Daniel Thomas Seidl

John Jakeman, Michael Eldred, Gianluca Geraci, Daniel Seidl, Thomas Smith, Alex Gorodetsky, Trung Pham, Akil Narayan, Xiaoshu Zeng, Roger Ghanem, (2022). Multi-fidelity information fusion and resource allocation https://doi.org/10.2172/1888363 Publication ID: 80245

Michael Eldred, Gianluca Geraci, Alex Gorodetsky, John Jakeman, Teresa Portone, Timothy Wildey, Ahmad Rushdi, Daniel Seidl, (2021). The Dakota Project: Connecting the Pipeline from Uncertainty Quantification R&D to Mission Impact https://www.osti.gov/servlets/purl/1891078 Publication ID: 76127

Daniel Seidl, Elizabeth Jones, Brian Lester, (2021). Comprehensive Material Characterization and Simultaneous Model Calibration for Improved Computational Simulation Credibility https://doi.org/10.2172/1820000 Publication ID: 75609

Paul Mariner, Timothy Berg, Bert Debusschere, Aubrey Eckert, Jacob Harvey, Tara LaForce, Rosemary Leone, Melissa Mills, Michael Nole, Heeho Park, Perry, Daniel Seidl, Laura Swiler, Kyung Chang, (2021). GDSA Framework Development and Process Model Integration FY2021 https://doi.org/10.2172/1825056 Publication ID: 76168

Daniel Seidl, John Jakeman, (2021). Improving Digital Twins by Learning from a Fleet of Assets https://doi.org/10.2172/1889023 Publication ID: 75878

John Jakeman, Michael Eldred, Gianluca Geraci, Teresa Portone, Ahmad Rushdi, Daniel Seidl, Thomas Smith, (2021). Multi-fidelity Machine Learning https://doi.org/10.2172/1876608 Publication ID: 79162

Friedrich Menhorn, Gianluca Geraci, Daniel Seidl, Michael Eldred, Ryan King, Hans-Joachim Bungartz, Youssef Marzouk, (2021). Multilevel Estimators for Measures of Robustness in Optimization under Uncertainty https://doi.org/10.2172/1881729 Publication ID: 79510

Daniel Seidl, Brian Granzow, (2021). Calibration of Elastoplastic Constitutive Model Parameters from Full-Field Data with Automatic Differentiation-based Sensitivities https://doi.org/10.2172/1884132 Publication ID: 79534

Alan Hsieh, David Maniaci, Gianluca Geraci, Daniel Seidl, Thomas Herges, Kenneth Brown, James Cutler, (2021). Application of Multifidelity Uncertainty Quantification Towards Multi-turbine Interaction and Wake Characterization https://doi.org/10.2172/1870979 Publication ID: 78674

Timothy Berg, Paul Mariner, Bert Debusschere, Daniel Seidl, Rosemary Leone, Kyung Chang, (2021). Machine Learning Surrogates for the Fuel Matrix Degradation Model https://www.osti.gov/servlets/purl/1869760 Publication ID: 78570

Timothy Berg, Kyung Chang, Rosemary Leone, Daniel Seidl, Paul Mariner, Bert Debusschere, (2021). Surrogate Modeling of Spent Fuel Degradation for Repository Performance Assessment https://doi.org/10.2172/1854307 Publication ID: 77449

Friedrich Menhorn, Gianluca Geraci, Daniel Seidl, Michael Eldred, Ryan King, Hans-Joachim Bungartz, Youssef Marzouk, (2021). Multifidelity Monte Carlo Estimators for Robust Formulations in Optimization under Uncertainty https://doi.org/10.2172/1847580 Publication ID: 77379

Samuel Fayad, Elizabeth Jones, Phillip Reu, Daniel Seidl, John Lambros, (2021). Sensitivity-Based Simultaneous Experimentation and Calibration of Complex Elasto-Plastic Models https://www.osti.gov/servlets/purl/1847583 Publication ID: 77258

Friedrich Menhorn, Gianluca Geraci, Daniel Seidl, Michael Eldred, Ryan King, Hans-Joachim Bungartz, Youssef Marzouk, (2020). Multifidelity strategies for optimization under uncertainty of wind power plants https://doi.org/10.2172/1836901 Publication ID: 72258

Daniel Seidl, Brian Granzow, (2020). Elastoplastic Constitutive Model Calibration with Automatic Differentiation-based Sensitivities https://doi.org/10.2172/1830965 Publication ID: 71066

David Maniaci, Alan Hsieh, Gianluca Geraci, Daniel Seidl, Thomas Herges, Michael Eldred, Myra Blaylo, Brent 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 https://www.osti.gov/servlets/purl/1778659 Publication ID: 73286

