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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Heat Transfer and Pressure Loss of Additively Manufactured Internal Cooling Channels With Various Shapes

Abstract Additive manufacturing (AM) provides the ability to fabricate highly customized internal cooling passages that are relevant to gas turbine components. This experimental study examines the pressure loss and heat transfer performance of a range of fundamental channel shapes that were produced using direct metal laser sintering. Circular, hexagonal, pentagonal, elliptical, diamond, square, rectangular, trapezoidal, and triangular channel cross sections were investigated. To maintain the same convective surface area between shapes, the wetted perimeters of the channel cross sections were kept constant. Parallel computational fluid dynamic simulations were performed to understand the relationships in cooling performance between several channel shapes. Several characteristic length scales were evaluated to scale the pressure loss and heat transfer measurements. Among the channel shapes investigated, the diamond channel showed the lowest Nusselt number and friction factor. The pentagon exhibited a similar Nusselt number as the circular channel despite having a lower friction factor. There was no difference in scaling the friction factor or Nusselt number results of the different channel shapes between using the square root of cross-sectional area compared to hydraulic diameter as the characteristic length scale

Engineering↗
DOE OSTI2021

In-situ digital image correlation and thermal monitoring in directed energy deposition additive manufacturing

As in welding, directed energy deposition (DED) additive manufacturing (AM) generates complex residual stresses and distortions commensurate with the complexity of the scan pattern used for deposition. To date, measuring DED distortions on complex geometries has only been achieved post process, discarding the complex thermomechanical history that leads to that final material state. In this work, surround stereo digital image correlation (DIC) is used to 3D map surfaces and strain tensors in-situ in a powder-blown laser DED system. Infrared thermography is then projected onto these surfaces to record the full thermomechanical history of printed parts. DIC presents a unique challenge to DED AM, as no part exists at the beginning of deposition, which (a) prevents application of an appropriate speckle pattern and (b) denies the user a zero strain reference frame. Solutions to these problems are proposed and their limitations explored herein. In sum, this work presents a relatively low-cost solution to monitoring and optimizing the unique temporal artifacts induced by complex scan strategies that was previously unobtainable.

42 ENGINEERING↗
DOE OSTI2021

In Situ Synchrotron Tensile Investigations on Ultrasonic Additive Manufactured (UAM) Zirconium

The microstructure evolution of ultrasonic additive manufactured (UAM) zirconium under room temperature uniaxial tensile straining is reported. Miniature dog-bone tensile specimens of two orientations were cut from a UAM zirconium bar for in situ synchrotron tensile tests. Wide-angle X-ray scattering (WAXS) scanning at the Advanced Photon Source (APS) at Argonne National Laboratory was used to unveil the changes in microstructure of the entire gauge regions throughout the straining. A series of WAXS data analysis methods were utilized to quantify both elastic and plastic deformation mechanisms within the strained specimens. Stress concentrations were identified during early stage of plastic deformation, which become candidate necking positions and eventually lead to failure. Fracture surface analysis implied that these stress concentration locations may be correlated to the fabrication defects, providing insightful guidance for future improvement of the UAM zirconium process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Project Fringe, Testing and Validation on Metal Additive Manufacturing

Oak Ridge National Laboratory (ORNL) worked with Additive Monitoring Systems (AMS) to demonstrate the real-time inspection of additive manufacturing (AM) binder jet fusion 3D printing (BJF). Test coupons on the ExOne Innovent were printed and monitored using AMS’s Project Fringe structured light system. Anomalies were detected automatically and classified post build as recoater powder layer non-uniformities, binder powder interaction, depressions, and sub optimal print area. These anomalies were not apparent in the visual spectrum, which suggests that the structured light system has advanced the monitoring techniques state-of-the-art for BJF.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development and Evaluation of a Novel Fuel Injector Design Method using Hybrid-Additive Manufacturing (Final Report)

The widespread application of metal additive manufacturing (AM) technologies has enabled exploration of complex design spaces to achieve optimally performing components. Current optimization techniques make use of several advanced methods to provide designs that are superior to existing versions. However, they seldom discuss the manufacturability of the optimal designs. The objective of this project was to develop a design optimization tool that simultaneously optimizes fuel injector hardware and the combustor flow field with optimization functions and constraints that consider both combustor performance and manufacturability using advanced AM methods and post-processing. In this way, the resultant hardware design is inherently imbued with our most advanced knowledge of combustion physics and AM methods from its conception.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Characteristics and Processing of Hydrogen-Treated Copper Powders for EB-PBF Additive Manufacturing

