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May 19, 2026Journal of Materials in Civil Engineering0 citations

Effect of Edge Distance on Sheathing-to-Frame Nail Connections: Experimental and Statistical Analysis

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JCJixing CaoJDJiaoyan DuZWZhiqi Wang

Key Points

  • This research aims to explore the impact of nail edge distance on sheathing-to-frame nail connections under monotonic loading.
  • Conducted experimental tests with six specimen groups under controlled monotonic loading conditions.
  • Analyzed the performance relating to nail edge distance, OSB sheathing thickness, and loading direction.
  • Employed statistical methods including Monte Carlo simulations and sensitivity analysis for data processing and error evaluation.
  • Increased nail edge distance leads to significant improvements in load-bearing capacity and ultimate displacement.
  • Stiffness responses were non-linear, indicating complexity in stiffness behavior with varying edge distances.
  • Maximum load-bearing capacity and stiffness were best modeled using normal distribution.

Abstract

Sheathing-to-frame nail connections (SFNCs) are integral to light-frame wood shear walls. This study presents experimental results from six groups of specimens subjected to monotonic loading to analyze failure modes and load-displacement relationships. The study primarily focuses on the effect of nail edge distance on the performance of the connection, considering other factors such as OSB sheathing panel thickness and loading direction relative to the wood grain. The results demonstrate that, within a certain range, increasing the nail edge distance can significantly enhance the load-bearing capacity and ultimate displacement of the connections. However, the effect on stiffness is more complex, exhibiting nonlinear characteristics. The study also proposes a statistical evaluation framework for SFNCs, which includes data processing, random variable distribution fitting, and evaluation of fitting errors. The results indicate that both the maximum load-bearing capacity and stiffness of the connections are best described by a normal distribution. Monte Carlo simulations and Sobol sensitivity analysis were then performed to assess the impact of various parameters on model outputs.

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Cite This Study

Cao et al. (2026) studied this question.

synapsesocial.com/papers/6a0bfde8166b51b53d3793fbhttps://doi.org/10.1061/jmcee7.mteng-21618
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