Michael S. Eldred

Optimization & Uncertainty Quantification

Author profile picture

Optimization & Uncertainty Quantification

mseldre@sandia.gov

(505) 844-6479

Sandia National Laboratories, New Mexico
P.O. Box 5800
Albuquerque, NM 87185-1318

Biography

Mike led the DAKOTA project for 15 years (1994-2009) and now leads algorithm research activities that target new capabilities for DAKOTA. Mike’s research interests include uncertainty quantification, design under uncertainty, multifidelity modeling, surrogate-based optimization, and high-performance computing, with application to stockpile stewardship and energy initiatives through NNSA and Office of Science programs (ASCSciDAC, et al.). A number of his publications are available on the DAKOTA web site.

Education

Mike received his B.S. in Aerospace Engineering from Virginia Tech in 1989, his M.S.E. and Ph.D. in Aerospace Engineering from the University of Michigan in 1990 and 1993, and is currently a Distinguished Member of the Technical Staff in the Optimization and Uncertainty Quantification Department within the Center for Computing Research at Sandia National Laboratories.

Mike is an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and a member of the Society for Industrial and Applied Mathematics (SIAM), the International Society for Structural and Multidisciplinary Optimization (ISSMO), and the United States Association for Computational Mechanics (USACM). Mike currently serves as an alumni member of the AIAA Nondeterministic Approaches Technical Committee and on the editorial board for the International Journal for Uncertainty Quantification.

Publications

Lauren Partin, Gianluca Geraci, Ahmad Rushdi, Michael S. Eldred, Daniele Schiavazzi, (2022). Training and predictive uncertainty for multifidelity Convolutional Neural Networks SIAM Conference on Mathematics of Data Science (MDS22) Document ID: 1574383

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

Gianluca Geraci, Michael S. Eldred, Alex Gorodetsky, John Davis Jakeman, Teresa Portone, Bryan William Reuter, (2022). Overview and perspectives on multifidelity UQ Inria Platon projet-team seminar Document ID: 1562979

Teresa Portone, Michael S. Eldred, Gianluca Geraci, Laura Painton Swiler, (2022). Multimodel Methods for Uncertainty Quantification of Repository Systems ANS 2022 International High Level Radioactive Waste Management Meeting Document ID: 1551631

Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Ryan King, Michael S. Eldred, Hans-Joachim Bungartz, Youssef Marzouk, (2022). Multilevel Monte Carlo derivative-free optimization under uncertainty of wind power plants 8th European Congress on Computational Methods in Applied Sciences and Engineering Document ID: 1540542

Michael S. Eldred, (2022). ECCOMAS June2022 Alternates 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS) Document ID: 1540222

Gianluca Geraci, Elliott Marshall Ridgway, Brian M. Adams, Bryan William Reuter, Michael S. Eldred, (2022). Multifidelity UQ Workflows with Dakota’s Graphcal User Interface Eccomas 2022 Document ID: 1539968

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

James Derek Tucker, Michael S. Eldred, Devin Francom, (2022). Elastic Model Calibration using Dakota 8th European Congress on Computational Methods in Applied Sciences and Engineering Document ID: 1528929

Michael S. Eldred, Gianluca Geraci, Bryan William Reuter, Teresa Portone, John Davis Jakeman, Alex A. Gorodetsky, (2022). Model Tuning for Multifidelity Sampling in Dakota 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS) Document ID: 1527920

Yoona NMN Yang, Habib N. Najm, Judit Zador, Michael S. Eldred, (2022). A Neural Network Based Model for Reactive Heavy Hydrocarbon Potential Energy Surfaces 18th International Conference on Numerical Combustion Document ID: 1527887

Yoona NMN Yang, Carles Marti Aliod, Michael S. Eldred, Judit Zador, Habib N. Najm, (2022). Machine learning the C5H5 potential energy surface Unimolecular reactions Faraday Discussion Document ID: 1516415

Lauren Partin, Gianluca Geraci, Ahmad Rushdi, Michael S. Eldred, Daniele Schiavazzi, (2022). Multifidelity Data Fusion in Convolutional Encoder/Decoder Networks Rising Stars Event Document ID: 1505837

Michael S. Eldred, Gianluca Geraci, Teresa Portone, Alex A. Gorodetsky, John Davis Jakeman, (2022). All-at-Once (and Bi-Level) Model Tuning for Multifidelity Sampling SIAM Conference on Uncertainty Quantification (UQ22) Document ID: 1505114

Lauren Partin, Gianluca Geraci, Ahmad Rushdi, Michael S. Eldred, Daniele Schiavazzi, (2022). Multifidelity Data Fusion in Convolutional Encoder/Decoder Networks Siam Uq 22 Document ID: 1504908

Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Youssef Marzouk, Michael S. Eldred, Hans-Joachim Bungartz, (2022). Multilevel Monte Carlo estimators for derivative-free optimization under uncertainty Siam Uq 22 Document ID: 1504921

Michael Brian Merritt, Gianluca Geraci, Teresa Portone, Michael S. Eldred, (2022). Hybrid multilevel Monte Carlo polynomial chaos method for global sensitivity analysis Siam Uq 22 Document ID: 1504581

James Warner, Geoffrey Bomarito, Gianluca Geraci, Michael S. Eldred, Marten Thompson, John Davis Jakeman, Patrick Leser, Paul Leser, Alex Gorodetsky, (2022). Automating Model Selection and Tuning for Multifidelity UQ (MFUQ) Siam Uq 22 Document ID: 1494403

Lauren Partin, Gianluca Geraci, Ahmad Rushdi, Michael S. Eldred, Daniele Schiavazzi, (2022). Multifidelity Data Fusion in Convolutional Encoder/Decoder Networks Siam Uq 22 Document ID: 1504672

Teresa Portone, Michael S. Eldred, Gianluca Geraci, Laura Painton Swiler, (2022). Multimodel Methods for Uncertainty Quantification of Repository Systems 2022 International High Level Radioactive Waste Management Conference Document ID: 1482390

John Davis Jakeman, Sam Friedman, Michael S. Eldred, Lorenzo Tamellini, Alex Gorodestky, Doug Allaire, (2022). Adaptive experimental design for multi-fidelity surrogate modeling of multi-disciplinary systems International Journal For Numerical Methods In Engineering https://www.osti.gov/search/identifier:1855808 Document ID: 1481631

Yoona NMN Yang, Habib N. Najm, Judit Zador, Michael S. Eldred, (2022). A neural network based model for reactive heavy hydrocarbon potential energy surfaces 18th International Conference on Numerical Combustion | The Combustion Institute Document ID: 1471191

Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Ryan King, Michael S. Eldred, Hans-Joachim Bungartz, Youssef Marzouk, (2022). Multilevel Monte Carlo derivative-free optimization under uncertainty of wind power plants 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS) Document ID: 1438392

Habib N. Najm, Yoona NMN Yang, Judit Zador, Michael S. Eldred, (2021). Surrogate models and physics constraints in atomistic modeling RAMSESReduced order models; Approximation theory; Machine learning; Surrogates, Emulators and Simulators Document ID: 1405447

Gianluca Geraci, Elliott Marshall Ridgway, Brian M. Adams, Bryan William Reuter, Michael S. Eldred, (2021). Multifidelity Uq Workflows With Dakota?s Graphical User Interface 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS) Document ID: 1405448

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

Michael S. Eldred, Gianluca Geraci, Bryan William Reuter, Teresa Portone, John Davis Jakeman, Alex A. Gorodetsky, (2021). Model Tuning For Multifidelity Sampling In Dakota 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2022) Document ID: 1405437

