Multiphysics simulation of single pulse laser powder bed fusion: comparison of front capturing and front tracking methods

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yaasin Abraham Mayi ◽  
Alexis Queva ◽  
Morgan Dal ◽  
Gildas Guillemot ◽  
Charlotte Metton ◽  
...  
Keyword(s):  
Numerical Models ◽  
Single Pulse ◽  
Front Tracking ◽  
Powder Bed Fusion ◽  
Arbitrary Lagrangian Eulerian ◽  
Laser Powder Bed Fusion ◽  
Content Type ◽  
Powder Bed ◽  
Melt Pool ◽  
Tracking Model

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

Camera signal dependencies within coaxial melt pool monitoring in laser powder bed fusion

2020 ◽  
Vol 26 (1) ◽  
pp. 100-106 ◽  
Author(s):  
Tobias Kolb ◽  
Reza Elahi ◽  
Jan Seeger ◽  
Mathews Soris ◽  
Christian Scheitler ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Layer Thickness ◽  
Powder Layer ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Content Type ◽  
Powder Bed ◽  
Sensory Signals ◽  
Melt Pool ◽  
Research Activities

Purpose The purpose of this paper is to analyse the signal dependency of the camera-based coaxial monitoring system QMMeltpool 3D (Concept Laser GmbH, Lichtenfels, Germany) for laser powder bed fusion (LPBF) under the variation of process parameters, position, direction and layer thickness to determine the capability of the system. Because such and similar monitoring systems are designed and presented for quality assurance in series production, it is important to present the dominant signal influences and limitations. Design/methodology/approach Hardware of the commercially available coaxial monitoring QMMeltpool 3D is used to investigate the thermal emission of the interaction zone during LPBF. The raw images of the camera are analysed by means of image processing to bypass the software of QMMeltpool 3D and to gain a high level of signal understanding. Laser power, scan speed, laser spot diameter and powder layer thickness were varied for single-melt tracks to determine the influence of a parameter variation on the measured sensory signals. The effects of the scan direction and position were also analysed in detail. The influence of surface roughness on the detected sensory signals was simulated by a machined substrate plate. Findings Parameter variations are confirmed to be detectable. Because of strong directional and positional dependencies of the melt-pool monitoring signal a calibration algorithm is necessary. A decreasing signal is detected for increasing layer thickness. Surface roughness is identified as a dominating factor with major influence on the melt-pool monitoring signal exceeding other process flaws. Research limitations/implications This work was performed with the hardware of a commercially available QMMeltpool 3D system of an LPBF machine M2 of the company Concept Laser GmbH. The results are relevant for all melt-pool monitoring research activities connected to LPBF, as well as for end users and serial production. Originality/value Surface roughness has not yet been revealed as being one of the most important origins for signal deviations in coaxial melt-pool monitoring. To the best of the authors’ knowledge, the direct comparison of influences because of parameters and environment has not been published to this extent. The detection, evaluation and remelting of surface roughness constitute a plausible workflow for closed-loop control in LPBF.

scholarly journals Thermographic measurements of the commercial laser powder bed fusion process at NIST

2016 ◽  
Vol 22 (5) ◽  
pp. 778-787 ◽  
Author(s):  
Brandon Lane ◽  
Shawn Moylan ◽  
Eric P. Whitenton ◽  
Li Ma
Keyword(s):  
Process Monitoring ◽  
High Speed ◽  
Frame Rate ◽  
High Magnification ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Content Type ◽  
Powder Bed ◽  
Temperature Range ◽  
Melt Pool

Purpose Quantitative understanding of the temperatures, gradients and heating/cooling rates in and around the melt pool in laser powder bed fusion (L-PBF) is essential for simulation, monitoring and controls development. The research presented here aims to detail experiment design and preliminary results of high speed, high magnification, in-situ thermographic monitoring setup on a commercial L-PBF system designed to capture temperatures and dynamic process phenomena. Design/methodology/approach A custom door with angled viewport was designed for a commercial L-PBF system which allows close access of an infrared camera. Preliminary finite element simulations provided size, speed and scale requirements to design camera and optics setup to capture melt pool region temperatures at high magnification and frame rate speed. A custom thermal calibration allowed maximum measurable temperature range of 500°C to 1,025°C. Raw thermographic image data were converted to temperature assuming an emissivity of 0.5. Quantitative temperature results are provided with qualitative observations with discussion regarding the inherent challenges to future thermographic measurements and process monitoring. Findings Isotherms around the melt pool change in size depending on the relative location of the laser spot with respect to the stripe edges. Locations near the edges of a stripe are cooled to lower temperatures than the center of a stripe. Temperature gradients are highly localized because of rough or powdery surface. At a specific location, temperatures rise from below the measurable temperature range to above (<550°C to >1100°C) within two frames (<1.11 m/s). Particle ejection is a notable phenomenon with measured ejection speeds >11.7 m/s. Originality/value Several works are detailed in the Introduction of this paper that detail high-speed visible imaging (not thermal imaging) of custom or commercial LBPF processes, and lower-speed thermographic measurements for defect detection. However, no work could be found that provides calibrated, high-speed temperature data from a melt-pool monitoring configuration on a commercial L-PBF system. In addition, the paper elucidates several sources of measurement uncertainty (e.g. calibration, emissivity and time and spatial resolution), describes inherent measurement challenges based on observations of the thermal images and discusses on the implications to model validation and process monitoring and control.

