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Award Abstract #0205181
ITR/AP: A COMPUTATIONAL INFRASTRUCTURE FOR RELIABLE COMPUTER SIMULATIONS
| NSF Org: |
CNS
Division of Computer and Network Systems
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| Initial Amendment Date: |
August 15, 2002 |
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| Latest Amendment Date: |
August 15, 2002 |
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| Award Number: |
0205181 |
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| Award Instrument: |
Standard Grant |
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| Program Manager: |
Frederica Darema
CNS Division of Computer and Network Systems
CSE Directorate for Computer & Information Science & Engineering
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| Start Date: |
September 15, 2002 |
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| Expires: |
August 31, 2005 (Estimated) |
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| Awarded Amount to Date: |
$550003 |
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| Investigator(s): |
J. Tinsley Oden oden@ices.utexas.edu (Principal Investigator)
James Browne (Co-Principal Investigator)
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| Sponsor: |
University of Texas at Austin
P.O Box 7726
Austin, TX 78713 512/471-6424
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| NSF Program(s): |
ITR MEDIUM (GROUP) GRANTS
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| Field Application(s): |
0000099 Other Applications NEC
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| Program Reference Code(s): |
HPCC, 9218, 1687, 1652
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| Program Element Code(s): |
1687
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ABSTRACT
EIA-0205181 J. Tinsley Oden University of Texas, Austin ITR/AP: A COMPILATION INFRASTRUCTURE FOR RELIABLE COMPUTER SIMULATIONS
The research of this project will develop mathematical and computational processes for validation analogous to those used for verification and evaluate these processes by actual and computational experiments. At the core of the proposed integrated framework for verification and validation lies the concept of hierarchical modeling. Hierarchical modeling is a systematic coarsening of mathematical models from a base model which is known a priori to contain all of the information, which can be extracted from a given experiment to within quantifiable bounds. The goal is to determine, by introducing approximations into the base model, the computationally simplest model which contains the information content of the experiment. This process requires an ability to evaluate the error introduced by each approximation to the base model, a capability for capturing the semantic content of both models and experiments, a capability for comparing the information content of the experiments and simulations and a capability for implementing a family of computational systems implementing the sequence of models so that the conceptual process can be realized and evaluated.
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