2012
Autores
Chalmers, A; Mudge, M; Santos, LP;
Publicação
COMPUTERS & GRAPHICS-UK
Abstract
2011
Autores
Chalmers, A; Mudge, M; Santos, LP;
Publicação
COMPUTERS & GRAPHICS-UK
Abstract
2010
Autores
Debattista, K; Proenca, AJ; Santos, LP;
Publicação
COMPUTERS & GRAPHICS-UK
Abstract
2008
Autores
Santos, LP; Reiners, D; Favre, J;
Publicação
COMPUTERS & GRAPHICS-UK
Abstract
2010
Autores
Ferreira, V; Santos, LP; Simoes, R; Franzen, M; Ghouati, OO;
Publicação
International Conference on Mathematical and Computational Methods in Science and Engineering - Proceedings
Abstract
Within the development of motor vehicles, crash safety is one of the most important attributes. To comply with the ever increasing requirements of shorter cycle times and costs reduction, car manufacturers keep intensifying the use of virtual development tools, such as, for crash simulations, the explicit finite element method (FEM). The accuracy of the simulation process is highly dependent on the accuracy of the model, including the midplane mesh. One of the roughest approximations typically made is the actual part thickness which, although most frequently modelled as a constant value, can, in reality, vary locally. Availability of per element thickness information, which does not exist explicitly in the FEM model, is one key enabler and can significantly contribute to an improved crash simulation quality, especially regarding fracture prediction. Although not explicitly available, thickness 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.
2011
Autores
Ferreira, V; Santos, LP; Franzen, M; Ghouati, OO; Simoes, R;
Publicação
International Journal of Mathematics and Computers in Simulation
Abstract
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. hus, 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 an 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.
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