Abstract
Computer models for applications such as climate or materials have become increasingly complex. In particular, the input and output dimensions for these types of models has grown steadily larger, which has increased the computational burden of comparing these models with experimental data. This has spurred the development of statistical techniques for estimating outputs and reducing the dimension. This paper will show an example of these approaches applied to modeling and experiments for Tantalum, a material of interest for the Departments of Defense and Energy. We obtain results from a number of small-scale tests of Tantalum single crystals and use these results in a Bayesian statistical procedure to constrain the range and dimensionality of a Tantalum model.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Higdon, D., Gattiker, J., Williams, B., Rightley, M.: Computer model calibration using high-dimensional output. J. Am. Stat. Assoc. 103(482), 570–583 (2008)
Brynjarsdóttir, J., O’Hagan, A.: Learning about physical parameters: the importance of model discrepancy. Inverse Probl. 30(11), 114007 (2004)
Luscher, D.J., Mayeur, J.R., Mourad, H.M., Hunter, A., Kenamond, M.A.: Coupling continuum dislocation transport with crystal plasticity for application to shock loading conditions. Int. J. Plast. 76, 111–129 (2016)
Luscher, D.J., Addessio, F.L., Cawkwell, M.J., Ramos, K.J.: A dislocation density-based continuum model of the anisotropic shock response of single crystal α-cyclotrimethylene trinitramine. J. Mech. Phys. Solids. 98, 63–86 (2017)
Luscher, D.J., Buechler, M.A., Walters, D.J., Bolme, C.A., Ramos, K.J.: On computing the evolution of temperature for materials under dynamic loading. Int. J. Plast. 111, 188–210 (2018)
Lawrence, E., Heitmann, K., White, M., Higdon, D., Wagner, C., Habib, S., Williams, B.: The coyote universe. III. Simulation suite and precision emulator for the nonlinear matter power spectrum. Astrophys. J. 713(2), 1322 (2010)
Lawrence, E.: The emulator generating gadget (EGG). [Online]. Available: https://github.com/lanl/egg (2018)
McKay, M.D., Beckman, R.J., Conover, W.J.: Comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics. 21(2), 239–245 (1979)
Constantine, P.G., Dow, E., Wang, Q.: Active subspace methods in theory and practice: applications to kriging surfaces. SIAM J. Sci. Comput. 36(4), A1500–A1524 (2014)
Acknowledgements
We would like to thank James Valdez, Michael Torrez, and Carl Trujillo for their expertise and guidance in running the experiments. We would also like to thank Los Alamos National Laboratory for supporting our group and this project as part of the Los Alamos Dynamics Summer School program.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Society for Experimental Mechanics, Inc.
About this paper
Cite this paper
Myren, S. et al. (2020). Input Estimation and Dimension Reduction for Material Models. In: Barthorpe, R. (eds) Model Validation and Uncertainty Quantification, Volume 3. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-030-12075-7_16
Download citation
DOI: https://doi.org/10.1007/978-3-030-12075-7_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-12074-0
Online ISBN: 978-3-030-12075-7
eBook Packages: EngineeringEngineering (R0)