Data‐Driven Design for Metamaterials and Multiscale Systems: A Review
Metamaterials are artificial materials designed to exhibit effective material parameters that
go beyond those found in nature. Composed of unit cells with rich designability that are …
go beyond those found in nature. Composed of unit cells with rich designability that are …
Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial
On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an
essential layer of safety assurance that could lead to more principled decision making by …
essential layer of safety assurance that could lead to more principled decision making by …
Efficient diffusion models for vision: A survey
Diffusion Models (DMs) have demonstrated state-of-the-art performance in content
generation without requiring adversarial training. These models are trained using a two-step …
generation without requiring adversarial training. These models are trained using a two-step …
Biologically inspired design concept generation using generative pre-trained transformers
Biological systems in nature have evolved for millions of years to adapt and survive the
environment. Many features they developed can be inspirational and beneficial for solving …
environment. Many features they developed can be inspirational and beneficial for solving …
Generative transformers for design concept generation
Generating novel and useful concepts is essential during the early design stage to explore a
large variety of design opportunities, which usually requires advanced design thinking ability …
large variety of design opportunities, which usually requires advanced design thinking ability …
A comprehensive literature review of the applications of AI techniques through the lifecycle of industrial equipment
Driven by the ongoing migration towards Industry 4.0, the increasing adoption of artificial
intelligence (AI) has empowered smart manufacturing and digital transformation. AI …
intelligence (AI) has empowered smart manufacturing and digital transformation. AI …
Generative pre-trained transformer for design concept generation: an exploration
Novel concepts are essential for design innovation and can be generated with the aid of
data stimuli and computers. However, current generative design algorithms focus on …
data stimuli and computers. However, current generative design algorithms focus on …
Diffusion models beat gans on topology optimization
F Mazé, F Ahmed - Proceedings of the AAAI conference on artificial …, 2023 - ojs.aaai.org
Structural topology optimization, which aims to find the optimal physical structure that
maximizes mechanical performance, is vital in engineering design applications in …
maximizes mechanical performance, is vital in engineering design applications in …
Human-centered generative design framework: an early design framework to support concept creation and evaluation
Generative design uses artificial intelligence-driven algorithms to create and optimize
concept variants that meet or exceed performance requirements beyond what is currently …
concept variants that meet or exceed performance requirements beyond what is currently …
[HTML][HTML] ShipHullGAN: A generic parametric modeller for ship hull design using deep convolutional generative model
In this work, we introduce ShipHullGAN, a generic parametric modeller built using deep
convolutional generative adversarial networks (GANs) for the versatile representation and …
convolutional generative adversarial networks (GANs) for the versatile representation and …