| Optimizing a falling particle receiver geometry using CFD simulations to maximize the thermal efficiency B Mills, B Schroeder, L Yue, R Shaeffer, CK Ho AIP Conference Proceedings 2303 (1), 2020 | 19 | 2020 |
| Distinguishing between model- and data-driven inferences for high reliability statistical predictions L Hund, B Schroeder, K Rumsey, G Huerta Reliability Engineering & System Safety 180, 201-210, 2018 | 18 | 2018 |
| A causal perspective on reliability assessment L Hund, B Schroeder Reliability Engineering & System Safety 195, 106678, 2020 | 16 | 2020 |
| Simple effective conservative treatment of uncertainty from sparse samples of random variables and functions VJ Romero, BB Schroeder, JF Dempsey, NL Breivik, GE Orient, ... ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B …, 2018 | 16 | 2018 |
| Scale-bridging model development and increased model credibility BB Schroeder The University of Utah, 2015 | 15 | 2015 |
| TABS: A Thermal Battery Desktop Design Tool. SA Roberts, CF Jove-Colon, HK Moffat, ML Neilsen, ES Piekos, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018 | 14 | 2018 |
| Evaluation of a class of simple and effective uncertainty methods for sparse samples of random variables and functions V Romero, M Bonney, B Schroeder, VG Weirs Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2017 | 14 | 2017 |
| Multi-fidelity electrochemical modeling of thermally activated battery cells TG Voskuilen, HK Moffat, BB Schroeder, SA Roberts Journal of Power Sources 488, 229469, 2021 | 13 | 2021 |
| Theoretical framework for multiple-polymorph particle precipitation in highly supersaturated systems BB Schroeder, DD Harris, ST Smith, DO Lignell Crystal growth & design 14 (4), 1756-1770, 2014 | 13 | 2014 |
| Evaluation of a simple UQ approach to compensate for sparse stress-strain curve data in solid mechanics applications VJ Romero, JF Dampsey, B Schroeder, J Lewis, N Breivik, G Orient, ... 19th AIAA Non-Deterministic Approaches Conference, 0818, 2017 | 9 | 2017 |
| Multi-Physics Cost and Complexity Reduction Strategies for Modeling Thermally Activated Batteries. T Voskuilen, CF Jove-Colon, HK Moffat, BB Schroeder, B Trembacki, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018 | 8 | 2018 |
| Separability of mesh bias and parametric uncertainty for a full system thermal analysis BB Schroeder, H Silva III, KD Smith Journal of Verification, Validation and Uncertainty Quantification 3 (3), 031006, 2018 | 6 | 2018 |
| Cantilever beam end-to-end UQ test problem: handling experimental and simulation uncertainties in model calibration, model validation, and risk assessment V Romero, B Schroeder, M Glickman Sandia National Laboratories document SAND2017-4689 O, version …, 2017 | 5 | 2017 |
| ROBUST IMPORTANCE SAMPLING FOR BAYESIAN MODEL CALIBRATION WITH SPATIOTEMPORAL DATA K Neal, B Schroeder, J Mullins, A Subramanian, S Mahadevan International Journal for Uncertainty Quantification 11 (4), 2021 | 4 | 2021 |
| Supporting Credibility of Single Cell Thermal Battery Modeling through V&V/UQ Activities. BB Schroeder, E Allcorn, JC Hewson, HK Moffat, ES Piekos, B Trembacki, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018 | 4 | 2018 |
| Can-Crush Model and Simulations for Verifying Uncertainty Quantification Method for Sparse Stress-Strain Curve Data JF Dempsey, V Romero, N Breivik, G Orient, B Antoun, B Schroeder, ... ASME International Mechanical Engineering Congress and Exposition 50633 …, 2016 | 4 | 2016 |
| A Survey of Methods for Integration of Uncertainty and Model Form Error in Prediction. JG Mullins, BB Schroeder, RG Hills, LG Crespo Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2016 | 4 | 2016 |
| Summary of the 2014 Sandia Verification and Validation Challenge Workshop BB Schroeder, KT Hu, JG Mullins, JG Winokur Journal of Verification, Validation and Uncertainty Quantification 1 (1), 015501, 2016 | 4 | 2016 |
| The need for credibility guidance for analyses quantifying margin and uncertainty BB Schroeder, L Hund, RS Kittinger Model Validation and Uncertainty Quantification, Volume 3: Proceedings of …, 2020 | 3 | 2020 |
| Confidence in the prediction of unmeasured system output using roll-up methodology K Neal, C Li, Z Hu, S Mahadevan, J Mullins, B Schroeder, A Subramanian Model Validation and Uncertainty Quantification, Volume 3: Proceedings of …, 2019 | 3 | 2019 |
Justin WinokurSandia National LabsVerified email at sandia.gov