James Derek Tucker, Michael S. Eldred, Devin Francom, (2021). Elastic Model Calibration using Dakota 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2022) Document ID: 1404372

Geoffrey F. Bomarito, Gianluca Geraci, James E. Warner, Patrick E. Leser, William P. Leser, Michael S. Eldred, John Davis Jakeman, Alex A. Gorodetsky, (2021). Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning AIAA SciTech 2021 Document ID: 1404299

Geoffrey F. Bomarito, Gianluca Geraci, James E. Warner, Patrick E. Leser, William P. Leser, Michael S. Eldred, John Davis Jakeman, Alex A. Gorodetsky, (2021). Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning AIAA SciTech 2021 Document ID: 1404320

Michael S. Eldred, Gianluca Geraci, Gorodetsky, John Davis Jakeman, (2021). Leveraging Multiple Information Sources to Enable High-Fidelity Uncertainty Quantification AE585 Chair’s Distinguished Lecture Series Document ID: 1404176

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

James Warner, Geoffrey Bomarito, Patrick Leser, William Leser, Gianluca Geraci, Michael S. Eldred, John Davis Jakeman, (2021). Automating Model Selection and Tuning for Multifidelity UQ SIAM Conference on Uncertainty Quantification (UQ22) Document ID: 1369650

Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Youssef Marzouk, Michael S. Eldred, Hans-Joachim Bungartz, (2021). Multilevel Monte Carlo estimators for derivative-free optimization under uncertainty SIAM Conference on Uncertainty Quantification (UQ22) Document ID: 1369674

Lauren Partin, Gianluca Geraci, Ahmad Rushdi, Michael S. Eldred, Daniele Schiavazzi, (2021). Multifidelity data fusion in convolutional encoder/decoder networks SIAM Conference on Uncertainty Quantification (UQ22) Document ID: 1369695

Michael Merritt, Gianluca Geraci, Teresa Portone, Michael S. Eldred, Pierre Gremaud, (2021). Hybrid multilevel Monte Carlo polynomial chaos method for global sensitivity analysis SIAM Conference on Uncertainty Quantification (UQ22) Document ID: 1369697

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

Michael S. Eldred, Gianluca Geraci, Bryan William Reuter, (2021). Advanced multilevel and multifidelity UQ strategies: surrogates, forward propagation, inverse problems and optimization SIAM Conference of Uncertainty Quantification (UQ22) Document ID: 1367840

Anh Tran, Michael S. Eldred, Scott McCann, Yan Wang, (2021). srMO-BO-3GP: A sequential regularized multi-objective Bayesian optimization for constrained design applications using an uncertain Pareto classifier ASME Journal of Mechanical Design https://www.osti.gov/search/identifier:1820417 Document ID: 1355570

Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman, Teresa Portone, (2021). Efficient Deployment of Multifidelity Sampling Methods in Production Settings Usnccm16 Document ID: 1342732

Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Michael S. Eldred, Ryan King, Hans-Joachim Bungartz, Youssef Marzouk, (2021). Multilevel Estimators for Measures of Robustness in Optimization under Uncertainty 16th US National Congress on Computational Mechanics Document ID: 1342662

Xiaoshu Zeng, Gianluca Geraci, Michael S. Eldred, John Davis Jakeman, Alex Gorodetsky, Roger Ghanem, (2021). Adaptive Basis for Multifidelity Uncertainty Quantification 16th US National Congress on Computational Mechanics Document ID: 1332497

Merritt Michael, Gianluca Geraci, Michael S. Eldred, Teresa Portone, (2021). Hybrid multi-level Monte Carlo polynomial chaos method for global sensitivity analysis 16th US National Congress on Computational Mechanics Document ID: 1342526

John Davis Jakeman, Michael S. Eldred, Gianluca Geraci, Teresa Portone, Ahmad Rushdi, Daniel Thomas Seidl, Thomas M. Smith, (2021). Multi-fidelity Machine Learning Machine Learning and Deep Learning Conference https://www.osti.gov/search/identifier:1876608 Document ID: 1331137

John Davis Jakeman, Samuel Friedman, Michael S. Eldred, Lorenzo Tamellini, Alex Gorodetsky, Doug Allaire, (2021). Adaptive resource allocation for surrogate modeling of systems comprised of multiple disciplines with varying fidelity IX International Conference on Coupled Problems in Science and Engineering https://www.osti.gov/search/identifier:1872879 Document ID: 1318770

Sam Friedman, John Davis Jakeman, Michael S. Eldred, Lorenzo Tamellini, Alex Gorodestky, Doug Allaire, (2021). Adaptive resource allocation for surrogate modeling of systems comprised of multiple disciplines with varying fidelity https://www.osti.gov/search/identifier:1807453 Document ID: 1318164

John Davis Jakeman, Alex Gorodetsky, Michael S. Eldred, Gianluca Geraci, Thomas M. Smith, (2021). MFNETS: Multi-Fidelity Data-Driven Networks for Data Analysis MFNETSMulti-Fidelity Data-Driven Networks for Data Analysis https://www.osti.gov/search/identifier:1854429 Document ID: 1279900

Xiaoshu Zeng, Gianluca Geraci, Michael S. Eldred, Roger Ghanem, (2021). Exploring important directions for multifidelity uncertainty quantification by basis adaptation method Siam Cse 2021 https://www.osti.gov/search/identifier:1848037 Document ID: 1279971

Michael S. Eldred, Alex Arkady Gorodetsky, Gianluca Geraci, John Davis Jakeman, Teresa Portone, (2021). Recent Advances in Adaptive Refinement of (Regression-Based) Multifidelity Surrogates for UQ Siam Cse21 https://www.osti.gov/search/identifier:1847573 Document ID: 1279875

Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Michael S. Eldred, Ryan King, Hans-Joachim Bungartz, Youssef Marzouk, (2021). Multifidelity Monte Carlo Estimators for Robust Formulations in Optimization under Uncertainty Siam Cse 2021 https://www.osti.gov/search/identifier:1847580 Document ID: 1279913

Michael Merritt, Gianluca Geraci, Michael S. Eldred, Teresa Portone, (2021). Hybrid multi-level Monte Carlo polynomial chaos method for global sensitivity analysis Siam Cse 2021 https://www.osti.gov/search/identifier:1847581 Document ID: 1279942

Teresa Portone, Laura Painton Swiler, Gianluca Geraci, Michael S. Eldred, (2021). Application of Multifidelity Uncertainty Quantification Methods to a Subsurface Transport Model SIAM Conference on Computational Science and Engineering (CSE21) https://www.osti.gov/search/identifier:1847219 Document ID: 1279295

Michael S. Eldred, Gianluca Geraci, Alex Gorodetsky, John Davis Jakeman, (2021). Enhancing Multifidelity UQ with model tuning 16th U.S. National Congress on Computational Mechanics Document ID: 1267977

Michael Merritt, Gianluca Geraci, Teresa Portone, Michael S. Eldred, (2021). Global Sensitivity Analysis via hybrid MLMC PCE 16th U.S. National Congress on Computational Mechanics Document ID: 1267956

Xiaoshu Zeng, Gianluca Geraci, Michael S. Eldred, John Davis Jakeman, Alex Gorodetsky, Roger Ghanem, (2021). Adaptive Basis for Multifidelity Uncertainty Quantification 16th U.S. National Congress on Computational Mechanics Document ID: 1267957

Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Michael S. Eldred, Hans-Joachim Bungartz, Youssef Marzouk, (2021). Multilevel Estimators for Measures of Robustness in Optimization Under Uncertainty 16th U.S. National Congress on Computational Mechanics Document ID: 1267961

