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A two‐dimensional, macroscopic, stationary, finite element model is presented for both laser remelting and laser cladding of material surfaces. It considers, in addition to the heat transfer, the important fluid motion in the melt pool and the deformation of the liquid—gas interface. The velocity field in the melt is driven by thermocapillary forces for laser remelting, but also by forces due to powder injection for laser cladding. For a given velocity field within the liquid region, the stationary enthalpy (or Stefan) equation is solved. An efficient scheme allows the LU decomposition of the finite element matrix to be performed only once at the first iteration. Then, the velocity is updated using the Q₁—P₀ element with penalty methods for treating both the incompressibility condition and the slip boundary conditions. Numerical results for three different processing speeds for both laser remelting and laser cladding demonstrate the efficiency and robustness of the numerical approach. The influence of the thermocapillary and powder injection forces on the fluid motion and subsequently on the melt pool shape is seen to be important. This kind of calculations is thus necessary in order to predict with precision the temperature gradients across the solidification interface, which are essential data for microstructure calculations.

The purpose of this paper is to review the state of the art of laser powder deposition (LPD), a solid freeform fabrication technique capable of fabricating fully dense functional items from a wide range of common engineering materials, such as aluminum alloys, steels, titanium alloys, nickel superalloys and refractory materials.

The main R&D efforts and the major issues related to LPD are revisited.

During recent years, a worldwide series of R&D efforts have been undertaken to develop and explore the capabilities of LPD and to tap into the possible cost and time savings and many potential applications that this technology offers.

These R&D efforts have produced a wealth of knowledge, the main points of which are highlighted herein.

Direct energy deposition (DED) is an additive manufacturing process that allows to produce metal parts with complex shapes. DED process depends on several parameters, including laser power, deposition rate and powder feeding rate. It is important to control the manufacturing process to study the influence of the operating parameters on the final characteristics of these parts and to optimize them. Computational modeling helps engineers to address these challenges. This paper aims to establish a framework for the development, verification and application of meshless methods and surrogate models to the DED process.

Finite pointset method (FPM) is used to solve conservation equations involved in the DED process. A surrogate model is then established for the DED process using design of experiments with powder feeding rate, laser power and scanning speed as input parameters. The surrogate model is constructed using neutral networks (NN) approximations for the prediction of maximum temperature, clad angle and dilution.

The simulations of thin wall built of Ti-6Al-4V titanium alloy clearly demonstrated that FPM simulation is successful in predicting temperature distribution for different process conditions and compare favorably with experimental results from the literature. A methodology has been developed for obtaining a surrogate model for DED process.

This methodology shows how to achieve realistic simulations of DED process and how to construct a surrogate model for further use in optimization loop.

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 and powder metallurgy are briefly discussed. The range of applications of finite elements on the subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE 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 the last five years, and more than 1100 references are listed.

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 purpose of this paper is to provide a flexible tool to predict the particle temperature distribution for traditional laser applications and for the most recent diode laser processes. In the past few years, surface processing and rapid prototyping applications have frequently implemented the use of powder delivery nozzles and high power fibre‐coupled diode lasers with highly convergent laser beams. Owing to the complexity and variety of the process parameters involved in this technology, mathematical models are necessary to understand and predict the deposition behaviour. Modeling the dynamics of the melting pool and the particle temperature distribution is critical for achieving a good deposition quality.

This study focuses on the development of mathematical models to predict the particle temperature distribution over the melting pool. An analytical and a numerical solution are proposed for two cases of laser intensity distribution: top hat and Gaussian.

The results show that a more vertical position of powder delivery nozzle will lead to a higher and more uniform particle temperature distribution, in particular for the top‐hat intensity distribution case.

Previous work has dealt only with Gaussian laser spatial distributions and collimated laser beams. Therefore, they were limited to a specific class of laser processes. This work provides a flexible tool to predict the particle temperature distribution for traditional laser applications (powder delivery nozzle and Gaussian laser profile) and for the most recent diode laser processes (powder delivery nozzle and top‐hat laser distribution with highly convergent laser beam). In addition, the results demonstrate that the particle temperature does not monotonically increase while increasing the nozzle inclination as in the case of a collimated laser beam, but some particles show a minimum temperature for intermediate values of the nozzle inclination angle.

Particle velocity is a critical factor that can affect the deposition quality in manufacturing processes involving the use of a laser source and a powder‐particle delivery nozzle. The purpose of this paper is to propose a method to detect the speed and trajectory of particles during a laser deposition process.

A low‐power laser light sheet technique is used to illuminate particles emerging from a custom designed powder delivery nozzle. Light scattered by the particles is detected by a high‐speed camera. Image processing on the acquired images was performed using both edge detection and Hough transform algorithms.

The experimental data were analyzed and used to estimate particle velocity, trajectory and the velocity profile at the nozzle exit. The results have demonstrated that the particle trajectory remains linear between the nozzle exit and the deposition plate and that the particle velocity can be considered a constant.

