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During thermal laser processes, heat transfer and fluid flow in the melt pool are primary driven by complex physical phenomena that take place at liquid/vapor interface. Hence, the choice and setting of front description methods must be done carefully. Therefore, the purpose of this paper is to investigate to what extent front description methods may bias physical representativeness of numerical models of laser powder bed fusion (LPBF) process at melt pool scale.

Two multiphysical LPBF models are confronted: a Level-Set (LS) front capturing model based on a C++ code and a front tracking model, developed with COMSOL Multiphysics® and based on Arbitrary Lagrangian–Eulerian (ALE) method. To do so, two minimal test cases of increasing complexity are defined. They are simplified to the largest degree, but they integrate multiphysics phenomena that are still relevant to LPBF process.

LS and ALE methods provide very similar descriptions of thermo-hydrodynamic phenomena that occur during LPBF, providing LS interface thickness is correctly calibrated and laser heat source is implemented with a modified continuum surface force formulation. With these calibrations, thermal predictions are identical. However, the velocity field in the LS model is systematically underestimated compared to the ALE approach, but the consequences on the predicted melt pool dimensions are minor.

This study fulfils the need for comprehensive methodology bases for modeling and calibrating multiphysical models of LPBF at melt pool scale. This paper also provides with reference data that may be used by any researcher willing to verify their own numerical method.

The present paper addresses the computer modelling of pipe formation in metal castings.

As a preliminary, a brief review of the current state‐of‐the‐art in pipe shrinkage computation is presented. Then, in first part, the constitutive equations that have to be considered in thermomechanical computations are presented, followed by the main lines of the mechanical finite element resolution. A detailed presentation of an original arbitrary Lagrangian‐Eulerian (ALE) formulation is given, explaining the connection between the Lagrangian and the quasi Eulerian zones, and the treatment of free surfaces.

Whereas most existing methods are based on thermal considerations only, it is demonstrated in the current paper that this typical evolution of the free surface, originated by shrinkage at solidification front and compensating feeding liquid flow, can be effectively approached by a thermomechanical finite element analysis.

Future work should deal with the following points: identification of thermo‐physical and rheological data, automatic and adaptive mesh refinement, calculation of the coupled deformation of mold components, development of a two‐phase solid/liquid formulation.

An example of industrial application is given. The proposed method has been implemented in the commercial software THERCAST^® dedicated to casting simulation.

The proposed numerical methods provide a comprehensive approach, capable of modelling concurrently all the main phenomena participating in pipe formation.

The purpose of this paper is to present original methods related to the modeling of material deposit and associated heat sources for finite element simulation of gas metal arc welding (GMAW).

The filler deposition results from high-frequency impingements of melted droplets. The present modeling approach consists of a time-averaged source term in the mass equation for selected finite elements in the fusion zone. The associated expansion of the mesh is controlled by means of adaptive remeshing. The heat input includes a volume source corresponding to the droplets energy, for which a model from the literature is expressed in coherency with mass supply. Finally, an inverse technique has been developed to identify different model parameters. The objective function includes the differences between calculations and experiments in terms of temperature, but also shape of the fusion zone.

The proposed approach for the modeling of metal deposition results in a direct calculation of the formation of the weld bead, without any a priori definition of its shape. Application is shown on GMAW of steel 316LN, for which parameters of the model have been identified by the inverse method. They are in agreement with literature and simulation results are found quite close to experimental measurements.

The proposed algorithm for material deposit offers an alternative to the element activation techniques that are commonly used to simulate the deposition of filler metal. The proposed inverse method for parameter identification is original in that it encompasses an efficient and convenient technique to take into account the shape of the fusion zone.

The paper seeks to present an original method for the numerical treatment of thermal shocks in non‐linear heat transfer finite element analysis.

The 3D finite element thermal analysis using linear standard tetrahedral elements may be affected by spurious local extrema in the regions affected by thermal shocks, in such a severe ways to directly discourage the use of these elements. This is especially true in the case of solidification problems, in which melted alloys at very high temperature contact low diffusive mould materials. The present work proposes a slight modification to the discrete heat equation in order to obtain a system matrix in M‐matrix form, which ensures an oscillation‐free solution.

The proposed “diffusion‐split” method consists basically of using a modified conductivity matrix. It allows for solutions based on linear tetrahedral elements. The performance of the method is evaluated by means of a test case with analytical solution, as well as an industrial application, for which a well‐behaved numerical solution is available.

