A 3D Simulation of Bolted Joint and Fatigue Life Estimation Using Critical Distance Technique

• Main Authors: N. Habibi, M. Amoorezayi
• Format: Article
• Language: English
• Published: Bu-Ali Sina University 2019-09-01
• Series: Journal of Stress Analysis
• Subjects: critical distance technique; bolted joints; three-dimensional simulation; fatigue life estimation; preload; s-n curve
• Online Access: https://jrstan.basu.ac.ir/article_2990_50bfa3292aaa62aea953c079e4ec9d0e.pdf
• ISSN: 2588-2597; 2588-3054

Bolted joints are one of the most common joints in the industry and assemble the most of the machine elements and segments together. Majority of structures are affected by fluctuating forces, therefore there is the risk of fatigue failure that causes countless damages, thus fatigue life estimation of bolted joints have always been important. The value of high stress concentration at the threads root especially first engaged thread causes problems for fatigue life estimation, since by applying stresses lower than yield stress of the bolt material, plastic deformation occurs at zones of thread root that reach to ultimate stress but fracture does not happen and in some cases bolt-nut joints have infinite life, so that maximum stress at thread root is not fatigue life determinant. The modified critical distance technique and expressed stress at this distance were used for determination of fatigue life in joint. In this study, the bolted joint fatigue life prediction using critical distance technique was compared to experimental results. The three-dimensional finite element analysis for bolted joint was performed. Pre-tightening process and tensile axial force were simulated in ABAQUS software after applying two steps of force including rotation displacement to the center of the nut due to clamping joints (applied torque) and tensile force, the stress distribution resultant of different tensile forces by application of the critical distance technique and mechanical properties fatigue life were determined, and S-N curve prediction matched well with experimental data.