Add to ORKGThe current advances in generative AI for learning large neural network models with the capability to produce essays, images, music and even 3D assets from text prompts create opportunities for a manifold of disciplines. In the present paper, we study the potential of deep text-to-3D models in the engineering domain, with focus on the chances and challenges when integrating and interacting with 3D assets in computational simulation-based design optimization. In contrast to traditional design optimization of 3D geometries that often searches for the optimum designs using numerical representations, such as B-Spline surface or deformation parameters in vehicle aerodynamic optimization, natural language challenges the optimization framework by ...
Gradient-based numerical optimization of complex engineering designs promises to produce better desi...
This is the author accepted manuscript.Optimisation of designs using Computational Fluid Dynamics (C...
In the pursuit of efficient automated content creation, procedural generation, leveraging modifiable...
In design optimization problems, engineers typically handcraft design representations based on perso...
The current design of aerodynamic shapes, like airfoils, involves computationally intensive simulati...
In this study, we present a data-driven generative design approach that can augment human creativity...
In this thesis, we advocate that Computer-Aided Engineering could benefit from a Geometric Deep Lear...
Recently, diffusion-based deep generative models (e.g., Stable Diffusion) have shown impressive resu...
Deep generative models such as Variational Autoencoders (VAEs), Generative Adversarial Networks (GAN...
Deep Generative Machine Learning Models (DGMs) have been growing in popularity across the design com...
In automotive digital development, 3D prototype creation is a team effort of designers and engineers...
Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks...
Generative Design is the methodology for automatic creation of a large number of designs via an iter...
© 2016 IEEE. Shape optimization techniques are becoming increasingly important in design and enginee...
This thesis presents a computational method generating 3D models based on topology optimization name...
Gradient-based numerical optimization of complex engineering designs promises to produce better desi...
This is the author accepted manuscript.Optimisation of designs using Computational Fluid Dynamics (C...
In the pursuit of efficient automated content creation, procedural generation, leveraging modifiable...
In design optimization problems, engineers typically handcraft design representations based on perso...
The current design of aerodynamic shapes, like airfoils, involves computationally intensive simulati...
In this study, we present a data-driven generative design approach that can augment human creativity...
In this thesis, we advocate that Computer-Aided Engineering could benefit from a Geometric Deep Lear...
Recently, diffusion-based deep generative models (e.g., Stable Diffusion) have shown impressive resu...
Deep generative models such as Variational Autoencoders (VAEs), Generative Adversarial Networks (GAN...
Deep Generative Machine Learning Models (DGMs) have been growing in popularity across the design com...
In automotive digital development, 3D prototype creation is a team effort of designers and engineers...
Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks...
Generative Design is the methodology for automatic creation of a large number of designs via an iter...
© 2016 IEEE. Shape optimization techniques are becoming increasingly important in design and enginee...
This thesis presents a computational method generating 3D models based on topology optimization name...
Gradient-based numerical optimization of complex engineering designs promises to produce better desi...
This is the author accepted manuscript.Optimisation of designs using Computational Fluid Dynamics (C...
In the pursuit of efficient automated content creation, procedural generation, leveraging modifiable...