An accelerated shock fatigue life model for complex shock loads with load dispersion

IF 4.1 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Mechanics of Materials Pub Date : 2026-01-01 Epub Date: 2025-10-30 DOI:10.1016/j.mechmat.2025.105535

Yi Sun, Shuai Ma, Yongbin Dang, Zhiqiang Yang

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Abstract

This paper presents an accelerated shock fatigue life model based on load dispersion, which utilizes the experimental life data under high-magnitude loads to assess whether the structure meets the fatigue life design requirements under its original load conditions, thereby improving the experimental efficiency. Firstly, a shock fatigue life database is established by combining experiments with finite element analysis. Then, the shock load dispersion effect is quantified by data fitting, and the relationship between the shock response spectrum parameters and the Weibull parameters is obtained. Finally, a new accelerated shock fatigue life model is established by introducing a relative dispersion factor based on the inverse power law model. Taking BGA solder joints as an example, the shock fatigue damage equivalent boundary of BGA solder joints is calculated. The results show that the error between the predicted boundary and the actual boundary is in the range of −5 %–7 %, verifying the effectiveness of the model.

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考虑载荷分散的复杂冲击载荷的加速冲击疲劳寿命模型

本文提出了一种基于载荷分散的加速冲击疲劳寿命模型，利用高量级载荷下的实验寿命数据来评估结构在其原始载荷条件下是否满足疲劳寿命设计要求，从而提高了实验效率。首先，将实验与有限元分析相结合，建立了冲击疲劳寿命数据库；然后，通过数据拟合量化冲击载荷弥散效应，得到冲击响应谱参数与威布尔参数之间的关系。最后，在逆幂律模型的基础上引入相对弥散因子，建立了新的加速冲击疲劳寿命模型。以BGA焊点为例，计算了BGA焊点的冲击疲劳损伤等效边界。结果表明，预测边界与实际边界的误差在−5% ~ 7%之间，验证了模型的有效性。

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来源期刊

Mechanics of Materials 工程技术-材料科学：综合

CiteScore

7.60

自引率

5.10%

发文量

243

审稿时长

46 days

期刊介绍： Mechanics of Materials is a forum for original scientific research on the flow, fracture, and general constitutive behavior of geophysical, geotechnical and technological materials, with balanced coverage of advanced technological and natural materials, with balanced coverage of theoretical, experimental, and field investigations. Of special concern are macroscopic predictions based on microscopic models, identification of microscopic structures from limited overall macroscopic data, experimental and field results that lead to fundamental understanding of the behavior of materials, and coordinated experimental and analytical investigations that culminate in theories with predictive quality.