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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Role of Interface in Additively Manufactured Interpenetrating Composites

Additively Manufactured Interpenetrating Composites (AMIPCs) are a relatively new metal-metal chain composite in development for use in high energy absorption systems. In this system, reinforcing phase of additively manufactured continuous lattice configurations 316L austenitic stainless-steel is in melt infiltrated with a matrix phase of A356 aluminum-silicon casting alloy. Measurements and observations of this material system have shown that weakly bonded or open/porous interface between the reinforcement and matrix phases exhibits dramatically different mechanical properties of AMIPCs, which is not currently well understood. In this work, Finite Element Models (FEM) are used to model the effects of interfaces between the composite phases. Mechanical tensile tests measurements of various composite volume fractions and varying degrees of casting infiltration are also examined and used to show consistency with the FEM results. The outcome provides insight into material design criteria and performance predictions for new hybrid material systems with exceptional damage tolerance.

Allen, Jason↗
NASA NTRSDate not supplied

Advanced and Additive Manufacturing Technologies for Liquid Rocket Engine Components

Overview of advanced manufacturing and additive manufacturing development at NASA for liquid rocket engines. Presentation includes various material, process, design, and hot-fire testing developments demonstrating the use of advanced components for liquid rocket engines on launch vehicles and in-space systems.

Additive Manufacturing↗
NASA NTRS2015

Additive Manufacturing Infrared Inspection

The Additive Manufacturing Infrared Inspection Task started the development of a real-time dimensional inspection technique and digital quality record for the additive manufacturing process using infrared camera imaging and processing techniques. This project will benefit additive manufacturing by providing real-time inspection of internal geometry that is not currently possible and reduce the time and cost of additive manufactured parts with automated real-time dimensional inspections which deletes post-production inspections.

Gaddy, Darrell↗
DOE OSTI2022

In situ laser profilometry for material segmentation and digital reconstruction of a multicomponent additively manufactured part

In addition to its ability to produce geometrically complex parts, additive manufacturing offers a unique opportunity to collect data about a component while it is being fabricated. However, there has only been limited effort to characterize parts morphologically and compositionally in situ. In this article, we present a layer-by-layer, laser profilometry-based in situ characterization technique as a method to digitally reconstruct a multi-material part. Data collected by the laser profilometer yields height maps and grayscale images which are voxelized using purpose-built software to volumetrically reconstruct the part. Additionally, the same part was also analyzed using X-ray computed tomography (CT) which was not able to resolve the different compositional regions within the part, but captured the filament morphology. The part was then bisected to compare the digital reconstruction to the actual part morphology and composition. Overall, the digital reconstruction was in good agreement with both the CT and bisected images. Deviations between the digital reconstruction and the CT/bisected images are likely the result of image segmentation settings or material shifts after data was collected. The in situ characterization method demonstrated here sets the stage for real time process monitoring and paves the way for additively manufactured parts that are “born qualified.”

36 MATERIALS SCIENCE↗
DOE OSTI2020

Non-destructive simulation of node defects in additively manufactured lattice structures

Additive Manufacturing (AM), commonly referred to as 3D printing, offers the ability to not only fabricate geometrically complex lattice structures but parts in which lattice topologies in-fill volumes bounded by complex surface geometries. However, current AM processes produce defects on the strut and node elements which make up the lattice structure. This creates an inherent difference between the as-designed and as-fabricated geometries, which negatively affects predictions (via numerical simulation) of the lattice’s mechanical performance. Although experimental and numerical analysis of an AM lattice’s bulk structure, unit cell and struts have been performed, there exists almost no research data on the mechanical response of the individual as-manufactured lattice node elements. Here we propose a methodology that, for the first time, allows non-destructive quantification of the mechanical response of node elements within an as-manufactured lattice structure. A custom-developed tool is used to extract and classify each individual node geometry from micro-computed tomography scans of an AM fabricated lattice. Voxel-based finite element meshes are generated for numerical simulation and the mechanical response distribution is compared to that of the idealised computer-aided design model. The method demonstrates compatibility with Uncertainty Quantification methods that provide opportunities for efficient prediction of a population of nodal responses from sampled data. Overall, the non-destructive and automated nature of the node extraction and response evaluation is promising for its application in qualification and certification of additively manufactured lattice structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Dual Material System for Polymer Large Scale Additive Manufacturing