Sam Freidman, John Davis Jakeman, Michael S. Eldred, Lorenzo Tamellini, Gorodetsky Alex, Doug Allaire, (2021). Greedy resource allocation for analysis of integrated system models IX International Conference on Coupled Problems in Science and Engineering Document ID: 1267548

Michael S. Eldred, Brian Homer Adams, (2021). Dakota Application Examples Document ID: 1266897

Michael S. Eldred, (2021). Introduction of Michael S. Eldred 2021 Stanford TST review https://www.osti.gov/search/identifier:1843098 Document ID: 1266714

Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Michael S. Eldred, Ryan King, Hans-Joachim Bungartz, Youssef Marzouk, (2020). Multifidelity strategies for optimization under uncertainty of wind power plants AIAA SciTech 2021 https://www.osti.gov/search/identifier:1836901 Document ID: 1244281

Alex Gorodetsky, Kazuya Tsuji, John Davis Jakeman, Gianluca Geraci, Michael S. Eldred, (2020). Multifidelity information fusion via network models for uncertainty quantification in aerospace dynamical systems AIAA SciTech 2021 https://www.osti.gov/search/identifier:1836910 Document ID: 1244394

Alex Gorodetsky, John Davis Jakeman, Gianluca Geraci, Michael S. Eldred, (2020). Data-driven Network Representations For Multifidelity Surrogate Modeling (mfnets) Uncecomp 21 Document ID: 1243335

Michael S. Eldred, Gianluca Geraci, Gianluca Iaccarino, (2020). Foreword: Special Issue on Multilevel-Multifidelity Approaches for Uncertainty Quantification International Journal for Uncertainty Quantification https://www.osti.gov/search/identifier:1760360 Document ID: 1242799

Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Ryan King, Michael S. Eldred, Hans-Joachim Bungartz, (2020). Multifidelity Derivative-free Optimization Under Uncertainty For Wind Plants 14th World Congress on Computational Mechanics (WCCM) Document ID: 1208333

Alex Gorodetsky, John Davis Jakeman, Gianluca Geraci, Michael S. Eldred, (2020). Mfnets: Multi-fidelity Data-driven Networks For Bayesian Learning, Uncertainty Quantification, And Prediction 14th World Congress on Computational Mechanics (WCCM) Document ID: 1208334

Gianluca Geraci, Alex Gorodetsky, Michael S. Eldred, John Davis Jakeman, (2020). Multilevel/multifidelty Strategies For Uncertainty Quantification, Control And Design Under Uncertainty Of Expensive Computational Systems 14th World Congress on Computational Mechanics (WCCM) Document ID: 1208336

Gianluca Geraci, Michael S. Eldred, Alex Gorodetsky, John Davis Jakeman, (2020). Multifidelity Strategies in UQ: an overview on some recent trends in sampling based approaches Doctoral Course ? Aeronautical and Space Engineering ? Summer School 2020, University of Rome La Sapienzame https://www.osti.gov/search/identifier:1822111 Document ID: 1207495

John Davis Jakeman, Michael S. Eldred, Gianluca Geraci, Thomas M. Smith, Alex Gorodetsky, (2020). LDRD #218317: Learning Hidden Structure in Multi-Fidelity Information Sources for Efficient Uncertainty Quantification https://www.osti.gov/search/identifier:1668458 Document ID: 1196674

Michael S. Eldred, Alex Gorodetsky, Gianluca Geraci, John Davis Jakeman, Teresa Portone, (2020). Recent advances in adaptive refinement of multifidelity surrogates Siam Cse 2021 Document ID: 1196332

Xiaoshu Zeng, Gianluca Geraci, Michael S. Eldred, Roger Ghanem, (2020). Exploring important directions for multifidelity uncertainty quantification by basis adaptation method Siam Cse 2021 Document ID: 1196289

Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Michael S. Eldred, Youssef Marzouk, Hans-Joachim Bungartz, (2020). Multifidelity Monte Carlo Estimators for Robust Formulations in Optimization under Uncertainty Siam Cse 2021 Document ID: 1196286

Michael Merritt, Gianluca Geraci, Teresa Portone, Michael S. Eldred, (2020). Hybrid multilevel Monte Carlo polynomial chaos expansion method for global sensitivity analysis Siam Cse 2021 Document ID: 1196287

Teresa Portone, Michael S. Eldred, Gianluca Geraci, Laura Painton Swiler, (2020). Application of multifidelity UQ approaches to a subsurface transport model SIAM Conference on Computational Science and Engineering (CSE21) Document ID: 1196073

Anh Tran, Michael S. Eldred, Yan Wang, Scott McCann, (2020). srMO-BO-3GP: A sequential regularized multi-objective constrained Bayesian optimization for design applications ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference https://www.osti.gov/search/identifier:1811793 Document ID: 1183105

Alex Gorodetsky, John Davis Jakeman, Gianluca Geraci, Michael S. Eldred, (2020). MFNets: Multifidelity data-driven networks for Bayesian learning and prediction International Journal for Uncertainty Quantification https://www.osti.gov/search/identifier:1670735 Document ID: 1161876

Anh Tran, Michael S. Eldred, Scott McCann, Yan Wang, (2020). srMO-BO-3GP: A sequential regularized multi-objective constrained Bayesian optimization for design applications ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference https://www.osti.gov/search/identifier:1808255 Document ID: 1161645

Michael S. Eldred, (2020). FY20 Q3/Q4 Modularization Dakota Upstream Research planning https://www.osti.gov/search/identifier:1786300 Document ID: 1139156

Keith Dalbey, Michael S. Eldred, Gianluca Geraci, John Davis Jakeman, Kathryn Anne Maupin, Jason A. Monschke, Daniel Thomas Seidl, Laura Painton Swiler, Anh Tran, Friedrich Menhorn, Xiaoshu Zeng, (2020). Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.12 Theory Manual https://www.osti.gov/search/identifier:1630693 Document ID: 1127943

Brian M. Adams, William J. Bohnhoff, Keith Dalbey, Mohamed Salah Ebeida, John P. Eddy, Michael S. Eldred, Russell Hooper, Patricia D. Hough, Kenneth Hu, John Davis Jakeman, Mohammad Khalil, Kathryn Anne Maupin, Jason A. Monschke, Elliott Marshall Ridgway, Ahmad Rushdi, Daniel Thomas Seidl, John Adam Stephens, Laura Painton Swiler, Justin Winokur, (2020). Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.12 User?s Manual https://www.osti.gov/search/identifier:1630694 Document ID: 1127946

David Charles Maniaci, Alan Hsieh, Gianluca Geraci, Daniel Thomas Seidl, Thomas G. Herges, Michael S. Eldred, Myra L. Blaylo, Brent C Houchens, (2020). Verification, Validation, and Uncertainty Quantification (V&V/UQ) of Wind Plant Models Project, Overview of FY20 Q2 Milestone Completion: Wind Uncertainty Quantification Session and Publications FY20Q2 Report Overview https://www.osti.gov/search/identifier:1778659 Document ID: 1115975

Alex Gorodetsky, Gianluca Geraci, Michael S. Eldred, John Davis Jakeman, (2020). A Generalized Approximate Control Variate Framework For Multifidelity Uncertainty Quantification Journal of Computational Physics https://www.osti.gov/search/identifier:1601260 Document ID: 1090543

Patrick Joseph Blonigan, Gianluca Geraci, Francesco NMN Rizzi, Michael S. Eldred, (2020). Leveraging Reduced Order Models For Multifidelity Uncertainty Quantification World Congress on Computational Mechanics Document ID: 1079554

