Using Computer Experiments to Construct a Cheap Substitute for an Expensive Simulation Model,

Abstract

There is widespread use of computer models as tools in scientific research. As surrogates for physical or behavioral systems, such models can be subjected to experimentation, the goal being to predict how the corresponding real system would behave under certain conditions. For long-running (expensive) model codes, there may be a severe limitation on the number of experiments that can reasonably be done. This motivates the construction of a fast-running (cheap) approximation to the original code, for use in experiments where a large number of runs may be necessary. Here we discuss our approximation of a simulation model for the compression molding of sheet molding compound, applied to the manufacture of an automobile hood. The approximation was constructed using Bayesian interpolation methods for prediction of the movement of the flow front. The predictions were based on data generated by a sequence of computer experiments, using designs chosen according to a type of D-optimality criterion.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1992
Accession Number
ADP007149

Entities

People

  • Max Morris
  • Toby Mitchell

Organizations

  • Oak Ridge National Laboratory

Tags

DTIC Thesaurus Topics

  • Automobiles
  • Compression
  • Compression Molding
  • Computer Science
  • Computers
  • Computing-Related Activities
  • Construction
  • Data Science
  • Engineering
  • Information Science
  • Interdisciplinary Science
  • Interpolation
  • Mathematical Analysis
  • Moldings
  • Scientific Research
  • Simulations
  • Statistics

Readers

  • Computational Modeling and Simulation
  • Industrial Economics
  • Polymer Science and Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms