Theoretical and experimental studies on the bending properties of glued laminated timber manufactured with Chinese fir

Gong, Yingchun; Chen, Xu; Ren, Haiqing; Liu, Bailong; Zhang, Huanmin; Wang, Yurong

doi:10.1016/j.istruc.2024.107149

Structures

2024

DOI: 10.1016/j.istruc.2024.107149

|View full text |Cite

Theoretical and experimental studies on the bending properties of glued laminated timber manufactured with Chinese fir

Yingchun Gong,

Xu Chen,

Haiqing Ren

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...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Numerical Methods for Topological Optimization of Wooden Structural Elements

Țăpuși,

Sabău,

Savu

et al. 2024

Buildings

View full text Add to dashboard Cite

Timber represents a building material that aligns with the environmental demands on the impact of the construction sector on climate change. The most common engineering solution for modern timber buildings with large spans is glued laminate timber (glulam). This project proposes a tool for a topological optimized geometry generator of structural elements made of glulam that can be used for building a database of topologically optimized glulam beams. In turn, this can be further used to train machine learning models that can embed the topologically optimized geometry and structural behavior information. Topological optimization tasks usually require a large number of iterations in order to reach the design goals. Therefore, embedding this information into machine learning models for structural elements belonging to the same topological groups will result in a faster design process since certain aspects regarding structural behavior such as strength and stiffness can be quickly estimated using Artificial Intelligence techniques. Topologically optimized geometry propositions could be obtained by employing generative machine learning model techniques which can propose geometries that are closer to the topologically optimized results using FEM and as such present a starting point for the design analysis in a reduced amount of time.

show abstract

Numerical Methods for Topological Optimization of Wooden Structural Elements

Țăpuși,

Sabău,

Savu

et al. 2024

Buildings

View full text Add to dashboard Cite

show abstract

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

customersupport@researchsolutions.com

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

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

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.

Theoretical and experimental studies on the bending properties of glued laminated timber manufactured with Chinese fir

Cited by 1 publication

References 7 publications

Numerical Methods for Topological Optimization of Wooden Structural Elements

Numerical Methods for Topological Optimization of Wooden Structural Elements

Contact Info

Product

Resources

About