Big Area Additive Manufacturing (BAAM) technology allows for manufacturing of large-scale objects with a potential to reduce energy embedded in products, reduce or eliminate energy necessary for transportation of goods along with reducing the lead time and cost in some cases. Over the last few years, Oak Ridge National Laboratory (ORNL) has been focusing on large-scale printing of single material systems, typically un-reinforced or short fiber reinforced polymers, in order to address needs in stiffness-limited applications. This paper describes the development of a multi-material large-scale AM system through a collaboration with Cincinnati Inc. and Performance Feed Screw Inc. Modifications to the Big Area Additive Manufacturing (BAAM) system includes a new extruder design to accommodate a dual feed system, an expanded two-dryer system with a capacity of 273 kg/dryer, and a system that is capable of mixing pelletized materials up to 60Kg/hr. This article highlights the advantages and limitations of the multi-material system as well as potential applications.

Smith, Tyler↗
DOE OSTI2021

Utilizing a Dynamic Segmentation Convolutional Neural Network for Microstructure Analysis of Additively Manufactured Superalloy 718

Additive manufacturing (AM) is revolutionizing almost all industries through the production of intricate geometries previously prohibited by cost or machinability. Ni-based superalloys form a primary alloy class for high temperature applications in the petrochemical, aerospace, and nuclear industries because of their intrinsic resistance to creep and the ability to heat treat the superalloy for high strength. Despite these attractive properties, the extreme work hardening of Ni-based superalloys makes traditional manufacturing of complex shapes difficult and thus, these alloys are an attractive target for AM. Superalloy 718 was chosen as an example superalloy because of the wide variety of precipitates that can form within its composition space from the repetitive heating and cooling cycles of the AM process. The precipitates and other microstructure features, such as grain boundaries and dislocations, will dictate the mechanical properties and thus, there is an extensive challenge to characterize the size, number density, composition, and volume fraction of each microstructural feature from AM fabrication using analytical electron microscopy. This work focused on the application of a pixel-wise classification machine learning (ML) model called a dynamic segmentation convolutional neural network (DSCNN) to identify the microstructural features of an as-fabricated additively manufactured superalloy 718.

Taller, Stephen↗
DOE OSTI2021

Material properties and mechanical behaviour of functionally graded steel produced by wire-arc additive manufacturing

Metal Big Area Additive Manufacturing is an additive manufacturing technique based on Gas Metal Arc Welding (GMAW) with the option to use many shielding gases, and materials. The system is equipped with a dual torch design allowing for printing different materials; in our study, AISI 410 stainless steel and AWS ER70S-6 mild steel are both printed in the same component. Different print strategies were designed to highlight changes in material and mechanical properties. Deformation behaviour of a materials’ interface was analysed by two-dimensional digital image correlation of uniaxial tensile specimens in displacement-controlled tests. Instances of non-homogeneous local strains adjacent to the interface are observed, as well as variability in mechanical behaviour and microstructure based on location within the print. Optical and electron microscopy are used to evaluate three microstructural zones in a 5 mm range of the interface between mild steel and stainless steel. Areas far from the interface produced polygonal ferrite and pearlite, while areas close to the interface produced acicular ferrite and bainite. Chromium redistribution profiles are dependent on the print strategy used, as shown by scanning electron microscopy with Energy dispersive spectroscopy. Evidence produced via electron backscatter diffraction is shown to support the argument that transformation induced plasticity is not the cause for the non-homogeneous deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Part distortion monitoring in additive manufacturing using machining

In additive manufacturing, accumulation of residual stresses can result in severe part distortion from the desired preform shape. Current methods for in-situ part distortion monitoring in additive manufacturing typically require expensive sensors, or capital equipment, and require time-consuming post-processing to understand the shape deviation. This paper presents an in-situ method, in the context of hybrid manufacturing, for part distortion detection using machining of additively manufactured parts. As a surrogate, three test artifacts were used to represent different distorted geometries. The tool axis positions from the machine tool controller and the cutting power were monitored during a facing operation. Cutting power data was used to detect the tool entry and exit in the workpiece using a novel approach with power standard deviation metric. The workpiece geometry and distorted configuration was subsequently predicted for positional and rotational deviations to within 2 mm accuracy using synchronized tool position data with cutting power. The proposed method can be used in a hybrid (additive and subtractive) machine tool to periodically check part distortion in the additive build. The method is applicable for any additive process and is low-cost and computationally inexpensive.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Localized material compression to correct distortion in wire arc additive manufacturing

