An Analytical Model for Predicting the Axial Stress Distribution of Self-Tapping Screws Due to Axial Load and Moisture Swelling of Mass Timber Products

Self-tapping screws are becoming increasingly popular for use in modern timber structures. The axial stress distribution of self-tapping screws due to a mechanical load has been previously studied. However, the stress distribution of self-tapping screws due to moisture swelling-induced load from wood has not been explored so far. This research presents an analytical model to predict the axial stress distribution in self-tapping screws embedded in mass timber products under the combined effects of axial mechanical loading and wood moisture-induced swelling. The analytical model has been validated with numerical simulation. The input properties of the analytical model can be determined from withdrawal tests of self-tapping screws and the manufacturer’s guide of screw and mass timber products. A simple program has been developed to predict the stress distribution and maximum axial stress in self-tapping screws for a range of effective penetration lengths under a pre-load and moisture content change. Correctly predicting the maximum axial stress in self-tapping screws under the simultaneous action of a pre-load and wood moisture swelling-induced load can help design safer timber structures. This research provides a practical method for practicing engineers to predict the maximum axial stress in self-tapping screws due to pre-load and wood moisture swelling.

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Publication Details

Journal
Buildings
Published
2025-04-15
DOI
https://doi.org/10.3390/buildings15081297
Citations
2
Primary Topic
Wood Treatment and Properties
Type
article
Field-Weighted Citation Impact
2.01
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article

An Analytical Model for Predicting the Axial Stress Distribution of Self-Tapping Screws Due to Axial Load and Moisture Swelling of Mass Timber Products

Sara Keypoursangsari, Mehsam Tanzim Khan, Ying Hei Chui, Zengtao Chen et al.
2 citations
Buildings
Wood Treatment and Properties
2.01
article

An Analytical Model for Predicting the Axial Stress Distribution of Self-Tapping Screws Due to Axial Load and Moisture Swelling of Mass Timber Products

Sara Keypoursangsari, Mehsam Tanzim Khan, Ying Hei Chui, Zengtao Chen, Chun Ni
article en
2 citations

Abstract

Self-tapping screws are becoming increasingly popular for use in modern timber structures. The axial stress distribution of self-tapping screws due to a mechanical load has been previously studied. However, the stress distribution of self-tapping screws due to moisture swelling-induced load from wood has not been explored so far. This research presents an analytical model to predict the axial stress distribution in self-tapping screws embedded in mass timber products under the combined effects of axial mechanical loading and wood moisture-induced swelling. The analytical model has been validated with numerical simulation. The input properties of the analytical model can be determined from withdrawal tests of self-tapping screws and the manufacturer’s guide of screw and mass timber products. A simple program has been developed to predict the stress distribution and maximum axial stress in self-tapping screws for a range of effective penetration lengths under a pre-load and moisture content change. Correctly predicting the maximum axial stress in self-tapping screws under the simultaneous action of a pre-load and wood moisture swelling-induced load can help design safer timber structures. This research provides a practical method for practicing engineers to predict the maximum axial stress in self-tapping screws due to pre-load and wood moisture swelling.

BuildingsVol. 15(8)
Northwestern University (US), University of Alberta (CA), FPInnovations (CA)
Openalex Percentile: Top 15%
Wood Treatment and Properties
2.01
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An Analytical Model for Predicting the Axial Stress Distribution of Self-Tapping Screws Due to Axial Load and Moisture Swelling of Mass Timber Products — Sara Keypoursangsari, Mehsam Tanzim Khan, et al. · Buildings (2025) | TGRS Research Map | TGRS