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At least 505 records · Page 28

Feasibility of Using Additive Manufacturing to Produce Axial Flow Hydropower Turbine Housing, Runner, and Draft Tube

Oak Ridge National Laboratory (ORNL) worked with AMJET Turbine Systems, LLC (ATS), to demonstrate additive manufacturing of components for low head hydro turbine/generator applications. Several different types of additive manufacturing systems were used. Components were finished and assembled for testing in a turbine. However, one of the processes, Big Area Additive Manufacturing (BAAM),produced components that did not adequately perform due to persistent leaks that were caused by porosity in the parts produced. Therefore, the BAAM system was eliminated from contention. Vacuum infusion of rein into the parts eventually solved the porosity problem.Components were installed in anATS-8 turbine to be tested on the Keokuk Dam for operationally testing the unit.

13 HYDRO ENERGY↗

Crack mitigation in additively manufactured AlCrFe 2 Ni 2 high-entropy alloys through engineering phase transformation pathway

The far-from-equilibrium solidification during additive manufacturing often creates large residual stresses that induce solid-state cracking. Here we present a strategy to suppress solid-state cracking in an additively manufactured AlCrFe 2 Ni 2 high-entropy alloy via engineering phase transformation pathway. We investigate the solidification microstructures formed during laser powder-bed fusion and directed energy deposition, encompassing a broad range of cooling rates. At high cooling rates (10 4 –10 6 K/s), we observe a single-phase BCC/B2 microstructure that is susceptible to solid-state cracking. At low cooling rates (10 2 –10 4 K/s), FCC phase precipitates out from the BCC/B2 matrix, resulting in enhanced ductility (~10 %) and resistance to solid-state cracking. Site-specific residual stress/strain analysis reveals that the ductile FCC phase can largely accommodate residual stresses, a feature which helps relieve residual strains within the BCC/B2 phase to prevent cracking. Our work underscores the value of exploiting the toolbox of phase transformation pathway engineering for material design during additive manufacturing.

36 MATERIALS SCIENCE↗

Additively manufacturing high-temperature aluminum alloy for automotive engine pistons

The purpose of the project was to evaluate DuAlumin-3D, an ORNL designed Al alloy, for additive manufacturing of high-performance automotive components. The project consisted of additively manufacturing a cylindrical block of representative material which was then heat treated before machining into test coupons. Testing included tensile tests as a function of temperature, high-cycle fatigue testing as a function of temperature, density and elastic modulus measurements, and thermophysical property measurements. Fractography was also performed on failed high-cycle fatigue specimens. The results were compared against benchmark AM Al alloys and current high-performance conventionally manufactured alloys. Overall, the DuAlumin-3D material outperformed the incumbent materials in mechanical properties, especially at elevated temperatures, while maintaining broadly similar thermophysical properties. The results of this study support further maturation of the material for additive manufacturing of high-performance automotive components.

36 MATERIALS SCIENCE↗

Structural stability of thin overhanging walls during material extrusion additive manufacturing of thermoset-based ink

Recent developments have enabled material extrusion additive manufacturing of thermoset-based composite inks on the large scale. In addition, printing out-of-plane components is of broad interest to the polymer material extrusion community. Here, we address some of the challenges associated with both large-scale and out-of-plane thermoset material extrusion additive manufacturing by studying the height at which thin overhanging walls collapse. Walls at a range of overhang angles were printed until they collapsed. An optical camera captured the profile of each wall throughout the print, allowing the collapse height to be identified and the geometric fidelity to the programmed angle to be evaluated. Using previously measured rheological properties, predictive models were generated to approximate the collapse height and profile of the deflected walls. First, an analytical model was created to predict the height at which the walls would yield. The analytical model assumes the walls exhibit a perfectly linear profile; however, experiments proved this assumption to be false. Therefore, a finite element simulation was developed to account for the elastic deflection that occurs during printing. The finite element simulation predicts both the yield height and the deflected profile after the deposition of each layer. For the properties of the thermoset ink used here, the yield height predicted by the analytical model and finite element simulation are virtually identical. These predictions match experimental data reasonably well, but minor errors are observed. Accounting for the fully plastic moment appears to explain the small mismatch between experimental data and predictions. Additionally, the finite element simulation provides an excellent prediction of the deflected profile before the wall begins to collapse. Finally, by demonstrating that the collapse height and deflected profile of thin overhanging walls can be predicted, this work illustrates how the soft viscoelastic properties of thermoset-based composite inks limit the scale of a key feature required to print some nonplanar components. It also provides a basis to tailor in-process curing systems to suppress deflection and collapse of thin overhanging walls.

