Pull-Out Progressive Damage and Failure Analysis of Laminated Composite Bolted Joints DOI Open Access

Zhaowei Zeng,

Qixiang Fan, Feng Liao

и другие.

Materials, Год журнала: 2024, Номер 17(23), С. 5747 - 5747

Опубликована: Ноя. 24, 2024

Laminated composite bolted joints are increasingly used in the aerospace field, and their damage failure behavior has been studied depth. In view of complexity stability requirements laminated structures, accurate prediction evolution is significant to ensure safety reliability structures. this paper, a novel asymptotic model developed predict process joints. model, modified Puck criterion maximum shear stress for fiber yarns. The parabolic yield adopted matrix, fracture, inter-fiber fracture matrix considered at microscopic level. pull-out strength progressive countersunk convex structures predicted by using proposed corresponding experimental studies carried out. results show that good agreement with data, which verifies model. Additionally, effects different structural parameters (thickness aperture) on during analyzed correction factors obtained, provides powerful tool design, analysis progression joint

Язык: Английский

Optimization of assembly parameters for composite bolted joints aiming at time-varying bearing reliability improvement DOI
Qingyuan Lin, Yong Zhao, Yuming Liu

и другие.

Composite Structures, Год журнала: 2025, Номер unknown, С. 119113 - 119113

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

1

Layup optimization of composite B-pillar under side impact DOI
Wenbin Hou, Mengdi Li,

Yan Yang

и другие.

International Journal of Mechanical Sciences, Год журнала: 2025, Номер 287, С. 109927 - 109927

Опубликована: Янв. 6, 2025

Язык: Английский

Процитировано

0

Industrial Applications of AI in Aircraft Manufacturing: A PRISMA Systematic Literature Review DOI Creative Commons

Pierrick BOUGAULT,

Raphael Haddad,

Liang Ma

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Март 12, 2025

Abstract Aircraft industry, especially the commercial aircraft branch, is an important and specific field in manufacturing due to its distinct features such as high personalization low production output, expected grow significantly future. At same time, artificial intelligence (AI) machine learning (ML) have undertaken a major revolution sector with promising improvements. However, global deployment of AI/ML sphere still requires further operationalization. This study aims address challenges this implementation by providing PRISMA systematic literature review 89 articles. Several perspectives were analyzed, including word cloud analysis, distribution over years, geographical distribution, domains application, paradigms, models, materials, components. Additionally, synthesis was conducted on data augmentation, reduction, hardware employed, overall all relevant articles field. The findings revealed insights into trends applications terms techniques, influence, applications, materials contributes gathering present state-of-the-art research, identifying key elements, highlighting research opportunities, use LLMs integration human factors.

Язык: Английский

Процитировано

0

Industrial Applications of AI in Aircraft Manufacturing: A PRISMA Systematic Literature Review DOI

Pierrick BOUGAULT,

Raphael Haddad,

Liang Ma

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Май 19, 2025

Abstract Artificial Intelligence (AI) and Machine Learning (ML) are foundations in new manufacturing paradigms, yet their application the aircraft industry remains limited, as this industry's core expertise does not traditionally cover these technologies. Additionally, due to its specific features, presents unique challenges, for instance with data. To date, no systematic review has considered features enable stakeholders sector successfully undergo AI/ML transformation. This study aims analyze screen state of art by providing a PRISMA literature 89 articles, focusing on contexts, models, methods employed development solutions. The authors propose framework summarize findings regarding AI development, applications, benefits, challenges industry. contributes field meticulously gathering methodologies approaches that address integrate specificities use integration Furthermore, further research opportunities identified through comparison current theoretical concepts Industry 5.0, cutting-edge technologies, such Federated Learning, Transfer Large Language Models (LLMs), lack supply chain investigation, human factors, which emerging or notably absent major reviewed articles.

Язык: Английский

Процитировано

0

A cGAN-based fatigue life prediction of 316 austenitic stainless steel in high-temperature and high-pressure water environments DOI

Lvfeng Jiang,

Yanan Hu, Hui Li

и другие.

International Journal of Fatigue, Год журнала: 2024, Номер unknown, С. 108633 - 108633

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

2

Conditional generative adversarial network-based predictive method for crack initiation in a dual-phase austenite stainless weld DOI
Yule Wu, Jiamei Wang, Xianglong Guo

и другие.

Corrosion Science, Год журнала: 2024, Номер unknown, С. 112494 - 112494

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

1

TF-F-GAN: A GAN-based model to predict the assembly physical fields under multi-modal variables fusion on vision transformer DOI
Yuming Liu,

Wencai Yu,

Qingyuan Lin

и другие.

Advanced Engineering Informatics, Год журнала: 2024, Номер 62, С. 102871 - 102871

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

1

Pull-Out Progressive Damage and Failure Analysis of Laminated Composite Bolted Joints DOI Open Access

Zhaowei Zeng,

Qixiang Fan, Feng Liao

и другие.

Materials, Год журнала: 2024, Номер 17(23), С. 5747 - 5747

Опубликована: Ноя. 24, 2024

Laminated composite bolted joints are increasingly used in the aerospace field, and their damage failure behavior has been studied depth. In view of complexity stability requirements laminated structures, accurate prediction evolution is significant to ensure safety reliability structures. this paper, a novel asymptotic model developed predict process joints. model, modified Puck criterion maximum shear stress for fiber yarns. The parabolic yield adopted matrix, fracture, inter-fiber fracture matrix considered at microscopic level. pull-out strength progressive countersunk convex structures predicted by using proposed corresponding experimental studies carried out. results show that good agreement with data, which verifies model. Additionally, effects different structural parameters (thickness aperture) on during analyzed correction factors obtained, provides powerful tool design, analysis progression joint

Язык: Английский

Процитировано

0