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At least 1,207 records · Page 67

Additive Manufacturing of SiC Based Ceramics and Ceramic Matrix Composites

Silicon carbide (SiC) ceramics and SiC fiber reinforcedSiC ceramic matrix composites (SiCSiC CMCs) offer high payoff as replacements for metals in turbine engine applications due to their lighter weight, higher temperature capability, and lower cooling requirements. Additive manufacturing approaches can offer game changing technologies for the quick and low cost fabrication of parts with much greater design freedom and geometric complexity. Four approaches for developing these materials are presented. The first two utilize low cost 3D printers. The first uses pre-ceramic pastes developed as feed materials which are converted to SiC after firing. The second uses wood containing filament to print a carbonaceous preform which is infiltrated with a pre-ceramic polymer and converted to SiC. The other two approaches pursue the AM of CMCs. The first is binder jet SiC powder processing in collaboration with rp+m (Rapid Prototyping+Manufacturing). Processing optimization was pursued through SiC powder blending, infiltration with and without SiC nano powder loading, and integration of nanofibers into the powder bed. The second approach was laminated object manufacturing (LOM) in which fiber prepregs and laminates are cut to shape by a laser and stacked to form the desired part. Scanning electron microscopy was conducted on materials from all approaches with select approaches also characterized with XRD, TGA, and bend testing.

3-D printing↗

ASTM International Conference on Additive Manufacturing – 2022

The In-Situ Project: Correlating In-situ monitoring data and Non-Destructive Evaluation (NDE) methods to characterize defect populations in Laser Powder Bed Fusion (L-PBF) material NDE is critical to enable the safe use of additive manufactured (AM) parts in aerospace applications. However, traditional NDE methods are not fully adaptable to complex AM geometries to appropriately screen for critical defects, and L-PBF processes inherently generate defects. In-situ monitoring techniques can give information about the quality of the build process and indicate process variations that could potentially create defects. Proven, causal correlations between in-situ monitoring indications and resulting defects are needed to inform about the final quality of the part. Thus, the development of a new approach is necessary. NASA started a two-phase study that would investigate techniques for characterizing defect populations in L-PBF material, first in material with induced defects, then in a nominal L-PBF process, by correlating in-situ, NDE, and serial sectioning data. Objectives also include the evaluation of seeded defect methodologies for realistic defect creation, creating a baseline of defect populations in a Qualified Material Process (QMP), characterizing the effect of heat treatment, and correlating defect populations with tensile and fatigue properties. By comparing computed tomography images, in-situ monitoring images, and metallography images, the team has been able to draw preliminary conclusions. They include a better understanding of the limitation of the NDE tools, learning about the “healing” of the samples observed during layer building and a comparison study on different laser power variation samples. Those preliminary conclusions will help dictate the follow-up work that will be presented at the conference.

additive manufacturing↗

Space Environmental Effects on Additively Manufactured (AM) Parts on MISSE-9/10

The Materials on International Space Station Experiment (MISSE) experiments have made a continuous presence on the ISS and allowed for testing of performance and durability of materials exposed to the Low Earth Orbit (LEO) space environment. Additive Manufacturing (AM) has been included on several MISSE flights, and many companies (Made in Space and Stratasys) and NASA centers wanted to test various AM material samples. The goal of studying Space Environmental Effects on AM Parts with MISSE 9/10 was to fly promising metal and polymer AM material samples (dogbones) that could have future manufacturing capabilities in space and conduct post-flight analysis of these materials via mechanical and optical properties. On these flights, MISSE-9 contained three Inconel and 12 polymer samples and MISSE-10 included three Inconel and 16 polymer samples. Before flying to the ISS, all the samples underwent thermal vacuum bakeout (at 60°C for 24 hours and 10-6 torr). After bakeout, control and flight experiments were weighed, and optical properties were taken. Optical properties such as solar absorptance and infrared emittance were taken on the control samples and the flight samples (preflight and postflight). To understand more about the mechanical properties of the AM samples, tensile testing was conducted on the samples to determine the yield and ultimate tensile strength of the dogbone samples against the control. Lastly, the torque on the fasteners securing the dogbone samples were loosened and measured using a torque wrench, and they were compared to their preflight torque specification required. Optical properties and masses were recorded before flight, and the postflight results were recorded and collected in June 2022 to study the effects. With the postflight analysis, NASA engineers can now better characterize how UV radiation and thermal cycling affect the material properties.

