Melt Pool Geometry Research Articles

Single-Track Laser Scanning as a Method for Evaluating Printability: The Effect of Substrate Heat Treatment on Melt Pool Geometry and Cracking in Medium Carbon Tool Steel

Nearly all commercially available alloys have been developed for manufacturing processes other than additive manufacturing. Most of those alloys are not suitable for laser powder bed fusion (L-PBF) processing due to the non-weldable nature of the alloys developed for casting, forging, and machining. Even some weldable alloys can be difficult to produce with L-PBF because the characteristics of L-PBF, such as highly concentrated heat input and the extremely high cooling rate, can lead to very high residual stresses and cracking. In order to speed up the development process of new alloys for additive manufacturing, a powder-free evaluation method was used to evaluate the materials processing window and susceptibility to cracking. Single tracks were scanned with an L-PBF machine onto H13 steel substrates. The substrate condition was varied, and its effect on melt pool geometry and cracking behavior was evaluated. The results clearly show that thermal history of the substrate influences its thermal conductivity, affecting melt pool volume. Melting point of the substrate was not found as significant factor as thermal conductivity on melt pool dimensions. Cracking type was noted to differ between substrates. If printability is assessed without powder, the substrate microstructure should be similar to rapidly solidified material. It is recognized that single-track tests are not adequate in terms of residual stress evaluation, but they can give valuable information about materials’ melting, segregation, and micro-scale cracking behavior.

Numerical modeling of thermal behavior of melt pool in laser additive manufacturing of Ni-based diamond tools

In this paper the heat absorption, heat transfer and solidification evolution of melt pool in the laser additive manufacturing of Ni–Cr metal bonded diamond tools were studied. Based on the ray tracing theory, the influence of diamond and Ni–Cr alloy powder parameters on laser energy absorptivity was analyzed and the temperature model of mixed powder bed was constructed. Combined with the model and experiment, the impact of the diamond itself and its arrangement on the temperature distribution and shape of melt pool was explored and compared. The change rule of melt pool and microstructure in laser multi-track scanning was investigated. The evolution of melt pool solidification and microstructure with the influence of diamond was revealed. The results show that the powder thickness has a great influence on laser energy absorptivity. The diamond has obvious influence on the temperature distribution and geometry of melt pool, and the influence degree and variation rule are related to the diamond arrangement and position. In the process of laser multi-track scanning, the temperature increases and the geometry of melt pool enlarges gradually. Near the diamond, the diamond changes the direction of temperature gradient of metal melt, accelerates crystals solidification, makes the growth direction of crystals approximately perpendicular to diamond, and increases the endogenetic nucleation phenomenon of crystals near the diamond interface.

Characterization of Surface Topography Features for the Effect of Process Parameters and Their Correlation to Quality Monitoring in Metal Additive Manufacturing

Layering deposition methodology in metal additive manufacturing (AM) and the influence of different processing parameters, such as energy source level and deposition speed, which can change the melt pool condition, are known to be the important influencing factors on properties of components fabricated via AM. The effect of melt pool conditions and geometry on properties and quality of fabricated AM components has been widely studied through experimental and simulation techniques. There is a need for better understanding the influence of solidified melt pool topography on characteristics of next deposition layer that can be applied to complex surfaces, especially those with sparse topographical features, such as those that occur in AM deposition layers. Topography of deposited layers in metal additive manufacturing is a significant aspect on the bonding condition between the layers and defect generation mechanism. Characterization of the topography features in AM deposition layers offers a new perspective into investigation of defect generation mechanisms and quality evaluation of AM components. In this work, a feature-based topography study is proposed for the assessment of process parameters’ influence on AM deposition layers topography and defect generation mechanism. Titanium alloy (Ti6Al4V) samples deposited on steel substrate, by direct energy deposition (DED) AM technique at different process conditions, were used for the assessment. Topography datasets and analysis of shape and size differences pertaining to the relevant topographic features have been performed. Different AM process parameters were investigated on metallic AM samples manufactured via direct energy deposition (DED) and the potential defect generation mechanism was discussed. The assessment of the topography features was used for correlation study with previously published in-situ monitoring and quality evaluation results, where useful information was obtained through characterization of signature topographic formations and their relation to the in-situ acoustic process monitoring, as the indicators of the manufacturing process behavior and performance.