Gianluca Geraci, Xiaoshu Zeng, Alex Gorodetsky, Michael S. Eldred, John Davis Jakeman, Roger Ghanem, (2020). Uncertainty Quantification With Multifidelity Strategies Based On Models With Dissimilar Parameterizations 14th World Congress on Computational Mechanics (WCCM) Document ID: 1079630

Alan Hsieh, David Charles Maniaci, Thomas Herges, Gianluca Geraci, Daniel Thomas Seidl, Michael S. Eldred, Lawrence Cheung, Myra L. Blaylock, Brent C Houchens, (2020). Multilevel-Multifidelity Uncertainty Quantification Using Dakota of Atmospheric Boundary Layers Under Different Stability Regimes 14th World Congress in Computational Mechanics (WCCM) ECCOMAS Congress 2020 Document ID: 1079551

Alan Hsieh, David Charles Maniaci, Thomas Herges, Gianluca Geraci, Daniel Thomas Seidl, Michael S. Eldred, Myra L. Blaylock, Brent C Houchens, (2020). Multilevel Uncertainty Quantification Using CFD and OpenFAST Simulations of the SWiFT Facility AIAA SciTech 2020 https://www.osti.gov/search/identifier:1760989 Document ID: 1079056

Patrick Joseph Blonigan, Gianluca Geraci, Francesco NMN Rizzi, Michael S. Eldred, (2020). Towards an integrated and efficient framework for leveraging reduced order models for multifidelity Uncertainty Quantification AIAA SciTech 2020 https://www.osti.gov/search/identifier:1761001 Document ID: 1078857

Patrick Joseph Blonigan, Gianluca Geraci, Francesco NMN Rizzi, Michael S. Eldred, (2020). Towards an integrated and efficient framework for leveraging reduced order models for multifidelity Uncertainty Quantification AIAA SciTech 2020 https://www.osti.gov/search/identifier:1761000 Document ID: 1078858

Menhorn Friedrich, Gianluca Geraci, Daniel Thomas Seidl, Michael S. Eldred, King Ryan, Bungartz Hans-Joachim, Marzouk Youssef, (2020). Higher moment multilevel estimators for optimization under uncertainty applied to wind plant design AIAA Scitech 2020 https://www.osti.gov/search/identifier:1643359 Document ID: 1078776

Gianluca Geraci, Patrick Joseph Blonigan, Francesco NMN Rizzi, Alex Gorodetsky, Kevin Carlberg, Michael S. Eldred, (2019). An integrated and efficient framework for embedded Reduced Order Models for multifidelity Uncertainty Quantification American Physical Society https://www.osti.gov/search/identifier:1643587 Document ID: 1066790

Gianluca Geraci, Michael S. Eldred, Alex Gorodetsky, John Davis Jakeman, (2019). Recent advancement in Multifidelity Uncertainty Quantification NATO/STO Lecture SeriesUncertainty Quantification in Computational Fluid Dynamics https://www.osti.gov/search/identifier:1642820 Document ID: 1033397

Michael S. Eldred, Gianluca Geraci, Daniel Thomas Seidl, Friedrich Menhorn, Ryan King, Thomas Herges, Alan Hsieh, David Charles Maniaci, (2019). Milestone: Develop multilevel emulator-based Bayesian inference capabilities and demonstrate data assimilation for SWiFT configuration A2e FY19 milestone completion evidence https://www.osti.gov/search/identifier:1646013 Document ID: 1032321

Patrick Joseph Blonigan, Gianluca Geraci, Francesco NMN Rizzi, Michael S. Eldred, Kevin carlberg, (2019). On-line Generation and Error Handling for Surrogate Models within Multifidelity Uncertainty Quantification https://www.osti.gov/search/identifier:1567834 Document ID: 1031520

Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman, (2019). Multilevel / Multifidelity Sampling and Emulation for Forward UQ Applied Math Visioning Workshop https://www.osti.gov/search/identifier:1645988 Document ID: 1021104

Habib N. Najm, Cosmin Safta, Xun Huan, Tiernan Albert Casey, Khachik Sargsyan, Joseph Oefelein, Guilhem Lacaze, Zachary Vane, Michael S. Eldred, Gianluca Geraci, (2019). Uncertainty Quantification in Computational Models of Large Scale Physical Systems US National Congress on Computational Mechanics https://www.osti.gov/search/identifier:1641505 Document ID: 997815

Gianluca Geraci, Michael S. Eldred, Alex Arkady Gorodetsky, John Davis Jakeman, (2019). Recent Advancements for Multifidelity UQ and OUU in Dakota: Capability Overview and Perspectives US National Congress of Computational Mechanics https://www.osti.gov/search/identifier:1641419 Document ID: 997237

Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman, (2019). Experience with Multilevel/Multifidelity/Multi-Index Sampling and Surrogate Approaches for Forward Uncertainty Quantification 15th US National Congress on Computational Mechanics (USNCCM) https://www.osti.gov/search/identifier:1641388 Document ID: 997103

Habib N. Najm, Cosmin Safta, Xun Huan, Tiernan Albert Casey, Khachik Sargsyan, Joseph Oefelein, Guilhem Lacaze, Michael S. Eldred, Gianluca Geraci, (2019). Uncertainty Quantification in Large Scale Computational Models International Congress on Industrial and Applied Mathematics https://www.osti.gov/search/identifier:1641089 Document ID: 985486

Tiernan Albert Casey, Bert Debusschere, Michael S. Eldred, Gianluca Geraci, Roger Ghanem, John Davis Jakeman, Youssef Marzouk, Habib N. Najm, Cosmin Safta, Khachik Sargsyan, (2019). FASTMath: UQ Algorithms SciDAC PI Meeting 2019 https://www.osti.gov/search/identifier:1641088 Document ID: 985493

Alan Hsieh, David Charles Maniaci, Thomas Herges, Gianluca Geraci, Michael S. Eldred, Myra L. Blaylock, Brent C Houchens, (2019). Multilevel Uncertainty Quantification Using CFD and OpenFAST Simulations of the SWiFT Facility 2020 AIAA SciTech Forum Document ID: 984841

Michael S. Eldred, (2019). Advanced UQ Methods in Dakota Sandia visit of David Etim, DOE ASC V&V Program Manager https://www.osti.gov/search/identifier:1645509 Document ID: 984602

Michael S. Eldred, (2019). Multifidelity Modeling Workshop Panel Session: User Stories, Success Cases and Target Areas Multifidelity Modeling Workshop https://www.osti.gov/search/identifier:1645443 Document ID: 973976

Patrick Joseph Blonigan, Gianluca Geraci, Francesco NMN Rizzi, Kevin Thomas Carlberg, Michael S. Eldred, (2019). Towards an integrated and efficient framework for leveraging reduced order models for multifidelity uncertainty quantification AIAA Scitech 2020 Document ID: 973513

Myra L. Blaylock, Brent C Houchens, Ari Louis Frankel, David Charles Maniaci, Thomas Herges, Gianluca Geraci, Michael S. Eldred, Robert C. Knaus, Philip Sakievich, (2019). Comparison of Field Measurements and Large Eddy Simulations of the Scaled Wind Farm Technology (SWiFT) Site Asme Ajk Fluids 2019 https://www.osti.gov/search/identifier:1640113 Document ID: 901758

John Davis Jakeman, Fabian Franzelin, Akil Narayan, Michael S. Eldred, Dirk Pflueger, (2019). Polynomial chaos expansions for dependent random variables https://www.osti.gov/search/identifier:1762354 Document ID: 936669