36 MATERIALS SCIENCE↗

Machinability comparison of additively manufactured and traditionally wrought Ti-6Al-4V alloys using single-point cutting

Post-machining is often needed to provide high dimensional accuracy and fine surface finish for additively manufactured Ti-6Al-4V (Ti64). The material inhomogeneity, such as pores and microstructures, can affect the machining behavior of this already difficult-machine alloy. This study adopts a holistic approach to compare the machinability of additively manufactured and traditionally wrought Ti64 in terms of key machining factors, including forces, temperature, and vibration and the major machining outcomes including tool life, surface finish, and dimensional accuracy. Stress-relief annealing is applied to each of the part conditions as a secondary variable to observe the additional effects. The results show that AM is not particularly more difficult to machine in terms of cutting force and temperature, but it creates high cutting vibrations across a wide range of frequencies (to and over 5 kHz). The high vibrations do not lead to worse surface finish or dimensional accuracy but tend to worsen the tool life by chipping off the cutting edge. The vibration can be attributed to the brittle martensitic microstructure found in additively manufactured Ti64, which is also evidenced by the more serrated chips. Stress-relieving is found to change the microstructure and reduce the level of vibration to that of the wrought counterpart.

36 MATERIALS SCIENCE↗

Additive manufacturing print-heads for exotic material applications

Described herein is an additive manufacturing apparatus that is well-suited for constructing piezoelectric sensors. The additive manufacturing apparatus includes an extrusion nozzle formed of a conductive material such as aluminum. The extrusion nozzle has a channel by way of which printing material exits the extrusion nozzle, wherein a build plate is configured to receive the printing material responsive to the printing material exiting the extrusion nozzle. An arc suppressor formed of a semiconductor is coupled to the extrusion nozzle and is configured to dissipate excess charge that would otherwise exist on the extrusion nozzle when a relatively high bias voltage is applied to the extrusion nozzle. Thus, the arc suppressor mitigates arcing between the extrusion nozzle and the build plate. Arc suppressing gas is also optionally introduced into a printing region, thereby further mitigating arcing between the extrusion nozzle and the build plate.

Washburn, Cody M.↗

Development of a Multi-physics Model to Optimize Continuous Liquid Interface Production (CLIP) for Additive Manufacturing (Carbon3D HPC4Mfg Final Report)

Continuous Liquid Interface Production (CLIP) is poised to bring additive manufacturing to multiple American manufacturing sectors owing to its unique combination of rapid print speeds and material options that resemble injection molding thermoplastics. In spite of these benefits, CLIP is still a maturing process. To improve our understanding and control of the process, this project developed a multi-physics computational model that encompasses the coupled chemical-physical processes of photopolymerization and fluid flow to predict part outcomes. A physically predictive model can enable rapid optimization of CLIP and reduce the current cycle time and waste associated with optimization by four-fold. Ultimately, this effort will help open the U.S. $400B plastic manufacturing industry to the key benefits of additive manufacturing, namely mass customization, unlimited design space, and a cost- and energy-effective path to mainstream manufacturing. In the course of the project we produced a model which coupled fluid-flow, species transport, and photochemistry to model the Carbon CLIP process. As the development proceeded, we validated the code against theory and experiments. The resulting code was transferred to Carbon, and we expect it to be a useful part of their modeling capability. Future work includes improvements to the fluid solver’s robustness and performance, along with the addition of additional physics models.