Materials on International Space Station Experimen↗

Additive Manufacturing of Poly(phenylene Sulfide) Aerogels via Simultaneous Material Extrusion and Thermally Induced Phase Separation

Abstract Additive manufacturing (AM) of aerogels increases the achievable geometric complexity, and affords fabrication of hierarchically porous structures. In this work, a custom heated material extrusion (MEX) device prints aerogels of poly(phenylene sulfide) (PPS), an engineering thermoplastic, via in situ thermally induced phase separation (TIPS). First, pre‐prepared solid gel inks are dissolved at high temperatures in the heated extruder barrel to form a homogeneous polymer solution. Solutions are then extruded onto a room‐temperature substrate, where printed roads maintain their bead shape and rapidly solidify via TIPS, thus enabling layer‐wise MEX AM. Printed gels are converted to aerogels via postprocessing solvent exchange and freeze‐drying. This work explores the effect of ink composition on printed aerogel morphology and thermomechanical properties. Scanning electron microscopy micrographs reveal complex hierarchical microstructures that are compositionally dependent. Printed aerogels demonstrate tailorable porosities (50.0–74.8%) and densities (0.345–0.684 g cm −3 ), which align well with cast aerogel analogs. Differential scanning calorimetry thermograms indicate printed aerogels are highly crystalline (≈43%), suggesting that printing does not inhibit the solidification process occurring during TIPS (polymer crystallization). Uniaxial compression testing reveals that compositionally dependent microstructure governs aerogel mechanical behavior, with compressive moduli ranging from 33.0 to 106.5 MPa.

Chemistry↗

In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

Abstract In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size, velocity, and shape. These droplet characteristics, in turn, determine the functional quality of the printed parts. Hence, to ensure repeatable and reliable part quality it is necessary to monitor and control the droplet characteristics. Existing approaches for in-situ monitoring of droplet behavior in DoD-LMJ rely on high-speed imaging sensors. The resulting high volume of droplet images acquired is computationally demanding to analyze and hinders real-time control of the process. To overcome this challenge, the objective of this work is to use time series data acquired from an in-process millimeter-wave sensor for predicting the size, velocity, and shape characteristics of droplets in DoD-LMJ process. As opposed to high-speed imaging, this sensor produces data-efficient time series signatures that allows rapid, real-time process monitoring. We devise machine learning models that use the millimeter-wave sensor data to predict the droplet characteristics. Specifically, we developed multilayer perceptron-based non-linear autoregressive models to predict the size and velocity of droplets. Likewise, a supervised machine learning model was trained to classify the droplet shape using the frequency spectrum information contained in the millimeter-wave sensor signatures. High-speed imaging data served as ground truth for model training and validation. These models captured the droplet characteristics with a statistical fidelity exceeding 90%, and vastly outperformed conventional statistical modeling approaches. Thus, this work achieves a practically viable sensing approach for real-time quality monitoring of the DoD-LMJ process, in lieu of the existing data-intensive image-based techniques.

Gaikwad, Aniruddha (ORCID:0000000285642621)↗

Additive manufacturing of bimetallic structures

Abstract Metals of 12Cr2Si and 9Cr1Mo are investigated with femtosecond fiber laser additive manufacturing. A smooth phase transition is found at the interface of the two gradated composition metals, indicating a strong bonding. In contrast, the comparison group of SS316L and SA508 shows an abrupt transition.

Bai, Shuang↗

Using post-processing heat treatments to elucidate precipitate strengthening of additively manufactured superalloy 718

The poor machinability and extensive work hardening of Ni-based superalloys makes additive manufacturing an attractive option for producing geometrically complex components with distinct microstructures. Although previous studies show recovery of high strength at room temperature, very few studies demonstrate successful properties at elevated temperatures required for industrial applications. Here, the objectives of this study are to present a post-build heat treatment for high strength across a wide temperature range, determine the strength contribution of nanoscale precipitating phases to the overall mechanical properties of superalloy 718, and from these, provide a comprehensive microstructure-property relationship for wrought and AM 718 to guide efforts to simulate the properties of AM components. Laser powder bed fusion–produced superalloy 718 was characterized at multiple length scales using scanning electron microscopy and transmission electron microscopy in the as-built condition and with multiple heat treatments designed to form combinations of γ', γ", and δ precipitates. Uniaxial tensile tests performed from room temperature to 600 °C on subsize specimens determined the yield strength, elastic modulus, ultimate tensile strength, fracture stress, and uniform elongation. Precipitates in this work proved to be weak barriers to dislocation motion through a dispersed barrier model, but they provided strength to the alloy through their consistent high density. The relative contribution to the yield strength from γ" remained consistent between 48% and 57% of the total strength up to 600 °C, the primary influence on the high temperature strength of superalloy 718. The strength factors for γ" and δ precipitates were found to trend inversely with tensile test temperature and may be attributable to the differences in precipitate coherency. A post-build heat treatment is recommended to maintain high strength at elevated temperatures. A quantitative microstructure-property relationship, dependent on precipitate size, density, and morphology, was derived and can estimate the yield strength across a wide temperature range applicable to the operational regimes for superalloy 718.

