Controlling grain nucleation and morphology by laser beam shaping in metal additive manufacturing
Not Available
36 MATERIALS SCIENCE↗
SEARCH · Engineering Papers
Results for “laser manufacturing”
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Method for Rapid Modeling of Distortion in Laser Powder Bed Fusion Metal Additive Manufacturing Parts
The simulation and modeling of part-level distortion and residual stress in diverse metal additive manufacturing (AM) geometries has great potential to enable the rapid adoption of this technology in engineering design. Moreover, the use of additive manufacturing component libraries (CLs) offer a computationally efficient means of quantifying these part-level defects resultant from AM processing. We report on how the individual simulations of simple shapes, potential entries in a CL, can be superimposed to provide an indication of distortion and residual stresses in complex geometries. Laser powder bed fusion AM was used to construct test geometries of varied shapes and their combinations in the form of CLs in an effort to characterize location-dependent and feature-dependent distortion distributions. Blue light scanning was used to experimentally measure 3D distortions in order to investigate the interaction between the component shapes and local boundary conditions. Overall, part-level distortions were highly dependent on test component geometry, local boundary conditions, and shape combination. Commercial finite element software was used to verify experimental trends and to make predictions of distortion. The use of CLs resulted in over 20 times savings in computational cost while reproducing overall trends in distortion for test geometry assemblies. Therefore, it is anticipated that the use of CLs for L-PBF AM geometries has demonstrated potential to facilitate efficient simulations of full component AM assemblies, thereby reducing the need for costly trial-and-error-type experimental analysis.
36 MATERIALS SCIENCE↗
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 μm, 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.
36 MATERIALS SCIENCE↗
Melt pool temperature measurement and monitoring during laser powder bed fusion based additive manufacturing via single-camera two-wavelength imaging pyrometry (STWIP)
Melt pool (MP) temperature is one of the determining factors and a key signature for evaluating the properties of printed components in metal additive manufacturing (AM). The state-of-the-art measurement systems are hindered, primarily by the large-scale data acquisition and processing demands. In this work, we introduce a novel coaxial, high-speed, single-camera two-wavelength imaging pyrometer (STWIP) system as opposed to the typical utilization of multiple cameras for measuring MP temperature profiles in laser powder bed fusion (LPBF) processes. Developed on a commercial LPBF machine (EOS M290), the STWIP system demonstrated its ability to quantitatively monitor the MP temperature and its variation for 50 layers at high framerates (>30,000 fps) for a real-world application (standard fatigue specimens) print. High performance computing is employed to analyze the acquired big data (MP images), for determining each MP's average temperature and 2D temperature profile. The MP temperature evolution in the gage section of a fatigue specimen is also examined at a temporal resolution of 1 ms, by evaluating the MP temperatures in the samples' first, middle, and last layers. This report is the first of its kind on monitoring MP temperature distribution and evolution at such a large, detailed scale for longer durations in practical applications.
42 ENGINEERING↗
Laser diagnostics to characterize the in-flame growth of platinum nanoparticles manufactured by the reactive spray deposition technology
Reactive Spray Deposition Technology (RSDT) is an atmospheric pressure, flame-based advanced manufacturing method used to fabricate Membrane Electrode Assemblies (MEAs) for proton exchange fuel cells and water electrolyzers. RSDT combines the flame synthesis of catalyst nanoparticles and their deposition onto the membrane in one step. The properties of the synthesized nanoparticles, such as their Size Distribution Function (SDF), determine the manufactured electrodes’ performance, which can be evaluated when the deposition is complete via ex-situ characterization of the products. Efforts to improve RSDT for manufacturing state-of-the-art MEAs can be significantly enhanced with integrated laser diagnostics that enable in situ measurement of the synthesized catalyst nanoparticles. This paper reports the implementation of laser diagnostics in an RSDT facility and evaluates their potential to assist the manufacturing process. Laser Light Scattering (LS) and Laser-Induced Incandescence (LII) measurements are performed in the oxygen-rich zone of the flame at various distances from the flame fuel jet nozzle downstream of its luminous region. The measurements quantitatively track the evolution in size and volume fraction of platinum-based nanoparticles in two flames that yield different catalytic properties in the manufactured electrodes. The profiles of the measured nanoparticles’ volume fraction along the flame axis can be estimated a priori so that the average nanoparticle sizes can be measured in quasi-real time via LS. Nanoparticles experience an extremely slow growth rate while being convected at distances from 150 nm to 300 nm from the fuel nozzle. Complementary characterizations of the synthesized nanoparticles are performed ex-situ via High-Angle Annular Darkfield Scanning Transmission Electron Microscopy (HAADF-STEM) image analyses of samples collected on grids at a fixed distance from the fuel jet nozzle. Comparing the results from laser and microscopy techniques not only cross-validates the findings but also provides the parameters to infer the bimodal SDF in-situ and yields evidence that the coagulation efficiency of the synthesized nanoparticles has extremely low values in the investigated zone of the flames.
