Melt Pool Behavior Research Articles

Boosting Coercivity of 3D Printed Hard Magnets through Nano-Modification of the Powder Feedstock.

The demand for strong, compact permanent magnets essential for the energy transition drives innovation in magnet manufacturing. Additive manufacturing, particularly Powder Bed Fusion of metals using a laser beam (PBF-LB/M), offers potential for near-net-shaped Nd-Fe-B permanent magnets but often falls short compared to conventional methods. A less explored strategy to enhance these magnets is feedstock modification with nanoparticles. It is demonstrated that modifying a Nd-Fe-B-based feedstock with 1wt.%Ag nanoparticles boost the coercivity of the magnets to a record value of 935±6kAm-1 without further post-processing or heat treatments. Suitable volumetric energy densities for the PBF-LB/M process are determined using finite element simulations predicting melt pool behavior and part density. Microstructural analyses reveal finer grain sizes and more equiaxed nanocrystalline structures due to the modification. Atom probe tomography identifies three phases in the Ag-modified samples, with Ag forming nanophase regions with rare-earth elements near the amorphous Zr-Ti-B-rich intergranular phase, potentially decoupling the Nd2Fe14B primary phase. The study shows that superior magnetic properties primarily result from microstructure modification rather than part density. These findings highlight inventive material design approaches via feedstock surface modification to achieve superior magnetic performance in additively manufactured Nd-Fe-B magnets.

Effect of Laser Powder Bed Fusion Parameters on the Evolution of Melt Pool, Densification, Microstructure, and Hardness in 420 Stainless Steel Parts

Laser powder bed fusion (LPBF) involves depositing, melting, and solidifying metal powder particles layer by layer to create 3D components. In this study, a deep fundamental understanding on how process parameters—laser power, scan speed, and hatch spacing—affect the melt pool, densification, microstructure, hardness, and thermal behavior of 420 stainless steel (420SS) parts produced by such technology is provided. The conducted investigation considers five levels of laser power and hatch spacing, and four scan speeds. Optimal single tracks, based on geometry and profile, are achieved with laser powers between 40 and 80 W and a scan speed of 10 mm s−1. In the multitrack analysis, it is indicated that a dense, smooth surface is obtained with a hatch spacing of 250 μm, corresponding to an overlapping rate of ≈30%. The 420SS samples show high densification (≈99%) and low surface roughness (≈3.62 μm). The microstructure consisted of martensite laths and retained austenite. The hardness and thermal conductivity of the samples are measured at 540 HV and 15.3 W m−1 K−1, respectively. In this study, the understanding of the process–structure–property relationships in LPBF of 420SS is expanded.

Relating vapor emissions to melt pool behavior during laser processing

Relating vapor emissions to melt pool behavior during laser processing

SAMPO-P: A prototypical scale low-temperature experiment on two-layer melt pool heat transfer in LWR lower head

To better understand the thermal behavior of a two-layer melt pool with a high Rayleigh number—a pattern observed in the RASPLAV study, which indicates a significant risk to pressure vessel integrity and the success of in-vessel retention (IVR) strategies—this paper reports experimental findings from a 2D, full-scale (1:1 ratio) prototypical stratified melt pool (SAMPO-P). A series of experimental tests were carried out with varying heating powers and top layer heights, achieving a Rayleigh number of 3.77×1015, comparable to that found in light water reactors (LWR). Water was used to simulate the bottom layer, while n-octanol represented the top layer. Internal decay heat was modeled in the bottom layer using electric heating rods. After analyzing the main heat transfer parameters from the experiment, this paper derived several useful heat transfer correlations. The normalized temperature and heat flux distributions remained consistent across different power levels, and the normalized heat flux in the bottom layer aligned well with existing experimental correlations. In the bottom layer, the downward heat transfer coefficient was lower compared to other single-layer correlations, likely due to increased upward heat transfer.

