Estimating the mechanical residual strength from IR spectra using machine learning for degraded adhesives-Reference-Cited by-同舟云学术

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Estimating the mechanical residual strength from IR spectra using machine learning for degraded adhesives

Published:2021-09-27 Issue: Volume: Page:1-23
ISSN:0021-8464
Container-title:The Journal of Adhesion
language:en
Short-container-title:The Journal of Adhesion

Author:

Shimamoto K.¹,Akiyama H.¹

Affiliation:

1. Nanomaterials Research Institute, the National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan

Publisher

Informa UK Limited

Subject

Materials Chemistry,Surfaces, Coatings and Films,Surfaces and Interfaces,Mechanics of Materials,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/00218464.2021.1978293

Reference44 articles.

1. Behaviour of environmentally degraded epoxy adhesives as a function of temperature

2. Predicting the residual strength for environmentally degraded adhesive lap joints

3. Degradation of Epoxy-Steel Single Lap Joints Immersed in Water

4. Durability assessment of structural sealant glazing systems applying a performance test method

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1. Hydrothermal degradation behaviour of bonded joints using open-faced specimens;International Journal of Adhesion and Adhesives;2024-09

2. Using machine learning and experimental study to correlate and predict accelerated aging with natural aging of GFRP composites in hygrothermal conditions;Construction and Building Materials;2024-08

3. Investigation of the quantitative relationship between IR spectra and stress–strain curves of cured adhesives immersed in water;International Journal of Adhesion and Adhesives;2024-06

4. Machine learning-based assessment of hygrothermal aging performance in CFRP-aluminum alloy adhesive bonded structures;The Journal of Adhesion;2023-11-22

5. A high-throughput technique to evaluate the probability distribution of strength of adhesively bonded joints after moisture absorption;The Journal of Adhesion;2023-10-19

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