Alan Hsieh, David Maniaci, Thomas Herges, Gianluca Geraci, Daniel Seidl, Michael Eldred, Myra Blaylock, Brent Houchens, (2020). Multilevel Uncertainty Quantification Using CFD and OpenFAST Simulations of the SWiFT Facility https://doi.org/10.2514/6.2020-1949 Publication ID: 70698

Paul Mariner, Bert Debusschere, Glenn Hammond, Daniel Seidl, swiler laura, Jonathon Vo , (2020). Surrogate Modeling of Spatially Heterogeneous Source Terms for Probabilistic Assessment of Repository Performance https://www.osti.gov/servlets/purl/1763614 Publication ID: 70908

Menhorn Friedrich, Gianluca Geraci, Daniel Seidl, Michael Eldred, King Ryan, Bungartz Hans-Joachim, Marzouk Youssef, (2019). Higher moment multilevel estimators for optimization under uncertainty applied to wind plant design https://www.osti.gov/servlets/purl/1643359 Publication ID: 66951

Paul Mariner, Bert Debusschere, James Jerden, Daniel Seidl, Laura Swiler, Jonathan Vo, (2019). Lessons Learned in the Development of Source Term Surrogate Models for Repository Performance Assessment https://www.osti.gov/servlets/purl/1643084 Publication ID: 66069

Samuel Fayad, Daniel Seidl, Phillip Reu, (2019). Minimizing Pattern Induced Bias in Digital Image Correlation https://www.osti.gov/servlets/purl/1642830 Publication ID: 65655

Paul Mariner, Laura Connolly, Leigh Cunningham, Bert Debusschere, David Dobson, Jennifer Frederick, Glenn Hammond, Spencer Jordan, Tara LaForce, Michael Nole, Heeho Park, Frank Perry, Ralph Rogers, Daniel Seidl, Stephen Sevougian, Emily Stein, Peter Swift, Laura Swiler, Jonathan Vo, Michael Wallace, (2019). Progress in Deep Geologic Disposal Safety Assessment in the U.S. since 2010 https://doi.org/10.2172/1570094 Publication ID: 65476

Michael Eldred, Gianluca Geraci, Daniel Seidl, Friedrich Menhorn, Ryan King, Thomas Herges, Alan Hsieh, David Maniaci, (2019). Milestone: Develop multilevel emulator-based Bayesian inference capabilities and demonstrate data assimilation for SWiFT configuration https://www.osti.gov/servlets/purl/1646013 Publication ID: 65367

Samuel Fayad, Phillip Reu, Daniel Seidl, (2019). Pattern Induced Bias in Digital Image Correlation https://www.osti.gov/servlets/purl/1640639 Publication ID: 68924

Paul Mariner, Laura Swiler, Daniel Seidl, Jonathan Vo, (2019). Lessons Learned in the Development of Source Term Surrogate Models for Repository Performance Assessment https://www.osti.gov/servlets/purl/1640670 Publication ID: 69032

Paul Mariner, Daniel Seidl, Laura Swiler, Bert Debusschere, Jonathan Vo, Jim Jerden, Jennifer Frederick, (2019). Surrogate Modeling of Fuel Dissolution https://www.osti.gov/servlets/purl/1648825 Publication ID: 68682

Paul Mariner, Laura Swiler, Daniel Seidl, Bert Debusschere, Johnathan Vo, Jennifer Frederick, (2019). High Fidelity Surrogate Modeling of Fuel Dissolution for Probabilistic Assessment of Repository Performance https://www.osti.gov/servlets/purl/1639277 Publication ID: 67301

Paul Mariner, Laura Swiler, Daniel Seidl, Bert Debusschere, Johnathan Vo, Jennifer Frederick, (2019). High Fidelity Surrogate Modeling of Fuel Dissolution for Probabilistic Assessment of Repository Performance https://www.osti.gov/servlets/purl/1602117 Publication ID: 67105

Paul Mariner, Laura Swiler, Daniel Seidl, Bert Debusschere, Jonathan Vo, Jennifer Frederick, James Jerden, (2019). High fidelity surrogate modeling of fuel dissolution for probabilistic assessment of repository performance International High-Level Radioactive Waste Management 2019, IHLRWM 2019 https://www.osti.gov/servlets/purl/1595546 Publication ID: 64431

