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The purpose of this paper is to establish a three-dimensional flow field model of the Invar alloy laser–metal inert gas (laser–MIG) hybrid welding process to investigate the influence of different heat sources between different layers and to analyze the flow field based on the two different heat source models for the multilayer welding.

The Invar steel plates with 19.5 mm thickness are welded into three layers’ seam using the hybrid laser–MIG welding technology. The flow field based on different heat source models is studied and then used to investigate the influence of different heat sources in different layers during the laser–MIG hybrid welding process. The simulation results of flow field using two different heat source models are compared with experiments.

The flow field simulations results show that using the Gaussian rotating body heat source model to simulate the temperature field is more consistent with the experiment of the hybrid laser–MIG welding where its flow field between different layers better reflects the characteristics of the hybrid laser–MIG welding.

The findings will be useful in the study of a variety of thick-plate laser–MIG hybrid welding process fluid flows.

The purpose of this paper is to investigate the relationship between the keyhole geometry and acoustic signatures from the backside of a workpiece. It lays a solid foundation for monitoring the penetration state in variable polarity keyhole plasma arc welding.

The experiment system is conducted on 6-mm-thick aluminum alloy plates based on a dual-sensor system including a sound sensor and a charge coupled device (CCD) camera. The first step is to extract the keyhole boundary from the acquired keyhole images based on median filtering and edge extraction. The second step is to process the acquired acoustic signal to obtain some typical time domain features. Finally, a prediction model based on the extreme learning machine (ELM) technique is built to recognize different keyhole geometries through the acoustic signatures and then identify the welding penetration status according to the recognition results.

The keyhole geometry and acoustic features after processing can be closely related to dynamic change information of keyhole. These acoustic features can predict the keyhole geometry accurately based on the ELM model. Meanwhile, the predict results also can identify different welding penetration status.

This paper tries to make a foundation work to achieve the monitoring of keyhole condition and penetration status through image and acoustic signals. A useful model, ELM, is built based on these features for predicting the keyhole geometry. Compared with back-propagating neural network and support vector machine, this proposed model is faster and has better generalization performance in the case studied in this paper.

The purpose of this paper is to present the calibration of a laser welding model suitable for solving problems with input data that are either unknown or known only approximately.

The calibration starts from the measured temperature profile of the weld, and the aim is to get a similar profile by the solution of the model. The corresponding procedure is based on replacing the material characteristics that are known only approximately by polynomial or rational functions whose coefficients are determined using a suitable optimization process. The algorithm is supplemented with a simplified model of the keyhole shape.

The big advantage of the proposed approach is the velocity of solution of the problem and low consumption of the sources (hardware and software). In comparison with solving the full model of laser welding, the methodology provides results of a still acceptable accuracy by several orders faster. On the other hand, the results also depend on the strategy of selecting the points at which the temperature is verified and on “manual” setting of the deformation parameters.

Application of the methodology is conditioned by several experiments with the used material (without experiment it is impossible to carry out the calibration and set the shape of the keyhole), while the full model allows it. On the other hand, the full model is not able to predict the errors in the case when some input data is unknown or known only approximately and the results have to be also confirmed experimentally.

The presented methodology may be used for determining unknown material characteristics and faster modelling of laser welding.

This paper proposes a novel methodology for evaluation of quality of laser welds in cases of unknown or partially unknown material parameters and substantial acceleration (by 2-3 orders) of the numerical solution of the model of laser welding.

The paper aims to describe the modeling of the induction-assisted laser welding process taking into account the keyhole effect and phase changes in the material.

A sophisticated mathematical model of the above heat treatment process is presented, taking into account the above phenomena and all available nonlinearities of the material. Its numerical solution is carried out using the finite element method incorporating algorithms for the deformation of geometry and solution of the flow field.

Unlike various simplified models solved in the past, this approach incorporating a sophisticated model of heat transfer and flow of melt is able to reach a very accurate solution, differing only by a small error (not more than 8 per cent) from the experiment.

