Publication: Exploiting Jacobian Sparsity in a Large-scale Distillation Column
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Exploiting Jacobian Sparsity in a Large-scale Distillation Column

- Part of a collection -
 

Area
Process Engineering

Author(s)
M. Petera , A. Rasch , H. M. Bücker

Published in
Proceedings of the Fifth EUROMECH Nonlinear Dynamics Conference, ENOC 2005, Eindhoven, NL, August 7--12, 2005

Editor(s)
D. H. van Campen, M. D. Lazurko, W. P. J. M. van den Oever

Year
2005

Publisher
Eindhoven University of Technology

Abstract
The evaluation of a sparse Jacobian matrix arising from an industrial distillation column is described using automatic differentiation. In contrast to divided differencing, the derivatives are computed without truncation error. Rather than generating the full sparse Jacobian matrix, all its nonzero entries are computed in a compressed fashion, leading to a significant reduction in the computation time.

AD Tools
ADiCape

AD Theory and Techniques
Sparsity

BibTeX
@INPROCEEDINGS{
         Petera2005EJS,
       author = "M. Petera and A. Rasch and H. M. B{\"u}cker",
       title = "Exploiting {J}acobian Sparsity in a Large-scale Distillation Column",
       booktitle = "Proceedings of the Fifth {EUROMECH} Nonlinear Dynamics Conference, ENOC~2005,
         Eindhoven, NL, August~7--12, 2005",
       editor = "D. H. van Campen and M. D. Lazurko and W. P. J. M. van den Oever",
       publisher = "Eindhoven University of Technology",
       pages = "825--827",
       address = "Eindhoven, NL",
       abstract = "The evaluation of a sparse Jacobian matrix arising from an industrial distillation
         column is described using automatic differentiation. In contrast to divided differencing, the
         derivatives are computed without truncation error. Rather than generating the full sparse Jacobian
         matrix, all its nonzero entries are computed in a compressed fashion, leading to a significant
         reduction in the computation time.",
       year = "2005",
       ad_area = "Process Engineering",
       ad_tools = "ADiCape",
       ad_theotech = "Sparsity"
}


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