A Machine learning model to predict fracture of solder joints considering geometrical and environmental factors

Theoretical and Applied Fracture Mechanics, Journal Year: 2025, Volume and Issue: 136, P. 104865 - 104865

Published: Feb. 4, 2025

Language: Английский

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Machine learning-based prediction of hydrogen-assisted fatigue crack growth rate in Cr–Mo steel

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 122, P. 1 - 11

Published: April 1, 2025

Language: Английский

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Nature’s Load-Bearing Design Principles and Their Application in Engineering: A Review

Biomimetics, Journal Year: 2024, Volume and Issue: 9(9), P. 545 - 545

Published: Sept. 9, 2024

Biological structures optimized through natural selection provide valuable insights for engineering load-bearing components. This paper reviews six key strategies evolved in nature efficient mechanical load handling: hierarchically structured composites, cellular structures, functional gradients, hard shell–soft core architectures, form follows function, and robust geometric shapes. The also discusses recent research that applies these to design, demonstrating their effectiveness advancing technical solutions. challenges of translating nature’s designs into applications are addressed, with a focus on how advancements computational methods, particularly artificial intelligence, accelerating this process. need further development innovative material characterization techniques, modeling approaches heterogeneous media, multi-criteria structural optimization advanced manufacturing techniques capable achieving enhanced control across multiple scales is underscored. By highlighting holistic approach designing components, advocates adopting similarly comprehensive methodology practices shape the next generation

Language: Английский

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A new method for prediction of fatigue crack propagation life under variable amplitude spectrum loading

Theoretical and Applied Fracture Mechanics, Journal Year: 2024, Volume and Issue: 131, P. 104355 - 104355

Published: March 3, 2024

Language: Английский

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Optimising fatigue crack growth predictions for small cracks under variable amplitude loading

International Journal of Fatigue, Journal Year: 2024, Volume and Issue: 185, P. 108339 - 108339

Published: April 18, 2024

Language: Английский

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Prediction of corrosion fatigue crack growth rate in aluminum alloys based on incremental learning strategy

International Journal of Fatigue, Journal Year: 2024, Volume and Issue: 187, P. 108481 - 108481

Published: June 28, 2024

Language: Английский

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Data-driven void growth prediction of aluminum under monotonic tension using deep learning

Journal of Constructional Steel Research, Journal Year: 2024, Volume and Issue: 222, P. 109002 - 109002

Published: Sept. 1, 2024

Language: Английский

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Machine learning approach for predicting and understanding fatigue crack growth rate of austenitic stainless steels in high-temperature water environments

Theoretical and Applied Fracture Mechanics, Journal Year: 2024, Volume and Issue: 133, P. 104499 - 104499

Published: June 5, 2024

Language: Английский

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Regression prediction model for shear strength of cold joint in concrete

Structures, Journal Year: 2024, Volume and Issue: 68, P. 107168 - 107168

Published: Sept. 3, 2024

Language: Английский

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Enhanced fatigue crack growth rate prediction in alloy steels using particle swarm optimized neural network

Theoretical and Applied Fracture Mechanics, Journal Year: 2024, Volume and Issue: unknown, P. 104826 - 104826

Published: Dec. 1, 2024

Language: Английский

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