The fabrication of high purity copper using additive manufacturing has proven difficult because of oxidation of the powder feedstock. Here, we present work on the hydrogen heat treatment of copper powders for electron beam powder bed fusion (EB-PBF), in order to enable the fabrication of high purity copper components for applications such as accelerator components and vacuum electronic devices. Copper powder with varying initial oxygen contents were hydrogen heat-treated and characterized for their chemistry, morphology, and microstructure. Higher initial oxygen content powders were found to not only reduce surface oxides, but also reduce oxides along the grain boundaries and form trapped H 2 O vapor inside the particles. The trapped H 2 O vapor was verified by thermogravimetric analysis (TGA) and residual gas analysis (RGA) while melting. The mechanism of the H 2 O vapor escaping the particles was determined by in-situ SEM heated stage experiments, where the particles were observed to crack along the grain boundaries. To determine the effect of the EB-PBF processing on the H 2 O vapor, the thermal simulation and the validation of single melt track width wafers were conducted along with melting single layer discs for chemistry analysis. A high speed video of the EB-PBF melting was performed in order to determine the effect of the trapped H 2 O vapor on the melt pool. Finally, solid samples were fabricated from hydrogen-treated copper powder, where the final oxygen content measured ~50 wt. ppm, with a minimal residue hydrogen content, indicating the complete removal of trapped H 2 O vapor from the solid parts.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Summary of NDE of Additive Manufacturing Efforts in NASA

(1) General Rationale for Additive Manufacturing (AM): (a) Operate under a 'design-to-constraint' paradigm, make parts too complicated to fabricate otherwise, (b) Reduce weight by 20 percent with monolithic parts, (c) Reduce waste (green manufacturing), (e) Eliminate reliance on Original Equipment Manufacturers for critical spares, and (f) Extend life of in-service parts by innovative repair methods; (2) NASA OSMA NDE of AM State-of-the-Discipline Report; (3) Overview of NASA AM Efforts at Various Centers: (a) Analytical Tools, (b) Ground-Based Fabrication (c) Space-Based Fabrication; and (d) Center Activity Summaries; (4) Overview of NASA NDE data to date on AM parts; and (5) Gap Analysis/Recommendations for NDE of AM.

Waller, Jess↗
NASA NTRSDate not supplied

Convolutional Neural Networks for Image Classification in Metal Selective Laser Meting Additive Manufacturing

Selective laser melting (SLM) is a metal additive manufacturing process that has several advantages such as the large range of metal materials that can be accommodated, 3D printing of complex shape components, the ability to adjust material properties, and cost reduction as expensive production equipment may not be required. Therefore, process monitoring is crucial in different stages of the component building. In this work, convolutional neural networks (CNNs) are investigated as a suitable technique for post-inspection of builds. The monitoring of manufactured parts was conducted by collecting computed tomography (CT) images and identifying defects. Five CNN models were implemented and tested for the classification of the CT images. The models were based on NASNetMobile and DenseNet121, and a custom built CNN model. The results of this work show that CNNs can be feasible and reliable for rapid monitoring and classification of defects in CT images from build fabrication using SLM.

Rodolfo Ledesma↗
DOE OSTI2018

Reinforcement Learning for Generating Toolpaths in Additive Manufacturing

Generating toolpaths plays a key role in additive manufacturing processes. In the case of 3-Dimensional (3D) printing, these toolpaths are the pathways the printhead will follow to fabricate a part in a layer-by-layer fashion. Most toolpath generators use nearest neighbor (NN), branch-and-bound, or linear programming algorithms to produce valid toolpaths. These algorithms often produce sub-optimal results or cannot handle large sets of traveling points. In this paper, the researchers at Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) propose using a machine learning (ML) approach called reinforcement learning (RL) to produce toolpaths for a print. RL is the process of two agents, the player and the critic, learning how to maximize a score based upon the actions of the player in a defined state space. In the context of 3D printing, the player will learn how to find the optimal toolpath that reduces printhead lifts and global print time.

