Author(s):
Ferreira, Vânio
; Santos, Luís Paulo
; Franzen, Markus
; O. Ghouati, Omar
; Simões, Ricardo
Date: 2011
Persistent ID: http://hdl.handle.net/11110/429
Origin: CiencIPCA
Subject(s): Automotive crash simulations; structural modelling; FEM mesh; thickness estimation; ray tracing
Description
Within the development of motor vehicles, crash
safety (e.g. occupant protection, pedestrian protection, low speed
damageability), is one of the most important attributes. In order
to be able to fulfill the increased requirements in the framework
of shorter cycle times and rising pressure to reduce costs, car
manufacturers keep intensifying the use of virtual development
tools such as those in the domain of Computer Aided Engineering
(CAE). For crash simulations, the explicit finite element method
(FEM) is applied. The accuracy of the simulation process is highly
dependent on the accuracy of the simulation model, including the
midplane mesh. One of the roughest approximations typically
made is the actual part thickness which, in reality, can vary
locally. However, almost always a constant thickness value is
defined throughout the entire part due to complexity reasons.
On the other hand, for precise fracture analysis within FEM,
the correct thickness consideration is one key enabler.
Thus, availability of per element thickness information, which
does not exist explicitly in the FEM model, can significantly
contribute to an improved crash simulation quality, especially
regarding fracture prediction. Even though the thickness is not
explicitly available from the FEM model, it can be inferred from
the original CAD geometric model through geometric calculations.
This paper proposes and compares two thickness estimation
algorithms based on ray tracing and nearest neighbour 3D range
searches. A systematic quantitative analysis of the accuracy of
both algorithms is presented, as well as a thorough identification
of particular geometric arrangements under which their accuracy
can be compared. These results enable the identification of each
technique’s weaknesses and hint towards a new, integrated,
approach to the problem that linearly combines the estimates
produced by each algorithm. We acknowledge the Foundation for Science and Technology,
Lisbon, Portugal, through the 3o Quadro Comunit´ario de
Apoio and also the POCTI and FEDER programs.