The Use of Neural Networks as a Method of Correlating Thermal Fluid Data to Provide Useful Information on Thermal Systems

Abstract

A study on the use of neural networks as a method of correlating thermal fluid data to provide useful information on thermal systems was conducted using a neural network code package. Two separate thermal fluid systems were analyzed: tube bank data with variable geometries and tube bank boiling data with variable parameters. Both studies show the effectiveness of neural networks as a viable alternative to the current practice of correlating data. This is achieved by displaying a reduction in error, requiring fewer assumptions, and providing an easier method of devising predictions and correlations.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2000
Accession Number
ADA380226

Entities

People

  • Thomas J. Cronley

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • California
  • Computational Science
  • Computer Programs
  • Computers
  • Data Sets
  • Engineering
  • Fluid Mechanics
  • Heat Exchangers
  • Heat Flux
  • Heat Transfer
  • Mechanical Engineering
  • Neural Networks
  • Reynolds Number
  • Simulations
  • Transfer Functions

Readers

  • Computer Vision.
  • Petroleum Engineering
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks