Publications

Grant, R.E., Hammond, S.D., Bachman, W.B., Levenhagen, M., Olivier, S.L., Bachman, W.B., Ward, L., Younge, A.J., & Younge, A.J. (2023). Enabling power measurement and control on Astra: The first petascale Arm supercomputer. Concurrency and Computation: Practice and Experience, 35(15). https://doi.org/10.1002/cpe.7303

Bachman, W.B., Maupin, K.A., Rodgers, T., & Rodgers, T. (2023). Monotonic Gaussian Process for Physics-Constrained Machine Learning With Materials Science Applications. Journal of Computing and Information Science in Engineering, 23(1). https://doi.org/10.1115/1.4055852

Bachman, W.B., Sun, J., Liu, D., Wang, Y., Wildey, T., & Wildey, T. (2022). A Stochastic Reduced-Order Model for Statistical Microstructure Descriptors Evolution. Journal of Computing and Information Science in Engineering, 22(6). https://doi.org/10.1115/1.4054237

Bachman, W.B., Wildey, T., Lim, H., & Lim, H. (2022). Microstructure-Sensitive Uncertainty Quantification for Crystal Plasticity Finite Element Constitutive Models Using Stochastic Collocation Methods. Frontiers in Materials, 9. https://doi.org/10.3389/fmats.2022.915254

Mariner, P.E., Debusschere, B.J., Fukuyama, D.E., Harvey, J.A., Laforce, T., Leone, R.C., Bachman, W.B., Swiler, L.P., Taconi, A., & Taconi, A. (2022). GDSA Framework Development and Process Model Integration FY2022. https://doi.org/10.2172/1893995

Laforce, T., Basurto, E., Chang, K.W., Ebeida, M., Eymold, W., Faucett, C.A., Jayne, R., Kucinski, N., Leone, R.C., Mariner, P.E., Bachman, W.B., & Bachman, W.B. (2022). GDSA Repository Systems Analysis Investigations in FY2022. https://doi.org/10.2172/1898245

Maupin, K.A., Bachman, W.B., Bachman, W.B., Knapp, P.F., Joseph, V.R., Wu, C.F.J., Glinsky, M.E., Valaitis, S.M., & Valaitis, S.M. (2022). Towards Z-Next: The Integration of Theory, Experiments, and Computational Simulation in a Bayesian Data Assimilation Framework. https://doi.org/10.2172/1891191

Hansen, S.B., Baczewski, A.D., Gomez, T., Hentschel, T.W., Jennings, C.A., Kononov, A., Nagayama, T., Adler, K., Cangi, A., Cochrane, K.R., Bachman, W.B., Schleife, A., & Schleife, A. (2022). Improving Predictive Capability in REHEDS Simulations with Fast, Accurate, and Consistent Non-Equilibrium Material Properties. https://doi.org/10.2172/1890268

Bachman, W.B., Portone, T., Dandekar, R., Rackauckas, C., Bandy, R.J., Huerta, J.G., Dytzel, I., & Dytzel, I. (2022). Model-Form Epistemic Uncertainty Quantification for Modeling with Differential Equations: Application to Epidemiology. https://doi.org/10.2172/1888443

Robinson, A.C., Swan, M.S., Harvey, E.C., Klein, B., Lawson, G., Milewicz, R.M., Bachman, W.B., Schmitz, M.E., Warnock, S.A., & Warnock, S.A. (2022). An introduction to developing GitLab/Jacamar runner analyst centric workflows at Sandia. https://doi.org/10.2172/1885645

Swiler, L.P., Basurto, E., Brooks, D.M., Eckert, A., Leone, R.C., Mariner, P.E., Portone, T., Bachman, W.B., & Bachman, W.B. (2022). Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2022). https://doi.org/10.2172/1884909

Roberds, N.A., Cartwright, K.L., Sandoval, A.J., Beckwith, K., Cyr, E.C., Bachman, W.B., & Bachman, W.B. (2022). Numerical simulation of a relativistic magnetron using a fluid electron model. Physics of Plasmas, 29(8). https://doi.org/10.1063/5.0090351

