| Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis: version 6.13 user's … BM Adams, WJ Bohnhoff, KR Dalbey, MS Ebeida, JP Eddy, MS Eldred, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2020 | 1176 | 2020 |
| Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis: Version 6.16 theory … KR Dalbey, MS Eldred, G Geraci, JD Jakeman, KA Maupin, JA Monschke, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021 | 78 | 2021 |
| DIC challenge 2.0: developing images and guidelines for evaluating accuracy and resolution of 2D analyses: focus on the metrological efficiency indicator PL Reu, B Blaysat, E Andò, K Bhattacharya, C Couture, V Couty, D Deb, ... Experimental Mechanics 62 (4), 639-654, 2022 | 58 | 2022 |
| Biomechanical imaging of cell stiffness and prestress with subcellular resolution EP Canović, DT Seidl, SR Polio, AA Oberai, PE Barbone, D Stamenović, ... Biomechanics and modeling in mechanobiology 13, 665-678, 2014 | 51 | 2014 |
| Spatial DIC errors due to pattern-induced bias and grey level discretization SS Fayad, DT Seidl, PL Reu Experimental Mechanics 60 (2), 249-263, 2020 | 42 | 2020 |
| The Coupled Adjoint-State Equation in forward and inverse linear elasticity: Incompressible plane stress DT Seidl, AA Oberai, PE Barbone Computer Methods in Applied Mechanics and Engineering 357, 112588, 2019 | 27 | 2019 |
| Three-dimensional traction microscopy accounting for cell-induced matrix degradation D Song, DT Seidl, AA Oberai Computer Methods in Applied Mechanics and Engineering 364, 112935, 2020 | 14 | 2020 |
| Surrogate Model Development of Spent Fuel Degradation for Repository Performance Assessment PE Mariner, TM Berg, KW Chang, BJ Debusschere, RC Leone, DT Seidl Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2020 | 12 | 2020 |
| Multilevel uncertainty quantification using cfd and openfast simulations of the swift facility A Hsieh, DC Maniaci, TG Herges, G Geraci, DT Seidl, MS Eldred, ... AIAA Scitech 2020 Forum, 1949, 2020 | 12 | 2020 |
| Progress in deep geologic disposal safety assessment in the US since 2010 PE Mariner, LA Connolly, LJ Cunningham, BJ Debusschere, DC Dobson, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2019 | 12 | 2019 |
| Born qualified grand challenge LDRD final report RA Roach, N Argibay, K Allen, DK Balch, LL Beghini, JE Bishop, B Boyce, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2018 | 12 | 2018 |
| On the importance of direct-levelling for constitutive material model calibration using digital image correlation and finite element model updating SS Fayad, EMC Jones, DT Seidl, PL Reu, J Lambros Experimental Mechanics 63 (3), 467-484, 2023 | 9 | 2023 |
| Calibration of elastoplastic constitutive model parameters from full‐field data with automatic differentiation‐based sensitivities DT Seidl, BN Granzow International Journal for Numerical Methods in Engineering 123 (1), 69-100, 2022 | 8 | 2022 |
| Advances in GDSA framework development and process model integration P Mariner, M Nole, E Basurto, TM Berg, KW Chang, B Debusschere, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2020 | 8 | 2020 |
| Simultaneous inversion of shear modulus and traction boundary conditions in biomechanical imaging DT Seidl, BG van Bloemen Waanders, TM Wildey Inverse Problems in Science and Engineering 28 (2), 256-276, 2020 | 8 | 2020 |
| Stiffness versus prestress relationship at subcellular length scale EP Canović, DT Seidl, PE Barbone, ML Smith, D Stamenović Journal of biomechanics 47 (12), 3222-3225, 2014 | 8 | 2014 |
| GDSA Framework Development and Process Model Integration FY2021 PE Mariner, TM Berg, BJ Debusschere, AC Eckert, J Harvey, TC LaForce, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021 | 7 | 2021 |
| Multifidelity strategies for forward and inverse uncertainty quantification of wind energy applications DT Seidl, G Geraci, R King, F Menhorn, A Glaws, MS Eldred AIAA Scitech 2020 Forum, 1950, 2020 | 6 | 2020 |
| Machine learning surrogates of a fuel matrix degradation process model for performance assessment of a nuclear waste repository BJ Debusschere, DT Seidl, TM Berg, KW Chang, RC Leone, LP Swiler, ... Nuclear Technology 209 (9), 1295-1318, 2023 | 5 | 2023 |
| A computational framework for elliptic inverse problems with uncertain boundary conditions DT Seidl Boston University, 2015 | 5 | 2015 |
