Application of a neural network to a design optimization process

1992 ◽  
Vol 7 (8) ◽  
pp. 743-763
Author(s):  
A. Zandi-nia ◽  
H. Koppelaar
Author(s):  
Myung-Jin Choi ◽  
Min-Geun Kim ◽  
Seonho Cho

We developed a shape-design optimization method for the thermo-elastoplasticity problems that are applicable to the welding or thermal deformation of hull structures. The point is to determine the shape-design parameters such that the deformed shape after welding fits very well to a desired design. The geometric parameters of curved surfaces are selected as the design parameters. The shell finite elements, forward finite difference sensitivity, modified method of feasible direction algorithm and a programming language ANSYS Parametric Design Language in the established code ANSYS are employed in the shape optimization. The objective function is the weighted summation of differences between the deformed and the target geometries. The proposed method is effective even though new design variables are added to the design space during the optimization process since the multiple steps of design optimization are used during the whole optimization process. To obtain the better optimal design, the weights are determined for the next design optimization, based on the previous optimal results. Numerical examples demonstrate that the localized severe deviations from the target design are effectively prevented in the optimal design.


2018 ◽  
Vol 10 (1) ◽  
pp. 168781401875472 ◽  
Author(s):  
Wei Sun ◽  
Xiaobang Wang ◽  
Maolin Shi ◽  
Zhuqing Wang ◽  
Xueguan Song

A multidisciplinary design optimization model is developed in this article to optimize the performance of the hard rock tunnel boring machine using the collaborative optimization architecture. Tunnel boring machine is a complex engineering equipment with many subsystems coupled. In the established multidisciplinary design optimization process of this article, four subsystems are taken into account, which belong to different sub-disciplines/subsytems: the cutterhead system, the thrust system, the cutterhead driving system, and the economic model. The technology models of tunnel boring machine’s subsystems are build and the optimization objective of the multidisciplinary design optimization is to minimize the construction period from the system level of the hard rock tunnel boring machine. To further analyze the established multidisciplinary design optimization, the correlation between the design variables and the tunnel boring machine’s performance is also explored. Results indicate that the multidisciplinary design optimization process has significantly improved the performance of the tunnel boring machine. Based on the optimization results, another two excavating processes under different geological conditions are also optimized complementally using the collaborative optimization architecture, and the corresponding optimum performance of the hard rock tunnel boring machine, such as the cost and energy consumption, is compared and analysed. Results demonstrate that the proposed multidisciplinary design optimization method for tunnel boring machine is reliable and flexible while dealing with different geological conditions in practical engineering.


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