scholarly journals Optimization of Laser Powder Bed Fusion Processing Using a Combination of Melt Pool Modeling and Design of Experiment Approaches: Density Control

2019 ◽  
Vol 3 (1) ◽  
pp. 21 ◽  
Author(s):  
Morgan Letenneur ◽  
Alena Kreitcberg ◽  
Vladimir Brailovski
Keyword(s):  
Scanning Speed ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Density Prediction ◽  
Melt Pool ◽  
Density Control ◽  
Pool Model ◽  
Conventional Material ◽  
Prediction Approach

A simplified analytical model of the laser powder bed fusion (LPBF) process was used to develop a novel density prediction approach that can be adapted for any given powder feedstock and LPBF system. First, calibration coupons were built using IN625, Ti64 and Fe powders and a specific LPBF system. These coupons were manufactured using the predetermined ranges of laser power, scanning speed, hatching space, and layer thickness, and their densities were measured using conventional material characterization techniques. Next, a simplified melt pool model was used to calculate the melt pool dimensions for the selected sets of printing parameters. Both sets of data were then combined to predict the density of printed parts. This approach was additionally validated using the literature data on AlSi10Mg and 316L alloys, thus demonstrating that it can reliably be used to optimize the laser powder bed metal fusion process.

A Physics-Informed Two-Level Machine Learning Model for Predicting Melt-Pool Size in Laser Powder Bed Fusion

2021 ◽  
Author(s):  
Yong Ren ◽  
Qian Wang ◽  
Panagiotis (Pan) Michaleris
Keyword(s):  
Machine Learning ◽  
Initial Temperature ◽  
Pool Size ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Input Feature ◽  
Melt Pool Size ◽  
Melt Pool Characteristics

Abstract Laser powder bed fusion (L-PBF) additive manufacturing (AM) is one type of metal-based AM process that is capable of producing high-value complex components with a fine geometric resolution. As melt-pool characteristics such as melt-pool size and dimensions are highly correlated with porosity and defects in the fabricated parts, it is crucial to predict how process parameters would affect the melt-pool size and dimensions during the build process to ensure the build quality. This paper presents a two-level machine learning (ML) model to predict the melt-pool size during the scanning of a multi-track build. To account for the effect of thermal history on melt-pool size, a so-called (pre-scan) initial temperature is predicted at the lower-level of the modeling architecture, and then used as a physics-informed input feature at the upper-level for the prediction of melt-pool size. Simulated data sets generated from the Autodesk's Netfabb Simulation are used for model training and validation. Through numerical simulations, the proposed two-level ML model has demonstrated a high prediction performance and its prediction accuracy improves significantly compared to a naive one-level ML without using the initial temperature as an input feature.

A printability assessment framework for fabricating low variability nickel-niobium parts using laser powder bed fusion additive manufacturing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bing Zhang ◽  
Raiyan Seede ◽  
Austin Whitt ◽  
David Shoukr ◽  
Xueqin Huang ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Uncertainty Quantification ◽  
Process Optimization ◽  
Powder Bed Fusion ◽  
Assessment Framework ◽  
Laser Powder Bed Fusion ◽  
Content Type ◽  
Powder Bed ◽  
Analytical Thermal Model