Modulating fracture toughness through processing-mediated mesostructure in additively manufactured Al-12Si alloy

Al-12Si alloy processed through additive manufacturing exhibits a complex hierarchical structure. At the mesoscale, its melt pool boundaries constitute a network of weak interfaces that provides preferred pathways for crack kinking, leading to both marked anisotropy and apparent enhancement in the fracture energy. In this study, a multiscale cohesive zone-based computational model and a semi-analytical approach for kinked cracks are used to investigate the effect of melt pool configuration on fracture energy enhancement and anisotropy due to crack path tortuosity. We experimentally validate our methodology using fracture toughness testing of compact tension specimens, then systematically study the simultaneous effects of hatch spacing, layer thickness, and crack surface orientation on variations of the fracture energy. While the fracture energy increases with increasing hatch spacing and decreasing layer thickness, processing defects such as keyholing give practical limits to the melt pool geometry, limiting the fracture energy enhancement. We found that the fracture energy can be enhanced as high as a factor of two with an optimal crack surface orientation that is linearly proportional to the ratio of hatch spacing to layer thickness and varies between 60° and 100°.

Quantification and prediction of lack-of-fusion porosity in the high porosity regime during laser powder bed fusion of Ti-6Al-4V

Although lack-of-fusion porosity due to incomplete melting of powder can limit the mechanical properties of additively manufactured metals, quantification and prediction of these defects remains challenging. We compare three common strategies to measure porosity: the Archimedes, micrograph-based, and micro-computed tomography approaches. We find that while these methods work equally well at low void fraction, their predictions diverge at higher void fractions (> 5 %). We find that the disparity comes since the Archimedes method measures the total amount of solid in the sample, while micrograph-based approach neglects loose powder trapped inside the samples that can be removed during the preparation process. We conclude that these two methods make use of divergent definitions of porosity. While the Archimedes method measures a “total porosity” defined by the total volume fraction of void in the material, the micrograph method measures an “effective porosity” that only accounts for the continuous material. On the other hand, the resolution of micro-computed tomography is limited by voxel size, leading to ambiguity of trapped powder being identified as solid or void. Consequently, the number density of defects from micro-computed tomography are noticeably smaller than that from micrograph-based approach. A geometric model for porosity prediction is implemented and used to evaluate different models for melt pool geometry. Our numerical predictions of melt pool profiles are surprisingly insensitive to our choice of heat source models. Finally, an analytical geometric model is developed for fast estimation of total and effective porosities and shows good agreement with both numerical simulations and experimental measurement.

Towards predicting process parameters for selective laser melting of titanium alloys through the modelling of melt pool characteristics

Various researchers have investigated the use of experimental melt pool characterization to speed up the optimisation process of selective laser melting parameters and found this to be possible. From their studies, it has become clear that the incorporation of modelling into this approach could provide efficient and predictable results that would minimise the experimental validation work required. This paper reports on progress made towards characterising the melt pool through simulation. The development of a numerical model is discussed. Subsequently, experimental validation of the numerical model is presented. This is done through a comparison of the simulation results with the experimentally determined cross-sectional geometry of single tracks created with various sets of process parameters. Melt pool size and shape are considered. Based on these results, it is concluded that using an identical simulation setup, verified simulation method, and verified material properties, it was possible to accurately determine the melt pool geometry for some, but not all process parameters.

On the effect of thin-wall thickness on melt pool dimensions in laser powder-bed fusion of Hastelloy X: Numerical modeling and experimental validation

Laser Powder-bed Fusion (LPBF) is a common technique categorized as one of the Additive Manufacturing (AM) processes to efficiently fabricate complex geometries. The involvement of complex phenomena relating to laser and metal powder requires a thorough investigation to understand the complex multi-physics behind this process. Modeling and simulation tools shed light on predicting the temperature distribution and melt pool dimensions which have a significant impact on the quality of the final parts. In this study, a three-dimensional (3D) heat transfer model is developed to investigate the influence of the thickness of the printed thin-walls on melt pool dimensions and temperature distribution. The results indicate that the single-track simulation can predict the melt pool dimensions accurately and the calibrated model can be extended to the multi-track simulation for investigating the effect of thin-wall thicknesses on melt pool geometries. The simulation results demonstrate the evolution of melt pool geometries during the process. Due to the existence of heat accumulation during the process, decreasing the thicknesses of the thin-walls leads to enlarging the melt pool width significantly. Moreover, the simulation results show a higher temperature gradient during the LPBF process of thinner parts leading to a smaller grain size of the final microstructure. The validation of the simulation results showed the high capability of the model in predicting the transient temperature profile and melt pool geometries. The percentage difference between simulated and experimental melt pool width for thin-wall thicknesses 0.5 mm, 0.75 mm, and 1 mm are 7%, 7%, and 11%, respectively. Lastly, a process map has been provided to guide the selection of process parameters for printing thin-wall structures.

