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Is Bolt Loosening Based on Advanced Pretension Functionality Predictable?



Abstract


In mechanical engineering, bolts are frequently used as standard fastening elements, which have to fulfil important mechanical functions like strength and safety. In Finite Element (FE) analysis, there exist a great number of possibilities to model bolts dependent on their importance for the desired analysis and on the focus on global or local structural behavior. When it comes to local stress and strength, there is a clear trend to apply solid models for the bolts, where all parameters are like the real bolt including pretension but the thread is not detailed. Fasteners can be mission critical, i.e. if bolts lose pretension during operation, the structure will fail. In many cases it is not necessary to make an absolute statement as to whether the screw will loosen or not. It is sufficient to state whether the tendency to loosen screws is increasing or decreasing. With this knowledge, the assembly can be improved through simulation. It was assumed that a detailed modeling of the thread is necessary in order to obtain this knowledge. But the more details are increasing the computation time drastically, which makes this approach not usable for multi body designs. So, simplified bolt models with advanced pretension functionality are needed, which gives reliable indication for bolt loosening. This leads to the main question: Is an advanced pretension functionality for model without thread sufficient to evaluate the tendency of loosening? An advanced contact with thread system on cylindrical model is shown. The accuracy of the contact directions and the contact forces in the thread area is significantly increased through the use of screw parameters and thread coordinate system. At the same time, the modeling effort and the computing time are kept low. The screw connection of a rim is shown as an example. Different rim geometries are compared to check the predictability of the new approach.

Document Details

ReferenceNWC21-167-c
AuthorKlein. M
LanguageEnglish
TypePresentation Recording
Date 26th October 2021
OrganisationINTES
RegionGlobal

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