Heat transfer and fluid flow modeling of steel-Inconel laser welding in an overlap configuration

This paper introduces a multiphysical model for laser welding in a lap joint configuration with dissimilar metals. Initially solved in a 2D axisymmetric configuration for static shots, the model is extended to 3D to simulate laser welding with a weld seam formation. Heat transfer, fluid flow, and species tracking are solved with the level set method to describe dynamically the keyhole and melt pool behavior. Validation against experimental data shows an accurate description of the main phenomena. The paper mainly highlights the need of introducing a thermal contact resistance to correctly predict the melted area dimensions. The study emphasizes the importance of considering imperfect material contact and proposes an effective approach for thermal contact resistance, a phenomenon poorly discussed in the literature.

Correlation between microstructural inhomogeneity and architectural design in additively manufactured NiTi shape memory alloys

ABSTRACT Additively manufactured Nitinol (NiTi) architectured materials, designed with unit cell architectures, hold promise for customisable applications. However, the common assumption of homogeneity in modeling and additive manufacturing of these architectured materials needs further investigation because geometric-dependent melt pool behaviour results in inhomogeneous microstructure and thermomechanical properties. This study shows that property inhomogeneity at the mesoscale is one reason for pseudo-linear response and partial superelasticity of the fabricated NiTi body-centered cubic (BCC) architectured materials. We modeled using a phenomenological constitutive relation and additively manufactured NiTi architectured materials with varying relative densities. These fabricated samples showed distinct microstructural textures and compositions that affected their local recoverability. The edge effects and laser turn regions were identified as the causes underlying the observed microstructural inhomogeneity. The dimensionless Fourier number is used to describe the transition of printing modes. This study provides valuable information on rigorous experimental/computational consistency in future work.

Interaction of contour and hatch parameters on vertical surface roughness in laser powder bed fusion

In Laser Powder Bed Fusion (L-PBF), surface roughness is pivotal for controlling the mechanical and functional performances, as well as the geometrical accuracy of the final product. This study extensively investigated the interactions of hatch and contour processing parameters, along with contour offset distance, on vertical surface roughness for 316L stainless steel in L-PBF. Melt pool morphology and surface arithmetic average roughness (Sa) were quantified using confocal microscopy, while scanning electron microscopy was employed to interpret the detailed microstructure of surface features. Under low volumetric energy density (VED) hatch conditions (e.g., 66.7 J/mm3), varying the contour offset distance has a negatable effect on the surface roughness when the contour VED is lower than 121.6 J/mm3, remaining relatively smooth surfaces dominated by bare melt tracks with sparely attached partially melted particles. Increasing the hatch or contour VED (e.g., 166.7 J/mm3), dross formation, identified by the microstructural differences and explained by the melt pool instability and migration, is inevitable, which dictates the surface roughness with higher Sa values. The larger contour offset distance further promotes the dross occurrence with irregularity and increases Sa. Employing a low contour VED with an appropriate offset distance and adopting the contour-first scan strategy was demonstrated as an effective solution to reduce the dross formation. Through the analysis of melt pool behavior, surface topography, and microstructure, this study elucidates the mechanisms governing dominant surface characteristics under the combined influence of hatch and contour parameters. It lays the foundation for precise control of surface roughness without altering hatching parameters, enabling the tailored manipulation of performance in additively manufactured structures.

Multi-fidelity surrogate with heterogeneous input spaces for modeling melt pools in laser-directed energy deposition

Multi-fidelity (MF) modeling is a powerful statistical approach that can intelligently blend data from varied fidelity sources. This approach finds a compelling application in predicting melt pool geometry for laser-directed energy deposition (L-DED). One major challenge in using MF surrogates to merge a hierarchy of melt pool models is the variability in input spaces. To address this challenge, this paper introduces a novel approach for constructing an MF surrogate for predicting melt pool geometry by integrating models of varying complexity, that operate on heterogeneous input spaces. The first thermal model incorporates five input parameters i.e., laser power, scan velocity, powder flow rate, carrier gas flow rate, and nozzle height. In contrast, the second thermal model can only handle laser power and scan velocity. A mapping is established between the heterogeneous input spaces so that the five-dimensional space can be morphed into a pseudo two-dimensional space. Predictions are then blended using a Gaussian process-based co-kriging method. The resulting heterogeneous multi-fidelity Gaussian process (Het-MFGP) surrogate not only improves predictive accuracy but also offers computational efficiency by reducing evaluations required from the high-dimensional, high-fidelity thermal model. The tested Het-MFGP yields an R2 of 0.975 for predicting melt pool depth. This surpasses the comparatively modest R2 of 0.592 achieved by a GP trained exclusively on high-dimensional, high-fidelity data. Similarly, in the prediction of melt pool width, the Het-MFGP excels with an R2 of 0.943, outshining the GP's performance, which registers a lower R2 of 0.588. The results underscore the benefits of employing Het-MFGP for modeling melt pool behavior in L-DED. The framework successfully demonstrates how to leverage multimodal data and handle scenarios where certain input parameters may be difficult to model or measure.

