Modeling of Rivets Using a Cohesive Approach for Crash Simulation of Vehicles in RADIOSS

Event
WCX™ 17: SAE World Congress Experience
Authors Abstract
Content
Rivets, especially self-piercing rivets (SPR), are a primary joining technology used in aluminum bodied vehicles. SPR are mechanical joining elements used to connect sheets to create a body in white (BiW) structure. To ensure the structural performance of a vehicle in crash load cases it is necessary to describe physical occurring failure modes under overloading conditions in simulations. One failure mode which needs to be predicted precisely by a crash simulation is joint separation. Within crash simulations a detailed analysis of a SPR joint would require a very high computational effort. The conflict between a detailed SPR joint and a macroscopic vehicle model needs to be solved by developing an approach that can handle an accurate macroscopic prediction of SPR behavior with a defined strength level with less computational effort. One approach is using a cohesive material model for a SPR connection. The paper describes cohesive element characteristics and calibration effort. Investigated element characteristics are an updated momentum calculation resulting from shear loads. It allows the adjustment of the width-height ratio for a constant meshing approach; handling of lateral distortion of cohesive elements based on sheet deformation or failure of sheet elements and an elemental stabilization if the cohesive element becomes unconnected that comes along with advanced material models and deletion of sheet elements. The updated element characteristics are shown on principle models and the calibration is shown based on coupon level samples. Outlook is given on a vehicle level and application for other joining technologies.
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DOI
https://doi.org/10.4271/2017-01-1472
Pages
9
Citation
Pasligh, N., Schilling, R., and Bulla, M., "Modeling of Rivets Using a Cohesive Approach for Crash Simulation of Vehicles in RADIOSS," SAE Int. J. Trans. Safety 5(2):208-216, 2017, https://doi.org/10.4271/2017-01-1472.
Additional Details
Publisher
Published
Mar 28, 2017
Product Code
2017-01-1472
Content Type
Journal Article
Language
English