Parallel Computational Environment for Substructure Optimization

TITLE AND SUBTITLE:
Parallel Computational Environment for Substructure Optimization

AUTHOR(S):
Atef S. Gendy, Surya N. Patnaik, Dale A. Hopkins, and Laszlo Berke

REPORT DATE:
December 1995

FUNDING NUMBERS:
WU-505-63-5B

PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES):
National Aeronautics and Space Administration
Lewis Research Center
Cleveland, Ohio 44135-3191

PERFORMING ORGANIZATION REPORT NUMBER:
E-9504

SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES):
National Aeronautics and Space Administration
Washington, D.C. 20546-0001

REPORT TYPE AND DATES COVERED:
Technical Memorandum

SPONSORING/MONITORING AGENCY REPORT NUMBER:
NASA TM-4680

SUPPLEMENTARY NOTES:
Atef S. Gendy, National Research Council-NASA Research Associate at Lewis Research Center; Surya N. Patnaik, Ohio Aerospace Institute, 22800 Cedar Point Road, Cleveland, Ohio 44142; Dale A. Hopkins and Laszlo Berke, NASA Lewis Research Center. Responsible person, Dale A. Hopkins, organization code 5210, (216) 433-3260.

ABSTRACT:
Design optimization of large structural systems can be attempted through a substructure strategy when convergence difficulties are encountered. When this strategy is used, the large structure is divided into several smaller substructures and a subproblem is defined for each substructure. The solution of the large optimization problem can be obtained iteratively through repeated solutions of the modest subproblems. Substructure strategies, in sequential as well as in parallel computational modes on a Cray YMP multiprocessor computer, have been incorporated in the optimization test bed CometBoards. CometBoards is an acronym for Comparative Evaluation Test Bed of Optimization and Analysis Routines for Design of Structures. Three issues, intensive computation, convergence of the iterative process, and analytically superior optimum, were addressed in the implementation of substructure optimization into CometBoards. Coupling between subproblems as well as local and global constraint grouping are essential for convergence of the iterative process. The substructure strategy can produce an analytically superior optimum different from what can be obtained by regular optimization. For the problems solved, substructure optimization in a parallel computational mode made effective use of all assigned processors.

SUBJECT TERMS:
Design code CometBoards; Substructure optimization; Sequential and parallel computational modes; Constraint grouping; Coupling between substructures

NUMBER OF PAGES:
24

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