Uncertainties Induced by Processing Parameter Variation in Selective Laser Melting of Ti6Al4V Revealed by In-Situ X-ray Imaging.

Selective laser melting (SLM) additive manufacturing (AM) exhibits uncertainties, where variations in build quality are present despite utilizing the same optimized processing parameters. In this work, we identify the sources of uncertainty in SLM process by in-situ characterization of SLM dynamics induced by small variations in processing parameters. We show that variations in the laser beam size, laser power, laser scan speed, and powder layer thickness result in significant variations in the depression zone, melt pool, and spatter behavior. On average, a small deviation of only ~5% from the optimized/reference laser processing parameter resulted in a ~10% or greater change in the depression zone and melt pool geometries. For spatter dynamics, small variation (10 , 11%) of the laser beam size could lead to over 40% change in the overall volume of the spatter generated. The responses of the SLM dynamics to small variations of processing parameters revealed in this work are useful for understanding the process uncertainties in the SLM process.

Microstructural Development in Inconel 718 Nickel-Based Superalloy Additively Manufactured by Laser Powder Bed Fusion

Excellent weldability and high temperature stability make Inconel 718 (IN718) one of the most popular alloys to be produced by additive manufacturing. In this study, we investigated the effects of laser powder bed fusion (LPBF) parameters on the microstructure and relative density of IN718. The samples were fabricated with independently varied laser power (125–350 W), laser scan speed (200–2200 mm/s), and laser scan rotation (0°–90°). Archimedes’ method, optical microscopy, and scanning electron microscopy were employed to assess the influence of LPBF parameters on the relative density and microstructure. Optimal processing windows were identified for a wide range of processing parameters, and relative density greater than 99.5% was achieved using volumetric energy density between 50 and 100 J/mm3. Microstructural features including melt pool geometry, lack of fusion defect, keyhole porosity, and sub-grain cellular microstructure were examined and quantified to correlate to LPBF parameters. A simple empirical model was postulated to relate relative sample density and LPBF volumetric energy density. Melt pool dimensions were quantitatively measured and compared to estimations based on Rosenthal solution, which yielded a good agreement with the width, but underestimated the depth, particularly at high energy input, due to lack of consideration for keyhole mode. In addition, the sub-grain cellular-dendritic microstructure in the as-built samples was observed to decrease with increasing laser scan speed. Quantification of the sub-micron cellular-dendritic microstructure yielded estimated cooling rate in the order of 105–107 K/s.

Effect of Process Parameters on Melt Pool Geometry in Laser Powder Bed Fusion of Metals: A Numerical Investigation

Numerical simulation of melt pool behavior during laser powder bed fusion (LPBF) is essential to provide more effective control of the process and choose an optimal set of input parameters for defect-free fabrication. In this work, we use the smoothed particle hydrodynamics (SPH) method to investigate the impact of laser power and scan speed on the melt pool geometry in LPBF. The developments here follow the state-of-the-art numerical algorithms for implementing the most relevant physical phenomena in the melt pool region, such as recoil pressure and Marangoni surface tension forces. 3D simulation results for a single-track LPBF process are reported, analyzing the sensitivity of the melt pool geometry to laser power and scan speed.

Multiphysics Modeling of Thermal Behavior, Melt Pool Geometry, and Surface Topology During Laser Additive Manufacturing

Multiphysics Modeling of Thermal Behavior, Melt Pool Geometry, and Surface Topology During Laser Additive Manufacturing

Validated dimensionless scaling law for melt pool width in laser powder bed fusion

The melting process during laser powder bed fusion (LPBF) is accompanied by complex physical phenomena, which can be rarely scaled with acceptable effort to utilize the melting process in component design to obtain tailored mechanical properties with adequate machine productivity. A constitutive law relating melt pool geometry to the process parameters thereby plays an essential role in practically fostering machine productivity and component quality in LPBF. In this work, we derive an improved dimensionless scaling law based on dimensional analysis to characterize the melt pool width, which is also capable of scaling the beam-size-dependent laser attenuation. Measurements from LPBF-produced specimens and 3D phenomenological LPBF finite element simulations are also performed in batch to validate the derived law. The regression analysis presents the correlation ∼97–98% for the simulated melt pool widths and ∼70–90% for experimental measured ones, with fabricated minimum strut thickness of 113 μm. After scaling the effective laser power with the calibrated laser attenuation, the proposed scaling law can be extended to be beam-size independent, as demonstrated by the regression of overall experimental measurements and simulation results, performed under different laser beam diameter, to the unified law with correlation ≥97%. It demonstrates the feasibility of proposed scaling law in melt pool controlled LPBF manufacturing for designing and producing thin-walled components with strut thicknesses in the micrometer range.

