Sandwich panel design and performance optimization based on triply periodic minimal surfaces. (October 2019)

• Record Type: Journal Article
• Authors: Feng, Jiawei; Fu, Jianzhong; Shang, Ce; Lin, Zhiwei; Li, Bin
• Is Part Of: Computer aided design. Volume 115(2019)
• Page Start: 307
• Page End: 322
• Publication Date: 2019-10
• Subjects: Triply periodic minimal surfaces -- Sandwich panel -- T-spline surfaces -- Additive manufacturing; Computer-aided design -- Periodicals; Engineering design -- Data processing -- Periodicals; Computer graphics -- Periodicals; Conception technique -- Informatique -- Périodiques; Infographie -- Périodiques; Computer graphics; Engineering design -- Data processing; Periodicals; Electronic journals; 620.00420285
• DOI: 10.1016/j.cad.2019.06.007
• Languages: English
• ISSNs: 0010-4485

Abstract

Abstract: Sandwich panel is a promising engineering structure, attracting more and more research attention. Most of current sandwich panels are constructed with plane skins and lattice cores via traditional fabrication processes. In this work, the skin faces of sandwich panels are designed by the freeform T-spline surfaces. The triply periodic minimal surface (TPMS) structures can be accurately generated as porous internal cores. In order to evaluate the performances of TPMS units, a cross-section analysis framework is developed. Based on that, an improved particle swarm optimization (IPSO) algorithm is discussed to seek optimal parameters. Moreover, considering the multifunctional requirements of actual applications, a constrained improved particle swarm optimization (CIPSO) algorithm is introduced to acquire both ideal mechanical and structural performances. Eventually, the designed sandwich panels can be fabricated by the state-of-the-art additive manufacturing technology. Experimental results validate the effectiveness of the presented design method and performance optimization algorithms. Highlights: A novel sandwich panel designed with TPMS cores and T-spline skin surfaces. An analysis and optimization framework for TPMS based on the cross-sections. An improved PSO algorithm for seeking the optimal parameters of TPMS. A constrained improved PSO algorithm for multifunctional design.