Cited by A machine learning strategy for enhancing the strength and toughness in metal matrix composites

Broad bandgap active metamaterials with optimal time-delayed control DOI

Yuqiang Gao, Lifeng Wang

International Journal of Mechanical Sciences, Год журнала: 2023, Номер 254, С. 108449 - 108449

Опубликована: Май 10, 2023

Язык: Английский

Процитировано

Few-shot learning-based generative design of metamaterials with zero Poisson’s ratio DOI

Xiangbei Liu, Huan Zhao,

Ya Tang

и другие.

Materials & Design, Год журнала: 2024, Номер 244, С. 113224 - 113224

Опубликована: Авг. 1, 2024

Metamaterials with a zero Poisson's ratio offer significant advantages in robotic actuation and space exploration due to their precise control of deformation. However, existing machine learning techniques cannot be directly used accelerate the design such materials scarcity this property. We propose few-shot learning-based framework generate non-periodic metamaterials ratio. Our incorporates an out-of-distribution (OOD) target-oriented sampler into conditional variational autoencoder (cVAE). Unlike other metamaterial generative models that only deal continuous pixel data, our approach can handle discrete unit cell patterns by computing probability distributions. found controlling focus during training process effectively mitigate acceptable data within set. This mitigation is achieved repeatedly selecting target samples through OOD sampler. Incorporating active further enhance model efficiency adaptively adjusting between unacceptable samples. The impacts size, effective composition, number iterations on are discussed detail. Compared random trial-and-error generation, demonstrates substantial increase rate, from 0.3 % 39 %.

Язык: Английский

Процитировано

Improving mechanical properties of lattice structures using nonuniform hollow struts DOI

Chuang Liu, Rui Ni,

Kang Ji

и другие.

International Journal of Mechanical Sciences, Год журнала: 2024, Номер 283, С. 109674 - 109674

Опубликована: Авг. 26, 2024

Язык: Английский

Процитировано

Prediction and optimization of global temperature field of composite materials under multiple heat sources DOI

Sen Yang,

Wen Yao,

Lin-Feng Zhu

и другие.

Composite Structures, Год журнала: 2024, Номер 334, С. 117974 - 117974

Опубликована: Фев. 20, 2024

Язык: Английский

Процитировано

A machine learning strategy for enhancing the strength and toughness in metal matrix composites DOI

Zhiyan Zhong, Jun An, Dian Wu

и другие.

International Journal of Mechanical Sciences, Год журнала: 2024, Номер 281, С. 109550 - 109550

Опубликована: Июль 8, 2024

Язык: Английский

Процитировано