36 MATERIALS SCIENCE↗

Multi-physics modeling of grain growth during solidification in electron beam additive manufacturing of Inconel 718

While experimental work has shown promising results regarding control of additive manufacturing metal grain structure, the effects of processing parameters on the grain structure is difficult to understand and predict from experiment alone. To this end, a modeling framework is developed which sequentially couples a macro-scale, semi-analytic thermal model, and a meso-scale, cellular automata-based microstructure model. This framework is applied to electron beam additive manufacturing of Inconel 718 using a complex spot scan pattern. The model shows that, with the same scan pattern, variations in the spot time and electron-beam current produce thermal histories with significant spatial and temporal differences, which then produce complex solidification conditions from the interplay between molten pools in the same layer and subsequent layers, resulting in vastly different grain structures. Additionally, it is noted that the framework can significantly reduce the computational expenses for coupled thermal-metallurgical problems, and has the potential to be used for component level problems.

36 MATERIALS SCIENCE↗

Additively manufactured polymer composites for heat exchanger applications: evaluation of critical thermophysical properties

Polymeric heat exchangers (PHXs) have been used in applications involving weight restrictions, chemical compatibility, and fouling issues. Additive manufacturing (AM) or 3D printing provide new solutions to previously inaccessible combinations of properties and geometries. There are some advancements in the PHXs by AM; however, the process and the properties of materials still need further investigation to improve the overall performance. In this study, additively manufactured polyethylene terephthalate glycol (PETG) composites reinforced with graphite and pitch-based carbon fibers were evaluated for their potential application as PHXs. The thermal conductivity, volumetric heat capacity, coefficient of thermal expansion, creep behavior, and long-term performance were studied in detail. Our results reveal that the composites have an anisotropic thermal conductivity. The thermal conductivity along the printing direction is higher than the layer building direction due to the shear-induced alignment of the fillers. The printed composites achieve good thermal stability with 80% lower CTE at room temperature than neat PETG. Creep tests suggest the creep and creep recovery were highly temperature-dependent, and the deformation can be recovered when the temperature is below glass transition. These results suggest additive manufactured composites be potentially used for heat exchanger applications at low temperatures.

36 MATERIALS SCIENCE↗

Combined DSC/TGA Analysis to Rationalize the As-Sintered Microstructure in Binder Jet Additively Manufactured H13 Tool Steel

In this study, a combined DSC/TGA analysis has been used to rationalize the constant liquid channel width at higher sintering temperatures in H13 tool steel manufactured by binder jet additive manufacturing. Using enthalpy conservation along with coupled DSC + TGA analysis, the phase fractions of liquid and austenite phases during heating and cooling respectively were estimated. The estimates from the DSC/TGA analysis were compared with equilibrium phase fraction predictions from ThermoCalc. The resulting phase evolution was correlated to the as-sintered microstructure to rationalize the unexpected lack of change in liquid channel width at higher sintering temperatures.

Kannan, Rangasayee↗

Advanced Materials & Manufacturing Technology (AMMT): Development of Additive Manufacturing Agnostic Process Parameter Procedure, 316H Stainless Steel Readiness Level Data Sets, and Machine Maintenance Plan

The University of California, Davis is involved in a project to deploy and enhance an artificial intelligence (AI) system for predicting and preventing plasma disruptions on the DIII D tokamak, under the funding from Department of Energy DE-SC0023500 (title: AI/Deep Learning FRNN Software for Prediction & Real-Time Control of DIII-D Plasma Control System (PCS)). The overarching goal is to demonstrate that real-time, AI-guided intervention can proactively modify the plasma state to avoid or mitigate disruptions—a critical challenge for the future of fusion energy.

