Computational Issues in Damping Identification for Large Scale Problems.

Abstract

Two damping identification methods are tested for efficiency in large-scale applications. One is an iterative routine and the other a least squares method. Numerical simulations have been performed on multiple degree-of-freedom models to test the effectiveness of the algorithm and the usefulness of parallel computation for the problems. High Performance Fortran is used to parallelize the algorithm. Tests were performed using the IBM-SP2 at NASA Ames Research Center. The least squares method tested incurs high communication costs which reduces the benefit of high performance computing. This method's memory requirement grows at a very rapid rate meaning that larger problems can quickly exceed available computer memory. The iterative method's memory requirement grows at a much slower pace and is able to handle problems with 500+ degrees of freedom on a single processor. This method benefits from parallelization, and significant speedup can be seen for problems of 100+ degrees-of-freedom.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1997
Accession Number
ADA329241

Entities

People

  • Daniel J Inman
  • Deborah F. Pilkey
  • Kevin P. Roe

Tags

Communities of Interest

  • Biomedical
  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Computer Programming
  • Computers
  • Eigenvalues
  • Eigenvectors
  • Engineering
  • Frequency
  • Frequency Response
  • High Performance Computing
  • Identification
  • Inverse Problems
  • Least Squares Method
  • Parallel Computing
  • Parallel Processors
  • Simulations
  • Transfer Functions

Readers

  • Computational Fluid Dynamics (CFD)
  • Structural Dynamics.
  • Systems Analysis and Design