Special issue on Computer-Aided Design on Advances in Generative Design
摘要截稿:
全文截稿: 2018-05-15
影响因子: 3.156
期刊难度:
CCF分类: B类
中科院JCR分区:
• 大类 : 计算机科学 - 2区
• 小类 : 计算机:软件工程 - 2区
Overview
Recent advances in manufacturing and material science enable the fabrication of complex digital geometric models that are difficult or impossible to produce by using conventional manufacturing technologies. The unprecedented manufacturing flexibility offers opportunities and challenges for computer-aided design of such digital models. Even for the most experienced designers, their intuition might be limited when manually exploring such unprecedented large design space. To empower designers, computer algorithms are being developed to generate desired designs under given design objectives and constraints. Such an algorithm-driven design process is now known as generative design. Example approaches range from shape and topology optimization to shape grammar based design, and to machine learning based designs, among others. The flexibilities in generative design and additive manufacturing are increasingly being combined to produce disruptive high-performance functional structures and digital materials with applications in aerospace, automotive, medical implants, soft robots, customized consumer products, and beyond. This vibrant research area is receiving growing attention in multiple disciplines, such as geometric modelling, graphics, numerical optimization, and computational mechanics.
The goal of this special issue is to bring together researchers from relevant fields into a common forum, to share cutting-edge research on generative design, and to push forward new design methods for advanced manufacturing. The joint efforts will accelerate the transition of generative design from the stage of conceptual design to final design, and the movement of additive manufacturing from prototyping to industrial production. The main topics include, but are not limited to the following:
- Shape and topology optimization
- Design through machine learning
- Big-data driven designs
- Genetic algorithms based design
- Design through shape grammars
- Generative design of digital material
- Generative design of lattice and cellular structures
- Generative design under manufacturability constraints
- Generative design considering multi-physics
- Shape modelling and analysis for generative design