Purpose There is recent emphasis on designing new materials and alloys specifically for metal additive manufacturing (AM) processes, in contrast to AM of existing alloys that were developed for other traditional manufacturing methods involving considerably different physics. Process optimization to determine processing recipes for newly developed materials is expensive and time-consuming. The purpose of the current work is to use a systematic printability assessment framework developed by the co-authors to determine windows of processing parameters to print defect-free parts from a binary nickel-niobium alloy (NiNb5) using laser powder bed fusion (LPBF) metal AM. Design/methodology/approach The printability assessment framework integrates analytical thermal modeling, uncertainty quantification and experimental characterization to determine processing windows for NiNb5 in an accelerated fashion. Test coupons and mechanical test samples were fabricated on a ProX 200 commercial LPBF system. A series of density, microstructure and mechanical property characterization was conducted to validate the proposed framework. Findings Near fully-dense parts with more than 99% density were successfully printed using the proposed framework. Furthermore, the mechanical properties of as-printed parts showed low variability, good tensile strength of up to 662 MPa and tensile ductility 51% higher than what has been reported in the literature. Originality/value Although many literature studies investigate process optimization for metal AM, there is a lack of a systematic printability assessment framework to determine manufacturing process parameters for newly designed AM materials in an accelerated fashion. Moreover, the majority of existing process optimization approaches involve either time- and cost-intensive experimental campaigns or require the use of proprietary computational materials codes. Through the use of a readily accessible analytical thermal model coupled with statistical calibration and uncertainty quantification techniques, the proposed framework achieves both efficiency and accessibility to the user. Furthermore, this study demonstrates that following this framework results in printed parts with low degrees of variability in their mechanical properties.

Measurement of the Melt Pool Length During Single Scan Tracks in a Commercial Laser Powder Bed Fusion Process

2017 ◽  
Author(s):  
J. C. Heigel ◽  
B. M. Lane
Keyword(s):  
Laser Power ◽  
High Speed ◽  
Infrared Camera ◽  
Powder Bed Fusion ◽  
Single Track ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Significant Difference ◽  
Scan Speed

This work presents high speed thermographic measurements of the melt pool length during single track laser scans on nickel alloy 625 substrates. Scans are made using a commercial laser powder bed fusion machine while measurements of the radiation from the surface are made using a high speed (1800 frames per second) infrared camera. The melt pool length measurement is based on the detection of the liquidus-solidus transition that is evident in the temperature profile. Seven different combinations of programmed laser power (49 W to 195 W) and scan speed (200 mm/s to 800 mm/s) are investigated and numerous replications using a variety of scan lengths (4 mm to 12 mm) are performed. Results show that the melt pool length reaches steady state within 2 mm of the start of each scan. Melt pool length increases with laser power, but its relationship with scan speed is less obvious because there is no significant difference between cases performed at the highest laser power of 195 W. Although keyholing appears to affect the anticipated trends in melt pool length, further research is required.

scholarly journals A processing diagram for high-density Ti-6Al-4V by selective laser melting

2018 ◽  
Vol 24 (9) ◽  
pp. 1469-1478 ◽  
Author(s):  
Yinmin (Morris) Wang ◽  
Chandrika Kamath ◽  
Thomas Voisin ◽  
Zan Li
Keyword(s):  
Mechanical Properties ◽  
Energy Density ◽  
Processing Parameters ◽  
High Density ◽  
Low Density ◽  
Laser Powder Bed Fusion ◽  
Content Type ◽  
Powder Bed ◽  
Melt Pool ◽  
Hatch Spacing

Purpose Density optimization is the first critical step in building additively manufactured parts with high-quality and good mechanical properties. The authors developed an approach that combines simulations and experiments to identify processing parameters for high-density Ti-6Al-4V using the laser powder-bed-fusion technique. A processing diagram based on the normalized energy density concept is constructed, illustrating an optimized processing window for high- or low-density samples. Excellent mechanical properties are obtained for Ti-6Al-4V samples built from the optimized window. Design/methodology/approach The authors use simple, but approximate, simulations and selective experiments to design parameters for a limited set of single track experiments. The resulting melt-pool characteristics are then used to identify processing parameters for high-density pillars. A processing diagram is built and excellent mechanical properties are achieved in samples built from this window. Findings The authors find that the laser linear input energy has a much stronger effect on the melt-pool depth than the melt-pool width. A processing diagram based on normalized energy density and normalized hatch spacing was constructed, qualitatively indicating that high-density samples are produced in a region when 1 < E* < 2. The onset of void formation and low-density samples occur as E* moves beyond a value of 2. The as-built SLM Ti-6Al-4V shows excellent mechanical performance. Originality/value A combined approach of computer simulations and selected experiments is applied to optimize the density of Ti-6Al-4V, via laser powder-bed-fusion (L-PBF) technique. A series of high-density samples are achieved. Some special issues are identified for L-PBF processes of Ti-6Al-4V, including the powder particle sticking and part swelling issues. A processing diagram is constructed for Ti-6Al-4V, based on the normalized energy density and normalized hatch spacing concept. The diagram illustrates windows with high- and low-density samples. Good mechanical properties are achieved during tensile tests of near fully dense Ti-6Al-4V samples. These good properties are attributed to the success of density optimization processes.

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