Integrated CAE Methods for Perceived Quality Assurance of Vehicle Outer Panels

Paper #:
  • 2014-01-0366

Published:
  • 2014-04-01
DOI:
  • 10.4271/2014-01-0366
Citation:
Jang, J., "Integrated CAE Methods for Perceived Quality Assurance of Vehicle Outer Panels," SAE Technical Paper 2014-01-0366, 2014, doi:10.4271/2014-01-0366.
Author(s):
Affiliated:
Pages:
9
Abstract:
Oil canning and initial stiffness of the automotive roofs and panels are considered to be sensitive customer ‘perceived quality’ issues. In an effort to develop more accurate objective requirements, respective simulation methods are continuously being developed throughout automotive industries. This paper discusses a latest development on oil canning predictions using LS-DYNA® Implicit, including BNDOUT request, MORTAR contact option and with the stamping process involved, which resulted in excellent correlations especially when it comes to measurements at immediate locations to the feature lines of the vehicle outer panels.Furthermore, in pursuit of light-weighting vehicles with thinner roofs, a new CAE method was recently developed to simulate severe noise conditions exhibited on some of developmental properties while going through a car wash. This paper introduces such a method to discuss Fluid Structure Interaction (FSI) approach using an Arbitrary Lagrangian Eulerian (ALE) formulation in LS-DYNA® for vehicle roof car wash boom noise prediction. This CAE method was developed to simulate force behavior from airflow as the car wash air blowers are expelling high speed air at the vehicle roofs during car wash. LS-DYNA® was proven an appropriate tool to precisely simulate popping noises by creating instantaneous local instabilities - recoverable/non-recoverable - and continuous fluttering of the roof.This paper additionally briefs the history of oil canning CAE method developments from inaccurate hand push evaluation to approaches using MSC Nastran® to Abaqus/Standard®, and then the final evolution to LS-DYNA® Implicit to provide optimized vehicle solutions.
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