36 MATERIALS SCIENCE↗

Temperature-dependent mechanical properties and crystal plasticity parameters for additively manufactured Haynes-214 alloy: Experiments and numerical modeling

Our experimental mechanical testing data demonstrated that the additively manufactured (AM) laser powder bed fusion (L-PBF) Haynes-214 alloy exhibits non-linear mechanical properties as the temperature rises from ambient to 870 °C. Crystal plasticity (CP) simulations provide an effective approach to gaining deeper insights into microstructure-property linkages under thermomechanical loading. This method can reduce the need for costly high-temperature mechanical testing while accounting for the effects of crystallographic texture and grain morphology on the mechanical behavior of AM materials. However, calibrating a CP model is time-consuming because individual simulations are computationally expensive and hundreds (or more) of iterations over parameter sets may be required. To address this issue, we have designed a machine learning-differential evolution (ML-DE) CP framework that can accurately interpolate the tensile properties of AM L-PBF Haynes-214 alloy across a wide temperature range from ambient to 870 °C, with minimal reliance on experimental data. The framework uses electron backscatter diffraction (EBSD) measurements to generate statistically equivalent microstructural volume elements to serve as inputs to the CP modeling framework. Stress–strain curves were generated from 1000 CP simulations, which serve as the training data set for the three ML regression algorithms explored: linear, extra-trees, and multi-layer perceptron. These three regression models were independently evaluated to compare their efficiency and identify the most suitable algorithm for the given problem. Results revealed that the extra-trees ML regressor outperforms the other models in both qualitative and quantitative aspects with an R 2 of 0.98. Subsequently, the differential evolution optimization approach is employed to calibrate the ML-based CP material parameters with experimental results obtained at various temperatures. Finally, temperature-dependent CP material parameters are formulated. The effectiveness and efficiency of the designed framework are validated through comparison with experimental results, demonstrating a high degree of agreement. These calibrated parametric constitutive equations enable further use of the CP model to study the deformation behavior of this alloy under a wide range of thermo-mechanical loading conditions.

36 MATERIALS SCIENCE↗

Hybrid additive manufacturing of AISI 316L via asynchronous powder and hot-wire laser directed energy deposition

Hybrid Additive Manufacturing (AM) offers a way to leverage the advantages of different AM technologies, enabling the efficient production of sizeable parts without compromising material properties or geometric complexity capabilities. This study presents an asynchronous hybrid Directed Energy Deposition (DED) strategy employing laser powder DED and laser hot-wire DED. AISI 316L parts comprising multiple powder and wire segments were fabricated with optional machining on AISI 316L substrates to investigate how quality is impacted by (i) alternative process sequences (laser powder DED followed by laser hot-wire DED and vice versa), (ii) machined vs. as-printed interfacial conditions, and (iii) material deposition on top vs. alongside previously built segments. Optical microscopy, X-ray computed tomography, and Vickers hardness were used to characterize the morphology and microstructure of the parts, localized porosity and lack of fusion defects, bulk density, and mechanical properties. Interfacial machining was necessary for dimensional control but promoted lack of fusion voids, resulting in a 99.71 ± 0.01% dense part. As-printed interfaces resulted in a denser part (99.82 ± 0.02%) at the expense of dimensional accuracy. The hardness of the parts with as-printed and machined interfaces was 196 ± 0.37 HV and 192 ± 0.40 HV, respectively, compared to 156 ± 1.4 HV for the substrate. Depositing powder alongside or on top of wire sections resulted in interfaces with a hardness of 217 ± 2.2 HV, compared to 185 ± 3.4 HV for the wire-powder interfaces.

36 MATERIALS SCIENCE↗

Cast or Additively Manufactured Coils with End Turn Enhanced Heat Transfer Surfaces for Spray or Jet Cooling

Cast or additively manufactured coils present a new opportunity for creativity in thermal management of electric machines. Improvements to the heat transfer of spray or jet cooling of coil end turns through the incorporation of pins or enhanced heat transfer surfaces in the cast end turn surfaces is explored. The thermal response of cast copper half-turns is measured for a range of spray/jet volumetric flow rates and ohmic loss heat fluxes. A significant reduction, ~30%, in the steady state temperature and increased spray cooling heat transfer coefficients was experimentally measured when the pins or enhanced heat transfer surfaces are incorporated.