Hamlin, N.D., Smith, T.M., Roberds, N.A., Bachman, W.B., Beckwith, K., & Beckwith, K. (2022). Electrostatic Relativistic Fluid Models of Electron Emission in a Warm Diode. IEEE International Conference on Plasma Science (ICOPS), 2022, pp. 1-26. https://doi.org/10.1109/icops45751.2022.9813152

Schonbein, W., Barrett, B.W., Brightwell, R.B., Grant, R.E., Hemmert, K.S., Bachman, W.B., Underwood, K., Riesen, R., Hoefler, T., Barbe, M., Suraty Filho, L.H., Ratchov, A., MacCabe, A.B., & MacCabe, A.B. (2022). The Portals 4.3 Network Programming Interface. https://doi.org/10.2172/1875218

Adams, B.M., Bohnhoff, W.J., Dalbey, K.R., Ebeida, M.S., Eddy, J.P., Eldred, M.S., Hooper, R.W., Hough, P.D., Hu, K.T., Jakeman, J.D., Khalil, M., Maupin, K.A., Monschke, J.A., Ridgway, E.M., Rushdi, A.A., Seidl, D.T., Stephens, J.A., Swiler, L.P., Bachman, W.B., Winokur, J.G., & Winokur, J.G. (2021). Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis (V.6.16 User's Manual). https://doi.org/10.2172/1868142

Bachman, W.B., Schleife, A., Baczewski, A.D., Hansen, S.B., Kononov, A., & Kononov, A. (2021). Optical Properties of Be at High Temperatures from First Principles [Conference Presenation]. https://doi.org/10.2172/1897695

Steiner, A.M., Siefert, C., Shipley, G.A., Redline, E., Dickens, S.M., Jaramillo, R., Chavez, T.P., Hutsel, B.T., Bachman, W.B., Peterson, K.J., Bell, K., Balogun, S., Losego, M., Sammeth, T., Kern, I., Harjes, C., Gilmore, M., Lehr, J., & Lehr, J. (2021). Investigating Volumetric Inclusions of Semiconductor Materials to Improve Flashover Resistance in Dielectrics [Conference Poster]. https://doi.org/10.2172/1899533

Leger, M., Darling, M.C., Jones, S.T., Matzen, L.E., Stracuzzi, D.J., Wilson, A.T., Bueno, D., Christentsen, M., Ginaldi, M., Bachman, W.B., Heidbrink, S., Howell, B.C., Leger, C., Reedy, G., Rogers, A.N., Williams, J., & Williams, J. (2021). Exploring Explicit Uncertainty for Binary Analysis (EUBA). https://doi.org/10.2172/1832314

Bachman, W.B., Tranchida, J., & Tranchida, J. (2021). Multi-fidelity Gaussian process and Bayesian optimization for materials design: Application to ternary random alloys [Conference Presenation]. https://doi.org/10.2172/1898471

Bachman, W.B., Eldred, M., McCann, S., Wang, Y., & Wang, Y. (2021). srMO-BO-3GP: A sequential regularized multi-objective Bayesian optimization for constrained design applications using an uncertain Pareto classifier. Journal of Mechanical Design, 144(3). https://doi.org/10.1115/1.4052445

Oldfield, R., Kramer, S., Rushdi, A., Bachman, W.B., Emery, J., Kuberry, P., Ray, J., Ackerman, S., Cyr, E.C., Saavedra, G., Hughes, C., Cardwell, S.G., Smith, J.D., & Smith, J.D. (2021). The ASC Advanced Machine Learning Initiative at Sandia National Laboratories: FY21 Accomplishments and FY22 Plans [Presentation]. https://www.osti.gov/biblio/1895016

Smith, M.R., Bachman, W.B., Ames, A., Carey, A., Cuellar, C.R., Field, R.V., Maxfield, T., Mitchell, S.A., Morris, E., Moss, B., Nyre-Yu, M., Rushdi, A., Stites, M.C., Smutz, C., Zhou, X., & Zhou, X. (2021). SAGE Intrusion Detection System: Sensitivity Analysis Guided Explainability for Machine Learning. https://doi.org/10.2172/1820253