Gianluca Geraci, Alex Gorodetsky, Michael S. Eldred, John Davis Jakeman, (2019). Recent advancements toward generalized sampling strategies for multifidelity Uncertainty Quantification Workshop on ‘Uncertainty Quantification for nonlinear problems and applications in porous media’ organized by NORCE Norwegian Research Centre https://www.osti.gov/search/identifier:1644568 Document ID: 937201

Gianluca Geraci, Michael S. Eldred, Alex Gorodetsky, John Davis Jakeman, (2019). Recent advancements in Multilevel-Multifidelity techniques for forward UQ in the DARPA Sequoia project AIAA SciTech Forum 2019 https://www.osti.gov/search/identifier:1582124 Document ID: 901672

Gianluca Geraci, Friedrich Menhorn, Xun Huan, Cosmin Safta, Youssef Marzouk, Habib N. Najm, Michael S. Eldred, (2019). Progress in Scramjet Design Optimization Under Uncertainty Using Simulations of the HIFire Configuration AIAA Scitech Forum 2019 https://www.osti.gov/search/identifier:1582123 Document ID: 901928

Habib N. Najm, Roger G. Ghanem, Michael S. Eldred, (2018). Design Optimization under Uncertainty in Large Scale Computational Models Invited seminar at SpaceX https://www.osti.gov/search/identifier:1594692 Document ID: 889608

Gianluca Geraci, Michael S. Eldred, John Davis Jakeman, (2018). Approximate Control Variates arXiv Document ID: 888903

Michael S. Eldred, Gianluca Geraci, Alex A. Gorodetsky, John Davis Jakeman, (2018). Multilevel-Multifidelity Sampling and Emulation for Forward UQ Workshop IIHPC and Data Science for Scientific Discovery Document ID: 878063

Cosmin Safta, Gianluca Geraci, Michael S. Eldred, Habib N. Najm, David Riegner, Wolfgang Windl, (2018). Interatomic Potentials Models for Cu-Ni and Cu-Zr Alloys https://www.osti.gov/search/identifier:1475252 Document ID: 876062

Gianluca Geraci, Michael S. Eldred, (2018). Leveraging Intrinsic Principal Directions for Multifidelity Uncertainty Quantification https://www.osti.gov/search/identifier:1475254 Document ID: 875851

Michael S. Eldred, Gianluca Geraci, Alex Gorodetsky, John Davis Jakeman, (2018). Lecture 1: Multilevel-Multifidelity with Monte Carlo Sampling; Algorithms and deployment experience Uncertainty Quantification Summer School https://www.osti.gov/search/identifier:1582192 Document ID: 842780

Michael S. Eldred, Gianluca Geraci, Alex Gorodetsky, John Davis Jakeman, (2018). Lecture 3: Multilevel-Multifidelity Optimization; Deterministic Design and Design Under Uncertainty Uncertainty Quantification Summer School Document ID: 842782

Michael S. Eldred, Gianluca Geraci, Alex Gorodetsky, John Davis Jakeman, (2018). Lecture 2: Multilevel-Multifidelity beyond Monte Carlo; Polynomial chaos and Stochastic collocation Uncertainty Quantification Summer School Document ID: 842781

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

Cosmin Safta, Xun Huan, Habib N. Najm, Khachik Sargsyan, Michael S. Eldred, Gianluca Geraci, (2018). Adaptive Sparse Quadrature for Multifidelity Scramjet Simulations SIAM Annual Meeting https://www.osti.gov/search/identifier:1569685 Document ID: 830643

Myra L. Blaylock, Ari Louis Frankel, David Charles Maniaci, Thomas Herges, Gianluca Geraci, Michael S. Eldred, (2018). Multilevel Uncertainty Quantification Using CFD and OpenFAST Simulations of the SWiFT Facility AIAA 2019 SciTech Forum Document ID: 819742

David Charles Maniaci, Ari Louis Frankel, Gianluca Geraci, Myra L. Blaylock, Michael S. Eldred, (2018). Multilevel Uncertainty Quantification of a Wind Turbine Large Eddy Simulation Model Eccm-ecfd 2018 https://www.osti.gov/search/identifier:1526815 Document ID: 808747

Friedrich Menhorn, Gianluca Geraci, Michael S. Eldred, Youssef Marzouk, (2018). Multifideliy Optimization Under Uncertainty For A Scramjet{inspired Problem 7th European Conference on Computational Fluid Dynamics (ECFD 7) https://www.osti.gov/search/identifier:1525656 Document ID: 795430

Gianluca Geraci, Alex Gorodetsky, Michael S. Eldred, John Davis Jakeman, (2018). Towards Leveraging Active Direction For Efficient Multifidelity Uq Strategies 7th European Conference on Computational Fluid Dynamics (ECFD 7) https://www.osti.gov/search/identifier:1525631 Document ID: 795451

Cosmin Safta, Xun Huan, Khachik Sargsyan, Habib N. Najm, Michael S. Eldred, Gianluca Geraci, (2018). Sparse multifidelity approximations for forward UQ SIAM Uncertainty Quantification https://www.osti.gov/search/identifier:1510682 Document ID: 795216

David Charles Maniaci, Ari Louis Frankel, Gianluca Geraci, Myra L. Blaylock, Michael S. Eldred, (2018). Multi-level Uncertainty Quantification of a Wind Turbine Large Eddy Simulation Model 7th European Conference on Computational Fluid Dynamics https://www.osti.gov/search/identifier:1525640 Document ID: 795408

Gianluca Geraci, Michael S. Eldred, Gianluca Iaccarino, (2018). Multilevel /multifidelity Monte Carlo For Wave Propagation In Heterogeneous Media Siam Uq 18 https://www.osti.gov/search/identifier:1525626 Document ID: 785084

Michael S. Eldred, Gianluca Geraci, Alex A. Gorodetsky, John Davis Jakeman, (2018). Adaptive Refinement Strategies for Multilevel Polynomial Chaos Expansions SIAM Conference on Uncertainty Quantification (UQ18) https://www.osti.gov/search/identifier:1575179 Document ID: 784845

Habib N. Najm, Bert Debusschere, Neil Sparks, Khachik Sargsyan, Xun Huan, Joseph Oefelein, Zachary Vane, Michael S. Eldred, Gianluca Geraci, O. Knio, I. Sraj, G. Scovazzi, O. Colomes, Y. Marzouk, O. Zahm, F. Menhorn, R. Ghanem, P. Tsilifis, (2018). Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine ? ScramjetUQ ? Quaterly DARPA Review https://www.osti.gov/search/identifier:1572447 Document ID: 738214

Xun Huan, Cosmin Safta, Khachik Sargsyan, Gianluca Geraci, Michael S. Eldred, Zachary Phillips Vane, Guilhem Martial Louis Lacaze, Joseph Oefelein, Habib N. Najm, (2018). Global Sensitivity Analysis and Estimation of Model Error, Toward Uncertainty Quantification in Scramjet Computations AIAA Journal https://www.osti.gov/search/identifier:1431213 Document ID: 589185

Gianluca Geraci, Alex Gorodetsky, John Davis Jakeman, Michael S. Eldred, (2018). SAMPLING-BASED MULTILEVEL/MULTIFIDELITY UNCERTAINTY QUANTIFICATION for Computational Fluid Dynamics applications Eccomas Eccm-ecfd 2018 Document ID: 750177

David Charles Maniaci, Ari Louis Frankel, Gianluca Geraci, Myra L. Blaylock, Michael S. Eldred, (2018). Multi-level Uncertainty Quantification of a Wind Turbine Large Eddy Simulation Model 7th European Conference on Computational Fluid Dynamics Document ID: 750275