R. Roach, Nicolas Argibay, Kyle Allen, Dorian Balch, Lauren Beghini, Joseph Bishop, Brad Boyce, Judith Brown, Ross Burchard, Michael Chandross, Adam Cook, Christopher DiAntonio, Amber Dressler, Eric Forrest, Kurtis Ford, Thomas Ivanoff, Bradley Jared, Kyle Johnson, Daniel Kammler, Joshua Koepke, Andrew Kustas, Judith Lavin, Nicholas Leathe, Brian Lester, J. Madison, Seethambal Mani, Mario Martinez, Daniel Moser, Theron Rodgers, Daniel Seidl, Harlan Brown-Shaklee, Joshua Stanford, Michael Stender, Joshua Sugar, Laura Swiler, Samantha Taylor, Bradley Trembacki, (2018). Born Qualified Grand Challenge LDRD Final Report https://doi.org/10.2172/1481619 Publication ID: 59393

Brian Granzow, Daniel Seidl, (2018). Adjoint-based Calibration of Plasticity Model Parameters from Digital Image Correlation Data https://doi.org/10.2172/1474264 Publication ID: 59095

Elizabeth Jones, Jay Carroll, Kyle Karlson, Sharlotte Kramer, Richard Lehoucq, Phillip Reu, Daniel Seidl, Daniel Turner, (2018). High-throughput Material Characterization using the Virtual Fields Method https://doi.org/10.2172/1474817 Publication ID: 59110

Timothy Wildey, Troy Butler, John Jakeman, Daniel Seidl, Bart van Bloemen Waanders, (2018). Data-informed Multiscale Modeling of Additive Materials https://www.osti.gov/servlets/purl/1523778 Publication ID: 62297

Daniel Seidl, Bart van Bloemen Waanders, Timothy Wildey, (2018). Multiscale Interfaces for Large Scale Optimization https://www.osti.gov/servlets/purl/1525680 Publication ID: 61583

R. Roach, Bradley Jared, Adam Cook, David Keicher, Bart van Bloemen Waanders, Laura Swiler, Daniel Seidl, Timothy Wildey, Shaun Whetten, (2018). Born Qualified EAB Telecon https://www.osti.gov/servlets/purl/1514821 Publication ID: 60282

Daniel Seidl, Daniel Turner, Elizabeth Jones, Kyle Karlson, Phillip Reu, (2018). Optimal Mechanical Testing for Constitutive Parameter Identification https://www.osti.gov/servlets/purl/1498447 Publication ID: 60905

Timothy Wildey, Bart van Bloemen Waanders, Daniel Seidl, (2017). Adaptive Multiscale Modeling Using Generalized Mortar Methods https://www.osti.gov/servlets/purl/1513505 Publication ID: 57313

Timothy Wildey, Bart van Bloemen Waanders, Daniel Seidl, (2017). Multiscale Modeling Using Mortar Methods https://www.osti.gov/servlets/purl/1458195 Publication ID: 56724

Daniel Seidl, Bart van Bloemen Waanders, Timothy Wildey, (2017). Multiscale Interfaces for Large Scale Optimization https://www.osti.gov/servlets/purl/1456522 Publication ID: 55715

Bart van Bloemen Waanders, Timothy Wildey, Daniel Seidl, Harriet Li, (2017). Multiscale optimization under uncertainty for additive manufacturing https://www.osti.gov/servlets/purl/1426379 Publication ID: 55236

Daniel Seidl, Bart van Bloemen Waanders, Timothy Wildey, (2017). Simultaneous Estimation of Material Parameters and Neumann Boundary Conditions in a Linear Elastic Model by PDE-Constrained Optimization https://www.osti.gov/servlets/purl/1458297 Publication ID: 54920

Bart van Bloemen Waanders, Timothy Wildey, Daniel Seidl, Harriet Li, (2017). Multiscale optimization under uncertainty https://www.osti.gov/servlets/purl/1458249 Publication ID: 55002

Timothy Wildey, Bart van Bloemen Waanders, Daniel Seidl, (2016). Uncertainty Quantification for Multiscale Mortar Methods https://www.osti.gov/servlets/purl/1368791 Publication ID: 50172

Timothy Wildey, Bart van Bloemen Waanders, Daniel Seidl, Todd Arbogast, Ben Ganis, Vivette Girault, Gergina Pencheva, Mary Wheeler, Guangri Xue, Ivan Yotov, Simon Tavener, Martin Vohralik, (2016). Multiscale Mortar Methods: Theory Applications and Future Directions https://www.osti.gov/servlets/purl/1365248 Publication ID: 49573

Bart van Bloemen Waanders, Timothy Wildey, Daniel Seidl, Harriet Li, (2016). Multiscale Optimization Under Uncertainty https://www.osti.gov/servlets/purl/1348106 Publication ID: 48990