Data Driven Computing
Data Driven Computing is a new field of computational analysis which uses provided data to directly produce predictive outcomes. This thesis first establishes definitions of Data-Driven solvers and working examples of static mechanics problems to demonstrate efficacy. Significant extensions are th...
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Online Access: | https://thesis.library.caltech.edu/10431/8/Kirchdoerfer_Trenton_2017_Thesis.pdf Kirchdoerfer, Trenton Thomas (2018) Data Driven Computing. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9Z899MV. https://resolver.caltech.edu/CaltechTHESIS:09122017-092017294 <https://resolver.caltech.edu/CaltechTHESIS:09122017-092017294> |
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ndltd-CALTECH-oai-thesis.library.caltech.edu-104312021-10-29T05:01:32Z https://thesis.library.caltech.edu/10431/ Data Driven Computing Kirchdoerfer, Trenton Thomas Data Driven Computing is a new field of computational analysis which uses provided data to directly produce predictive outcomes. This thesis first establishes definitions of Data-Driven solvers and working examples of static mechanics problems to demonstrate efficacy. Significant extensions are then explored to both accommodate noisy data sets and apply the deveoloped methods to dynamic problems within mechanics. Possible method improvements discuss incorporation of data quality metrics and adaptive data sampling, while new applications focus on multi-scale analysis and the need for public databases to support constitutive data collaboration. 2018 Thesis NonPeerReviewed application/pdf en other https://thesis.library.caltech.edu/10431/8/Kirchdoerfer_Trenton_2017_Thesis.pdf Kirchdoerfer, Trenton Thomas (2018) Data Driven Computing. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9Z899MV. https://resolver.caltech.edu/CaltechTHESIS:09122017-092017294 <https://resolver.caltech.edu/CaltechTHESIS:09122017-092017294> https://resolver.caltech.edu/CaltechTHESIS:09122017-092017294 CaltechTHESIS:09122017-092017294 10.7907/Z9Z899MV |
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en |
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Others
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description |
Data Driven Computing is a new field of computational analysis which uses provided data to directly produce predictive outcomes. This thesis first establishes definitions of Data-Driven solvers and working examples of static mechanics problems to demonstrate efficacy. Significant extensions are then explored to both accommodate noisy data sets and apply the deveoloped methods to dynamic problems within mechanics. Possible method improvements discuss incorporation of data quality metrics and adaptive data sampling, while new applications focus on multi-scale analysis and the need for public databases to support constitutive data collaboration.
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author |
Kirchdoerfer, Trenton Thomas |
spellingShingle |
Kirchdoerfer, Trenton Thomas Data Driven Computing |
author_facet |
Kirchdoerfer, Trenton Thomas |
author_sort |
Kirchdoerfer, Trenton Thomas |
title |
Data Driven Computing |
title_short |
Data Driven Computing |
title_full |
Data Driven Computing |
title_fullStr |
Data Driven Computing |
title_full_unstemmed |
Data Driven Computing |
title_sort |
data driven computing |
publishDate |
2018 |
url |
https://thesis.library.caltech.edu/10431/8/Kirchdoerfer_Trenton_2017_Thesis.pdf Kirchdoerfer, Trenton Thomas (2018) Data Driven Computing. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9Z899MV. https://resolver.caltech.edu/CaltechTHESIS:09122017-092017294 <https://resolver.caltech.edu/CaltechTHESIS:09122017-092017294> |
work_keys_str_mv |
AT kirchdoerfertrentonthomas datadrivencomputing |
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1719491548111962112 |