Wire Arc Additive Manufacturing (WAAM) is an advanced manufacturing technology which utilizes welding systems to generate three dimensional geometries in a layer-by-layer fashion. Distortion or warping of a print substrate and WAAM components due to thermally induced residual stresses is an ongoing challenge limiting the widespread adoption of WAAM technologies for producing components. In this manuscript, a novel approach is described to address thermal distortion in deposited components by applying lateral compressions along the length of the deposited material. To demonstrate this method, a series of single-track walls were printed and compressed at evenly spaced intervals using a modified hydraulic cutter tool. The jaws of the tool were modified to compress material rather than to shear it. A mathematical model was developed to relate the curvature of the deposited material to the volume of compression required to eliminate this distortion. Validation of this model was performed using 3D scan data to compare the change in wall curvature induced by compression to the volume of the applied compressions. Substrate deflection was also compared against a control wall, and implementation of wall compression reduced maximum deflections by 93% across a series of four depositions and subsequent compressions. Wall cross sections were also analyzed to determine the impact of compression on material hardness and grain structure. The results demonstrate that successively placed lateral compressions can effectively control and potentially eliminate bending distortion in printed parts. This methodology can be further developed to form a robust model for correction of thermally-induced distortion in WAAM components.

Additive manufacturing↗
DOE OSTI2022

Altering the Supply of Shielding Gases to Fabricate Distinct Geometry in GMA Additive Manufacturing

Wire arc additive manufacturing (WAAM) is the process by which large, metallic structures are built, layer-by-layer, using a welding arc to melt wire feedstock. In this process, the proper selection of the shielding gas plays a vital role in the achievement of structurally acceptable part geometries and quality surface finishes. In this study, the authors used either a ternary mix (He, Ar and CO 2 ) or a binary mix (Ar and CO 2 ) of shielding gases to deposit wall geometries using an open loop-controlled WAAM system developed at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility. The binary blend produced a wider and shorter geometry, while the ternary blend resulted in a narrower build that was more equivalent to the CAD geometry. The data indicated that the binary blend provided a higher oxygen concentration in the weld as compared to that of the ternary blend. The results imply that the arc characteristics and heat input had a significantly higher impact on the weld penetration than the surface tension effect of surface active elements. This was further verified by developing and applying a high-fidelity computational fluid dynamics (CFD) model of the thermophysical properties of gas mixtures. The results from the model showed that, while the influence of increased oxygen concentration on the surface tension for the binary blend led to a deeper penetration, the ternary blend gave rise to heat flux to the workpiece.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phase transformation dynamics guided alloy development for additive manufacturing

Fusion-based additive manufacturing technologies enable the fabrication of geometrically and compositionally complex parts unachievable by conventional manufacturing methods. However, the non-uniform and far-from-equilibrium heating/cooling conditions pose a significant challenge to consistently obtaining desirable phases in the as-printed parts. Here, in this study, we report a martensite stainless steel development guided by phase transformation dynamics revealed by in-situ high-speed, high-energy, high-resolution X-ray diffraction. This developed stainless steel consistently forms desired fully martensitic structure across a wide range of cooling rates (10 2 –10 7 °C/s), which enables direct printing of parts with fully martensitic structure. The as-printed material exhibits a yield strength of 1157 ± 23 MPa, comparable to its wrought counterpart after precipitation-hardening heat-treatment. The as-printed property is attributed to the fully martensitic structure and the fine precipitates formed during the intrinsic heat treatment in additive manufacturing. The phase transformation dynamics guided alloy development strategy demonstrated here opens the path for developing reliable, high-performance alloys specific for additive manufacturing.

17–4 PH stainless steel↗
NASA NTRSDate not supplied

Nanomechanical Characterization of Additive Manufactured GRCop-42 Alloy Developed by Directed Energy Deposition Methods

Propulsion applications such as combustion chambers and nozzles for liquid rocket engines require the use of unique materials with superior mechanical and thermal properties. GRCop-42(Cu-4 wt.% Cr-2 wt.% Nb) is one such candidate material developed by NASA and is now being manufactured using additive manufacturing (AM) techniques. AM offers a unique processing environment different from traditional metal fabrication processes. This study characterized the mechanical and structural properties of as-deposited and heat-treated GRCop-42manufactured with Blown Powder Directed Energy Deposition (BPD)based on preliminary testing. The materials were characterized using several techniques including surface profiling by laser microscopy, mechanical stiffness by instrumented indentation, crystal structure, residual stress measurements using XRD and residual XRD, and chemical composition and microstructural evaluation using SEM with EBSD. The results of the study are compared using the BPD techniques for samples in the as-deposited and heat-treated conditions.

GRCop-42↗