Improved image interpreting and modeling technique for automated structural optimization system
The automated structural optimization system (ASOS) proposed in the previous work incorporates the image-preprocessing techniques, the image-interpreting technique, and the automated shape-optimization modeling techniques to successfully obtain an autonomously integrated topology and shape optimization. However, the characteristic value-based image-interpreting technique used in ASOS is unable to accurately interpret complicated hole shapes, necessitating the use of the hole shape-adjusting strategy in addition to the hole-expanding strategy and the interference analysis in the automated shape-optimization modeling techniques to obtain a viable initial design and side constraints of design variables. In order to solve the above-mentioned problem in ASOS, this paper proposes the improved automated structural optimization system (IASOS) and uses the polygonal image-interpreting technique to replace the characteristic value-based image-interpreting technique used in ASOS. This alteration significantly increases the accuracy of image interpretation. Moreover, it can simplify the process of automated shape-optimization modeling techniques, reduce the design duration, and produce better results.
automated structural optimization shape optimization polygonal image-interpreting technique topology optimization integrated structural configuration design automated design system