Patrick, Steven↗
DOE OSTI2020

System and method for high power diode based additive manufacturing

A system is disclosed for performing an Additive Manufacturing (AM) fabrication process on a powdered material forming a substrate. The system may make use of a diode array for generating an optical signal sufficient to melt a powdered material of the substrate. A mask may be used for preventing a first predetermined portion of the optical signal from reaching the substrate, while allowing a second predetermined portion to reach the substrate. At least one processor may be used for controlling an output of the diode array.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Additive manufacturing system and method having toolpath analysis

An additive manufacturing (AM) system is disclosed for constructing a three dimensional (3D) part with optimized orthotropy. The system combines an electronic processor which calculates an optimal set of physically achievable toolpaths to meet a given design objective, and a 3D printing direct ink write machine capable of printing inks with reinforcing particles that result in orthotropic materials. The electronic processor may combine a Domain of Interest subsystem that transforms a mathematical description of a desired part orthotropy to a plurality of guidepaths, a toolpath generate subsystem that develops a plurality of physically realizable toolpaths from those guidepaths with a minimum number of starts and stops, a finite element subsystem that computes spatially varying material orthotropy from those toolpaths and then solves a boundary value problem to determine a figure of merit for the design, and an optimization subsystem that uses that figure of merit to update the mathematical description of the part orthotropy to iteratively develop an improved part. The optimization subsystem also includes convergence criteria to indicate when toolpaths have been achieved that yield a sufficiently optimal part has been achieved. The toolpath generate can then output the final toolpaths, which are converted to suitable code that controls the motion of the 3D printer toolhead and allows the optimized 3D part to be manufactured.

King, Michael J.↗
DOE OSTI2022

System and method for sub micron additive manufacturing

An apparatus is disclosed for performing an additive manufacturing operation to form a structure by processing a photopolymer resist material. The apparatus may incorporate a laser for generating a laser beam, and a tunable mask for receiving the laser beam which has an optically dispersive element. The mask splits the laser beam into a plurality of emergent beams each having a subplurality of beamlets of varying or identical intensity, with each beamlet emerging from a unique subsection of illuminated regions of the mask. A collimator collimates at least one of the emergent beams to form a collimated beam. One or more focusing elements focuses the collimated beam into a focused beam which is projected as a focused image plane on or within the resist material. The focused beam simultaneously illuminates a layer of the resist material to process an entire layer in a parallel fashion.

Saha, Sourabh Kumar↗
DOE OSTI2023

Multimaterial powder bed patterning for additive manufacturing method

The present disclosure relates to an additive manufacturing system. In one embodiment the system makes use of a reservoir for holding a granular material feedstock. A nozzle is in communication with the reservoir for releasing the granular material feedstock in a controlled fashion from the reservoir to form at least one layer of a part. An excitation source is included for applying a signal which induces a controlled release of the granular material feedstock from the nozzle as needed, to pattern the granular material feedstock as necessary to form a layer of the part.

Dudukovic, Nikola↗
DOE OSTI2023

System and method for microwave volumetric additive manufacturing

The present disclosure relates to a volumetric additive manufacturing system for forming a structure from a volume of resin using microwave energy. The system makes use of an electronic controller and at least one beam forming algorithm accessible by the electronic controller for generating information relating to an amplitude and a time delay for forming a microwave signal, where the microwave signal will be used in irradiating a build volume, and where the build volume is formed by the volume of resin. A microwave signal generating subsystem is included which is responsive to the information generated by the beam forming algorithm, and which generates a microwave signal using the amplitude and the time delay determined by the beam forming algorithm. An antenna is used to receive the microwave signal and project the microwave signal as a microwave beam, in accordance with the amplitude and time delay, into the build volume to form the structure.

Mukherjee, Saptarshi↗
DOE OSTI2025

Automated design of an additive manufactured compact broadband antenna for plasma reflectometry

Broadband antennas operating in the gigahertz frequency range are regularly used for plasma reflectometry diagnostics. Due to a lack of space and unique diagnostic constraints, these antennas are often custom in design and frequency range. Recent advances in additive manufacturing of high temperature copper alloys allow for expanded freedom in design of these diagnostic antennas. In this work, a heuristic simulated annealing algorithm is used alongside 3-D finite element simulation to automate the design of a double ridged rectangular horn antenna for a reflectometry diagnostic on the DIII-D tokamak. Optimization of antenna performance given the design constraints results in a compact broadband (6-20+ GHz) antenna design. Measured transmission from the additively manufactured antenna matches simulation within reasonable error, and experimental plasma electron density profiles from the DIII-D high-field side scrape-off layer are shown.