Rayleigh Light Scattering (LS)↗
"Sintering" Models and In-Situ Experiments: Data Assimilation for Microstructure Prediction in SLS Additive Manufacturing of Nylon Components
Selective laser sintering methods are workhorses for additively manufacturing polymer-based components. The ease of rapid prototyping also means it is easy to produce illicit components. It is necessary to have a data-calibrated in-situ physical model of the build process in order to predict expected and defective microstructure characteristics that inform component provenance. Toward this end, sintering models are calibrated and characteristics such as component defects are explored. This is accomplished by assimilating multiple data streams, imaging analysis, and computational model predictions in an adaptive Bayesian parameter estimation algorithm. From these data sources, along with a phase-field model, bulk porosity distributions are inferred. Model parameters are constrained to physically-relevant search directions by sensitivity analysis, and then matched to predictions using adaptive sampling. Using this feedback loop, data-constrained estimates of sintering model parameters along with uncertainty bounds are obtained.
3D printing, Additive Manufacturing, polymer, sint↗
Method for fabricating zig-zag slabs for solid state lasers
A method for batch manufacturing of slabs for zig-zag lasers including steps of bonding two non-active media to either side of an active medium to form a sandwich, dicing the sandwich to provide slices, rendering two surfaces of each slice into total-internal-reflection (TIR) surfaces, and then dicing the slices perpendicular to the TIR surfaces to provide a plurality of zig-zag slabs.
Sridharan, Arun Kumar↗
A 3D Printable Alloy Designed for Extreme Environments
Multiprincipal-element alloys are an enabling class of materials owing to their impressive mechanical and oxidation-resistant properties, especially in extreme environments. Here we develop a new oxide-dispersion-strengthened NiCoCr-based alloy using a model-driven alloy design approach and laser-based additive manufacturing. This oxide-dispersion-strengthened alloy, called GRX-810, uses laser powder bed fusion to disperse nanoscale Y 2 O 3 particles throughout the microstructure without the use of resource-intensive processing steps such as mechanical or in situ alloying. We show the successful incorporation and dispersion of nanoscale oxides throughout the GRX-810 build volume via high-resolution characterization of its microstructure. The mechanical results of GRX-810 show a twofold improvement in strength, over 1,000-fold better creep performance and twofold improvement in oxidation resistance compared with the traditional polycrystalline wrought Ni-based alloys used extensively in additive manufacturing at 1,093 °C. The success of this alloy highlights how model-driven alloy designs can provide superior compositions using far fewer resources compared with the ‘trial-and-error’ methods of the past. These results showcase how future alloy development that leverages dispersion strengthening combined with additive manufacturing processing can accelerate the discovery of revolutionary materials.
Timothy M. Smith↗
Detection of Part Porosity in Additive Manufacturing Using Machining
Monitoring of part porosity in additive manufacturing is critical for part qualification and process parameter development. This article describes the monitoring of porosity in additive manufacturing using machining. Grade 91 steel samples with different levels of porosity were additively manufactured using a laser blown-powder process. The samples were machined, and the tool position and cutting power were monitored using the machine controller and an external power transducer, respectively. Results show that the power transducer is sensitive to machining porosities. A novel approach using the standard deviation of cutting power was developed to determine the location of porosities along the length of the machining pass. Test cuts were completed at different machining process parameters. Results showed that the probability of detection was one for pore volume greater than 0.3 mm 3 at different machining parameters. In conclusion, although the detection of porosity using machining is a destructive method for evaluation, it offers a low-cost and fast approach for monitoring porosity in additive manufacturing.
36 MATERIALS SCIENCE↗
Selective laser melting of 304L stainless steel: Role of volumetric energy density on the microstructure, texture and mechanical properties
The role of volumetric energy density on the microstructural evolution, texture and mechanical properties of 304L stainless steel parts additively manufactured via selective laser melting process is investigated. 304L is chosen because it is a potential candidate to be used as a matrix in a metal matrix composite with nanoparticles dispersion for energy and high temperature applications. The highest relative density of 99 %±0.5 was achieved using a volumetric energy density of 1400 J/mm 3 . Both XRD analysis and Scheil simulation revealed the presence of a small trace of the delta ferrite phase, due to rapid solidification within the austenitic matrix of 304L. Here, a fine cellular substructure ranged between 0.4–1.8 μm, was detected across different energy density values. At the highest energy density value, a strong texture in the direction of [100] was identified. At lower energy density values, multicomponent texture was found due to high nucleation rate and the existing defects. Yield strength, ultimate tensile strength, and microhardness of samples with a relative density of 99 % were measured to be 540 ± 15 MPa, 660 ± 20 MPa and 254 ± 7 HV, respectively and higher than mechanical properties of conventionally manufactured 304L stainless steel. Heat treatment of the laser melted 304L at 1200 °C for 2 h, resulted in the nucleation of recrystallized equiaxed grains followed by a decrease in microhardness value from 233 ± 3 HV to 208 ± 8 HV due to disappearance of cellular substructure.
