Deep learning in mechanical metamaterials: from prediction and generation to inverse design
Mechanical metamaterials are meticulously designed structures with exceptional
mechanical properties determined by their microstructures and constituent materials …
mechanical properties determined by their microstructures and constituent materials …
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 …
3d-ldm: Neural implicit 3d shape generation with latent diffusion models
Diffusion models have shown great promise for image generation, beating GANs in terms of
generation diversity, with comparable image quality. However, their application to 3D …
generation diversity, with comparable image quality. However, their application to 3D …
Nature-inspired architected materials using unsupervised deep learning
SC Shen, MJ Buehler - Communications Engineering, 2022 - nature.com
Nature-inspired material design is driven by superior properties found in natural architected
materials and enabled by recent developments in additive manufacturing and machine …
materials and enabled by recent developments in additive manufacturing and machine …
[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 …
TPMS-infill MMC-based topology optimization considering overlapped component property
Engineering designs involving multiple materials suffer either difficult interface modeling or
finding physically meaningful transition domains with a clear or even optimal structural …
finding physically meaningful transition domains with a clear or even optimal structural …
Controlling auxeticity in curved-beam metamaterials via a deep generative model
G Felsch, N Ghavidelnia, D Schwarz… - Computer Methods in …, 2023 - Elsevier
Lattice-based mechanical metamaterials are known to exhibit quite a unique mechanical
behavior owing to their rational internal architecture. This includes unusual properties such …
behavior owing to their rational internal architecture. This includes unusual properties such …
[HTML][HTML] Inverse design of 3D cellular materials with physics-guided machine learning
M Abu-Mualla, J Huang - Materials & Design, 2023 - Elsevier
This paper investigates the feasibility of data-driven methods in automating the engineering
design process, specifically studying inverse design of cellular mechanical metamaterials …
design process, specifically studying inverse design of cellular mechanical metamaterials …
New families of triply periodic minimal surface-like shell lattices
Triply periodic minimal surface (TPMS)-based shell lattices are increasingly recognized for
their exceptional geometric and mechanical attributes. Their open-cell configuration further …
their exceptional geometric and mechanical attributes. Their open-cell configuration further …
Deep learning-enabled design for tailored mechanical properties of SLM-manufactured metallic lattice structures
The lattice structures obtained by combining repetitive light cellular forms provide superior
high strength to weight capabilities compared to monolithic solid bodies. These properties of …
high strength to weight capabilities compared to monolithic solid bodies. These properties of …