1,720,962 research outputs found
Model order reduction and parametric metamodeling of the multiphysics induction heating process
No full textLa modélisation par éléments finis (MEF) représente aujourd'hui l'outil de calcul le plus attrayant pour prédire et optimiser de nombreux problèmes industriels. Cependant, la MEF devient inefficace en ce qui concerne les problèmes complexes multiphysiques paramétrés, tels que le traitement de chauffage par induction, en raison de son coût de calcul élevé. L'objectif de cette thèse est de définir une méthodologie de réduction de modèles multiphysiques adaptée au procédé de chauffage par induction et de proposer une solution paramétrique pour quelques quantités physiques d'intérêt, notamment l'évolution temporelle de la température et du taux d'austénite sur un pignon droit en acier C45, en utilisant une approche de modélisation non intrusive basée sur les données comme alternative à la MEF pour une prédiction en temps réel. Pour ce faire, un ensemble de solutions synthétiques a été collecté, au niveau de certains capteurs dans la pièce et pour différentes valeurs de paramètres d'entrée (fréquence et puissance), en se basant sur des données de la simulation numérique obtenues via le logiciel de calcul par éléments finis FORGE®. En effet, une étude de faisabilité et de convergence a d'abord été effectuée afin de figer une configuration qui converge et qui suit les bonnes tendances. Les résultats obtenus par simulation selon un échantillonnage de type hypercube latin ont ensuite été traités. Pour le modèle de température, une réduction dimensionnelle par la méthode ''proper orthogonal decomposition" (POD) couplée avec trois méthodes de régression non linéaire (sPGD, SVR, et GB) ont été appliquées pour construire une base réduite et créer un modèle représentatif de la solution dans l'espace de faible dimension. Pour le taux d'austénite, deux métamodèles ont été développés pour différents instants qui caractérisent la transformation austénitique. Les résultats ont montré que les méthodes sPGD et SVR donnent comparativement une meilleure prédiction. Par conséquent, une prédiction en temps réel de l'évolution temporelle de la température et du taux d'austénite peut être calculée pour un nouvel ensemble des paramètres d'entrée et au niveau des capteurs considérés. Ensuite, une interpolation spatiale a été réalisée pour étendre la solution partout dans la zone affectée thermiquement. Pour la température, deux approches ont été proposées; la première est basée sur la réduction de dimensionnalité non linéaire par la méthode ''locally linear embedding" et la méthode ''POD" avec interpolation par fonction de base radiale, tandis que la deuxième est basée sur la ''gappy POD". Les deux approches génèrent de bonnes approximations malgré leurs différences. Pour le taux d'austénite, une généralisation de l'approche proposée précédemment a été effectuée en prenant en considération des paramètres géométriques. Une comparaison des trois méthodes de régression a été menée. Enfin, une étude de l'effet d'un changement dimensionnel du pignon sur l'évolution de la température a été effectuée, ceci sans passer par un nouveau plan d'expérience, mais en s'appuyant sur les résultats de la géométrie de référence. Pour ce faire, deux approches ont été proposées pour prédire l'évolution de la température dans des nouvelles géométries. La première approche est basée sur le réseau de neurone en utilisant comme paramètres d'entrée quelques incréments initiaux des courbes temporelles de la température. La deuxième approche est basée sur la ''POD" et la régression par sPGD en utilisant la puissance de chauffe comme quantité intermédiaire. Il a été montré que les résultats sont prometteurs, cependant, il est difficile d'approximer des phénomènes non-linéaires dépendant du temps à partir des données partielles extraites au début du procédé.Mots clés: Modélisation par éléments finis; Modélisation non intrusive; Chauffage par induction; Réduction de dimensionnalité; Métamodèle; Acier C45; régression non linéaires; InterpolationFinite element (FE) modeling has recently become the most attractive computational tool to predict and optimize many industrial problems. However, it becomes ineffective as far as complex multiphysics parameterized problems, such as the induction heating process, are concerned because of the high computational cost. This thesis aims at defining a multiphysics model order reduction methodology for the induction heating process and proposing a parametric-based solution for some physical quantities of interest, namely the temporal evolution of temperature and austenite phase rate within a C45 steel spur-gear, using a non-intrusive data-driven modeling approach as an alternative to the FE modeling for a real-time prediction. To achieve this goal, a set of synthetic solutions was collected, at some sparse sensors in the workpiece and for different values of input parameters (frequency and power), from numerical simulation via FORGE® software. Indeed, a convergence study was first conducted to choose the best numerical configuration that converges and follows the right trends. Next, according to the Latin hypercube sampling design of experiments (DoE), FE results were obtained and then treated. For the temperature modeling, a dimensionality reduction by the proper orthogonal decomposition (POD) method coupled with three nonlinear regression methods (sPGD, SVR, and GB) was applied to build a reduced basis and create models for the low-dimensional representation of the initial snapshots. For the austenite rate, two metamodels were developed for the time instants t_Ac1 and t_Ac3 characterizing the beginning and the complete austenitic transformation. It was shown that better predictions were obtained with the sPGD and SVR methods, comparatively. Therefore, a real-time prediction of the temperature and austenite phase evolution could be calculated for a new set of process parameters and for the considered sensors. Then, spatial interpolation was performed to extend the solution everywhere in the heat-affected zone. For the temperature field, two approaches were proposed; the first one is