Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Templeton, Jeremy A."'
In this work we employ data-driven homogenization approaches to predict the particular mechanical evolution of polycrystalline aggregates with tens of individual crystals. In these oligocrystals the differences in stress response due to microstructur
Externí odkaz:
http://arxiv.org/abs/1901.10669
We use machine learning (ML) to infer stress and plastic flow rules using data from repre- sentative polycrystalline simulations. In particular, we use so-called deep (multilayer) neural networks (NN) to represent the two response functions. The ML p
Externí odkaz:
http://arxiv.org/abs/1809.00267
Autor:
Rizzi, Francesco, Khalil, Mohammad, Jones, Reese E., Templeton, Jeremy A., Ostien, Jakob T., Boyce, Brad L.
The advent of fabrication techniques such as additive manufacturing has focused attention on the considerable variability of material response due to defects and other microstructural aspects. This variability motivates the development of an enhanced
Externí odkaz:
http://arxiv.org/abs/1809.01009
Exascale computing promises quantities of data too large to efficiently store and transfer across networks in order to be able to analyze and visualize the results. We investigate Compressive Sensing (CS) as a way to reduce the size of the data as it
Externí odkaz:
http://arxiv.org/abs/1508.06314
We present a method for computing reduced-order models of parameterized partial differential equation solutions. The key analytical tool is the singular value expansion of the parameterized solution, which we approximate with a singular value decompo
Externí odkaz:
http://arxiv.org/abs/1306.4690
Publikováno v:
In Journal of Computational Physics 1 August 2016 318:22-35
Publikováno v:
In Journal of Computational Physics 2010 229(6):2364-2389
Autor:
Debusschere, Bert, Sadler, Lorraine, Antoun, Bonnie, Templeton, Jeremy, Kolda, Tammy, Elebeoba May
Whitepaper submitted to the 2017 DOE ASCR Applied Math Meeting Bert Debusschere, Lorraine Sadler, Bonnie Antoun, Jeremy Templeton, Tammy Kolda Sandia National Laboratories, Livermore, CA Elebeoba May University of Houston, Houston, TX This paper addr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26f0774bb8d0ec5026a5b4e82df281df
Whitepaper submitted to the 2017 DOE ASCR Applied Math MeetingAll authors are affiliated with Sandia National LaboratoriesFrom the list at https://www.orau.gov/ascr-appliedmath-pi2017/whitepaper-questions.htm, this white paper addresses the questions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1151c311113b530d759d60f487a646b2
Publikováno v:
Journal of Chemical Physics; Aug2013, Vol. 139 Issue 5, p054115, 10p, 2 Charts, 9 Graphs