Beam-shaping in laser-based powder bed fusion of metals: A computational analysis of point-ring intensity profiles

Laser-based powder bed fusion has the potential to enable manufacturing of local material properties and locally varying alloys. One promising approach under research is shaping of the applied laser beam. The current commercial standard using a Gaussian laser beam profile is associated with a high energy intensity peak and strong gradients. A potential alternative beam shape is the point-ring profile where laser energy is distributed between a central spot and an outer ring. We conduct a numerical study of beam shape impact on melt-pool shapes, surface temperatures, evaporation and flow dynamics of single-melt-tracks. To that end, we apply a Weakly Compressible Smoothed Particle Hydrodynamics solver coupled with a ray-tracing laser scheme. A point-ring profile is compared to a standard Gaussian profile. The profiles are studied at two different beam sizes to find the influence of beam size on the shape effect. We find good agreement between numerical results and experimental data for both narrow and deep, as well as wide and shallow melt-tracks. The simulation results show that beam size and thus energy density influence the effect beam-shaping has on the melt-pool dynamics. Both the distribution of evaporation and surface tension forces over the melt-pool surface are found to depend on the used beam shape. The study highlights the importance of distinguishing between size and shape effects when investigating laser beam shapes. Both energy density and its distribution need to be tuned for the desired melt-pool behavior.

Avoiding heat source calibration for finite element modeling of the laser powder bed fusion process

The melt pool characteristics govern process stability and microstructure development during Laser Powder Bed Fusion (LBPF). The melt pool is strongly affected by the laser parameters and based on the melt pool depth-to-width ratio, three melting modes can be distinguished: conduction, transition, and keyhole mode. Finite element (FE) simulations have been extensively used to investigate the cyclic thermal history of the LPBF process and the effects of different process parameters on the part quality. However, the heat sources applied in such simulations can only accurately predict the melt pool behavior, and thus the temperature profile, when processing in conduction mode. As for the transition and keyhole regime modeling, heat source parameters or material properties are usually adjusted to make the simulated melt pool dimensions match the real values. This study proposes a novel approach to bypass the conventional heat source calibration strategy to simulate the LBPF process across different melting regimes. The predicted melt pool dimensions are validated for a wide range of process parameters applied to three different alloys: Ti-6Al-4 V, 316 L austenitic stainless steel (316 L), and 2507 super duplex stainless steel (SDSS). The average errors obtained on the melt pool width, depth, length, and aspect ratio are 9.7 %, 12.4 %, 14.5 %, and 14.3 % respectively. These results demonstrate how the proposed approach can capture the melt pool dimensions throughout different materials and melting modes eliminating the time-consuming heat source calibration steps and facilitating the LPBF modeling workflow.

Study on the lower head failure in severe accidents Part II: Thermal-mechanical coupling behavior analysis on CAP1400 reactor lower head