33 ADVANCED PROPULSION SYSTEMS↗

Nondiffractive beam shaping for enhanced optothermal control in metal additive manufacturing

High thermal gradients and complex melt pool instabilities involved in powder bed fusion–based metal additive manufacturing using focused Gaussian-shaped beams often lead to high porosity, poor morphological quality, and degraded mechanical performance. We show here that Bessel beams offer unprecedented control over the spatiotemporal evolution of the melt pool in stainless steel (SS 316L) in comparison to Gaussian beams. Notably, the nondiffractive nature of Bessel beams enables greater tolerance for focal plane positioning during 3D printing. We also demonstrate that Bessel beams significantly reduce the propensity for keyhole formation across a broad scan parameter space. High-speed imaging of the melt pool evolution and solidification dynamics reveals a unique mechanism where Bessel beams stabilize the melt pool turbulence and increase the time for melt pool solidification, owing to reduced thermal gradients. Consequently, we observe a distinctively improved combination of high density, reduced surface roughness, and robust tensile properties in 3D-printed test structures.

36 MATERIALS SCIENCE↗

Advancing flexible electronics and additive manufacturing

There is high interest in the synergism of thin-film and flexible electronics with additive manufacturing. This review primarily focuses on the prospective developments in convergence with flexible electronics manufacturing technologies. Specifically, this paper covers the latest 3D printing and hybrid manufacturing technologies, the utility of specific types of materials, their functionalization and characterization, post-processing and testing strategies toward fabricating robust and application-specific flexible electronics. Besides exploring the advances in this area of research—it also highlights the limitations and gaps that have been observed in the previous years that will challenge and offer opportunities for advancing research and development. Lastly, the future of 3D-printed flexible electronics is discussed in the aspects of customizability, scalability, and its game-changing and state-of-the-art potential for intelligent sensing, instrumentation, and wearables for various medical, engineering, and industrial applications.

36 MATERIALS SCIENCE↗

High plasticity in refractory composite fabrication by ultrasonic additive manufacturing

Refractory metal composites are desirable for use in extreme environments that require materials with high specific strengths and resilience to external environments such as that found in nuclear and aerospace. However, due to the high melting temperature of refractories, liquid state joining processes such as welding remains difficult. Ultrasonic additive manufacturing (UAM) provides a potential route for processing refractory composites because it is a solid-state (i.e., no-melting) process and allows for intermittent machining operations to be performed between welds. Further, to demonstrate refractory composite fabrication, this study utilized UAM to machine a cavity to locate and sequester a Mo foil in a Zircaloy-4 (Zry-4) baseplate and additively build over the top with Zry-4 foils, thereby embedding the Mo in Zry-4 matrix. Significant deformation of the Zry-4 microstructure was observed: this deformation caused adiabatic heating and subsequent dynamic recrystallization through the transformation from α→β and then back to α as the material cooled. Flexural testing of the Zr–Mo composite revealed no delamination or failure, but the strength was not as expected, falling lower than a cold-worked Zry-4 sample. Finite element analysis supported that some bonding must have existed between the Zry-4 and Mo. There was indeed an interdiffusion zone at the Zry-4 foil–Mo foil interface, observing a metastable body-centered cubic β-Zr lathe. It was determined that sufficient strain energy was present to encourage the nucleation of the β-Zr grain along α-Zr grains. Future work is warranted to investigate UAM for refractory composite fabrication.

36 MATERIALS SCIENCE↗

NASA/ORNL/AFRL Project Work on EBM LSHR: Additive Manufacturing of High-Temperature Gamma-Prime Strengthened Ni-Based Superalloys

Powder-bed fabrication of aerospace alloys may revolutionize production by eliminating the need for extensive machining and expensive tooling. Heated-bed electron-beam melting (EBM) offers advantages over non-heated laser additive manufacturing (AM) methods, including lower residual stress, reduced risk of contamination, slower cooling rates, and faster build times. NASA Glenn Research Center has joint project work with Oak Ridge National Lab and the Air Force Research Laboratory to explore the feasibility of fabricating advanced Ni-based gamma-prime superalloys with EBM AM.

additive manufacturing↗

A Review Towards the Design Optimization of High-Performance Additively Manufactured Rotating Detonation Rocket Engine Injectors

