Estimating Parametric, Model Form, and Solution Contributions Using Integral Validation Uncertainty Quantification

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One of the final steps in building a numerical model of a physical, mechanical, thermal, or chemical process, is to assess its accuracy as well as its sensitivity to input parameters and modeling technique. In this work, we demonstrate one simple process to take a top-down or integral view of the model, one which can implicitly reflect any couplings between parameters, to assess the importance of each aspect of modeling technique. We illustrate with an example of a comparison of a finite element model with data for violent reaction of explosives in accident scenarios. We show the relative importance of ... continued below

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12 p. (0.3 MB)

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Logan, R W; Nitta, C K & Chidester, S K February 28, 2006.

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Description

One of the final steps in building a numerical model of a physical, mechanical, thermal, or chemical process, is to assess its accuracy as well as its sensitivity to input parameters and modeling technique. In this work, we demonstrate one simple process to take a top-down or integral view of the model, one which can implicitly reflect any couplings between parameters, to assess the importance of each aspect of modeling technique. We illustrate with an example of a comparison of a finite element model with data for violent reaction of explosives in accident scenarios. We show the relative importance of each of the main parametric inputs, and the contributions of model form and grid convergence. These can be directly related to the importance factors for the system being analyzed as a whole, and help determine which factors need more attention in future analyses and tests.

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12 p. (0.3 MB)

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PDF-file: 12 pages; size: 0.3 Mbytes

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  • Report No.: UCRL-TR-219879
  • Grant Number: W-7405-ENG-48
  • DOI: 10.2172/894762 | External Link
  • Office of Scientific & Technical Information Report Number: 894762
  • Archival Resource Key: ark:/67531/metadc891341

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Office of Scientific & Technical Information Technical Reports

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  • February 28, 2006

Added to The UNT Digital Library

  • Sept. 22, 2016, 2:13 a.m.

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  • April 13, 2017, 4:22 p.m.

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Logan, R W; Nitta, C K & Chidester, S K. Estimating Parametric, Model Form, and Solution Contributions Using Integral Validation Uncertainty Quantification, report, February 28, 2006; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc891341/: accessed August 20, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.