The presented model does not consider several subtle phenomena related to the evaporation of metal after irradiation of the material by a laser beam. In fact, at the heated spot, all three phases of the material coexist. The evaporated metal forms a capillary leak off and forms a cloud above the spot of irradiation. Due to the absorption of laser power in this cloud, the process of heating decelerates, which leads to a decrease in the process efficiency.

The presented model and methodology of its solution may represent a basis for design of the process of laser welding.

The main value is the proposal of numerical model for solution a complex multiphysical model with respecting several physical phenomena whose results are available in a short time and still with a good agreement with the experimental verification.

Laser powder bed fusion (LPBF) provides the means to produce unique components with almost no restriction on geometry in an extremely short time. However, the high-temperature gradient and high cooling rate produced during the fabrication process result in residual stress, which may prompt part warpage, cracks or even baseplate separation. Accordingly, an appropriate selection of the LPBF processing parameters is essential to ensure the quality of the built part. This study, thus, aims to develop an integrated simulation framework consisting of a single-track heat transfer model and a modified inherent shrinkage method model for predicting the curvature of an Inconel 718 cantilever beam produced using the LPBF process.

The simulation results for the curvature of the cantilever beam are calibrated via a comparison with the experimental observations. It is shown that the calibration factor required to drive the simulation results toward the experimental measurements has the same value for all settings of the laser power and scanning speed. Representative combinations of the laser power and scanning speed are, thus, chosen using the circle packing design method and supplied as inputs to the validated simulation framework to predict the corresponding cantilever beam curvature and density. The simulation results are then used to train artificial neural network models to predict the curvature and solid cooling rate of the cantilever beam for any combination of the laser power and scanning speed within the input design space. The resulting processing maps are screened in accordance with three quality criteria, namely, the part density, the radius of curvature and the solid cooling rate, to determine the optimal processing parameters for the LPBF process.

It is shown that the parameters lying within the optimal region of the processing map reduce the curvature of the cantilever beam by 17.9% and improve the density by as much as 99.97%.

The present study proposes a computational framework, which could find the parameters that not only yield the lowest distortion but also produce fully dense components in the LPBF process.

This paper aims to describe a three-dimensional mathematical and numerical model based on finite volume method to simulate the fluid dynamics in weld pool, droplet transfer and keyhole behaviors in the laser-MIG hybrid welding process of Fe36Ni Invar alloy.

Double-ellipsoidal heat source model and adaptive Gauss rotary body heat source model were used to describe electric arc and laser beam heat source, respectively. Besides, recoil pressure, electromagnetic force, Marangoni force, buoyancy as well as liquid material flow through a porous medium and the heat, mass, momentum transfer because of droplets were taken into consideration in the computational model.

The results of computer simulation, including temperature field in welded plate and velocity field in the fusion zone were presented in this article on the basis of the solution of mass, momentum and energy conservation equations. The correctness of elaborated models was validated by experimental results and this proposed model exhibited close correspondence with the experimental results with respect to weld geometry.

It lays foundation for understanding the physical phenomena accompanying hybrid welding and optimizing the process parameters for laser-MIG hybrid welding of Invar alloy.

This paper presents the influence of beam incidence angle on austenitic stainless steel sheet subjected to a high density laser beam having Gaussian power density distribution. Bead‐on trials are conducted on 3.15 mm thick commercial AISI 304 austenitic stainless steel sheet using a Nd:YAG laser source with a maximum output of 2kW in the continuous wave mode. The effects of beam incident angle on the weld bead geometry are studied using finite element analysis. Experiments are conducted with 600, 1000 and 1400W laser power and 800, 1400 and 2000mm/min welding speed. A three dimensional finite element model is developed for the simulation of non‐linear transient thermal analysis of the weld bead geometry for different beam incident angles using the finite element code ANSYS. The result reveals that by increasing the beam incident angle with constant beam power and welding speed, there is a considerable reduction in the depth of penetration‐to‐width ratio (d/w). Further, it is noticed that the process enters into conduction mode of welding from the keyhole mode of welding as the beam angle is increased beyond 10o. The comparison of the simulation results and the experimental data for weld bead geometry with different beam incident angles show good agreement.

