Abstract

In preliminary ship design, a parametric study is a more realistic way to explore design space and analyze design problem than an optimization technique due to time-consuming computational work or a difficulty in incorporating all constraints into the optimization formulation. In the parametric study, feasible alternatives are examined in various aspects; the best one can be selected. Among the aspects, the strength assessment by FE analysis is an essential process in the ship design. This paper proposes a system to facilitate a parametric study for FE model based on design of experiment (DOE). It works on a FE pre-processor environment and assists a user to define a parametric study by interacting with FE model. It also provides an interface module with a FE solver in order to control the input file and extract predefined FE results from the output file. Based on the proposed system, a better understating and a better design are expected to be achieved.

주제어

#parametric study   #FE analysis   #design of experiment  

참고문헌 (16)

1. Park, S.H. and B.S. Lee. 1995. Developing a Maneuvering Design Capability for Naval Vessels. Proc. PRADS'95, Seoul, pp. 1.616-1.628 
2. Phadke, M.S. 1989. Quality Engineering Using Robust Design, Prentice Hall, New Jersey 
3. Rajeev, S., and C.S. Krishnamoorthy. 1992. Discrete Optimization of Structures Using Genetic Algorithms, Journal of Structural Engineering, ASCE, 118, 1233-1250 
4. Wu, S.J. and P.T. Chow. 1995. Genetic Algorithms for Nonlinear Mixed Discrete-Integer Optimization problems via Meta-Generic Parameter Optimization, Engineering Optimization, 24, 137-159 
5. Yu, Y.G. 2003. Development of a CAD based General Purpose Optimal Design and Its Application to Structural Shape for Fatigue Life, Master's thesis of KAIST 
6. Engineous Software, Inc. 1999. iSIGHT Designer's Guide : version 5.0, North Carolina, 1999 
7. Vanderplaats Research & Development, Inc. 1998. VisualDOC Manual : version 1.0, Colorado Springs, CO 
8. Huh, J.S. 2000. Development of a Mechanical Design Tool for MEMS Integrating Commercial Code, Master's thesis of KAIST 
9. Haftka, R.T., R.V. Grandhi. 1986. Structural shape optimization-a survey, Computer Methods in Applied Mechanics and Engineering. 57, 91-106 
10. Kwak, B.M. 1994. A review on shape optimal design and sensitivity analysis, JSCE Journal Structure Engineering/Earthquake Engineering, 10, 4, 159-174 
11. Park, G.J. and Arora, K.S. 1987 Role of Database Management in Design Optimization System, Journal of Aircraft, 24, 11, 745-750 
12. Ku, J.K., S.S. Rao and L. Chen. 1998. Taguchi-aided Search Method for Design Optimization of Engineering Systems, Engineering Optimization, 30, 1-23 
13. Salajegheh, E. and G.N. Vanderplassts. 1993. Optimum Design of Structures with Discrete Size and Shape Variables, Structural Optimization, 6, 2, 79-85 
14. Peace, G.S. 1995. Taguchi Methods: A hands-On Approach to Quality Engineering Addison Wesley, Massachusetts 
15. Shin, J.H., B.M. Kwak. 2001. Optimization of Machine Tools Structure using a CADbased Optimal Design System, Proceedings of the KSME 2001 Spring Annual Meeting, 926-931 
16. Goldberg, D.E. 1989. Genetic Algorithms in Search, Optimization and Machine Learning, Addison Wesley, Massachusetts 

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