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Generating efficient executable models for complex virtual experimentation with the Tornado kernel.

Filip H A Claeys1, Peter Fritzson, Peter A Vanrolleghem

  • 1BIOMATH, Ghent University, Coupure Links 653, B-9000 Gent, Belgium. filip.claeys@biomath.ugent.be

Water Science and Technology : a Journal of the International Association on Water Pollution Research
|September 28, 2007
PubMed
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This study introduces automated generation of efficient executable models for complex virtual experimentation, particularly in water quality management. Promising results were achieved using techniques like equiv substitution and equation lifting within the Tornado kernel.

Area of Science:

  • Computational science
  • Environmental modeling
  • Software engineering

Background:

  • Virtual experimentation, encompassing simulation, optimization, and scenario analysis, is crucial for complex model evaluation.
  • High computational demands necessitate efficient model implementations for virtual experimentation.
  • Water quality management frequently employs complex virtual experimentation, yet automated generation of efficient models remains underdeveloped.

Purpose of the Study:

  • To address the need for automated generation of efficient executable models for complex virtual experimentation.
  • To explore and report on promising results in executable model generation.
  • To advance the field of efficient model implementation in scientific domains like water quality management.

Main Methods:

Related Experiment Videos

  • Development and application of techniques within the Tornado kernel.
  • Utilizing equation lifting for model optimization.
  • Employing equiv substitution to enhance model efficiency.

Main Results:

  • Demonstrated promising results in the automated generation of executable models.
  • Showcased the effectiveness of equiv substitution and equation lifting in creating efficient implementations.
  • Provided a foundation for more efficient virtual experimentation in complex domains.

Conclusions:

  • Automated generation of efficient executable models is feasible and beneficial for complex virtual experimentation.
  • Techniques like equiv substitution and equation lifting show significant potential for improving model efficiency.
  • Further research in this area can enhance the application of virtual experimentation in water quality management and other scientific fields.