The use of low‐power laser light sheet illumination facilitates the detection of isolated particle streaks even in high‐powder flow rate condition. Identification of particle streaks in three subsequent images ensures that particle velocity vectors are in the plane of illumination, and also offers the potential to evaluate in a single measurement both velocity and particle size based on the observed scattered characteristics. The method provides a useful simple tool to investigate particle dynamics in a rapid prototyping application as well as other research fields involving the use of powder delivery nozzles.

The purpose of this paper is to develop, apply and validate a mesh-free graph theory–based approach for rapid thermal modeling of the directed energy deposition (DED) additive manufacturing (AM) process.

In this study, the authors develop a novel mesh-free graph theory–based approach to predict the thermal history of the DED process. Subsequently, the authors validated the graph theory predicted temperature trends using experimental temperature data for DED of titanium alloy parts (Ti-6Al-4V). Temperature trends were tracked by embedding thermocouples in the substrate. The DED process was simulated using the graph theory approach, and the thermal history predictions were validated based on the data from the thermocouples.

The temperature trends predicted by the graph theory approach have mean absolute percentage error of approximately 11% and root mean square error of 23°C when compared to the experimental data. Moreover, the graph theory simulation was obtained within 4 min using desktop computing resources, which is less than the build time of 25 min. By comparison, a finite element–based model required 136 min to converge to similar level of error.

This study uses data from fixed thermocouples when printing thin-wall DED parts. In the future, the authors will incorporate infrared thermal camera data from large parts.

The DED process is particularly valuable for near-net shape manufacturing, repair and remanufacturing applications. However, DED parts are often afflicted with flaws, such as cracking and distortion. In DED, flaw formation is largely governed by the intensity and spatial distribution of heat in the part during the process, often referred to as the thermal history. Accordingly, fast and accurate thermal models to predict the thermal history are necessary to understand and preclude flaw formation.

This paper presents a new mesh-free computational thermal modeling approach based on graph theory (network science) and applies it to DED. The approach eschews the tedious and computationally demanding meshing aspect of finite element modeling and allows rapid simulation of the thermal history in additive manufacturing. Although the graph theory has been applied to thermal modeling of laser powder bed fusion (LPBF), there are distinct phenomenological differences between DED and LPBF that necessitate substantial modifications to the graph theory approach.

A novel ternary flocculant was prepared by a simple compounding method to achieve efficient and rapid mud-water separation. This paper aims to discuss the possible mud-water separation mechanism.

This experimental study aims to investigate the effects of different types of flocculants on the separation of waste mud water and the degradation of flocculants in the supernatant. The flocculating component, the ratio of the flocculating accelerator to the flocculant and the addition amount of the novel ternary flocculant were optimized.

The experimental results show that the composition of the new ternary flocculant is cationic polyacrylamide (CP-02), grafted starch (GS-501) and flocculation sedimentation accelerator, the best effect, the mass ratio is 1:0.5: 0.75. According to 0.25:1 (volume ratio), the new ternary flocculant is pre-configured into a solution with a concentration of 3 kg/m³ to achieve efficient and rapid mud-water separation.

The new ternary flocculant is used for the separation of mud and water in the underground continuous wall waste mud, improving the level of civilized construction.

This paper aims to develope the electromagnetic interference shielding materials with high performance. To develop advanced polymer-based electromagnetic interference shielding materials with rather high temperature stability, good processability and moderate mechanical properties, the authors chose the polyimide (PI) foam as matrix and ferriferrous oxide (Fe₃O₄) as fillers to prepare the composite foams with lightweight and rather good electromagnetic interference shielding performance.

Some polyimide nanocomposite foams with Fe₃O₄ as fillers have been prepared by in situ dispersion and foaming with pyromellitic dianhydride (PMDA) and isocyanate (PAPI) as raw materials and water as foaming agent. By varying the Fe₃O₄ contents, a series of PI/Fe₃O₄ nanocomposite foams with fine microstructures and high thermal stability were obtained. The structure and performances of nanocomposite foams were examined, and the effects of Fe₃O₄ on the microstructure and properties of composite foams were investigated.

This work demonstrates that PI/Fe₃O₄ foams could be fabricated by thermally treating the polyimide foam intermediates with Fe₃O₄ nanoparticles through a blending reaction of precursors. The final PI/Fe₃O₄ composite foams maintained the excellent thermal property and showed a super paramagnetic behaviour, which has a positive effect on the improvement of electromagnetic shielding performance.

In this paper, the effects of Fe₃O₄ on the performances of PI/Fe₃O₄ composite foam were reported. It provided an effective methodology for the preparation of polymer/Fe₃O₄ nanocomposite foams, which hold great promise towards the potential application in the areas of electromagnetic shielding materials.

A series of PI/Fe₃O₄ composite foams with different contents of Fe₃O₄ were prepared by blending reaction of the precursors. The effects of Fe₃O₄ on the structures and properties of PI/Fe₃O₄ composite foam were discussed in detail.