Alex Gorodetsky, Gianluca Geraci, Michael S. Eldred, John Davis Jakeman, (2018). Latent Variable Networks For Multifidelity Uncertainty Quantification And Data Fusion Eccomas Eccm-ecfd 2018 Document ID: 749951

Friedrich Menhorn, Gianluca Geraci, Michael S. Eldred, Youssef Marzouk, (2018). Multifidelity Optimization Under Uncertainty For A Scramjet Inspired Problem Eccomas Eccm-ecfd 2018 Document ID: 749952

Oriol Colomes, Gianluca Geraci, Michael S. Eldred, Guglielmo Scovazzi, (2018). A Multilevel Monte Carlo Approach With An Embedded Error Estimator For Computational Fluid Dynamics Applications Eccomas Eccm-ecfd 2018 Document ID: 749954

Alex Gorodetsky, Gianluca Geraci, Michael S. Eldred, John Davis Jakeman, (2018). Multifidelity Model Management using Latent Variable Bayesian Networks 2nd Physics Informed Machine Learning https://www.osti.gov/search/identifier:1513639 Document ID: 749486

Michael S. Eldred, Gianluca Geraci, Alex Gorodetsky, John Davis Jakeman, (2018). Multilevel-Multifidelity Approaches for Forward UQ in the DARPA SEQUOIA Project 2018 AIAA SciTech Forum and Exposition https://www.osti.gov/search/identifier:1513488 Document ID: 738567

Cosmin Safta, Xun Huan, Gianluca Geraci, Michael S. Eldred, Khachik Sargsyan, Zachary Vane, Joseph Oefelein, Habib N. Najm, (2018). Multifidelity Statistical Analysis of Large Eddy Simulations in Scramjet Computations AIAA Scitech 2018 https://www.osti.gov/search/identifier:1513486 Document ID: 738725

Gianluca Geraci, Alex Gorodetsky, Michael S. Eldred, John Davis Jakeman, (2018). Multilevel and Multifidelity approaches for Uncertainty Quantification 13th World Congress in Computational Mechanics Document ID: 739249

Alex Gorodetsky, Gianluca Geraci, Michael S. Eldred, John Davis Jakeman, (2018). Multifidelity model management using latent variable Bayesian networks 13th World Congress in Computational Mechanics Document ID: 739250

Xun Huan, Gianluca Geraci, Cosmin Safta, Michael S. Eldred, Khachik Sargsyan, Zachary P. Vane, Joseph C. Oefelein, Habib N. Najm, (2018). Multifidelity Statistical Analysis of Large Eddy Simulations in Scramjet Computations AIAA SciTech Forum https://www.osti.gov/search/identifier:1513171 Document ID: 738827

Michael S. Eldred, Gianluca Geraci, (2018). Multilevel/Multifidelity sampling strategies for forward UQ DARPA ScramjetUQ Site Visit Document ID: 738016

Xun Huan, Gianluca Geraci, Zachary Phillips Vane, Cosmin Safta, Michael S. Eldred, Joseph Oefelein, Habib N. Najm, Khachik Sargsyan, (2018). Multifidelity Statistical Analysis of Large Eddy Simulations in Scramjet Computations AIAA SciTech Forum and Exposition https://www.osti.gov/search/identifier:1512061 Document ID: 625997

Michael S. Eldred, Gianluca Geraci, Friedrich Menhorn, Youssef Marzouk, (2017). Tutorial on Optimization Under Uncertainty with Application to Scramjet Design DARPA ScramjetUQ Site Visit https://www.osti.gov/search/identifier:1488337 Document ID: 737752

Cosmin Safta, Xun Huan, Michael S. Eldred, Gianluca Geraci, (2017). Tackling High-Dimensionality and Computational Cost in Scramjet LES Darpa Program Review https://www.osti.gov/search/identifier:1511975 Document ID: 737751

Gianluca Geraci, Michael S. Eldred, Gianluca Iaccarino, (2017). Multilevel/Multifidelity Monte Carlo for wave propagation in heterogeneous media Siam Uq 18 Document ID: 703869

Habib N. Najm, Bert Debusschere, Cosmin Safta, Khachik Sargsyan, Xun Huan, Joseph Oefelein, Zachary Vane, Michael S. Eldred, G. Geraci, O. Knio, I. Sraj, G. Scovazzi, O. Colomes, Y. Marzouk, O. Zahm, F. Menhorn, R. Ghanem, P. Tsilifis, (2017). Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine Quarterly DARPA Review Telecon https://www.osti.gov/search/identifier:1574094 Document ID: 670947

John Davis Jakeman, Alex Arkady Gorodetsky, Michael S. Eldred, (2017). Tractable Uncertainty Quantification: Exploiting Structure Sandia CIS Review https://www.osti.gov/search/identifier:1466103 Document ID: 659820

Xun Huan, Cosmin Safta, Khachik Sargsyan, Gianluca Geraci, Michael S. Eldred, Zachary Phillips Vane, Guilhem Lacaze, Joseph C. Oefelein, Habib N. Najm, (2017). Global Sensitivity Analysis and Quantification of Model Error in Scramjet Computations arXiv https://www.osti.gov/search/identifier:1429819 Document ID: 659134

Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman, (2017). Multilevel-Multifidelity Expansions with Application to Forward UQ, OUU, and Emulator-Based Bayesian Inference 14th U.S. National Congress on Computational Mechanics (USNCCM14) https://www.osti.gov/search/identifier:1507501 Document ID: 638105

Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman, Michael S. Eldred, (2017). Sampling, Polynomial Chaos and Functional Tensor Train Multilevel/Multifidelity Strategies for Forward UQ SIAM Annual 17 https://www.osti.gov/search/identifier:1507076 Document ID: 638004

Irina Kalashnikova Tezaur, John Davis Jakeman, Michael S. Eldred, Mauro Perego, Stephen (LANL) Price, Andrew G. Salinger, (2017). Large-scale Deterministic Inversion and Bayesian Calibration in Land-Ice Modeling 14th U.S. National Congress on Computational Mechanics (USNCCM14) https://www.osti.gov/search/identifier:1460158 Document ID: 637178

Gianluca Geraci, Michael S. Eldred, Iaccarino Gianluca, (2017). Multifidelity Uncertainty Quantification Strategies for Computational Fluid Dynamics Applications ECCM – ECFD 2018 6th European Conference on Computational Mechanics (Solids, Structures and Coupled Problems) 7th European Conference on Computational Document ID: 637215

Angel Urbina, Laura Painton Swiler, Michael S. Eldred, Brian M. Adams, (2017). An introduction to the Dakota software International Modal Analysis Conference XXXVI Document ID: 626549

Michael S. Eldred, Jason A. Monschke, John Davis Jakeman, Gianluca Geraci, (2017). Multilevel-Multifidelity Approaches for Uncertainty Quantification and Design Siam Cse 2017 https://www.osti.gov/search/identifier:1455372 Document ID: 599563

Laura Painton Swiler, Michael S. Eldred, Brian M. Adams, Laura Painton Swiler, (2017). Dakota Software: Explore and Predict with Confidence Document ID: 610852

Xun Huan, Cosmin Safta, Gianluca Geraci, Michael S. Eldred, Zachary Phillips Vane, Guilhem Martial Louis Lacaze, Joseph Oefelein, Khachik Sargsyan, Habib N. Najm, (2017). Robust Compressive Sensing with Application to Multifidelity Analysis of Complex Turbulent Flows SIAM Conference on Computational Science and Engineering https://www.osti.gov/search/identifier:1427446 Document ID: 599894

Gianluca Geraci, Michael S. Eldred, Iaccarino Gianluca, (2017). A multifidelity multilevel Monte Carlo method for ncertainty propagation in aerospace applications AIAA SciThech2017 https://www.osti.gov/search/identifier:1505910 Document ID: 565590

