Issue |
Mechanics & Industry
Volume 17, Number 5, 2016
|
|
---|---|---|
Article Number | 503 | |
Number of page(s) | 11 | |
DOI | https://doi.org/10.1051/meca/2015079 | |
Published online | 10 June 2016 |
A stochastic approach for the evaluation of the reliability of wood furniture in an industrial context: managing virtual standardization tests
1 UniversitéParis-Est, Laboratoire
Modelisation et Simulation Multi Echelle, MSME UMR 8208 CNRS,
5 bd Descartes, 77454
Marne-la-Vallée,
France
2 Institut technologique Forêt
Cellulose Bois-Construction Ameublement, FCBA, 10 avenue de Saint-Mandé, 75012
Paris,
France
a Corresponding author:
luc.chevalier@univ-paris-est.fr
Received:
9
April
2015
Accepted:
29
September
2015
In this paper, a procedure is developed in order to manage virtual tests using numerical simulation in order to reduce time and to optimize design before the real validation tests on wood products. This procedure in 3 steps can be used in an industrial context: (i) characterization of the material properties, (ii) construction of probabilistic density function for each parameter, (iii) Monte Carlo simulation of the structural behavior of the wood products furniture. For this purpose, experimental tests associated with digital image correlation technique were managed using 3 point bending tests easy to develop in an industrial environment. A probabilistic density function was constructed for each mechanical parameter based on the test results using the principle of maximum entropy. The simulation is managed by a FEA developed in the Matlab environment and allows a Monte-Carlo simulation in a reasonable CPU time. We can then evaluate the effect of the input data dispersions on the overall reaction of the structure. A real test is performed on a prototype product in order to confirm the simulation results and to validate the approach.
Key words: Virtual validation test / spruce wood furniture / anisotropic elasticity characterization / digital image correlation / finite element analysis / probabilistic approach
© AFM, EDP Sciences 2016
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