Deep learning, deconvolutional neural network inverse design of strut-based lattice metamaterials-Reference-Cited by-同舟云学术

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Deep learning, deconvolutional neural network inverse design of strut-based lattice metamaterials

Published:2024-09 Issue: Volume:244 Page:113258
ISSN:0927-0256
Container-title:Computational Materials Science
language:en
Short-container-title:Computational Materials Science

Author:

Dos Reis Francisco,Karathanasopoulos Nikolaos^ORCID

Publisher

Elsevier BV

Reference66 articles.

1. Design of architectured materials based on mechanically driven structural and compositional patterning;Estrin;Adv. Eng. Mater.,2019

2. Effective stiffness, wave propagation, and yield surface attributes of menger sponge-like pre-fractal topologies;Viet;Int. J. Mech. Sci.,2022

3. Multi-objective optimisation of bio-inspired lightweight sandwich structures based on selective laser melting;Meng;Virtual Phys. Prototyp.,2020

4. Topology optimisation in structural steel design for additive manufacturing;Ribeiro;Appl. Sci.,2021

5. Functionally graded lattice structure topology optimization for the design of additive manufactured components with stress constraints;Cheng;Comput. Methods Appl. Mech. Engrg.,2019

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