based on nonlinear dimensionality reduction by locally linear embedding and POD with radial basis function interpolation, while the second one is based on gappy POD. Both approaches generate good approximations despite their differences. For the austenite rate, a generalization of the previously proposed approach was carried out by taking into consideration geometrical parameters. A comparison between the results of the three regression methods was conducted. Finally, the effect of the gear geometrical change on the temperature-time evolution was analyzed, by using the results of the reference geometry considered so far and without using a new DoE. Two approaches were proposed to predict the temperature-time evolution in new geometries. The first approach is based on the artificial neural network by considering the beginning of the temperature curves, known at few time steps, as input parameters. The second approach is based on POD and sPGD regression by using the internal heat source as an intermediate quantity. The obtained results were promising, however, it remains difficult to approximate nonlinear time-dependent phenomena from partial data extracted at the beginning of the process.Keywords: Finite element modeling; Non-intrusive modeling; Induction heating; Dimensionality reduction; Metamodel; C45 steel; Nonlinear regression; Interpolatio
On the characterization of Johnson-Cook constants : numerical and experimantal study of high speed machining aerospace alloys
No full textThe aerospace industry would eventually replace chemical machining by mechanical machining which is more accurate, more predictable and more ecological. In fact, the discharges in the case of chemical machining contain especially carbon dioxide and solvents that are difficult to degrade in groundwater. The mechanical machining also avoids an important quantity of hazardous substances and provides better chips recycling. However, the control of mechanical machined parts quality goes through the prediction and the optimization of the metal cutting processes. The most attractive computational tool to predict and optimize metal cutting processes is the finite element modeling (FEM). The success and the reliability of any FEM depend strongly on the constitutive laws which describe the thermo-mechanical behavior of the machined materials. The most commonly used one is that of Johnson and Cook (JC) which combines the effect of strains, strain rates, and temperatures. The determination of the material constants of JC under high strains, strain rates, and temperatures during machining conditions has long been a major challenge but a necessity for those who apply finite element modeling techniques in machining processes at the chip formation scale.
This study aims at treating this subject in order to better understand the effect of the JC constitutive law on the prediction of cutting parameters (cutting forces, residual stresses, etc.) for aluminum alloys. In addition, in order to meet the interests of aerospace industry, three aluminum alloys (Al2024-T3, Al6061-T6 and Al7075-T6) commonly used in aircraft applications have been selected.
This research work is divided into three consecutive steps.
Firstly, a new approach to identify the material constants of JC for metal cutting is proposed. The approach is based on the inverse method (orthogonal machining tests) and the response surface methodology which allows generating a large number of cutting conditions within fixed ranges of cutting speed, feed rate, and rake angle. Based on this approach, the sensitivity of the material constants of JC to the rake angle for the three alloys was analysed. It was found that, for these three alloys, one set of the material constants obtained from the proposed approach predicts more accurate values of flow stresses as compared to those reported in the literature. Moreover, a 2D FEM investigation of the orthogonal cutting also showed a good agreement between the predicted cutting parameters (cutting forces and chip thickness) and experimental ones when using the material constants obtained by the proposed approach.
Secondly, a specific focus was put on the influence of the rake angle on the material constants of JC and hence on the predicted cutting parameters (cutting forces, chip morphology, and tool-chip contact length). To achieve this goal, different sets of JC constants obtained at different rake angles (-8°, -5°, 0°, +5°, and +8°) were used in conjunction with a 2D finite element model to simulate the machining behavior of Al2024-T3 alloy. It was found that the material constants set obtained with 0° rake angle gives overall more accurate predictions of the cutting parameters as compared to other studied sets.
Finally, the last step of this study is devoted to the prediction of induced residual stresses within the machined workpiece (Al2024-T3) and the temperature of the cutting tool(uncoated carbide). Three sets of JC based on the results obtained from the previous step with rake angles of -8°, 0°, and +8° were considered. Two finite element models were used; a 2D thermo-mechanical simulation to simulate chip formation and a 3D pure thermal analysis to obtain the temperature distribution. The results show that a better prediction of the residual stresses is obtained with JC at 0° while the other sets of JC at -8° and +8° tend to overestimate or underestimate the measured residual stresses, respectively. As far as the temperature of the cutting tool is concerned, the average values of the predicted températures of the cutting tool for each studied set of JC was considered in order to evaluate the best prediction. Based on these average values, the effect of the three sets of JC was not significant since the difference between the measured temperatures and the predicted average ones are less than 5.5% with the three cutting conditions
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Shot-peening simulations with artificial surface defect using multiple impacts and eigenstrain reconstruction method
No full textInternational audienc
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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