Brandt, J.M., Cook, J., Aaziz, O., Allan, B., Devine, K., Bachman, W.B., Gentile, A.C., Hammond, S., Kelley, B., Lopatina, L., Moore, S.G., Olivier, S.L., Bachman, W.B., Poliakoff, D., Pawlowski, R., Regier, P., Schmitz, M.E., Schwaller, B., Surjadidjaja, V., … Walton, S.P. (2021). Integrated System and Application Continuous Performance Monitoring and Analysis Capability [Presentation]. https://www.osti.gov/biblio/1886175

Shand, L., Bachman, W.B., Staid, A., Roesler, E.L., Lyons, D., Simonson, K.M., Patel, L., Hickey, J., Gray, S., & Gray, S. (2021). Local limits of detection for anthropogenic aerosol-cloud interactions. https://doi.org/10.2172/1855009

Bachman, W.B. (2021). Gaussian process and Bayesian optimization - Bridging the gap between theory and practice in materials science [Conference Presenation]. https://doi.org/10.2172/1888412

Aaziz, O., Allan, B., Brandt, J.M., Cook, J., Devine, K., Elliott, J., Gentile, A.C., Hammond, S., Kelley, B., Lopatina, L., Moore, S.G., Olivier, S.L., Bachman, W.B., Poliakoff, D., Pawlowski, R., Regier, P., Schmitz, M.E., Schwaller, B., Surjadidjaja, V., … Walton, S.P. (2021). Integrated System and Application Continuous Performance Monitoring and Analysis Capability. https://doi.org/10.2172/1819812

Oldfield, R., Plimpton, S.J., Bachman, W.B., Poliakoff, D., Sornborger, A., & Sornborger, A. (2021). Memo regarding the Final Review of FY21 ASC L2 Milestone 7840: Neural Mini-Apps for Future Heterogeneous HPC Systems. https://doi.org/10.2172/1825628

Swiler, L.P., Basurto, E., Brooks, D.M., Eckert, A., Leone, R.C., Mariner, P.E., Portone, T., Bachman, W.B., Stein, E., & Stein, E. (2021). Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2021). https://doi.org/10.2172/1855018

Bachman, W.B., Schleife, A., Kononov, A., Hansen, S.B., Baczewski, A.D., & Baczewski, A.D. (2021). Optical Properties of Be at High Temperatures from First Principles [Presentation]. https://www.osti.gov/biblio/1884067

Harvey-Thompson, A.J., Geissel, M., Crabtree, J.A., Weis, M.R., Gomez, M.R., Fein, J.R., Ampleford, D.J., Awe, T.J., Chandler, G.A., Galloway, B.R., Hansen, S.B., Hanson, J., Harding, E.C., Jennings, C.A., Kimmel, M., Knapp, P.F., Lamppa, D.C., Bachman, W.B., Mangan, M.A., … Smith, G.E. (2021). Increased preheat energy to MagLIF targets with cryogenic cooling [Conference Presenation]. https://doi.org/10.2172/1888953

Laros, J.H., Hammond, S., Bachman, W.B., & Bachman, W.B. (2021). Vanguard-II Application Evaluation Thrust [Presentation]. https://www.osti.gov/biblio/1884443

Younge, A.J., Hammond, S., Bachman, W.B., Bachman, W.B., & Bachman, W.B. (2021). Sandias Experiences with Arm [Conference Presenation]. https://doi.org/10.2172/1875380

Younge, A.J., Fuller, T.J., Bachman, W.B., Bova, S.W., & Bova, S.W. (2021). A Case Study in Using Containers to Build and Distribute HPC Applications: ALEGRA [Conference Presenation]. https://doi.org/10.2172/1876620

Wildey, T., Butler, T., Jakeman, J.D., Bachman, W.B., & Bachman, W.B. (2021). Solving Stochastic Inverse Problems for Property-Structure Relationships in Computational Materials Science [Conference Presenation]. https://doi.org/10.2172/1890916

Maupin, K.A., Bachman, W.B., Glinsky, M.E., & Glinsky, M.E. (2021). Multi-Output Surrogate Construction for Fusion Simulations [Conference Presenation]. https://doi.org/10.2172/1888976

Portone, T., Bachman, W.B., Dandekar, R., Rackauckas, C., & Rackauckas, C. (2021). Learning Missing Mechanisms in a Dynamical System from a Subset of State Variable Observations [Conference Presenation]. https://doi.org/10.2172/1889367

