Bio-inspired generative design for engineering products: A case study for flapping wing shape exploration

Jiang，Zhoumingju1; Ma，Yongsheng2; Xiong，Yi1

2023-10-01

10.1016/j.aei.2023.102240

Advanced Engineering Informatics   影响因子和分区

1474-0346

1873-5320

Nature has undergone millions of years of evolution, enabling organisms to adapt and survive in their environment. The remarkable features developed by these organisms serve as a rich source of inspiration for designers involved in engineering design. However, the effective application of bio-inspired design faces challenges due to the gap between biology and engineering, as well as the limited level of design automation. This paper proposes a bio-inspired generative design framework (BIGD), containing three main steps of dataset building, generator modeling, and design evaluation, which aims to automatically produce innovative designs by synthesizing a diverse range of natural designs using deep generative models. Specifically, a computational workflow is established for automated bio-inspired wing shape synthesis. The process of constructing a dataset typically involves web crawling data from various sources, followed by data preprocessing to ensure clarity. The data is then structured with prior knowledge from the biological domain and outliers are excluded. Finally, design knowledge is extracted through data mining and knowledge extraction techniques. In the case of a flapping wing shape design, the deep generative model is constructed using a bird wing dataset created with a strong foundation in biological domain knowledge. The wings generated by BIGD exhibit superior lift performance across a range of working conditions, showcasing the advantages of using BIGD to directionally guide the evolution of generative models based on biological knowledge. This research highlights the potential of using computational methods in bio-inspired design to rapidly generate innovative and high-performance designs.

Bio-inspired design Deep generative models Design automation Engineering design Generative design Shape synthesis

SCI ; EI

英语

第一 ; 通讯

National Natural Science Foundation of China[52105261] ; Guangdong Basic and Applied Basic Research Foundation[2022A1515010316]

Computer Science ; Engineering

Computer Science, Artificial Intelligence ; Engineering, Multidisciplinary

WOS:001108583600001

ELSEVIER SCI LTD

20234515014942

Automation ; Biomimetics ; Computer aided design ; Data mining ; Product design ; Web crawler

Biotechnology:461.8 ; Biology:461.9 ; Data Processing and Image Processing:723.2 ; Computer Applications:723.5 ; Automatic Control Principles and Applications:731 ; Production Engineering:913.1

ENGINEERING

2-s2.0-85175581326

Scopus

1.School of System Design and Intelligent Manufacturing,Southern University of Science and Technology,Shenzhen,518055,China
2.Department of Mechanical and Energy Engineering,Southern University of Science and Technology,Shenzhen,518055,China

Jiang，Zhoumingju,Ma，Yongsheng,Xiong，Yi. Bio-inspired generative design for engineering products: A case study for flapping wing shape exploration[J]. Advanced Engineering Informatics,2023,58.

Jiang，Zhoumingju,Ma，Yongsheng,&Xiong，Yi.(2023).Bio-inspired generative design for engineering products: A case study for flapping wing shape exploration.Advanced Engineering Informatics,58.

Jiang，Zhoumingju,et al."Bio-inspired generative design for engineering products: A case study for flapping wing shape exploration".Advanced Engineering Informatics 58(2023).