Under severe accident conditions with core meltdown, large amounts of molten material relocate to the lower head at high temperatures. Significant thermal and mechanical loads may lead to failure of the reactor pressure vessel (RPV) lower head, spreading radioactive fission products. Lower head failure time and location are crucial for accident mitigation and consequence assessment. This study developed a thermodynamic failure analysis model for the lower head by investigating material failure mechanisms, coupling this into an Integrated Severe Accident Analysis code (ISAA), and conducting experimental validation and applied research. Part I mainly introduces the thermodynamic analysis module development, validation against OLHF experiments, and preliminary failure criteria analysis. Results indicate the model accurately predicts lower head failure behavior, and Larson-Miller life fraction and Hedl-Dorn parameter criteria accurately assess lower head integrity. Part II presents applied research after validation and preliminary analysis. Using the improved ISAA, melt pool behavior and lower head thermal–mechanical response were analyzed for a CAP1400 small break loss-of-coolant accident (SBLOCA), assuming multiple safety system failures. Results indicate the bottom of the lower head melt pool didn’t form a hard shell due to high heat release rate, only an oxide shell layer around the second layer. Decay heat from melt pool components cannot be dissipated, leading to lower head failure. Further External Reactor Vessel Cooling (ERVC) heat transfer model analysis and research are needed in ISAA. The two developed mechanical analysis models predict material failure at high temperatures, and the timing and location of lower head failure are consistent, at approximately 16,000 s at 25.38°±5.47° on the lower head. The predicted failure mode is similar to Part I validation, indicating both Larson-Miller life fraction and Hedl-Dorn parameter criteria provide consistent lower head integrity judgments.

Influence of alloy solidification path on melt pool behavior in additive manufacturing

Numerical models used to study transport phenomena in laser-powder bed fusion processes often rely on assumptions and simplifications to reduce their computational expense. One common simplification is in the description of latent heat evolution during the solid-liquid phase change (i.e., the solidification pathway), justified by the fact that the mushy zone thickness is similar to the numerical grid spacing used for continuum transport models. The lack of resolution of transport phenomena in the mushy zone motivates the use of computationally convenient solidification paths such as linear or sigmoidal relationships over pathways derived from fundamental solidification theory such as equilibrium or Scheil models. In the present work, an uncertainty quantification (UQ) framework is used to analyze the influence of solidification pathway selection on the solidification dynamics and melt pool geometries in laser based additive manufacturing (AM) of IN625. Results show the solidification pathway has a quantifiable influence on the cooling rate at the liquidus isotherm, mushy zone thickness, and solidification time. Due to similarities in the latent heat evolution at the beginning of solidification, the equilibrium and Scheil models predict similar cooling rates near the liquidus isotherm, however the wider freezing range of Scheil leads to a wider mushy zone compared to equilibrium. The non-physical latent heat release profiles of sigmoidal and linear paths lead to significant overpredictions of cooling rates at the liquidus isotherm compared to equilibrium and Scheil. These results indicate that careful consideration should be given to the choice of solidification pathway to ensure reliable model predictions.

Clad-geometric characteristics and melt-pool behavior on microstructure evolution of laser clad Stellite-6 on R260 grade rail steel

Clad-geometric characteristics and melt-pool behavior on microstructure evolution of laser clad Stellite-6 on R260 grade rail steel

The effect of the laser beam intensity profile in laser-based directed energy deposition: A high-fidelity thermal-fluid modeling approach

Modeling the thermal and fluid flow fields in laser-based directed energy deposition (DED-LB) is crucial for understanding process behavior and ensuring part quality. However, existing models often fail to accurately predict these fields due to simplifying assumptions, particularly regarding powder particle-induced attenuation in laser power and energy density distribution, and the variable material properties and process parameters. The present work introduces a high-fidelity multi-phase thermal-fluid model driven by a combination of the discrete element method (DEM) and the finite volume method (FVM). Incorporating an enhanced attenuation model for laser energy enables a more precise approximation of powder particle-induced attenuation effects in the laser power and energy density distribution. The study focuses on the influence of laser beam intensity profiles during DED-LB of austenitic stainless steel (AISI 316 L), with model validation conducted through experimental measurements of deposited track dimensions for different beam shapes. The results of numerical simulations demonstrate the critical impact of powder-induced attenuation on the laser power and intensity profiles. Neglecting laser energy attenuation, a common assumption in numerical simulations of DED-LB, leads to overestimations of the absorbed energy of the laser beam, affecting thermal and fluid flow fields, and melt pool dimensions. The present study unravels the complex relationship between the attenuation coefficient (due to the powder stream) and powder stream characteristics, describing the variations of the attenuation coefficient with changes in the powder mass flow rate and powder stream incidence angle. The findings show the critical effects of laser beam shaping on melt pool behavior in DED-LB, with square beams inducing larger melt pool volumes and circular beams creating smaller but deeper melt pools. The proposed enhanced thermal-fluid modeling framework offers a robust approach for optimizing laser-based additive manufacturing across diverse materials and laser systems.

