Lumped Model Generation and Evaluation: Sensitivity and Lie Algebraic Techniques with Applications to Combustion

Abstract

This program dealt with the development and application of new approaches for producing and evaluating lumped parameter models of physical processes. Local and global sensitivity analysis procedures were studied for achieving this goal. Specifically, Lie group formalism was developed to address global parameter space mapping issues of temporal kinetics problems and extended to more complex reactive-diffusive problems. Furthermore, Lie group theoretical techniques were also used to gain analytic insight into the solution of nonlinear kinetic systems. Using local gradient methods, the lumpability (or model reduction) of hydrogen/oxygen and carbon monoxide/hydrogen/oxygen kinetic mechanisms were studied in various physical environments. It was found that the presence of strong scaling and self similarity in the sensitivities allowed for kinetic model simplification. Such scaling and similarity was found associated with strong thermal coupling in the systems. Lastly, a general analysis method for the exact lumping of chemical kinetic mechanisms was developed and illustrated by simple.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1987
Accession Number
ADA190402

Entities

People

  • F. L. Dryer
  • H. Rabitz
  • R. Yetter

Organizations

  • Princeton University

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Applied Mathematics
  • Chemical Compounds
  • Chemical Engineering
  • Chemical Kinetics
  • Chemical Reaction Properties
  • Chemical Reactions
  • Chemistry
  • Combustion
  • Computational Fluid Dynamics
  • Computational Science
  • Differential Equations
  • Engineering
  • Kinetics
  • Mechanical Engineering
  • Military Research
  • Molecular Physics
  • Partial Differential Equations

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Combustion science or combustion engineering.
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • Space