Xun Huan, Cosmin Safta, Khachik Sargsyan, Gianluca Geraci, Michael S. Eldred, Zachary Phillips Vane, Guilhem Martial Louis Lacaze, Joseph Oefelein, Habib N. Najm, (2017). Global Sensitivity Analysis and Quantification of Model Error for Large Eddy Simulation in Scramjet Design AIAA SciTech Forum https://www.osti.gov/search/identifier:1417244 Document ID: 566744

Irina Kalashnikova Tezaur, Andrew G. Salinger, Mauro Perego, Raymond S. Tuminaro, John Davis Jakeman, Michael S. Eldred, Jerry Watkins, Stephen (LANL) Price, Irina (LANL) Demeshko, (2017). The Albany/FELIX Land-Ice Dynamical Core Albany User Group Meeting https://www.osti.gov/search/identifier:1416697 Document ID: 566474

Xun Huan, Cosmin Safta, Khachik Sargsyan, Gianluca Geraci, Michael S. Eldred, Zachary Phillips Vane, Guilhem Martial Louis Lacaze, Joseph Oefelein, Habib N. Najm, (2016). Global Sensitivity Analysis and Quantification of Model Form Error for Large Eddy Simulation of Scramjet Design American Institute of Aeronautics and Astronautics SciTech Forum https://www.osti.gov/search/identifier:1413414 Document ID: 565453

Habib N. Najm, Bert Debusschere, Cosmin Safta, Khachik Sargsyan, Xun Huan, Joseph Oefelein, Guilhem Martial Louis Lacaze, Zachary Phillips Vane, Michael S. Eldred, Gianluca Geraci, Omar Knio, I. Sraj, G. Scovazzi, O. Colomes, Y. Marzouk, O. Zahm, F. Menhorn, R. Ghanem, P. Tsilifis, (2016). Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine ? ScramjetUQ ? Army-Navy-NASA-Air Force (JANNAF) meeting https://www.osti.gov/search/identifier:1420843 Document ID: 553650

Jason A. Monschke, Michael S. Eldred, (2016). Multilevel-Multifidelity Acceleration of PDE-Constrained Optimization AIAA SciTech 2017 https://www.osti.gov/search/identifier:1406855 Document ID: 532509

Habib N. Najm, Bert Debusschere, Cosmin Safta, Khachik Sargsyan, Xun Huan, Joseph Oefelein, Guilhem Martial Louis Lacaze, Zachary Phillips Vane, Michael S. Eldred, G. Geraci, O. Knio, I. Sraj, G. Scovazzi, O. Colomes, Y. Marzouk, O. Zahm, F. Augustin, F. Menhorn, R. Ghanem, P. Tsilifis, (2016). Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine Annual DARPA Review https://www.osti.gov/search/identifier:1397105 Document ID: 530593

Xun Huan, Cosmin Safta, Michael S. Eldred, Zachary Phillips Vane, Guilhem Martial Louis Lacaze, Joseph Oefelein, Khachik Sargsyan, Habib N. Najm, (2016). Global Sensitivity Analysis for Large Eddy Simulation Models SIAM Annual Meeting https://www.osti.gov/search/identifier:1372012 Document ID: 476180

Jason Andrew Monschke, Michael S. Eldred, (2016). A Second-Order Consistent Multilevel-Multifidelity Optimization Scheme Los Alamos Postdoc Research Day https://www.osti.gov/search/identifier:1507246 Document ID: 442630

Mauro Perego, S. Price, G. Stadler, Andrew G. Salinger, Irina Kalashnikova Tezaur, Michael S. Eldred, John Davis Jakeman, (2016). Towards Uncertainty Quantification in 21st Century SeaLevel Rise Predictions: PDE Constrained Optimization as a First Step in Bayesian Calibration and Forward Propagation Siam Uq16 https://www.osti.gov/search/identifier:1366599 Document ID: 430780

Habib N. Najm, Bert Debusschere, Cosmin Safta, Khachik Sargsyan, Joseph Oefelein, Guilhem Martial Louis Lacaze, Michael S. Eldred, Omar Knio, G. Scovazzi, Y. Marzouk, R. Ghanem, (2016). Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine Stanford University https://www.osti.gov/search/identifier:1530652 Document ID: 341908

Irina Kalashnikova Tezaur, John Davis Jakeman, Michael S. Eldred, Mauro Perego, Andrew G. Salinger, Stephen (LANL) Price, (2016). Towards Uncertainty Quantification in 21st Century Sea-Level Rise Predictions: Efficient Methods for Bayesian Calibration and Forward Propagation of Uncertainty for Land-Ice Models SIAM Conference on Uncertainty Quantification https://www.osti.gov/search/identifier:1364846 Document ID: 430546

Jason Andrew Monschke, Michael S. Eldred, (2016). A Second-Order Consistent Multilevel-Multifidelity Optimization Scheme Los Alamos Postdoc Research Day Document ID: 430098

Mauro Perego, Michael S. Eldred, John Davis Jakeman, Andrew G. Salinger, Irina Kalashnikova Tezaur, Stephen (LANL) Price, Matthew (LANL) Hoffman, (2016). Towards quantifying uncertainty in Greenland’s contribution to 21st century sea-level rise 2015 AGU fall meeting https://www.osti.gov/search/identifier:1339212 Document ID: 366048

Laura Painton Swiler, Michael S. Eldred, Brian M. Adams, (2015). Uncertainty Quantification Methods in the Dakota Toolkit Handbook on Uncertainty Quantification https://www.osti.gov/search/identifier:1331537 Document ID: 219561

Irina Kalashnikova Tezaur, Andrew G. Salinger, Mauro Perego, John Davis Jakeman, Michael S. Eldred, Irina Demeshko, Raymond S. Tuminaro, Stephen (LANL) Price, (2015). Albany/FELIX: A Robust & Scalable Trilinos-Based Finite-Element Ice Flow Dycore Built for Advanced Architectures & Analysis International Conference on Industrial and Applied Mathematics (ICIAM) 2015 https://www.osti.gov/search/identifier:1301963 Document ID: 319387

Michael S. Eldred, Bert Debusschere, Kamaljit Singh Chowdhary, John Davis Jakeman, Prashant Rai, Cosmin Safta, Khachik Sargsyan, (2015). Sandia Software Enabling Extreme-Scale Uncertainty Quantification 2015 SciDAC PI Meeting https://www.osti.gov/search/identifier:1266821 Document ID: 308277

Irina Kalashnikova Tezaur, Mauro Perego, Raymond S. Tuminaro, Andrew G. Salinger, John Davis Jakeman, Michael S. Eldred, Lili (SC) Ju, Tong (SC) Zhang, Max (FSU) Gunzburger, Stephen (LANL) Price, (2015). Progress on the PISCEES FELIX Ice Sheet Dynamical Cores SciDAC Principal Investigators Meetin https://www.osti.gov/search/identifier:1576124 Document ID: 308302

Laura Painton Swiler, Michael S. Eldred, John N. Shadid, (2015). Whitepaper prepared for DOE Workshop on Integrated Simulations for Magnetic Fusion Energy Sciences https://www.osti.gov/search/identifier:1178923 Document ID: 254355

Michael S. Eldred, Patrick (MIT) Heimbach, Charles (UT Austin) Jackson, John Davis Jakeman, Mauro Perego, Stephen Price, Andrew G. Salinger, Georg (Courant) Stadler, Irina Kalashnikova Tezaur, (2015). From Deterministic Inversion to Uncertainty Quantification: Planning a Long Journey in Ice Sheet Modeling QUEST Workshop 2015 https://www.osti.gov/search/identifier:1246877 Document ID: 243502

