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Use of Receding Horizon Optimal Control to Solve MaxEP-Based Biogeochemistry Problems

  • Joseph J. Vallino
  • Christopher K. Algar
  • Nuria Fernández González
  • Julie A. Huber
Chapter
Part of the Understanding Complex Systems book series (UCS)

Abstract

The maximum entropy production (MaxEP) principle has been applied to steady state systems, but biogeochemical problems of interest are typically transient in nature. To apply MaxEP to biogeochemical reaction networks, we propose that living systems maximum entropy production over appropriate time horizons based on strategic information stored in their genomes, which differentiates them from inanimate chemistry, such as fire, that maximizes entropy production instantaneously. We develop a receding horizon optimal control procedure that maximizes internal entropy production over different intervals of time. This procedure involves optimizing the stoichiometry of a reaction network to determine how biological structure is partitioned to reactions over an interval of time. The modeling work is compared to a methanotrophic microcosm experiment that is being conducted to examine how microbial systems integrate entropy production over time when subject to time varying energy input attained by periodically cycling feed-gas composition. The MaxEP-based model agrees well with experimental results, and model analysis shows that increasing the optimization time horizon increases internal entropy production.

Accepted (July 2012) in: Beyond the Second Law: Entropy Production and Non-Equilibrium Systems. R. C. Dewar, C. H. Lineweaver, R. K. Niven and K. Regenauer-Lieb, Springer.

Keywords

Metabolic Network Entropy Production Biological Structure Characteristic Time Scale Half Reaction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This research was supported by NSF grant EF-0928742 (Huber, Fernández González, and Vallino), NSF grant OCE-1058747 (Algar, Vallino) and NSF grants CBET-0756562, OCE-1058747 (Vallino). We thank Stefanie Strebel for sample analyses and assistance in operation of the microcosms.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Joseph J. Vallino
    • 1
  • Christopher K. Algar
    • 1
  • Nuria Fernández González
    • 1
  • Julie A. Huber
    • 1
  1. 1.Marine Biological LaboratoryWoods HoleUSA

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