Influence of environmental pressure on the energy coupling and droplet transition behavior in laser welding with filler wire

The influence of environmental pressure on droplet behavior and weld formation in laser welding with filler wire for 304 stainless steel was investigated and the energy coupling behavior was analyzed. As ambient pressure increases from 5 kPa to 700 kPa, the weld depth decreases by 77 %, the variance of the weld width increases approximately 5 times, and the continuity of the weld surface formation deteriorates. During the welding process, a high-speed camera was employed to observe the melt pool, plasma, and melt drop transition behavior. With an increase in the ambient pressure followed by an increase in the metal evaporation temperature, the effects of shielding of the plasma and its internal metal vapor particles on the laser beam lead to a reduction in the depth of the melt. The inverse bremsstrahlung absorption of laser by plasma increased by approximately 36.3 times at 700 kPa compared with that at atmospheric pressure. The number of metal vapor particles at 700 kPa is approximately 3.58 times higher than that at 101 kPa, and the average particle diameter is approximately 0.4 times higher, causing enhanced absorption of laser light by the metal vapor particles. An increase in gas density at elevated ambient pressures resulted in a significant increase in the resistance to droplet descent and decrease in the drive force, leading to an increase in the droplet transition period. This change shifts from a liquid bridge transition to a particle transition, which is the main cause of the deterioration of weld surface formation at high pressures.

Understanding Melt Pool Behavior of 316L Stainless Steel in Laser Powder Bed Fusion Additive Manufacturing.

In the laser powder bed fusion additive manufacturing process, the quality of fabrications is intricately tied to the laser-matter interaction, specifically the formation of the melt pool. This study experimentally examined the intricacies of melt pool characteristics and surface topography across diverse laser powers and speeds via single-track laser scanning on a bare plate and powder bed for 316L stainless steel. The results reveal that the presence of a powder layer amplifies melt pool instability and worsens irregularities due to increased laser absorption and the introduction of uneven mass from the powder. To provide a comprehensive understanding of melt pool dynamics, a high-fidelity computational model encompassing fluid dynamics, heat transfer, vaporization, and solidification was developed. It was validated against the measured melt pool dimensions and morphology, effectively predicting conduction and keyholing modes with irregular surface features. Particularly, the model explained the forming mechanisms of a defective morphology, termed swell-undercut, at high power and speed conditions, detailing the roles of recoil pressure and liquid refilling. As an application, multiple-track simulations replicate the surface features on cubic samples under two distinct process conditions, showcasing the potential of the laser-matter interaction model for process optimization.

A comprehensive metal additive manufacturing platform to transform the marine industry

Direct Metal Deposition (DMD) is one of the underwater marine additive manufacturing (MAM) technologies known for its capability to build up on semi-finished products. This allows for the creation of complex structures and repair the damaged or worn-out areas. Employing this underwater technology needs a lot of consideration regarding the harsh environment of the ocean. This research endeavours to identify nickel-aluminium bronze’s structural characteristics printed underwater. Simulation studies can help to analyse grain and phase evolution, defects, and melt pool behaviour, enabling the optimization of printing parameters for high-quality marine alloy components. To achieve that a control systems and machine learning algorithms need to developed to enhance precision in the 3D printing process on a moving platform, addressing the challenges of six distinct vessel movements at sea. This integration aims to improve accuracy, contributing to optimal performance in dynamic maritime environments.