In situ absorption synchrotron measurements, predictive modeling, microstructural analysis, and scanning probe measurements of laser melted Ti-6Al-4V single tracks for additive manufacturing applications

In this work, the fundamental processing-structure-property (PSP) relationships that govern laser-based additive manufacturing were investigated with the Ti-6Al-4V alloy. X-ray synchrotron imaging carried out in conjunction with in-situ integrating sphere radiometry enabled real-time energy absorption measurements for a range of melting conditions that varied laser power and velocity. A thermal conduction model that incorporated the in-situ absorption data and final melt pool geometry was used to predict the thermal histories and diffusion distances along the heat-affected zone (HAZ) in the Ti-6Al-4V alloy to provide insight into the solid-state phase transformations that occurred in the unmelted regions adjacent to the melt pool. Resulting microstructural features were quantified using scanning electron microscopy techniques to elucidate changes in solidification behavior. Significant changes to α/β-Ti phase fractions were measured in the unmelted HAZ, across all test cases. Nanoindentation and scanning probe microscopy revealed differences in the hardness, modulus, and Volta potential across the resolidified melt pool, HAZ, and wrought base material. These measurements and simulations can be used to predict how processing changes lead to differences in the as-built performance of titanium parts that are used in aerospace and biomedical applications. This work demonstrates the utility of coupling in-situ absorption data with a conduction-only high speed model, which leads reasonable agreement with the synchrotron imaging measurements and microstructural transformations observed herein.

Selective Laser Melting of Pre-Alloyed NiTi Powder: Single-Track Study and FE Modeling with Heat Source Calibration.

Unique functional properties such as the low stiffness, superelasticity, and biocompatibility of nickel–titanium shape-memory alloys provide many applications for such materials. Selective laser melting of NiTi enables low-cost customization of devices and the manufacturing of highly complex geometries without subsequent machining. However, the technology requires optimization of process parameters in order to guarantee high mass density and to avoid deterioration of functional properties. In this work, the melt pool geometry, surface morphology, formation mode, and thermal behavior were studied. Multiple combinations of laser power and scanning speed were used for single-track preparation from pre-alloyed NiTi powder on a nitinol substrate. The experimental results show the influence of laser power and scanning speed on the depth, width, and depth-to-width aspect ratio. Additionally, a transient 3D FE model was employed to predict thermal behavior in the melt pool for different regimes. In this paper, the coefficients for a volumetric double-ellipsoid heat source were calibrated with bound optimization by a quadratic approximation algorithm, the design of experiments technique, and experimentally obtained data. The results of the simulation reveal the necessary conditions of transition from conduction to keyhole mode welding. Finally, by combining experimental and FE modeling results, the optimal SLM process parameters were evaluated as P = 77 W, V = 400 mm/s, h = 70 μm, and t = 50 μm, without printing of 3D samples.

Effects of melt convection on stray grain formation in single crystal superalloys during directed energy deposition

During laser repairing of Ni-based single crystal (SX) superalloys, stray grain (SGs) formation leads to a deterioration of high-temperature properties and hot cracking. The main goal is to prevent SGs formation from forming, which controls the local solidification front thermal gradient ( G ) and solidification velocity ( V ). Meanwhile, the melt pool geometry, which is influenced by melt convection, has a significant impact on G and V . Here, experiments and theoretical calculations were used to study the evolution of the melt pool geometry during melt convection and its effects on the formation of SGs. Melt convection, i.e., Marangoni convection, outperformed thermal conduction in the SX superalloys melt pool during directed energy deposition, as evidenced by the estimated Peclet number and Prandtl number. The integrative impact of laser power, scan velocity, and beam diameters exacerbated Marangoni convection as the laser energy density distribution increased. Marangoni convection caused the melt pool shape to change from a near-semicircle to an undulating morphology, promoting the oriented-to-misoriented crystal growth transition and resulting in high stray grain sensitivity. The heat and mass transport in front of the dendrite tips was altered by Marangoni convection, which aggravated the deviation of the epitaxial dendrite orientation with respect to the substrate. This work provides an in-depth insight into controlling SG formation during additive manufacturing of SX superalloys. • The melt pool geometry transformed from a near semicircle to an undulating morphology by Marangoni convection. • The interaction between the thermal conduction and thermal convection was calculated for SX superalloys. • The mechanism of the melt pool geometry evolution resulting from Marangoni convection was proposed. • Marangoni convection promoted the oriented-to-misoriented transition leading to high sensitivity of stray grains. • Marangoni convection aggravated the epitaxial growth deviation by altering the heat and mass transfer.

