Dans ce travail de thèse, une amélioration aussi bien à l’échelle globale qu’à l’échelle locale a été apportée sur la compréhension des mécanismes tribologiques aux interfaces outil-pièce-copeau durant l’usinage à sec de l’acier C45 avec des outils en carbure de tungstène revêtus en TIN. Dans une première partie expérimentale, des essais de frottement ont permis d’étudier la sensibilité des paramètres de frottement sur le comportement tribologique aux interfaces pion-pièce. Ainsi, l’évolution du coefficient de frottement, du flux de chaleur et du coefficient de partage de chaleur aux interfaces outil-pièce-copeau ont été identifiés pour le couple de matériau frottant et frotté. Pour mieux comprendre ces phénomènes, une étude métallographique a été effectuée sur des échantillons. Elle a notamment permis l’obtention des transformations métallurgiques au niveau de la surface superficielle de la pièce : des affinements des grains (déformation plastique) aux basses vitesses de frottement et des couches blanches (durcissement thermique) pour les grandes vitesses. Pour avoir plus de détails, un modèle numérique simulant l’essai de frottement a été développé en se basant sur l’approche Arbitraire Lagrangienne Eulérienne (A.L.E). Ce modèle nous a permis d’avoir plus d’informations sur les grandeurs locales de frottement (pression de contact, température de contact, vitesse locale de glissement, déformation plastique). Un modèle de frottement et un modèle de coefficient de partage de chaleur ont été identifiés à travers cette étude numérique. Dans la deuxième partie expérimentale, deux types d’essais d’usure ont été effectués dans des conditions similaires sur des pions et sur des plaquettes d’outils de coupe de même nuance. Des analyses microscopiques et au MEB couplés à une analyse EDS ont été faites afin de mieux analyser les mécanismes tribologiques durant les essais d’usure. Des similitudes de faciès d’usure ont été observées à différentes échelles d’analyse, sur les pions ainsi que sur les plaquettes d’outils de coupe. Ces similitudes ont permis d’aboutir à une corrélation des phénomènes tribologiques observés sur les pions et ceux observés sur les plaquettes. / In this work, improved both global and local levels has been made on understanding the tribological mechanisms at the chip-tool-workpiece interface in dry machining of a AISI 1045 steel with a TiN coated carbide tool. In the first part, several friction tests have been performed to study the sensitivity of friction parameters on the tribological behavior at pin-workpiece interface. Thus, evolutions of the apparent friction coefficient, of heat flux and of heat flux partition ratio have been identified. To better understand these phenomena, a metallographic study was performed on the samples of the workpiece.It has enabled the achievement of metallurgical transformations in terms of surface area of the room : the refinement of grains (plastic deformation) friction at low speeds and white layers (thermal curing)for high speeds. These results show that the initial state of the steel (ferritic-pearlitic microstructure) has been changed, In fact, two phenomena have been observed. The first phenomenon has been observed for low sliding velocities. In this range of the sliding velocities, the grains have been crushed because of the large plastic deformations. The second phenomenon has been observed by increasing the friction velocity. In fact, the white zones have been identified at the surface layer and which have presented a different structure compared to the initial state of the steel. A 3D A.L.E. numerical model, simulating the friction test, enables to extract local information from the contact area, especially the contact pressure, the contact temperature and the average local sliding velocity. An adhesive friction model and a heat partition coefficient model depending on average local sliding velocity have been identified. These friction models can be utilized in a FEM of the cutting process in order to improve the understanding of the material flow and temperature distribution around cutting tools. In the second part, pin wear in the friction tests and tool wear in machining tests have been performed. To compare the phenomena observed at the tool-chip interfaces during the wear tests in machining with the phenomena observed at the pin-workpiece during the wear tests of friction, similarities of faces have been observed at different scales of analysis on the pins and on the cutting tool inserts.

Recent technological, social, and economic trends and transformations are contributing to the production of what is usually referred to as Big Data. Big Data, which is typically defined by four dimensions -- Volume, Velocity, Veracity, and Variety -- changes the methods and tactics for using, analyzing, and interpreting data, requiring new approaches for data provenance, data processing, data analysis and modeling, and knowledge representation. The use and analysis of Big Data involves several distinct stages from "data acquisition and recording" over "information extraction" and "data integration" to "data modeling and analysis" and "interpretation", each of which introduces challenges that need to be addressed. There also are cross-cutting challenges, which are common challenges that underlie many, sometimes all, of the stages of the data analysis pipeline. These relate to "heterogeneity", "uncertainty", "scale", "timeliness", "privacy" and "human interaction". Using the Big Data analysis pipeline as a guiding framework, this paper examines the challenges arising in the use of Big Data in regional science. The paper concludes with some suggestions for future activities to realize the possibilities and potential for Big Data in regional science. / Series: Working Papers in Regional Science

In this paper we view learning as an unconstrained non-linear minimization problem in which the objective function is defined by the negative log-likelihood function and the search space by the parameter space of an origin constrained product unit neural spatial interaction model. We consider Alopex based global search, as opposed to local search based upon backpropagation of gradient descents, each in combination with the bootstrapping pairs approach to solve the maximum likelihood learning problem. Interregional telecommunication traffic flow data from Austria are used as test bed for comparing the performance of the two learning procedures. The study illustrates the superiority of Alopex based global search, measured in terms of Kullback and Leibler's information criterion.

The aim of diploma thesis was preparation of hardened layer on three chosen types of materials with different alloying components content without surface melt by using electron beam technology. The influence of chosen process parameters was observed on the prepared hardened layers properties and shapes. In the first part of bibliographic search there are described electron beam properties, possibilities of his influencing and control. There is given example of complete set of electron beam are mentioned in the second part of theoretical research.