Three-dimensional graded metamaterials with customizable thermal responses under space-variant temperature stimuli DOI
Kaiyu Wang,

Zhengtong Han,

Fan Lin

и другие.

Composite Structures, Год журнала: 2024, Номер 353, С. 118717 - 118717

Опубликована: Ноя. 16, 2024

Язык: Английский

Performance prediction and inverse design of cylindrical plate-type acoustic metamaterials based on deep learning DOI

Jiahan Huang,

Jianquan Chen, Huanzhuo Mai

и другие.

Applied Acoustics, Год журнала: 2025, Номер 234, С. 110633 - 110633

Опубликована: Март 3, 2025

Язык: Английский

Процитировано

2

A novel framework to predict transversal and shear parameters of unidirectional composites by combining experimental, numerical and machine learning methods DOI Creative Commons

Siqi Cheng,

Xiaoyu Wang, Yuxuan Gao

и другие.

Polymer Composites, Год журнала: 2025, Номер unknown

Опубликована: Янв. 25, 2025

Abstract This work presents a new method to predict the transversal and shear properties of unidirectional composites (UD) through combining experimental, numerical machine learning methods. The experimental results proved complexity difficulty explaining primary factors affecting mechanical UD. representative unit cell model was then created generate 500 virtual samples for learning. show that back propagation neural network (BP) is most suitable predicting UD, with an accuracy 98% within 2% error. minimum mean square absolute errors are 1.09E‐3 1.15E‐5, respectively. It interface has significant influences on all UD modulus composite in 12 directions (G c ) affected by input parameters optimized BP model. Due wide coverage data, proposed universal can be adopted made from different kinds fibers. Highlights Interface composites. Shear along intricated. Machine Specific beneficial improve predicted accuracy.

Язык: Английский

Процитировано

1

Design and optimization of a mechanical metamaterial featuring dual tunability in auxeticity and bandgap modulation DOI
Jiayi Hu, Zhi Gong, Yuanlong Li

и другие.

Composite Structures, Год журнала: 2025, Номер unknown, С. 119050 - 119050

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

1

Inverse design framework of hybrid honeycomb structure with high impact resistance based on active learning DOI Creative Commons

Xingyu Shen,

Ke Yan, Difeng Zhu

и другие.

Defence Technology, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

1

Intelligent Design of Low-Frequency Bandgaps in Cementitious Metamaterials for Enhanced Tunability DOI
Zhi Gong, Jiayi Hu, Peng Dong

и другие.

Thin-Walled Structures, Год журнала: 2024, Номер unknown, С. 112860 - 112860

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

3

Performance Prediction and Inverse Design of Cylindrical Plate-Type Acoustic Metamaterials Based on Deep Learning DOI

Jiahan Huang,

Jianquan Chen, Huanzhuo Mai

и другие.

Опубликована: Янв. 1, 2025

Acoustic metamaterials are artificial structures that possess distinctive acoustic characteristics, allowing for modulation effects challenging to achieve in the natural world. Nevertheless, design of is a process due intricate relationship between their structural parameters and nonlinear performance. In view limitations conventional methodologies, which rely on priori knowledge experts often hindered by prolonged computation times necessity iterative trials objectives, this paper introduces deep learning-based method performance prediction inverse Cylindrical Plate-type Metamaterials (CPAMs). The creation dataset initiated generating large number samples using parametric model, with bandgap characteristics calculated through finite element method. A forward-design learning model then developed, predicting upper lower limits based input parameters. Additionally, an constructed, enabling rapid generation desired results validated simulation experimentation, confirming accuracy reliability model. This study demonstrates potential efficiently designing complex metamaterials, offering promising solution CPAMs development.

Язык: Английский

Процитировано

0

Inverse design of a petal-shaped honeycomb with zero Poisson’s ratio and bi-directional tunable mechanical properties DOI

Ze-Yu Chang,

Hai‐Tao Liu,

Guangbin Cai

и другие.

Composite Structures, Год журнала: 2025, Номер unknown, С. 118967 - 118967

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Physically Constrained 3D Diffusion for Inverse Design of Fiber-reinforced Polymer Composite Materials DOI Creative Commons
Pei Xu, Yunpeng Wu, Alireza Zarei

и другие.

Composites Part B Engineering, Год журнала: 2025, Номер unknown, С. 112515 - 112515

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Neural networks based inverse design of inhomogeneous tetrachiral honeycombs for desired deformation DOI
Linzhe Du, Jian Sun, Yanju Liu

и другие.

Composite Structures, Год журнала: 2025, Номер unknown, С. 119236 - 119236

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Gear-Shifting Tunable Meta-Shaft for Low-Frequency Torsional Vibration Suppression DOI
Dongxian Wang,

Hao Zhou,

Jianlei Zhao

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0