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Uncertainty Analysis Based on Sensitivities Generated Using Automatic Differentiation

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Area
Beam Physics

Author(s)
Jacob Barhen , David B. Reister

Published in
Computational Science and Its Applications -- ICCSA 2003, Proceedings of the International Conference on Computational Science and its Applications, Montreal, Canada, May 18--21, 2003. Part II

Editor(s)
V. Kumar, M. L. Gavrilova, C. J. K. Tan, P. L'Ecuyer

Year
2003

Publisher
Springer

Abstract
The objective is to determine confidence limits for the outputs of a mathematical model of a physical system that consists of many interacting computer codes. Each code has many modules that receive inputs, write outputs, and depend on parameters. Several of the outputs of the system of codes can be compared to sensor measurements. The outputs of the system are uncertain because the inputs and parameters of the system are uncertain. The method uses sensitivities to propagate uncertainties from inputs to outputs through the complex chain of modules. Furthermore, the method consistently combines sensor measurements with model outputs to simultaneously obtain best estimates for model parameters and reduce uncertainties in model outputs. The method was applied to a test case where ADIFOR2 was used to calculate sensitivities for the radiation transport code MODTRAN.

Cross-References
Kumar2003CSa

AD Tools
ADIFOR

BibTeX
@INPROCEEDINGS{
         Barhen2003UAB,
       author = "Jacob Barhen and David B. Reister",
       title = "Uncertainty Analysis Based on Sensitivities Generated Using Automatic
         Differentiation",
       booktitle = "Computational Science and Its Applications -- ICCSA~2003, Proceedings of the
         International Conference on Computational Science and its Applications, Montreal, Canada,
         May~18--21, 2003. Part~II",
       editor = "V. Kumar and M. L. Gavrilova and C. J. K. Tan and P. {L'Ecuyer}",
       abstract = "The objective is to determine confidence limits for the outputs of a mathematical
         model of a physical system that consists of many interacting computer codes. Each code has many
         modules that receive inputs, write outputs, and depend on parameters. Several of the outputs of the
         system of codes can be compared to sensor measurements. The outputs of the system are uncertain
         because the inputs and parameters of the system are uncertain. The method uses sensitivities to
         propagate uncertainties from inputs to outputs through the complex chain of modules. Furthermore,
         the method consistently combines sensor measurements with model outputs to simultaneously obtain
         best estimates for model parameters and reduce uncertainties in model outputs. The method was
         applied to a test case where ADIFOR2 was used to calculate sensitivities for the radiation transport
         code MODTRAN.",
       volume = "2668",
       series = "Lecture Notes in Computer Science",
       publisher = "Springer",
       pages = "70--77",
       address = "Berlin",
       reference = "http://www.autodiff.org/?module=Workshops&submenu=iccsa03",
       ad_area = "Beam Physics",
       ad_tools = "ADIFOR",
       year = "2003",
       crossref = "Kumar2003CSa"
}

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