36 MATERIALS SCIENCE↗

Expansion of Additive Manufacturing Capabilities Into in Situ Alloying of Dispersion Strengthened, High Temperature Cu Alloys

New alloys and materials are potentially possible through additive manufacturing’s unique thermal history. Current literature explores the fabrication of eutectic and solid solution strengthened alloys through in-situ alloying, to take advantage of AM’s unique thermal history. The resulting lessons learned by in-situ alloying currently available materials will likely lead to the development of novel materials solely possible through in-situ alloying. This work will expand the application of in-situ alloying via additive manufacturing to NASA’s GRCop-42 (Cu-4at% Cr-2at% Nb), a high temperature copper alloy which has shown success in additively manufactured combustion chambers from pre-alloyed powders. GRCop-42 is unique to literature because a reaction to form the Cr2Nb dispersoids is required during the in-situ alloying. Both reaction completion rate and how input energy from the AM process influences the reaction progress will be evaluated. Ultimately, expansion of in-situ alloying capabilities provides further insight to develop novel materials using AM.

David Steven Scannapieco↗

Reclaimed Carbon Fiber Reinforced Automotive Part Using 3-DEP® Preforming Technology on Additive Manufacturing Tool Made with Reclaimed Carbon Fibers

The project focused on how well tools designed and built using reclaimed carbon fiber on the Big Area Additive Manufacturing (BAAM) can be used to manufacture preforms made with reclaimed carbon fibers. The project supported multiple Institute for Advanced Composite Manufacturing Innovation (IACMI) goals: • Enables the use of recycled carbon fibers in two areas: o Tooling material compounded with reclaimed carbon fiber. o Preforms made with recycled carbon fiber (rCF). • Lowers manufacturing costs by producing low cost 3-DEP® preform tooling. • Reduces manufacturing cycle time with quick additive manufacturing techniques. • Produces lightweight automotive components that will increase fuel economy which will in turn reduce greenhouse gas emissions. The project demonstrated a tool made from reclaimed carbon fibers, gathered technical data that will guide optimization of tooling materials, evaluated preforms made with the BAAM printed tool, and developed cost evaluations. This project has been a total success. First the project demonstrated that reclaimed carbon fiber can be compounded and successfully printed in the BAAM equipment. Second preforms were successfully made from reclaimed carbon fiber using a reclaimed fiber printed tool. Third the team successfully printed a molding tool out of reclaimed carbon fiber. Fourth the project went beyond the scope of this phase I project in 3 areas: (1)- Techmer PM compounded rCF in 2 resin systems instead of just one system (2)- Local Motors evaluated and collected data that will support their IACMI 3.6 project (Robert Bedsole, 2017) . (3)- University of Tennessee Knoxville (UTK) molded a part using the reclaimed preform on a molding tool made from printed reclaim fiber.

36 MATERIALS SCIENCE↗

Wire-arc Additive Manufacturing Benchmark

This is the dataset associated with the 2022 SRP Additive Manufacturing Prediction Challenge, originally hosted on Github at https://github.com/SRP-AM/SRP_AM_Prediction_Challenge. The benchmark was designed for validating prediction for the temperature history, residual stress, and distortion of an additively manufactured metal part with relatively simple geometry. A calibration problem with the same as-built geometry is provided with measured quantities of interest; including temperature histories at selective locations, post-build residual stress at selective locations, and overall distortion measurements. The challenge problem is presented with a different build sequence (i.e. thermal history). In this dataset, we include the actual recorded calibration and challenge measurements, as well as benchmark template files for testing predictions without incorporating the challenge data. Supplementary files around the materials and setup are available for transparency and reproducibility.