Limited research has attempted to reveal the different modes of the melt pool formation in additive manufacturing. This paper aims to study the mechanisms of surface roughness formation, especially on the aspect of melt pool formation which determine the surface profile and consequently significantly influence the surface roughness.

In this study, the conditions under which different modes of melt pool formation (conduction mode and keyhole mode) occur for the case of as-fabricated Hastelloy X using direct metal laser solidification (DMLS) are derived and validated experimentally. Top surfaces of uni-directionally built samples under various processing conditions are cut, grinded, polished and etched to reveal their individual melt pool morphologies. Similarly, up-skin (slope angle < 90°) and down-skin (slope angle > 90°) melt pool morphologies are also investigated to compare the differences. Surface tension gradients and resultant Marangoni flow, which dominate the melt flow in the melt pool, is also calculated to help better evaluate the melt pool shape forming.

Two types of melt pool formation modes are dominating in DMLS: conduction mode and keyhole mode. Melt pool formed by conduction mode generally has an aspect ratio of 1:2 (depth vs width) and is in elliptical shape. Appropriate selection of scanning laser power and speed are required to maintain a low characteristic length and width ratio to prevent ballings. Melt pool formed by keyhole mode has an aspect ratio of 1:1 or less. High-energy contour promotes formation of key-hole-shaped melt pool which fills the gaps between layers and smoothens the up-skin surface roughness. Low-energy contour scan is necessary for down-skin surface to form small melt pool profiles and achieve low Ra.

This paper provides valuable insight into the origins of surface quality problem of DMLS, which is a very critical issue for upgrading the process for manufacturing real components. This paper helps promote the understanding of the attributes and capabilities of this rapidly evolving three-dimensional printing technology and allow appropriate control of processing parameters for successful fabrication of components with sound surface quality.

This study presents a framework to estimate throughput and cost of additive manufacturing (AM) as related to process parameters, material thermodynamic properties and machine specifications. Taking a 3D model of the part design as input, the model uses a parametrization of the rate-limiting physics of the AM build process – herein focusing on laser powder bed fusion (LPBF) and scaling of LPBF melt pool geometry – to estimate part- and material-specific build time. From this estimate, per-part cost is calculated using a quantity-dependent activity-based production model.

Analysis tools that assess how design variables and process parameters influence production cost increase our understanding of the economics of AM, thereby supporting its practical adoption. To this aim, our framework produces a representative scaling among process parameters, build rate and production cost.

For exemplary alloys and LPBF system specifications, predictions reveal the underlying tradeoff between production cost and machine capability, and look beyond the capability of currently commercially available equipment. As a proxy for build quality, the number of times each point in the build is re-melted is derived analytically as a function of process parameters, showcasing the tradeoff between print quality due to increased melting cycles, and throughput.

Typical cost models for AM only assess single operating points and are not coupled to models of the representative rate-limiting process physics. The present analysis of LPBF elucidates this important coupling, revealing tradeoffs between equipment capability and production cost, and looking beyond the limits of current commercially available equipment.

The selective laser melting (SLM) technique, as a typical additive manufacturing process, is widely used for the fabrication of metallic biomedical components. In terms of biodegradability, zinc and its alloys represent an emerging generation of metallic materials for biomedical implants. The purpose of this paper is to obtain the Zn and Zn10Mg alloys with high mechanical properties using the SLM technology. The relationship between the processing parameters and the porosity of pure Zn and Zn10Mg alloy samples was investigated.

The samples were fabricated using SLM technology working in an inert gas closed chamber. Preliminary experiments were conducted to analyze the laser power and gas flow on evaporation, single track form and porosity. To evaluate the influence of factors on relative density, the response surface methodology was applied.

The satisfactory results of the proposed method were achieved, in which the relative density of the components reached up to 99.63%, and compression strength reached 214 ± 13 MPa under optimal processing conditions.

Zinc is categorized by its low melting and boiling point, which leads to the high porosity of the components. It is difficult to prepare the Zn alloy samples with high relative density using SLM technology. This work successfully achieved dense Zn and Zn10Mg samples and investigated their microstructure, mechanical properties and corrosion behavior.