A framework for assessing uncertainties in simulation predictions-Reference-Cited by-同舟云学术

A framework for assessing uncertainties in simulation predictions

Published:1999-09 Issue:1-4 Volume:133 Page:179-188
ISSN:0167-2789
Container-title:Physica D: Nonlinear Phenomena
language:en
Short-container-title:Physica D: Nonlinear Phenomena

Author:

Hanson Kenneth M

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Statistical and Nonlinear Physics

Reference36 articles.

1. Issues in Computational Fluid Dynamics Code Verification and Validation

2. Guide for the Verification and Validation of Computational Fluid Dynamics Simulations, Tech. Rep. G-077-98, Amer. Inst. Aeronautics and Astronautics, 1998.

3. S.G. Rabinovich, Measurements Errors: Theory and Practice, Amer. Inst. Phys., New York, 1995.

4. W.C. Thacker, Automatic differentiation from an oceanographer’s perspective, in: A. Griewank, G.F. Corliss (Eds.), Automatic Differentiation of Algorithms: Theory, Implementation, and Application, SIAM, Philadelphia, 1991, p. 191.

5. R. Giering, Tangent Linear and Adjoint Model Compiler, Technical Report TAMC 4.7, Max-Planck-Institut für Meteorologie, 1997 (e-mail: giering@dkrz.de).

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