald F. Susan, John Davis Jakeman, Timothy Michael Wildey, (2013). Deployment of Scalable UQ Methods for High-Fidelity Simulation-based Applications within the DOE Understand Variation to Realize Robust and Optimal Design and Production https://www.osti.gov/search/identifier:1673675 Document ID: 5329475

John N. Shadid, Roger P. Pawlowski, Eric Christopher Cyr, Timothy Michael Wildey, David L. Sondak, Paula D. Weber, (2013). Drekar::CFD-A Trilinos Component-Based Software Flow Solver Atmospheric Modeling at LES ScalesOpportunities and Challenges https://www.osti.gov/search/identifier:1296709 Document ID: 5327278

John Davis Jakeman, Timothy Michael Wildey, Leo W.T. Ng, (2013). Scalable Uncertainty Quantification Methods 8th Research Consortium for Multidisciplinary System Design Workshop https://www.osti.gov/search/identifier:1666168 Document ID: 5324918

John N. Shadid, Timothy Michael Wildey, Roger P. Pawlowski, Thomas M. Smith, (2013). Error Estimation with Adjoints in Drekar: Applications to Fluid Flow and Magnetohydrodynamics Models CIS External Review https://www.osti.gov/search/identifier:1661289 Document ID: 5322141

John R. Red-Horse, Timothy Michael Wildey, Paul G. Constantine, Roger Ghanem, Maarten Arnst, (2013). Stochastic Dimension Reduction of Multiphysics Systems through Measure Transformation SIAM Conference on Computational Science and Engineering https://www.osti.gov/search/identifier:1145287 Document ID: 5319200

John Davis Jakeman, Timothy Michael Wildey, (2013). Quantifying Uncertainty using a-posteriori Enhanced Sparse Grid Approximations 2013 SIAM Conference on Computational Science & Engineering https://www.osti.gov/search/identifier:1063316 Document ID: 5319031

Eric T. Phipps, Timothy Michael Wildey, Paul G. Constantine, (2013). Efficient uncertainty propagation for network multiphysics systems International Journal for Numerical Methods in Engineering https://www.osti.gov/search/identifier:1063360 Document ID: 5317730

Donald F. Susan, Timothy Michael Wildey, (2012). Propagation of Model Form Uncertainty for Thermal Hydraulics using RANS Turbulence Models in Drekar https://www.osti.gov/search/identifier:1051699 Document ID: 5310068

John Davis Jakeman, Timothy Michael Wildey, Michael S. Eldred, (2012). Adaptive sparse grids for uncertainty quantication Enhancing approximations using a posteriori error estimation 2nd Workshop on Sparse Grids and Applications https://www.osti.gov/search/identifier:1073416 Document ID: 5310074

John R. Red-Horse, Timothy Michael Wildey, Maarten Arnst, Paul Constantine, Roger Ghanem, (2012). Stochastic Dimension Reduction Techniques for Uncertainty Quantification of Multiphysics Systems SIAM Conference on Uncertainty Quantification https://www.osti.gov/search/identifier:1117584 Document ID: 5306315

Roger P. Pawlowski, John N. Shadid, Thomas M. Smith, Timothy Michael Wildey, (2011). Embedded UQ and QoI/Adjoints in Drekar: New Directions CASL THM Worksthop https://www.osti.gov/search/identifier:1113265 Document ID: 5302648

Mary F. Wheeler, Timothy Michael Wildey, (2011). A Dirichlet-to-Neumann Multigrid Algorithm for Locally Conservative Methods SIAM Conference on Mathematics and Computational Issues in the Geosciences https://www.osti.gov/search/identifier:1288632 Document ID: 5292826