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Antibes, France

Iorio L.,Polytechnic of Milan | Fourment L.,MINES ParisTech | Marie S.,Transvalor | Strano M.,Polytechnic of Milan
Key Engineering Materials | Year: 2015

The Game Theory is a good method for finding a compromise between two players in a bargaining problem. The Kalai and Smorodinsky (K-S) method is a solution the bargaining problem where players make decisions in order to maximize their own utility, with a cooperative approach. Interesting applications of the K-S method can be found in engineering multi-objective optimization problems, where two or more functions must be minimized. The aim of this paper is to develop an optimization algorithm aimed at rapidly finding the Kalai and Smorodinsky solution, where the objective functions are considered as players in a bargaining problem, avoiding the search for the Pareto front. The approach uses geometrical consideration in the space of the objective functions, starting from the knowledge of the so-called Utopia and Nadir points. An analytical solution is proposed and initially tested with a simple minimization problem based on a known mathematical function. Then, the algorithm is tested (thanks to a user friendly routine built-in the finite element code Forge®) for FEM optimization problem of a wire drawing operation, with the objective of minimizing the pulling force and the material damage. The results of the simulations are compared to previous works done with others methodologies. © (2015) Trans Tech Publications, Switzerland.


Material processing simulation originally started with the prediction of defects created by the forming stages as the main focus. More recently and driven by the quest for vehicle mass reduction we are seeing an emerging interest for enlarging the scope of simulation to "components in-use properties" predictions. This new scope requires a shift from a stage limited simulation focus to one that encapsulate the whole manufacturing process inclusive, of course, of heat treatment. In the first part of this paper we will demonstrate how Simulation can now predict and validate the whole manufacturing process using as an example a bevel gear forging from the initial phases through carburization, quenching and tempering. This idea that the whole process should be used to increase results quality may also be applied in other cases. Typically, when people are interested in tooling life (die,...), a standard approach is to do a stress analysis of the forming stage and eventually compute some abrasive wear but a closer look will show that the accumulation of the blows may have to be taken into account. In case of hot or warm forging, the tooling properties will heavily depend on local die temperature which cannot be obtained only from one simple forming stage simulation. © 2014 The Authors. Published by Elsevier Ltd.


Chen N.,MINES ParisTech | Chen N.,Beihang University | Thonnerieux M.,CETIM SAINT ETIENNE | Ducloux R.,Transvalor | And 2 more authors.
International Journal of Material Forming | Year: 2014

As one of the most reliable fasteners, solid riveted joints are widely utilized in many industrial areas. In the present work, the authors recalled some results on the riveting process and the strength of one kind of riveted joints obtained by simulation and experimental investigations in a previous paper. The numerical results were in very good agreement with the experimental results, allowing us to validate our simulation approach and its use for further studies. We selected several engineering parameters for the riveted joint: initial assembly, friction coefficient, rivet's geometry and sheets' geometry, in order to carry out a parametric study and determine their relative importance. These were conducted in FEA software. The results showed the impact on riveting process and the strength of the riveted joint by varying each parameter which was interesting for the industry. © 2012 Springer-Verlag France.


Thomas C.,Transvalor | Corpetti T.,RSIU Group | Memin E.,French Institute for Research in Computer Science and Automation
IEEE Transactions on Geoscience and Remote Sensing | Year: 2010

This paper focuses on the tracking and analysis of convective cloud systems from Meteosat Second Generation images. The highly deformable nature of convective clouds, the complexity of the physical processes involved, and also the partially hidden measurements available from image data make difficult the direct use of conventional image-analysis techniques for tasks of detection, tracking, and characterization. In this paper, we face these issues using variational-data-assimilation tools. Such techniques enable us to perform the estimation of an unknown state function according to a given dynamical model and to noisy and incomplete measurements. The system state we are setting in this study for the cloud representation is composed of two nested curves corresponding to the exterior frontiers of the clouds and to the interior coldest parts (core) of the convective clouds. Since no reliable simple dynamical model exists for such phenomena at the image grid scale, the dynamics on which we are relying has been directly defined from image-based motion measurements and takes into account an uncertainty modeling of the curve dynamics along time. In addition to this assimilation technique, we show in the Appendix how each cell of the recovered cloud system can be labeled and associated to characteristic parameters (birth or death time, mean temperature, velocity, growth, etc.) of great interest for meteorologists. © 2006 IEEE.


Ducloux R.,Transvalor | Fourment L.,MINES ParisTech | Marie S.,Transvalor | Monnereau D.,Bollhoff Ottalu
International Journal of Material Forming | Year: 2010

The use of material processing numerical simulation has spread widely in recent years in the engineering industry. It allows a strategy of trial and error to improve virtual processes without incurring material costs or interrupting production and therefore save a lot of money. On the other hand, it requires user time to analyze the results, adjust the operating conditions and restart the simulation. Automatic optimization seems the perfect complement to simulation. Evolutionary Algorithm coupled with metamodelling makes it possible to obtain industrially relevant results on a very large range of applications within a few tens of simulations and without any specific automatic optimization technique knowledge. In the frame of the LOGIC ANR French project, ten industrial partners have been selected to cover the different area of the mechanical forging industry and provide different examples of the forming simulation tools. An optimization module, fully embedded within the Forge2009 IHM, makes possible to cover all the defined examples, and the use of new multicore hardware to compute several simulations at the same time reduces the needed time dramatically. The presented examples demonstrate the method versatility. They include billet shape optimization of a common rail and the cogging of a bar. © 2010 Springer-Verlag France.

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