Deep learning-based semantic segmentation for morphological fractography

Engineering Fracture Mechanics, Год журнала: 2024, Номер 303, С. 110149 - 110149

Опубликована: Май 8, 2024

Язык: Английский

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Machine learning-based fatigue life prediction of lamellar titanium alloys: A microstructural perspective

Engineering Fracture Mechanics, Год журнала: 2024, Номер 303, С. 110106 - 110106

Опубликована: Апрель 24, 2024

Язык: Английский

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Design and Kinematic Analysis of Origami Honeycomb Metamaterials with One-DOF Radial Motion

Thin-Walled Structures, Год журнала: 2025, Номер unknown, С. 112978 - 112978

Опубликована: Янв. 1, 2025

Язык: Английский

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

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

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Multimodal Data Fusion Enhanced Deep Learning Prediction of Crack Path Segmentation in CFRP Composites

Composites Science and Technology, Год журнала: 2024, Номер 257, С. 110812 - 110812

Опубликована: Авг. 13, 2024

Язык: Английский

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

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

Опубликована: Июль 8, 2024

Язык: Английский

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Integrating analytical and machine learning methods for investigating nonlinear bending and post-buckling behavior of 3D-printed auxetic tubes

Engineering With Computers, Год журнала: 2024, Номер unknown

Опубликована: Дек. 15, 2024

Язык: Английский

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A generalizable framework of solution-guided machine learning with application to nanoindentation of free-standing thin films

Thin-Walled Structures, Год журнала: 2024, Номер 200, С. 111984 - 111984

Опубликована: Май 7, 2024

Язык: Английский

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A GAN-based stepwise full-field mechanical prediction model for architected metamaterials

International Journal of Mechanical Sciences, Год журнала: 2024, Номер 284, С. 109771 - 109771

Опубликована: Окт. 8, 2024

Язык: Английский

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Inverse design of programmable shape-morphing kirigami structures

International Journal of Mechanical Sciences, Год журнала: 2024, Номер unknown, С. 109840 - 109840

Опубликована: Ноя. 1, 2024

Язык: Английский

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