The proposed method should be helpful for computational engineers and software developers in the field of heat transfer analysis. It can be implemented in most existing finite element codes with minimal effort.

The year 1848 is considered by historians as a political and economic turning point in France: a major political crisis took place in the form of the February Revolution, accompanied by extensive financial troubles for the French government. The economists of that time actively debated the economic causes and consequences of the crisis. This chapter is devoted to the analysis of these financial controversies in French economic thought around 1848. If the political and philosophical debates of 1848 between the liberals and the socialists are quite well known by historians of economic thought, their financial side has been relatively neglected. According to the authors of this chapter, it is nevertheless of great interest to examine the liberal and socialist ideas of that time. This chapter aims to investigate this little-studied question by raising three main issues: the first one consists of presenting the different diagnoses of the 1848 financial crisis from socialist and liberal viewpoints. Second, it proposes an analysis of the content of theoretical controversies about ways to overcome the financial troubles, particularly regarding the trade-off between taxation and debt. Lastly, it emphasizes the role of this period for the subsequent constitution of a financial orthodoxy in France.

This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming, powder metallurgy and composite material processing are briefly discussed. The range of applications of finite elements on these subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE researchers/users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for 1994‐1996, where 1,370 references are listed. This bibliography is an updating of the paper written by Brannberg and Mackerle which has been published in Engineering Computations, Vol. 11 No. 5, 1994, pp. 413‐55.

This study aims to propose novel edge device-tailored federated learning algorithms of local classifiers (stochastic gradient descent, support vector machines), namely, FL-lSGD and FL-lSVM. These algorithms are designed to address the challenge of large-scale ImageNet classification.

The authors’ FL-lSGD and FL-lSVM trains in a parallel and incremental manner to build an ensemble local classifier on Raspberry Pis without requiring data exchange. The algorithms load small data blocks of the local training subset stored on the Raspberry Pi sequentially to train the local classifiers. The data block is split into k partitions using the k-means algorithm, and models are trained in parallel on each data partition to enable local data classification.

Empirical test results on the ImageNet data set show that the authors’ FL-lSGD and FL-lSVM algorithms with 4 Raspberry Pis (Quad core Cortex-A72, ARM v8, 64-bit SoC @ 1.5GHz, 4GB RAM) are faster than the state-of-the-art LIBLINEAR algorithm run on a PC (Intel(R) Core i7-4790 CPU, 3.6 GHz, 4 cores, 32GB RAM).

Efficiently addressing the challenge of large-scale ImageNet classification, the authors’ novel federated learning algorithms of local classifiers have been tailored to work on the Raspberry Pi. These algorithms can handle 1,281,167 images and 1,000 classes effectively.

People with pre-existing mental health conditions are more likely to be affected by global crises. The Covid-19 pandemic has presented them with unique challenges, including reduced contact with the psychiatric rehabilitation and support systems. Thus, understanding the emotional experience of this population may assist mental health organizations in future global crises.

In this paper, researchers analyzed the discourse of the mentally ill during the Covid-19 pandemic, as reflected in Israeli Facebook groups: three private groups and one public group. Researchers explored the language, reactions, emotions and sentiments used in these groups during the year before the pandemic, outbreak periods and remission periods, as well as the period before the vaccine’s introduction and after its appearance.

Analyzing groups’ discourse using the collective emotion theory suggests that the group that expressed the most significant difficulty was the Depression group, while individuals who suffer from social phobia/anxiety and PTSD were less affected during the lockdowns and restrictions forced by the outbreak.

Findings may serve as a tool for service providers during crises to monitor patients’ conditions, and assist individuals who need support and help.

This aim of this study is to identify the ways of helping public authorities bring about change to environmentally sustainable household food practices.

The authors identified the practices involved in this concept from the consumer perspective and measured their diffusion among French households. The analyses were conducted following two successive data collection campaigns comprising 571 and 501 respondents in France. The methodology involved two complementary scaling techniques: factor analysis and item response theory.

The results show that consumers understand sustainable food through five food practices: buying and cooking products with sustainable attributes, anti-waste storage, self-production, plant protein consumption and anti-waste cooking.

The findings suggest that while at the individual level people appear to have incorporated anti-waste practices into their daily lives, at the household level, there is still work to be done for improving diets and stimulating the production of home-grown food. It is also worth noting that the emerging vision typically involves sustainable foods that are organic, locally grown, seasonal, based on fair trade and packaging-free.