Bachus, Nicholas [UC Davis, Davis, CA]↗

X-ray Computed Tomography as a Metrology Technique for the Analysis of Additively Manufactured Material

X-ray computed tomography (X-ray CT) is an analytical technique used in materials science to non-destructively characterize features in a variety materials like polymer, metals, composites, and explosives. It also has the capability of imaging additively manufacture, machine and assembled parts. The non-destructive imaging allows for the analysis of features (voids and cracks), which give a fundamental understanding of the material characteristics. Additionally, X-ray CT can obtain accurate measurements of dimensional and topographic variations due to different stimuli and assess the accuracy of material production. This study focuses on parts manufactured via metal additive manufacturing (AM). Although AM produces parts faster and easier, the printing process can produce defects (pores and surface roughness) that undermine the part’s mechanical properties and performance. The analysis of 3D printed objects has an asset in that the material has an STL file from which the item was printed, which is not available in many manufactured materials (i.e., foams) due to stochastic structures. For this study, the print accuracy of four additively manufactured cylinders will be assessed via X-ray CTto approximate the surface roughness and visualize any major morphological changes to assess the dimensional accuracy of complex additively manufactured parts. It was concluded that using X-ray CT to measure surface roughness was affective because reasonable surface roughness values were measured. Additionally, itwas determined that small-scale features can be produced via additive manufacturing with strong dimensional accuracy so long as the features are highly complex with sharp grooves.

36 MATERIALS SCIENCE↗

When physics-informed data analytics outperforms black-box machine learning: A case study in thickness control for additive manufacturing

Aerosol jet printing (AJP) has emerged as a promising noncontact additive manufacturing method for high-resolution printing for a wide range of material systems. A key challenge limiting the broader adoption of AJP in the material science community is the lack of methods to precisely control thickness. Herein, we develop a model-based design of experiment (MBDoE) framework that integrates physics-informed models, nonlinear regression, and information criteria to postulate, select and calibrate the best model to describe and optimize the AJP manufacturing process. Starting with already available data from system commissioning (e.g., prior single variable sensitivity analysis), four candidate physics-informed models are postulated and trained. MBDoE identifies a single additional optimal experiment to validate these predictive models with quantified uncertainties, which are then used to determine the best experimental conditions to control printed film thickness. As a comparative benchmark, the analysis is repeated using the same dataset with nonparametric Gaussian process regression (GPR) model that does not incorporate physical information. Using MBDoE principles, we find that only five experiments are necessary to calibrate the nonlinear physics-informed parametric model, and with said limited data, this model outperforms the black-box machine learning GPR model. This key result underscores an emerging trend in the data science community: incorporating physical information into predictive models often drastically reduces the data requirements. Leveraging MBDoE further increased the data efficiency. By design, the proposed data science framework is general in nature and can be easily extended to other experimental and additive manufacturing systems beyond AJP.

Aerosol jet printing↗

New insights into the mechanism of ultrasonic atomization for the production of metal powders in additive manufacturing

Ultrasonic atomization is one of the promising technologies for producing metal powders for additive manufacturing, where precise control of particle size and morphology is essential. In this study, we coupled an ultrasonic transducer with a carbon fiber plate and atomized liquid droplets and films under different vibration amplitudes. Water, glycerol, and pure aluminum melt were used to study the atomization mechanism and the resulting droplet/powder characteristics, respectively. High-speed optical and ultrafast synchrotron X-ray imaging were used to study in situ the ultrasonic atomization dynamics, including pulsation and clustering of cavities inside the liquid layer/films, development of capillary waves, and formation of liquid droplets. For the first time, we observed and captured the occurrence of cavitation during the atomization of resting drops, films and impact droplets. The inertial cavitation events interfered with the capillary waves across the interphase boundary, puncturing and breaking the boundary to produce atomized mist. The in situ observation revealed the intricate dynamics of ultrasonic atomization and underscored the pivotal role of cavitation events throughout the entire atomization process. We also conducted experiments on ultrasonic atomization of liquid aluminum, producing particles of perfectly spherical shape. The particle size tended to decrease with reduced vibration amplitude Our work has demonstrated the important processing strategies on how to tailor the particle size while ensuring consistent particle shape and morphology, which is the key processing capability for producing high quality powders for additive manufacturing applications.

36 MATERIALS SCIENCE↗