Rotating Detonation Rocket Engines (RDRE) have been marketed primarily for their higher specific impulse potential over constant pressure (CP) liquid rocket engines. However, several other performance advantages exist such as heat transfer advantages for gas expander cycle, increased completeness of combustion at low chamber L*, compact engine design, reduced coolant channel pressure drop potential, and improved injector C* performance. NASA has paved the way for liquid engine system performance enhancement since the Apollo program and continues to do so with metal additive manufacturing (AM), new advanced materials, and advanced propulsion concepts. A team of propulsion development engineers at NASA are in the process of developing high-performance 7K lbf class RDRE hardware for their potential use in lander, upper stage, and even launch vehicle applications. Clear advantages have been demonstrated with AM including program cost and schedule reductions of up to 50%. It is well known that injector performance is integrally linked to the global performance of a combustion device. This is especially the case for RDREs since detonation stability is heavily dependent on the mixedness of propellants. A major goal of this work is to identify what has been done in the open experimental literature and what injectors design features are conducive to high performance in the detonation cycle. This paper reviews the available literature and reports the primary gaps in the knowledge base needed by the pressure gain combustion (PGC) community. Major conclusions are documented, and suggestions given towards the design of high-performance liquid RDRE injectors. In addition, the integration of metal AM into the design of liquid RDRE injector schemes is included.

rotating detonation rocket engine↗

Agency Additive Manufacturing (AM) Certification Support Team (AACT) Risk Reduction – Safe Life Category: Fracture Control Framework for Un-inspectable Fracture Critical AM Parts

The NASA Engineering and Safety Center (NESC) was requested to support the development of a governing philosophy to provide a consistent and systematic approach for fracture control certification of additive manufacturing (AM) hardware that cannot be reliably inspected. The overall goal of the NESC assessment was to make progress toward a framework for general certification of un-inspectable fracture critical AM hardware and toward approaches for evaluating risks associated with these components. This report contains the results of the assessment.

Additive Manufacturing↗

Thermal-Mechanical Analysis of an Additive Manufacturing Ceramic Heat Exchanger for High-Temperature Recuperator in a sCO2 Power System

Supercritical CO2 (sCO2) Brayton power cycle can be configured in a closed-loop power system and has a potentially high cycle efficiency. Compactness and high efficiency of a sCO2 power block make the sCO2 Brayton cycle a versatile power cycle in broad applications. While many heat sources are of sufficient intensity to produce high temperature working fluids to achieve high cycle efficiency, the thermal-mechanical stability of traditional materials (e.g., steels and nickel-based superalloys) used in construction of heat exchangers and turbine components limits the operating conditions and thus thermodynamic efficiency of the system. This effort seeks to establish the viability of ceramic heat exchanger technologies for the most extreme operating conditions envisioned for power generation and other high temperature processes. Heat exchangers constructed from ultra-high temperature ceramics, a class of extreme environment materials featuring melting points (Tmp.) above 3000 degrees C, is particularly appealing for sCO2 Brayton cycles given their ultra-low creep rates and very high retained strength at low homologous temperatures (i.e., T < 0.5 Tmp., or at least 1500 degrees C). To translate these materials properties to ultra-high temperature heat exchangers, innovations are required in ceramic manufacturing techniques to realize the complex architectures featured in compact heat exchangers with high power density. With appropriate processing, ZrB2-SiC based compositions can be sintered to near full density and shaped into complex topologies via ceramic additive manufacturing methods. This paper analyzes heat exchanger designs and explores thermal-mechanical implications of the operating environment. Thermal flow, heat transfer, and conjugate mechanical analyses provide insights into benefits and risks associated with the design approach.

additive manufacturing↗

Enhancing Metal Additive Manufacturing Training with the Advanced Vision Language Model: A Pathway to Immersive Augmented Reality Training for Non-Experts

This paper introduces an innovative training system for the Renishaw AM400 metal printer, leveraging the synergy of the advanced Vision Language Model (VLM) with Augmented Reality (AR) within the Digital Twins (DT) framework. Aimed at overcoming the limitations of conventional training methods in metal additive manufacturing (AM), our system integrates AR to provide an immersive learning environment, enhancing the real-world experience with interactive digital overlays. The core of the system lies in its use of VLM, which, pre-trained on diverse datasets, excels in processing multi-modal data, thereby offering nuanced and contextually relevant guidance for trainees. Key experiments demonstrate the system’s effectiveness, particularly highlighting the usage of VLM as an Artificial Intelligence (AI) agent to integrate external tools like YOLO-v7 for valve state classification and CRAFT for control panel text recognition. This approach significantly improves recognition accuracy, operational understanding, and human–machine interaction, especially for non-expert users, making complex metal AM operations more accessible. The research not only showcases the potential of AR and VLM in industrial training but also sets a new standard for smart manufacturing practices, indicating broader applications in various industrial domains.

Metal additive manufacturing↗