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A practical extension of the recursive multi‐fidelity model for the emulation of hole closure experiments
Author(s) -
Muyskens Amanda,
Schmidt Kathleen,
Nelms Matthew,
Barton Nathan,
Florando Jeffrey,
Kupresanin Ana,
Rivera David
Publication year - 2021
Publication title -
statistical analysis and data mining: the asa data science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.381
H-Index - 33
eISSN - 1932-1872
pISSN - 1932-1864
DOI - 10.1002/sam.11513
Subject(s) - emulation , computer science , fidelity , algorithm , grid , extension (predicate logic) , closure (psychology) , computer engineering , simulation , event (particle physics) , computational science , mathematics , geometry , market economy , telecommunications , economics , economic growth , physics , quantum mechanics , programming language
In regimes of high strain rate, the strength of materials often cannot be measured directly in experiments. Instead, the strength is inferred based on an experimental observable, such as a change in shape, that is matched by simulations supported by a known strength model. In hole closure experiments, the rate and degree to which a central hole in a plate of material closes during a dynamic loading event are used to infer material strength parameters. Due to the complexity of the experiment, many computationally expensive, three‐dimensional simulations are necessary to train an emulator for calibration or other analyses. These simulations can be run at multiple grid resolutions, where dense grids are slower but more accurate. In an effort to reduce the computational cost, a combination of simulations with different resolutions can be combined to develop an accurate emulator within a limited training time. We explore the novel design and construction of an appropriate functional recursive multi‐fidelity emulator of a strength model for tantalum in hole closure experiments that can be applied to arbitrarily large training data. Hence, by formulating a multi‐fidelity model to employ low‐fidelity simulations, we were able to reduce the error of our emulator by approximately 81% with only an approximately 1.6% increase in computing resource utilization.