KSME International Journal

, Volume 18, Issue 5, pp 814–819 | Cite as

Adaptive parallel decomposition for multidisciplinary design

  • Hyung-Wook Park
  • Se J. Lee
  • Hyun-Seop Lee
  • Dong-Hoon Choi
Article

Abstract

The conceptual design of a rotorcraft system involves many different analysis disciplines. The decomposition of such a system into several subsystems can make analysis and design more efficient in terms of the total computation time. Adaptive parallel decomposition makes the structure of the overall design problem suitable to apply the multidisciplinary design optimization methodologies and it can exploit parallel computing. This study proposes a decomposition method which adaptively determines the number and sequence of analyses in each sub-problem corresponding to the available number of processors in parallel. A rotorcraft design problem is solved and as a result, the adaptive parallel decomposition method shows better performance than other previous methods for the selected design problem.

Key Words

Parallel Decomposition Scheduling Rotorcraft Design Multidisciplinary Design Optimization (MDO) 

Nomenclature

N

The number of sub-problems

Nt

The total number of analyses

pi

Thei-th analysis module

pik

The z’-th analysis ink-th sub-problem

nk

The number of analyses ink-th sub-problem

U, CL

The amount of information transferred between sub-problems in upper and lower triangular regions

bk

The sum of feedback couplings of thek-th sub-problem

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References

  1. Altus, S. S., KrI. M. and Gage, P. J. 1995, “A Genetic Algorithm for Scheduling and Decomposition of Multidisciplinary Design Problems,”Advances in design automation, ASME paper 95–141.Google Scholar
  2. Gen, M. and Cheng, R. 1997,Genetic Algorithms and Engineering Design, pp. 234–248.Google Scholar
  3. Kusiak. A. and Wang, J. 1993, “Decomposition of the Design Process,”ASME Journal of Mechanical Design, Vol. 115, pp. 687–695.CrossRefGoogle Scholar
  4. Michelena, N. F. and Papalambros, P. Y. 1994, “A Network Reliability Approach to Optimal Decomposition of Design Problems,”Advances in Design Automation, ASME, New York Vol. 2, pp. 195–204.Google Scholar
  5. Park. H. W., Kim, M. S., Choi, D. H. and Mavris, D. N., 2002, “Optimizing the Parallel Process Flow for the Individual Discipline Feasible Method,”9th AIAA/ISSMO Symposium and Exhibit on Multidisciplinary Analysis and Optimization, September 4–6.Google Scholar
  6. Park, H. W., Kim, M. S., and Choi, D. H. 2003, “A System Decomposition Technique Using a Multi-Objective Genetic Algorithm.”KSME, Vol. 27. No. 4, pp. 499–506.MathSciNetGoogle Scholar
  7. Park. H. W. 2003, “A Parallel Decomposition Method for Multidisciplinary Design Optimization Based on a Multiobjective Genetic Algorithm.” Ph. D. Thesis, Hanyang University, School of Mechanical Engineering.Google Scholar
  8. Rogers, J. L. and Barthelemy, J. -F. M.. 1992, “Enhancements to the Design Manager's Aid for Intelligent Decomposition (DeMAID),”AIAA paper No. 92–4809.Google Scholar
  9. Rogers. J. L.. and Bloebaum, L. 1994, “Ordering Design Tasks Based on Coupling Strength,”AIAA paper No. 94–4362.Google Scholar
  10. Rogers, J. L., McCulley, M. and Bloebaum, L. 1999, “Optimizing the Process Flow for Complex Design Projects,”Design Optimkation: International Journal for Product & Process Improvement, Vol. 1, No. 3, pp. 281–292.Google Scholar
  11. Vanderplaats, G. N. 1995,DOT Users Manual Version 4.20, Vanderplaats Research & Development, Inc.Google Scholar

Copyright information

© The Korean Society of Mechanical Engineers (KSME) 2004

Authors and Affiliations

  • Hyung-Wook Park
    • 1
  • Se J. Lee
    • 2
  • Hyun-Seop Lee
    • 3
  • Dong-Hoon Choi
    • 4
  1. 1.R & D Division for Hyundai Motor CompanyKynnggi-DoKorea
  2. 2.Department of Mechanical EngineeringThe University of SeoulSeoulKorea
  3. 3.Research Assistant, the Center of Innovative Design Optimtation TechnologyHanyang UniversitySeoulKorea
  4. 4.Center of Innovative Design Optimtation TechnologyHanyang UniversitySeoulKorea

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