Mauro Perego, Stephen (LANL) Price, Georg (Curant) Stadler, Michael S. Eldred, Charles (UT Austin) Jackson, John Davis Jakeman, Andrew G. Salinger, Irina Kalashnikova Tezaur, (2015). Advances in Ice Sheet Model Initialization Using the First Order Model Siam CSE 2015 https://www.osti.gov/search/identifier:1245907 Document ID: 232557

Michael S. Eldred, Leo W.T. Ng, Matthew F. Barone, Stefan P. Domino, (2015). Multifidelity Uncertainty Quantification Using Spectral Stochastic Discrepancy Models Handbook of Uncertainty Quantification https://www.osti.gov/search/identifier:1191876 Document ID: 221762

Michael S. Eldred, Laura Painton Swiler, Brian M. Adams, (2014). Overview of Selected DOE/NNSA Predictive Science Initiatives: the Predictive Science Academic Alliance Program and the DAKOTA Project AIAA SciTech 2015 https://www.osti.gov/search/identifier:1315416 Document ID: 219531

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

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

John Davis Jakeman, Michael S. Eldred, Khachik Sargsyan, (2014). Enhancing `1-minimization estimates of polynomial chaos expansions using basis selection Journal of Computational Physics https://www.osti.gov/search/identifier:1182997 Document ID: 143056

Habib N. Najm, Michael S. Eldred, Bert Debusschere, Kamaljit Singh Chowdhary, John Davis Jakeman, Cosmin Safta, Khachik Sargsyan, (2014). An Overview of Select UQ Algorithms and their Utility in Applications https://www.osti.gov/search/identifier:1494413 Document ID: 143239

Michael S. Eldred, Bert Debusschere, Kamaljit Singh Chowdhary, John Davis Jakeman, Habib N. Najm, Cosmin Safta, Khachik Sargsyan, (2014). Sandia Software Enabling Extreme-Scale Uncertainty Quantification https://www.osti.gov/search/identifier:1494264 Document ID: 143017

Michael S. Eldred, (2014). Building on the Foundation: Optimization Under Uncertainty and Related Topics Uncertainty Quantification in Computational Fluid Dynamics – STO-AVT-235 https://www.osti.gov/search/identifier:1496693 Document ID: 111983

Michael S. Eldred, Richard V. Field, (2014). Introduction to Uncertainty Analysis Uncertainty Quantification in Computational Fluid Dynamics – STO-AVT-235 https://www.osti.gov/search/identifier:1497456 Document ID: 111982

Matthew F. Barone, Michael S. Eldred, A. Santiago Padron, Juan J. Alonso, F. Palacios, (2014). Multi-Fidelity Uncertainty Quantification: Application to a Vertical Axis Wind Turbine Under an Extreme Gust AIAA Aviation 2014 https://www.osti.gov/search/identifier:1315382 Document ID: 5337082

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

Cosmin Safta, Khachik Sargsyan, Habib N. Najm, Kamaljit Singh Chowdhary, Bert Debusschere, Laura Painton Swiler, Michael S. Eldred, (2014). Probabilistic Methods for Sensitivity Analysis and Calibration of Computer Models in the NASA Challenge Problem Journal of Aerospace Information Systems https://www.osti.gov/search/identifier:1141704 Document ID: 5334156

Khachik Sargsyan, Habib N. Najm, Kamaljit Singh Chowdhary, Bert Debusschere, Laura Painton Swiler, Michael S. Eldred, (2014). Uncertainty Quantification Methods for Model Calibration, Validation, and Risk Analysis 16th AIAA Non-Deterministic Approaches Conference https://www.osti.gov/search/identifier:1140342 Document ID: 5331824

Khachik Sargsyan, Habib N. Najm, Kamaljit Singh Chowdhary, Bert Debusschere, Laura Painton Swiler, Michael S. Eldred, (2013). Uncertainty Quantification Methods for Model Calibration, Validation, and Risk Analysis 16th AIAA Non-Deterministic Approaches Conference https://www.osti.gov/search/identifier:1122619 Document ID: 5331009

John Davis Jakeman, Michael S. Eldred, (2013). Constructing Polynomial Chaos Expansions via Compressed Sensing and Cross ValidationCompressed Sensing and Cross Validation 12th US National Congress on Computational Mechancx https://www.osti.gov/search/identifier:1106456 Document ID: 5325307

Stuart L. Kupferman, Irina Kalashnikova Tezaur, Mauro Perego, Raymond S. Tuminaro, Michael S. Eldred, John Davis Jakeman, (2013). Rapid Development of an Ice Sheet Climate Application using the Components-Based Approach CIS External Review https://www.osti.gov/search/identifier:1661056 Document ID: 5322040

Brian M. Adams, Michael S. Eldred, Laura Painton Swiler, (2013). Dakota: Advanced Exploration of Simulations SNL Engineering Science Research Foundations (ESRF), External Advisory Board https://www.osti.gov/search/identifier:1660832 Document ID: 5321464

Mauro NMN Perego, Michael S. Eldred, Max Gunazburger, Andrew G. Salinger, Irina Kalashnikova Tezaur, L. Ju, M Hoffman, W. Leng, S Price, G. Stadler, (2013). FELIX: advances in modeling forward and inverse icesheet problems EGU 2013 Conference https://www.osti.gov/search/identifier:1073162 Document ID: 5321007

Gary L Kellogg, Bert Debusschere, Michael S. Eldred, R. Ghanem, Ghattas. O, R. Moser, E Prudencio, D Higdon, J Gattiker, O Kino, Y Marzouk, (2012). Quantification of Uncertainty in Extreme Scale Computations (QUEST)in Extreme Scale Computations (QUEST) SciDAC PI Meeting, https://www.osti.gov/search/identifier:1073262 Document ID: 5312659

Brian M. Adams, Laura Painton Swiler, Michael S. Eldred, David M. Gay, (2012). DAKOTA Training 2008: Uncertainty Quantification DAKOTA Training 2008 Document ID: 5268444

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

Gary L Kellogg, Khachik Sargsyan, Cosmin Safta, Bert Debusschere, John Davis Jakeman, Michael S. Eldred, (2012). Sparse Polynomial Representations of High Dimensional ModelsDimensional Models 10th World Congress On Computational Mechanics https://www.osti.gov/search/identifier:1073443 Document ID: 5310093

James R Kamm, V. Gregory Weirs, Laura Painton Swiler, Brian M. Adams, William J. Rider, Michael S. Eldred, Marco Ratto, Stefano Tarantola, (2012). A Sensitivity Analysis of the Gas Dynamics Equations XII International Workshop on Supercomputing and Mathematical Modeling https://www.osti.gov/search/identifier:1121790 Document ID: 5287745

Brian M. Adams, Laura Painton Swiler, Michael S. Eldred, (2012). Practical UQ for Engineering Applications with DAKOTA SIAM Conference on Uncertainty Quantification (UQ12) https://www.osti.gov/search/identifier:1117563 Document ID: 5306236

Juan J. Alonso, K. Duraisamy, G. Iaccarino, G. Tang, J.A.S. Witteveen, Matthew F. Barone, Stefan P. Domino, Michael S. Eldred, D. Xiu, (2012). Large-Scale Uncertainty and Error Analysis for Time-dependent Fluid/Structure Interactions in Wind Turbine Applications: Summary of Advances in Algorithm Research and Deployment DOE Exascale Research Conference https://www.osti.gov/search/identifier:1068478 Document ID: 5305342

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