Bachman, W.B., Portone, T., & Portone, T. (2021). Assessing the Efficacy of Universal Differential Equations to Learn Missing Dynamics from a Subset of Observable State Variables [Conference Presenation]. https://doi.org/10.2172/1882346

Krygier, M., Labonte, T., Martinez, C., Norris, C., Sharma, K., Collins, L.N., Mukherjee, P.P., Bachman, W.B., & Bachman, W.B. (2021). Quantifying the Unknown: Impact of Segmentation Uncertainty on Image-based Simulations [Conference Presenation]. https://doi.org/10.2172/1884065

Giem, E., Bachman, W.B., Poliakoff, D., Teranishi, K., Hollman, D., & Hollman, D. (2021). Resilient Kokkos: Resilient Execution Spaces [Presentation]. https://www.osti.gov/biblio/1888644

Younge, A.J., Hammond, S., Bachman, W.B., Bachman, W.B., & Bachman, W.B. (2021). Containers and the Arm Ecosystem [Conference Presenation]. https://doi.org/10.2172/1871627

Rodgers, T., Abdeljawad, F., Moser, D.R., Bachman, W.B., Carroll, J.D., Jared, B.H., Bolintineanu, D.S., Mitchell, J.A., Madison, J., & Madison, J. (2021). Simulation of powder bed metal additive manufacturing microstructures with coupled finite difference-Monte Carlo method. Additive Manufacturing, 41. https://doi.org/10.1016/j.addma.2021.101953

Bachman, W.B. (2021). Advanced Tri-lab Software Environment (ATSE) [Presentation]. https://www.osti.gov/biblio/1869233

Bachman, W.B., Maniaci, D.C., Geraci, G., Seidl, D.T., Herges, T., Brown, K.A., Cutler, J.J., & Cutler, J.J. (2021). Application of Multifidelity Uncertainty Quantification Towards Multi-turbine Interaction and Wake Characterization [Conference Presenation]. https://doi.org/10.2172/1870979

Kramer, S., Bolintineanu, D.S., Long, K., Hamel, C., Frankel, A., Jones, R.E., Bachman, W.B., Swiler, L.P., Johnson, K.L., & Johnson, K.L. (2021). Mechanics of Materials Utilizing Machine Learning: Examples at Sandia National Laboratories [Conference Presenation]. https://doi.org/10.2172/1867564

Younge, A.J., Agelastos, A.M., Lawson, G., Bachman, W.B., & Bachman, W.B. (2021). Containers at Sandia [Conference Presenation]. https://doi.org/10.2172/1863696

Hammond, S., Bachman, W.B., Bachman, W.B., Younge, A.J., Hoekstra, R.J., & Hoekstra, R.J. (2021). Experiences with Arm [Presentation]. https://www.osti.gov/biblio/1866197

Hammond, S., Curry, M., Davis, K., Dang, V., Guba, O., Hoekstra, R.J., Bachman, W.B., Bachman, W.B., Poliakoff, D., Rajamanickam, S., Trott, C.R., Younge, A.J., & Younge, A.J. (2021). Fugaku and A64FX Update - April 2021 [Presentation]. https://www.osti.gov/biblio/1882368

Bachman, W.B., Ivie, J.A., Campbell, Q.T., Brickson, M.I., Schultz, P.A., Muller, R.P., Baczewski, A.D., Mounce, A.M., Bussmann, E., Misra, S., & Misra, S. (2021). Stochastic atomistic disorder in atomic-precision doping [Conference Presenation]. https://doi.org/10.2172/1855714

Olivier, S.L., Brightwell, R.B., Ferreira, K., Grant, R., Levy, S.L.N., Bachman, W.B., Younge, A.J., & Younge, A.J. (2021). SNL ATDM Software Ecosystem Operating Systems and On-Node Runtime [Presentation]. https://www.osti.gov/biblio/1861479

Bachman, W.B., Tranchida, J., Wildey, T., Thompson, A.P., & Thompson, A.P. (2021). Multi-fidelity ML/UQ and Bayesian Optimization for Materials Design: Application to Ternary Random Alloys [Conference Poster]. https://doi.org/10.2172/1853874