On the use of Machine Learning to Defeature CAD Models for Simulation
TypeArticles dans des revues avec comité de lecture
Numerical simulations play more and more important role in product development cycles and are increasingly complex, realistic and varied. CAD models must be adapted to each simulation case to ensure the quality and reliability of the results. The defeaturing is one of the key steps for preparing digital model to a simulation. It requires a great skill and a deep expertise to foresee which features have to be preserved and which features can be simplified. This expertise is often not well developed and strongly depends of the simulation context. In this paper, we propose an approach that uses machine learning techniques to identify rules driving the defeaturing step. The expertise knowledge is supposed to be embedded in a set of configurations that form the basis to develop the processes and find the rules. For this, we propose a method to define the appropriate data models used as inputs and outputs of the learning techniques.
Showing items related by title, author, creator and subject.
Prediction of CAD model defeaturing impact on heat transfer FEA results using machine learning techniques DANGLADE, Florence; VERON, Philippe; PERNOT, Jean-Philippe; FINE, Lionel (2014)Essential when adapting CAD model for finite element analysis, the defeaturing ensures the feasibility of the simulation and reduces the computation time. Processes for CAD model preparation and defeaturing tools exist but ...
DANGLADE, Florence; VERON, Philippe; PERNOT, Jean-Philippe; FINE, Lionel (2015)This paper adresses the way machine learning techniques based on neural networks can be used to predict the impact of simplification processes on CAD model for heat transfer FEA purposes.
A priori evaluation of simulation models preparation processes using artificial intelligence techniques DANGLADE, Florence; PERNOT, Jean-Philippe; VÉRON, Philippe; FINE, Lionel (Elsevier BV, 2017-10)Controlling the well-known triptych costs, quality and time during the different phases of the Product Development Process (PDP) is an everlasting challenge for the industry. Among the numerous issues that are to be ...
LOU, Ruding; PERNOT, Jean-Philippe; VERON, Philippe; GIANNINI, Franca; FALCIDIENO, Bianca; MIKCHEVITCH, Alexei; MARC, Raphael (IEEE Computer Society, 2010)Advances in modeling of discrete models have allowed the development of approaches for direct mesh modeling and modification. These tools mainly focus on modeling the visual appearance of the shape which is a key criterion ...
LI, Zongcheng; GIANNINI, Franca; FALCIDIENO, Bianca; PERNOT, Jean-Philippe; VERON, Philippe (Proceedings of the 4th IEEE Int. Conference on Cognitive Infocommunications (CogInfoCom'13), 2013)The construction of a Virtual Environments (VE) requires a long iterative modeling and modification process. Depending on the final purposes, many actors can be involved both in the early conception and in the detailed ...