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<p>The multi-scale uncertainty propagation mechanism in bolted joint interfaces remains poorly quantified due to the stochastic nature of microscopic surface morphology. To address this critical gap, this study establishes a novel hybrid framework that integrates fractal theory with an enhanced Monte Carlo simulation approach. Three fundamental advancements are presented. First, a fractal-based uncertainty quantification method is developed, which enables a refined characterization of surface morphology parameters through experimental-statistical calibration, thereby overcoming the deterministic limitations inherent in conventional roughness metrics. Then, the Monte Carlo method is employed to characterize the uncertain tangential contact parameters, and the intervals of these parameters under different contact gaps are extracted using Matlab. Simultaneously, the 95 % confidence region method is applied to transform these parameter intervals to reduce errors arising from uncertainty propagation. Finally, the Monte Carlo method is used again to embed the obtained 95 % confidence intervals into the established uncertain dynamic model, yielding interval estimates for the dynamic characteristics of the joint interface. The research results indicate that the uncertain factors present in microscopic joint interfaces significantly affect macroscopic dynamic characteristics. Moreover, during the process of joint uncertainty propagation, an accumulation of uncertainty is observed.</p>

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Uncertainty analysis of the dynamic properties of the binding surface

  • 期刊论文

  • 发表日期：

    2026年5月29日

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  • Litai Sun,
  • Guohao Lv,
  • Ling Li,
  • Yue Zhang

摘要

The multi-scale uncertainty propagation mechanism in bolted joint interfaces remains poorly quantified due to the stochastic nature of microscopic surface morphology. To address this critical gap, this study establishes a novel hybrid framework that integrates fractal theory with an enhanced Monte Carlo simulation approach. Three fundamental advancements are presented. First, a fractal-based uncertainty quantification method is developed, which enables a refined characterization of surface morphology parameters through experimental-statistical calibration, thereby overcoming the deterministic limitations inherent in conventional roughness metrics. Then, the Monte Carlo method is employed to characterize the uncertain tangential contact parameters, and the intervals of these parameters under different contact gaps are extracted using Matlab. Simultaneously, the 95 % confidence region method is applied to transform these parameter intervals to reduce errors arising from uncertainty propagation. Finally, the Monte Carlo method is used again to embed the obtained 95 % confidence intervals into the established uncertain dynamic model, yielding interval estimates for the dynamic characteristics of the joint interface. The research results indicate that the uncertain factors present in microscopic joint interfaces significantly affect macroscopic dynamic characteristics. Moreover, during the process of joint uncertainty propagation, an accumulation of uncertainty is observed.