Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part II: Application to Partial Differential Equations

Pawlowski, Roger P.; Phipps, Eric T.; Salinger, Andrew G.; Owen, Steven J.; Siefert, Christopher M.; Staten, Matthew L.

doi:10.1155/2012/818262

Title: Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part II: Application to Partial Differential Equations

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Abstract

A template-based generic programming approach was presented in Part I of this series of papers [Sci. Program. 20 (2012), 197–219] 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.

Authors:

Pawlowski, Roger P. ^[1]; Phipps, Eric T. ^[1]; Salinger, Andrew G. ^[1]; Owen, Steven J. ^[1]; Siefert, Christopher M. ^[1]; Staten, Matthew L. ^[1]

Department of Numerical Analysis and Applications, Sandia National Laboratories, Albuquerque, NM, USA

Publication Date:: Sun Jan 01 00:00:00 EST 2012

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:: 1197980

Resource Type:: Published Article

Journal Name:: Scientific Programming

Additional Journal Information:: Journal Name: Scientific Programming Journal Volume: 20 Journal Issue: 3; Journal ID: ISSN 1058-9244

Publisher:: Hindawi Publishing Corporation

Country of Publication:: Egypt

Language:: English

Citation Formats


                    Pawlowski, Roger P., Phipps, Eric T., Salinger, Andrew G., Owen, Steven J., Siefert, Christopher M., and Staten, Matthew L. Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part II: Application to Partial Differential Equations.  Egypt: N. p., 2012. 
Web.  doi:10.1155/2012/818262.

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                    Pawlowski, Roger P., Phipps, Eric T., Salinger, Andrew G., Owen, Steven J., Siefert, Christopher M., & Staten, Matthew L. Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part II: Application to Partial Differential Equations.  Egypt.  https://doi.org/10.1155/2012/818262

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                    Pawlowski, Roger P., Phipps, Eric T., Salinger, Andrew G., Owen, Steven J., Siefert, Christopher M., and Staten, Matthew L. Sun .  
"Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part II: Application to Partial Differential Equations".  Egypt.  https://doi.org/10.1155/2012/818262.

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@article{osti_1197980,

  title        = {Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part II: Application to Partial Differential Equations},

  author       = {Pawlowski, Roger P. and Phipps, Eric T. and Salinger, Andrew G. and Owen, Steven J. and Siefert, Christopher M. and Staten, Matthew L.},

  abstractNote = {A template-based generic programming approach was presented in Part I of this series of papers [Sci. Program. 20 (2012), 197–219] 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.},

  doi          = {10.1155/2012/818262},

  journal      = {Scientific Programming},

  number       = 3,

  volume       = 20,

  place        = {Egypt},

  year         = {Sun Jan 01 00:00:00 EST 2012},

  month        = {Sun Jan 01 00:00:00 EST 2012}

}

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