Additive manufacturing↗
NASA NTRSDate not supplied

Pragmatic Stress Prediction on Additively Manufactured Coupons

Prediction of residual stresses from process parameters for additively manufactured large metal parts is computationally expensive. NASA is currently developing meter-scale parts with direct energy deposition. Practically, the predictive computational methods need to efficiently scale-up to meter-scale parts. Coupled thermal-mechanical multi-physics simulations have been developed with the pragmatic method using ABAQUS, COMSOL Multiphysics, ALE3D software. The residual stresses are a result of the manufacturing process which creates thermal cycling of the build layers. The pragmatic method uses lumped thermal layers for stress predictions to reduce computational costs. The stress predictions as well as deformations of the different codes are compared with each other and with ANSYS Additive using identical material models, boundary and initial conditions. The codes were used to simulate three different geometries: a thin wall, hollow cylinder and twin-cantilever part. The coupon parts were then manufactured with Inconel-625. The residual stresses in these parts were measured using X-ray diffraction as well as neutron beam diffraction at NIST. The stress measurements for the two technologies are compared. The pragmatic stress prediction method enabled predictions of the multi-centimeter scale parts using desktop computer workstations in only a few hours for each coupon. The results of the simulated stress predictions compared favorably with the measured stresses even though thermally lumped layers were employed. Finally, a two-meter scale nozzle was simulated using ANSYS Additive. The simulations were used to examine the build orientation trade-space with respect to resulting geometric deformation. The predicted deformations were compared to measurements of an actual subscale part manufactured with direct energy deposition.

Additive Manufacturing↗
DOE OSTI2024

Adamantine 1.0: A Thermomechanical Simulator for Additive Manufacturing

Adamantine is a thermomechanical simulation code that is written in C++ and built on top of deal.II (Arndt et al., 2023), p4est (Burstedde et al., 2011), ArborX (Lebrun-Grandié et al., 2020), Trilinos (The Trilinos Project Team, 2020), and Kokkos (Trott et al., 2022). Adamantine was developed with additive manufacturing in mind and it is particularly well adapted to simulate fused filament fabrication, directed energy deposition, and powder bed fusion. Adamantine employs the finite element method with adaptive mesh refinement to solve a nonlinear anisotropic heat equation, enabling support for various additive manufacturing processes. It can also perform elastoplastic and thermoelastoplastic simulations. It can handle materials in three distinct phases (solid, liquid, and powder) to accurately reflect the physical state during different stages of the manufacturing process. To enhance simulation accuracy, adamantine incorporates data assimilation techniques (Asch et al., 2016). This allows it to integrate experimental data from sensors like thermocouples and infrared (IR) cameras. This combined approach helps account for errors arising from input parameters, material properties, models, and numerical calculations, leading to more realistic simulations that reflect what occurs in a particular print.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The performance of additively manufactured Haynes 282 in supercritical CO 2

The use of supercritical carbon dioxide (sCO 2 ) as a working fluid is garnering interest in next generation power production systems due to the possibility of increased operational efficiencies and lower associated costs. Its implementation requires alloys with excellent high temperature strength and corrosion resistance, which makes Haynes 282® (H282) a suitable candidate. With increasing adoption of additive manufacturing (AM) in the energy industry, there is a need to investigate long-term sCO2 exposure on AM produced materials. Additively manufactured H282 (AM-H282) samples built using laser powder bed fusion in two different orientations were analyzed through imaging, gravimetric analysis, and room-temperature tensile testing before and after 1000-h exposure to CO 2 at 750 °C and 20 MPa. Performed imaging included observation of the sample surfaces and of the material bulk (cross sections) through means of Scanning Electron Microscopy (SEM) and optical microscopy. In comparison to wrought H282, it was found that the exposed material exhibited a similar Cr 2 O 3 oxide protective layer about 2 μm in thickness with additional top-surface TiO 2 oxide and carbon-rich precipitates. It was also similarly observed that internal oxidation was present but limited to a depth of 20 μm, and a 1–3 μm γ’ denuded region appeared to surround all internal and surface oxidation. Thermal aging effects were noted with the precipitation of needle-like structures in the γ/γ’ matrix and a coarsening of the γ’ precipitates from 28 nm to 73 nm. Mass measurements analyzing oxide precipitation revealed a larger increase compared to wrought, representing an approximate 20% difference. Tensile testing results showed similar behavior to wrought with a slight increase in yield strength and a large reduction in elongation in the exposed samples.

36 MATERIALS SCIENCE↗