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Title:Hybrid intelligent optimization for extrusion and forging die shape design
Authors: YIN Ji-long LI Da-yong PENG Ying-hong(School of Mechanical Engineering Shanghai Jiaotong University Shanghai 200030 China) 
Unit:  
KeyWords: extrusion and forging process inductive learning optimization knowledge-based engineering 
ClassificationCode:TG315.2
year,vol(issue):pagenumber:2006,31(1):57-60
Abstract:
Numerical simulation technique has become the important verifying tools in extrusion and forging die shape design.It helps designers to know the design parameters space better.However,the vast computation cost,the implicity of object function and discontinuousness of search space limit the application of traditional gradient-based optimization methods.Some nongradient based optimization techniques,such as generic algorithm and simulated annealing usually need more simulation runs and become infeasible in a large scale simulation.In this paper,a hybrid intelligent optimization method based simulation knowledge is developed aiming at extrusion and forging process.The result of an extrusion-forging die shape optimization shows that this method is valid and feasible.
Funds:
国家自然科学基金(60304015);; 上海市国际合作项目(041107049)
AuthorIntro:
Reference:
[1]Altan,T,Vazquez V.Status of process simulation using 2Dand 3D finite element method’What is practical today?Whatcan we expect in the future?'[J].Journal of Materials Pro-cessing Technology,1997.71(1):49 63.
[2]Schwabacher M.,Ellman T,Hirsh H.Learning to set upnumerical optimizations of engineering designs[J].ArtificialIntelligence for Engineering Design,Analysis and Manufactur-ing:AIEDAM,1998,12(2):173 192.
[3]Robert L.Grossman eds Data mining for scientific and engi-neering applications[M].Kluwer Academic Publishers,2001.
[4]Saraiva P M,Stephanopoulos G.Continuous process improve-ment through inductive and analogical learning[J].AIChEJournal,1992.38(2):161 183.
[5]Wu C,Hsu Y.Optimal shape design of an extrusion-forgingdie using a polynomial network and a genetic algorithm[J].International Journal of Advanced Manufacturing Technology,2002.20(2):128 137.
[6]Yang X.,Teo K L,Caccetta L.Optimization methods andapplications[M].Dordrecht;Boston:Kluwer Academic Pub-lishers,xxxvii,2001,412.
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