Sensitivity of additively manufactured AA7075 to variation in feedstock composition and print parameters

We developed a combined finite element and CALPHAD based model of the Laser Powder Bed Fusion (LPBF) process for AA7075 alloy that considers the effect of feedstock composition and print parameters. A single-pass of a laser on a layer of AA7075 alloy powder has been considered. Sensitivity of temperature evolution and melt pool geometry to variation in the stoichiometry of the feedstock powder and laser source characteristics have been studied. Our results indicate that deviation (up to 10%) of the feedstock composition from the AA7075 raises the maximum temperature and increases melt pool size. Excess Cu content shows the largest melt pool width and depth among all the cases. The peak temperature is higher than the standard feedstock composition in all cases, except when the Cu concentration is reduced. Increasing the scan power also results in a higher peak temperature and a larger melt pool size. Furthermore, the temperature's rise time increases by lowering the scan speed.

Bayesian inverse uncertainty quantification of a MOOSE-based melt pool model for additive manufacturing using experimental data

Additive manufacturing (AM) technology is being increasingly adopted in a wide variety of application areas due to its ability to rapidly produce, prototype, and customize designs. AM techniques afford significant opportunities in regard to nuclear materials, including an accelerated fabrication process and reduced cost. High-fidelity modeling and simulation (M&S) of AM processes is being developed in Idaho National Laboratory (INL)’s Multiphysics Object-Oriented Simulation Environment (MOOSE) to support AM process optimization and provide a fundamental understanding of the various physical interactions involved. In this paper, we employ Bayesian inverse uncertainty quantification (UQ) to quantify the input uncertainties in a MOOSE-based melt pool model for AM. Inverse UQ is the process of inversely quantifying the input uncertainties while keeping model predictions consistent with the measurement data. The inverse UQ process takes into account uncertainties from the model, code, and data while simultaneously characterizing the uncertain distributions in the input parameters–rather than merely providing best-fit point estimates. We employ measurement data on melt pool geometry (lengths and depths) to quantify the uncertainties in several melt pool model parameters. Simulation results using the posterior uncertainties have shown improved agreement with experimental data, as compared to those using the prior nominal values. The resulting parameter uncertainties can be used to replace expert opinions in future uncertainty, sensitivity, and validation studies.

Laser spot size and scaling laws for laser beam additive manufacturing

Laser powder bed fusion (L-PBF) additive manufacturing (AM) requires the careful selection of laser process parameters for each feedstock material and machine, which is a laborious process. Scaling laws based on the laser power, speed, and spot size; melt pool geometry; and thermophysical properties can potentially reduce this effort by transferring knowledge from one material and/or laser system to another. Laser spot size is one critical parameter that is less well studied for scaling laws compared to laser power and scan speed. Consequently, single track laser scans were generated with a spot size (D4σ) range of 50 μm to 322 μm and melt pool aspect ratio (depth over spot radius) range from 0.1 to 7.0. These were characterized by in-situ thermography, cross-sectioning, and optical microscopy. Scaling laws from literature were applied and evaluated based on melt pool depth predictions. Scaling laws that contain a minimum of three dimensionless parameters and account for changing absorption between conduction and keyhole mode provide the most accurate melt pool depth predictions (<35% difference from experiments), which is comparable to thermal simulation results from literature for a select number of cases.

An Efficient Track-Scale Model for Laser Powder Bed Fusion Additive Manufacturing: Part 1- Thermal Model

This is the first of two manuscripts that presents a computationally efficient full field deterministic model for laser powder bed fusion (LPBF). A new Hybrid Line (HL) heat input model integrates an exponentially decaying (ED) heat input over a portion of a laser path to significantly reduce the computational time. Experimentally measured properties of the high gamma prime nickel-based superalloy RENÉ 65 are implemented in the model to predict the in-process temperature distribution, stresses, and distortions. The model accounts for specific properties of the material as different phases. The first manuscript presents the HL heat transfer model, which is compared with the beam-scale exponentially decaying model, along with the melt pool geometry obtained experimentally by varying the laser parameters. The predicted melt pool geometry of the beam-scale ED model is shown to have good agreement with experimental measurements. While the proposed HL model exhibits lesser accuracy in predicting the melt pool geometries, it can predict the cooling rates and nodal temperatures as accurately as to the ED model. Moreover, under large time integration steps, the HL model becomes more than 1,500 times faster than the ED model.

A Bayesian Approach to the Eagar–Tsai Model for Melt Pool Geometry Prediction with Implications in Additive Manufacturing of Metals

A Bayesian Approach to the Eagar–Tsai Model for Melt Pool Geometry Prediction with Implications in Additive Manufacturing of Metals