304L stainless steel↗
Compensating for Sintering Distortion in Additively Manufactured Shaped Charge Liners using Physics-Informed Machine Learning
Copper is a challenging material to process using laser-based additive manufacturing due to its high reflectivity and high thermal conductivity. Sintering-based processes can produce solid copper parts without the processing challenges and defects associated with laser melting; however, sintering can also cause distortion in copper parts, especially those with thin walls. In this study, we use physics-informed Gaussian process regression to predict and compensate for sintering distortion in thin-walled copper parts produced using a Markforged Metal X bound powder extrusion (BPE) additive manufacturing system. Through experimental characterization and computational simulation of copper’s viscoelastic sintering behavior, we can predict sintering deformation. We can then manufacture, simulate, and test parts with various compensation scaling factors to inform Gaussian process regression and predict a compensated as-printed (pre-sintered) part geometry that produces the desired final (post-sintered) part.
36 MATERIALS SCIENCE↗
Thermo-Mechanical Modeling and Evaluation of the Cracking Response of Additively Manufactured Monolithic SiC Lattice Structures Subjected to Laser Heating
Increasing operating temperatures of solar receivers is paramount to the efficiency of concentrated solar thermal (CST) and solar power (CSP) systems. Owing to its high temperature stability combined with excellent thermal and optical properties, SiC has been the material of choice for application in high-temperature solar receivers. The state-of-the-art SiC volumetric concentrating solar air receivers such as honeycomb design have been demonstrated in field tests to achieve exit air temperatures approaching 800oC. However, successful application of CST systems for decarbonization requires significant increase in temperature capability of SiC receiver technology. Supported by an award from the Solar Technology Office (SETO), US Department of Energy (DOE), GE Research in collaboration with Heliogen Holdings Inc, is engaged in the development of ultra-High Operating Temperature SiC-matrix Solar Thermal Air Receiver (HOTSSTAR) enabled by additive manufacturing. The program objective is to design and to demonstrate a techno-economically viable SiC air receiver technology to achieve exit air temperature of 1100oC for CST applications. This report summarizes the learnings of a computational study on additively manufactured SiC lattice structures subjected to laser heating. The results from this study aim to help guide the design of a SiC receiver through a better understanding of lattice structure geometric parameters and their implications on the cracking response of the structure. In the study, a heat flux was applied to the surface of a 2”-diameter cylindrical lattice structure to simulate a 4kW CO2 laser. The resulting temperature distribution was applied to a structural model to approximate the stress distribution within the lattice structure and a Weibull analysis was performed to gain insight into the probability of failure and to evaluate the cracking response of the structure. With this approach, the influence of lattice density on temperature, stress, and probability of failure was explored for two different lattice beam spacings. A discussion on modeling assumptions, a comparison with experimental results, and an evaluation of the lattice cracking response is provided.
14 SOLAR ENERGY↗
A Novel Laser 3D Printing Method for the Advanced Manufacturing of Protonic Ceramics
Protonic ceramics (PCs) with high proton conductivity at intermediate temperatures (300–600 °C) have attracted many applications in energy conversion and storage devices such as PC fuel/electrolysis cells, PC membrane reactors, hydrogen pump, hydrogen or water-permeable membranes, and gas sensors. One of the essential steps for fulfilling the practical utilization of these intermediate-temperature PC energy devices is the successful development of advanced manufacturing methods for cost-effectively and rapidly fabricating them with high energy density and efficiency in a customized demand. In this work, we developed a new laser 3D printing (L3DP) technique by integrating digital microextrusion-based 3D printing and precise and rapid laser processing (sintering, drying, cutting, and polishing), which showed the capability of manufacturing PCs with desired complex geometries, crystal structures, and microstructures. The L3DP method allowed the fabrication of PC parts such as pellets, cylinders, cones, films, straight/lobed tubes with sealed endings, microchannel membranes, and half cells for assembling PC energy devices. The preliminary measurement of the L3DP electrolyte film showed a high proton conductivity of ≈7 × 10−3 S/cm. This L3DP technique not only demonstrated the potential to bring the PCs into practical use but also made it possible for the rapid direct digital manufacturing of ceramic-based devices.
08 HYDROGEN↗
Processing parameters in laser powder bed fusion metal additive manufacturing
Not Available
Oliveira, J. P.↗
Grain nucleation from nanosecond laser induced cavitation instabilities in additive manufacturing melt pools
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Abere, Michael Joseph Kim↗
Laser Powder Bed Fusion (PBF) Additive Manufacturing (AM) of Polymethylpentene(PMP) Analyzing the Impact of Scan Strategy on the Powder Bed Fusion Process [Poster]
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McPhillips, Declan [Savannah River National Labora↗