The Parametric Mesh Method Based on History and Process Parameters Optimization


Article Preview

In engineering technology, it is necessary to compare different designs in an optimization project. Therefore a big problem is how to obtain finite element analysis (FEA) data involving different parameters and how to acquire optimization parameters from the results of FEA to solve the optimization problem rapidly. The parametric mesh (Paramesh) method, automatically based on history of complicated special surfaces, is developed to obtain many results of FEA involving different parameters. This paper is presented to demonstrate the method of parametric finite element analysis (PFEA). The optimization method of process parameters optimization is based on combining PFEA/ ANN (artificial nerve net)/GA (genetic arithmetic) to find out optimization parameters. This allows one to rapidly obtain optimization parameters during a design by doing FEA only once. The research indicates that the parameters optimization method based on PFEA/ANN/GA in the product design can short the product development cycle, decrease material consumption and guarantee product quality, etc.



Advanced Materials Research (Volumes 148-149)

Edited by:

Xianghua Liu, Zhengyi Jiang and Jingtao Han




J. H. Huang et al., "The Parametric Mesh Method Based on History and Process Parameters Optimization", Advanced Materials Research, Vols. 148-149, pp. 1217-1221, 2011

Online since:

October 2010




[1] Johann-Peter Sommer. Olaf Wittler, Dionysios Manessis, Bernd Michel. Thermo-mechanical analysis of advanced electronic packages in early system design Microsyst Technol (2005)12: 75–81.


[2] Kengo Anamia, Richard Sauseb, Hassan H. Abbasb. Influence of web corrugation geometry and flange geometry on web-flange weld toe stresses. International Journal of Fatigue 27 (2005) 373–381.


[3] Kuo, Jan-Tai; Wang, Ying-Yi; Lung, Wu-Seng A hybrid neural–genetic algorithm for reservoir water quality management.  Water Research, Apr2006, Vol. 40 Issue 7, pp.1367-1376.


[4] Liu, Ping; Su, Juan hua; Dong, Qi ming; Li, He jun. Optimization of aging treatment in lead frame copper alloy by intelligent technique. Materials Letters, Nov2005, Vol. 59 Issue 26, pp.3337-3342.


[5] Broad, D. R.; Dandy, G. C.; Maier, H. R. Water Distribution System Optimization Using Metamodels. Journal of Water Resources Planning & Management, Jun2005, Vol. 131 Issue 3, pp.172-180.


[6] Aijun, Li; Hejun, Li; Kezhi, Li; Zhengbing, Gu. Applications of neural networks and genetic algorithms to CVI processes in carbon/carbon composites.  Acta Materialia, Jan2004, Vol. 52 Issue 2, pp.299-204.


[7] Jinjun Rao,Key technology research of technology parameters Optimization on metal sheet forming. Dissertation for MS. D, Nanchang University. 2002. 5.