Relation of validation experiments to applications.

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Computational and mathematical models are developed in engineering to represent the behavior of physical systems to various system inputs and conditions. These models are often used to predict at other conditions, rather than to just reproduce the behavior of data obtained at the experimental conditions. For example, the boundary or initial conditions, time of prediction, geometry, material properties, and other model parameters can be different at test conditions than those for an anticipated application of a model. Situations for which the conditions may differ include those for which (1) one is in the design phase and a prototype of the ... continued below

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60 p.

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Hamilton, James R. (New Mexico State University, Las Cruces, NM) & Hills, Richard Guy February 1, 2009.

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Description

Computational and mathematical models are developed in engineering to represent the behavior of physical systems to various system inputs and conditions. These models are often used to predict at other conditions, rather than to just reproduce the behavior of data obtained at the experimental conditions. For example, the boundary or initial conditions, time of prediction, geometry, material properties, and other model parameters can be different at test conditions than those for an anticipated application of a model. Situations for which the conditions may differ include those for which (1) one is in the design phase and a prototype of the system has not been constructed and tested under the anticipated conditions, (2) only one version of a final system can be built and destructive testing is not feasible, or (3) the anticipated design conditions are variable and one cannot easily reproduce the range of conditions with a limited number of carefully controlled experiments. Because data from these supporting experiments have value in model validation, even if the model was tested at different conditions than an anticipated application, methodology is required to evaluate the ability of the validation experiments to resolve the critical behavior for the anticipated application. The methodology presented uses models for the validation experiments and a model for the application to address how well the validation experiments resolve the application. More specifically, the methodology investigates the tradeoff that exists between the uncertainty (variability) in the behavior of the resolved critical variables for the anticipated application and the ability of the validation experiments to resolve this behavior. The important features of this approach are demonstrated through simple linear and non-linear heat conduction examples.

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60 p.

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  • Report No.: SAND2009-1091
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/949007 | External Link
  • Office of Scientific & Technical Information Report Number: 949007
  • Archival Resource Key: ark:/67531/metadc935046

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • February 1, 2009

Added to The UNT Digital Library

  • Nov. 13, 2016, 7:26 p.m.

Description Last Updated

  • Dec. 9, 2016, 6:56 p.m.

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Hamilton, James R. (New Mexico State University, Las Cruces, NM) & Hills, Richard Guy. Relation of validation experiments to applications., report, February 1, 2009; United States. (digital.library.unt.edu/ark:/67531/metadc935046/: accessed June 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.