Computational Issues in Damping Identification for Large Scale Problems.
INSTITUTE FOR COMPUTER APPLICATIONS IN SCIENCE AND ENGINEERING HAMPTON VA
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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 methods memory requirement grows at a very rapid rate meaning that larger problems can quickly exceed available computer memory. The iterative methods 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.
- Numerical Mathematics
- Fluid Mechanics