Experimental study of the influence of inclined pre-cracks on shear behavior of RC beams without transverse reinforcement

Yang, Jingying; Shu, Jiangpeng; Li, Jun; Yu, Ke; Zandi, Kamyab; Bai, Yong

doi:10.1016/j.engstruct.2023.117133

Engineering Structures

2024

DOI: 10.1016/j.engstruct.2023.117133

|View full text |Cite

Experimental study of the influence of inclined pre-cracks on shear behavior of RC beams without transverse reinforcement

Jingying Yang,

Jiangpeng Shu,

Jun Li

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Proposing an inherently interpretable machine learning model for shear strength prediction of reinforced concrete beams with stirrups

Shu,

Yu,

Liu

et al. 2024

Case Studies in Construction Materials

View full text Add to dashboard Cite

Proposing an inherently interpretable machine learning model for shear strength prediction of reinforced concrete beams with stirrups

Shu,

Yu,

Liu

et al. 2024

Case Studies in Construction Materials

View full text Add to dashboard Cite

Experimental investigation on influence of vertical stirrup legs to shear failure behavior in RC beams

Abdullah,

Nakamura,

Miura

2024

Developments in the Built Environment

View full text Add to dashboard Cite

Estimation of load-carrying capacity of cracked RC beams using 3D digital twin model integrated with point clouds and images

Zhang,

Shu,

Zhang

et al. 2024

Engineering Structures

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Experimental study of the influence of inclined pre-cracks on shear behavior of RC beams without transverse reinforcement

Cited by 3 publications

References 38 publications

Proposing an inherently interpretable machine learning model for shear strength prediction of reinforced concrete beams with stirrups

Proposing an inherently interpretable machine learning model for shear strength prediction of reinforced concrete beams with stirrups

Experimental investigation on influence of vertical stirrup legs to shear failure behavior in RC beams

Estimation of load-carrying capacity of cracked RC beams using 3D digital twin model integrated with point clouds and images

Contact Info

Product

Resources

About