Advanced Methods for Atmospheric Modeling

Abstract

The evolution of physical processes in a numerical simulation of the atmosphere and the effects of their interactions on a forecast are very complex and difficult to isolate. An analysis was developed which uses artificial intelligence techniques to study the time-evolving quantities in a numerical simulation in order to determine the relationships among various flow parameters. This procedure was divided into two parts. First, the data was manipulated into a form that allowed the relationships of interest to be isolated. In particular, it was necessary to be able to see how several quantities may interact to affect the solution. The next step used an expert system to analyze the data based on the relationships. The test problem chosen was the numerical simulation of the decay of turbulence in a stratified fluid. Three different analyses were used to determine sensitivities, comparisons, and correlations among the flow quantities. The automation of this technique allowed the processing of the large amounts of data that were generated by a numerical simulation. For the test case, this method was able to draw similar conclusions about the nature of the flow solution compared with those given in the literature.

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Document Details

Document Type
Technical Report
Publication Date
Jan 31, 1991
Accession Number
ADA232966

Entities

People

  • Laura C. Rodman

Organizations

  • Nielsen Engineering & Research (United States)

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Atmospheric Sciences
  • Computational Fluid Dynamics
  • Computers
  • Differential Equations
  • Energy Transfer
  • Expert Systems
  • Fluid Dynamics
  • Fluid Flow
  • Fluid Mechanics
  • Froude Number
  • Mechanics
  • Simulations
  • Stratified Fluids
  • Three Dimensional
  • Turbulence

Readers

  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference