Automating embedded analysis capabilities and managing software complexity in multiphysics simulation part II: application to partial differential equations

A template-based generic programming approach was presented in a previous paper that separates the development effort of programming a physical model from that of computing additional quantities, such as derivatives, needed for embedded analysis algorithms. In this paper, we describe the implementat...

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Bibliographic Details
Published in:arXiv.org 2012-05
Main Authors: Pawlowski, Roger P, Phipps, Eric T, Salinger, Andrew G, Owen, Steven J, Siefert, Christopher M, Staten, Matthew L
Format: Article
Language:English
Subjects:
Algorithms
Computer simulation
Partial differential equations
Programming
Shape optimization
Software
Online Access:Get full text
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Summary:A template-based generic programming approach was presented in a previous paper that separates the development effort of programming a physical model from that of computing additional quantities, such as derivatives, needed for embedded analysis algorithms. In this paper, we describe the implementation details for using the template-based generic programming approach for simulation and analysis of partial differential equations (PDEs). We detail several of the hurdles that we have encountered, and some of the software infrastructure developed to overcome them. We end with a demonstration where we present shape optimization and uncertainty quantification results for a 3D PDE application.
ISSN:2331-8422