... computer-aided design data-driven design design optimization generative design The rapid advancements in artificial intelligence (AI) have revolutionized various domains, and the field of mechanical engineering is no exception. The significance of comprehensive and diverse datasets has become...

..., the underlying sequential design process encodes valuable information for designers. Many efforts have been made to automatically generate reasonable volumetric designs, but the quality of the generated design solutions varies, and evaluating a design solution requires either a prohibitively comprehensive set...

... artificial intelligence computational kinematics computer-aided engineering data-driven design generative design linkages mechanism synthesis Path-generating linkage mechanisms are fundamental in mechanical design due to their ability to translate rotational or linear input into specific...

... automation generative design machine learning Division of Civil, Mechanical and Manufacturing Innovation 10.13039/100000147 2245299 In computer graphics and the computer-aided design (CAD)/computer-aided manufacturing (CAM) industry, parametric smooth curves (e.g., Bézier, B-spline...

... Graphical Abstract Figure porous metamaterial graph neural network variational graph autoencoder design optimization generative design connectivity data-driven design design of engineered materials system machine learning Division of Civil, Mechanical and Manufacturing Innovation...

... the validity of generated designs. As shown in Table 4 , designs identified by MCD violate on average 0.92 constraints versus 1.51 for designs generated by NSGA-II. Collectively, MCD can identify valid designs that do not violate any constraints 35% of the time compared to NSGA-II’s 15%. These scores...

... by the Design Theory and Methodology Committee of ASME for publication in the J ournal of M echanical D esign . 18 02 2024 09 05 2024 14 05 2024 05 07 2024 Graphical Abstract Figure generative design conceptual design large language model FBS model creativity...

... to design, e.g., generative design (GD), to help expand designers' divergent thinking. However, generative design technologies are relatively new, we know little about generative design thinking in students. This research aims to advance our understanding of the relationship between aspects of generative...

... with a larger quality factor will have a higher call probability at the next temperature. Table 2 Average and standard deviation of total scaffold length ( sl ) of top ten generated designs per ten batches with input tetrahedral mesh using refined technique d (nm) s l ¯ σ...

...-Based Learning and Design of Metamaterial Systems ,” Comput. Meth. Appl. Mech. Eng. , 372 , p. 113377 . 10.1016/j.cma.2020.113377 stochastic microstructures architectured materials deep generative model curvature functional design representation artificial intelligence generative...

...Zhichao Wang; Shreyes Melkote; David W. Rosen Generative design (GD) techniques have been proposed to generate numerous designs at early design stages for ideation and exploration purposes. Previous research on GD using deep neural networks required tedious iterations between the neural network...

... Committee of ASME for publication in the J ournal of M echanical D esign . 26 04 2023 28 06 2023 29 06 2023 19 07 2023 topology optimization eigenfrequency matching frequency response analysis antiresonances design methodology design optimization generative design...

... artificial intelligence computer-aided design design for manufacturing generative design 19 09 2022 22 05 2023 22 05 2023 23 06 2023 Contributed by the Design Automation Committee of ASME for publication in the J ournal of M echanical D esign . 1 Corresponding author...

...Jana I. Saadi; Maria C. Yang Generative design tools empowered by recent advancements in artificial intelligence (AI) offer the opportunity for human designers and design tools to collaborate in new, more advanced modes throughout various stages of the product design process to facilitate...

... approach to bridge the gap. This paper proposes a generative design approach based on the generative pre-trained language model (PLM) to automatically retrieve and map biological analogy and generate BID in the form of natural language. The latest generative pre-trained transformer, namely generative pre...

...Chenxi Yuan; Tucker Marion; Mohsen Moghaddam Generative adversarial networks (GANs) have shown remarkable success in various generative design tasks, from topology optimization to material design, and shape parametrization. However, most generative design approaches based on GANs lack evaluation...

... 2022 09 12 2022 design automation artificial intelligence deep learning generalizability agent-based design data-driven design design representation generative design machine learning Monte Carlo Tree Search Solving design problems is one of the most ubiquitous processes...

... to the increasing scale of modern systems and the complicated underlying physical constraints. To tackle these challenges and design a resilient system efficiently, this study presents a generative design method that utilizes graph learning algorithms. The generative design framework contains a performance...

... a whole lattice structure ( c ). Since we aim at applying a generative design method for generating distinct lattice geometries, dozens of (novel) lattice designs can be generated for a set of predefined constraints, which can form an enriched unit cell library. Fig. 2 Straight or curved struts...

.... , and Hong , J. , 2019 , “ Non-Iterative Structural Topology Optimization Using Deep Learning ,” Comput. Aided Des. , 115 , pp. 172 – 180 . 10.1016/j.cad.2019.05.038 [24] Li , B. , Tang , W. , Ding , S. , and Hong , J. , 2020 , “ A Generative Design Method for Structural...