ParisTech

About: ParisTech is a education organization based out in Paris, France. It is known for research contribution in the topics: Finite element method & Residual stress. The organization has 1888 authors who have published 1965 publications receiving 55532 citations. The organization is also known as: Paris Institute of Technology & ParisTech Développement.

Influence of nanostructured CVD diamond coatings on dust emission and machinability of SiC particle-reinforced metal matrix composite

Abstract: This paper reports on experimental test program to study the effect of the coating structure associated with the machining of metal matrix composite (MMC). The composite materials investigated were respectively a 5%, 15% and 25% by volume SiC particle-reinforced A2009 aluminum alloy. The machining of these materials is indeed very difficult due to the abrasive effect of reinforcement upon the cutting tool. In this work, the ability of coated tools with nanostructured CVD diamond coatings to cut MMC components is discussed during dry machining. The performances of three different structures of CVD diamond coating are then considered using classical parameters (cutting forces, tool life, residual stress) and innovative criterion such as dust emission. The results show that in spite of their similar thickness, the coatings have various performances. The tool life was varied in a ratio of 1 to 6 irrespectively to the cumulative wear evolution which was monitored in situ with a power measurement and quantified ex situ using a white light interferometer.

Stochastic Block Models for Multiplex networks: an application to networks of researchers

Abstract: Modeling relations between individuals is a classical question in social sciences and clustering individuals according to the observed patterns of interactions allows to uncover a latent structure in the data. Stochastic block model (SBM) is a popular approach for grouping the individuals with respect to their social comportment. When several relationships of various types can occur jointly between the individuals, the data are represented by multiplex networks where more than one edge can exist between the nodes. In this paper, we extend the SBM to multiplex networks in order to obtain a clustering based on more than one kind of relationship. We propose to estimate the parameters --such as the marginal probabilities of assignment to groups (blocks) and the matrix of probabilities of connections between groups-- through a variational Expectation-Maximization procedure. Consistency of the estimates as well as statistical properties of the model are obtained. The number of groups is chosen thanks to the Integrated Completed Likelihood criteria, a penalized likelihood criterion. Multiplex Stochastic Block Model arises in many situations but our applied example is motivated by a network of French cancer researchers. The two possible links (edges) between researchers are a direct connection or a connection through their labs. Our results show strong interactions between these two kinds of connections and the groups that are obtained are discussed to emphasize the common features of researchers grouped together.

Risk analysis of maintenance activities in a LPG supply chain with a Multi-Agent approach

Abstract: This paper aims to present a new systemic modelling approach using the unified modelling language (UML) and Multi-Agents Systems (MAS) to model the complexity and analyze the risks of maintenance activities within a Liquefied Petroleum Gas (LPG) supply chain. This approach is a two steps corresponding to Modelling & Simulation and Risk Analysis. Based on a multi-agent simulator, the objective is to consider the complexity of maintenance tasks of supply chain equipment to better understand risks and to identify abnormal and accident prone situations. The case study is LPG supply chain located in France. AnyLogic simulator is used to assess safety of this supply chain. Through simulation, this proposed approach provides a whole view to ease understanding of maintenance activities within LPG supply chain and to lead to effective analysis of its safety. The final goal is orienting maintenance actors to the best risk minimizing decisions.