Multisensor fusion-based digital twin for localized quality prediction in robotic laser-directed energy deposition

Early detection of defects, such as keyhole pores and cracks is crucial in laser-directed energy deposition (L-DED) additive manufacturing (AM) to prevent build failures. However, the complex melt pool behaviour cannot be adequately captured by conventional single-modal process monitoring approaches. This study introduces a multisensor fusion-based digital twin (MFDT) for localized quality prediction in the robotic L-DED process. The data used in multisensor fusion includes features extracted from a coaxial melt pool vision camera, a microphone, and an off-axis short wavelength infrared thermal camera. The key novelty of this work is a spatiotemporal data fusion method that synchronizes multisensor features with the real-time robot motion data to achieve localized quality prediction. Optical microscope (OM) images of the printed part are used to locate defect-free and defective regions (i.e., cracks and keyhole pores), which serve as ground truth labels for training supervised machine learning (ML) models for quality prediction. The trained ML model is then used to generate a virtual quality map that registers quality prediction outcomes within the 3D volume of the printed part, thus eliminating the need of physical inspections by destructive methods. Experiments show that the virtual quality map closely matches the actual quality observed by OM. Compared to traditional single-sensor-based quality prediction, the MFDT has achieved a significantly higher quality prediction accuracy (96%), a higher ROC-AUC score (99%), and a lower false alarm rate (4.4%). As a result, the MFDT is a more reliable method for defect prediction. The proposed MFDT also lays the groundwork for our future development of a self-adaptive hybrid processing strategy that combines machining with AM for defect removal and quality improvement.

Revealing the effects of laser beam shaping on melt pool behaviour in conduction-mode laser melting

Laser beam shaping offers remarkable possibilities to control and optimise process stability and tailor material properties and structure in laser-based welding and additive manufacturing. However, little is known about the influence of laser beam shaping on the complex melt-pool behaviour, solidified melt-track bead profile and microstructural grain morphology in laser material processing. A simulation-based approach is utilised in the present work to study the effects of laser beam intensity profile and angle of incidence on the melt-pool behaviour in conduction-mode laser melting of stainless steel 316L plates. The present high-fidelity physics-based computational model accounts for crucial physical phenomena in laser material processing such as complex laser–matter interaction, solidification and melting, heat and fluid flow dynamics, and free-surface oscillations. Experiments were carried out using different laser beam shapes and the validity of the numerical predictions is demonstrated. The results indicate that for identical processing parameters, reshaping the laser beam leads to notable changes in the thermal and fluid flow fields in the melt pool, affecting the melt-track bead profile and solidification microstructure. The columnar-to-equiaxed transition is discussed for different laser-intensity profiles.

In situ observation of melt pool evolution in ultrasonic vibration-assisted directed energy deposition

The presence of defects, such as pores, in materials processed using additive manufacturing represents a challenge during the manufacturing of many engineering components. Recently, ultrasonic vibration-assisted (UV-A) directed energy deposition (DED) has been shown to reduce porosity, promote grain refinement, and enhance mechanical performance in metal components. Whereas it is evident that the formation of such microstructural features is affected by the melt pool behavior, the specific mechanisms by which ultrasonic vibration (UV) influences the melt pool remain elusive. In the present investigation, UV was applied in situ to DED of 316L stainless steel single tracks and bulk parts. For the first time, high-speed video imaging and thermal imaging were implemented in situ to quantitatively correlate the application of UV to melt pool evolution in DED. Extensive imaging data were coupled with in-depth microstructural characterization to develop a statistically robust dataset describing the observed phenomena. Our findings show that UV increases the melt pool peak temperature and dimensions, while improving the wettability of injected particles with the melt pool surface and reducing particle residence time. Near the substrate, we observe that UV results in a 92% decrease in porosity, and a 54% decrease in dendritic arm spacing. The effect of UV on the melt pool is caused by the combined mechanisms of acoustic cavitation, ultrasound absorption, and acoustic streaming. Through in situ imaging we demonstrate quantitatively that these phenomena, acting simultaneously, effectively diminish with increasing build height and size due to acoustic attenuation, consequently decreasing the positive effect of implementing UV-A DED. Thus, this research provides valuable insight into the value of in situ imaging, as well as the effects of UV on DED melt pool dynamics, the stochastic interactions between the melt pool and incoming powder particles, and the limitations of build geometry on the UV-A DED technique.