Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Manufacturing processes”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10.1)

This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, GammaPrint-700, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR). To download the dataset: (1) Create a Globus account. (2) Create a Globus Endpoint on your computer. (3) Transfer the dataset from the OLCF DOI-DOWNLOADS Collection to your Collection. Common troubleshooting steps: (a) Confirm that the transfer is going from OLCF DOI-DOWNLOADS to your Collection. (b) Create an exception for Globus in your antivirus software so that it can create an Endpoint. (c) Manually create a Globus access directory (where the data will be downloaded) by going to the Preferences > Access tab.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Co-Registered In-Situ and Ex-Situ Dataset from an Electron Beam Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-09)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from a single Arcam Q10 Electron Beam Powder Bed Fusion (EB-PBF) Inconel 738 build. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise Near Infrared (NIR) in-situ imaging data, in-situ temporal sensor data, ex-situ X-Ray Computed Tomography (X-CT) scans, and the target part geometries. Additionally, anomaly detections produced by a trained Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Co-Registered In-Situ and Ex-Situ Dataset from a Laser Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-10)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from a single Concept Laser M2 Laser Powder Bed Fusion (L-PBF) stainless steel 316L build. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise visible-light in-situ imaging data, the laser scan paths and parameters, in-situ temporal sensor data, X-Ray Computed Tomography (X-CT) scans, pycnometry and tensile test results, etched micrographs from selected locations, and the target part geometries. Additionally, anomaly detections produced by a modified Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Co-Registered In-Situ and Ex-Situ Tensile Properties Dataset from a Laser Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-11)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from five Concept Laser M2 Laser Powder Bed Fusion (L-PBF) stainless steel 316L builds containing 6,299 SS-J3 individually tracked tensile coupons. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise visible-light in-situ imaging data, the laser scan paths and parameters, in-situ temporal sensor data, room-temperature static tensile test results, and the target part geometries. Additionally, anomaly detections produced by a modified Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Binder Jet Additive Manufacturing Process and Material Characterization for High Temperature Heat Exchangers Used in Concentrated Solar Power Applications

The U.S. Department of Energy’s (DOE) Sunshot 2030 initiative has a goal of reducing the cost of concentrating solar power (CSP) to 5 cents per kWh for baseload power plants. One of the potential pathways to this goal includes a reduction in the cost of the supercritical CO2 (sCO2) power block to 0.9 cents per kWh. Recuperators—high and low temperatures, used in the sCO2 power cycle, contribute to >50% of the cost of the power cycle. This work studies the feasibility towards a ≥10% cost reduction for High Temperature Recuperators (HTR) used in the sCO2 power cycle. One way to address the cost reduction is by leveraging low-cost additive manufacturing, specifically, Binder Jet Additive Manufacturing (BJAM) to 3D print HTRs at scale. This study focuses on the development of a BJAM process towards 3D printing HTR cores using Stainless Steel alloy 316L (SS316L). To evaluate the suitability of the BJ process towards the HTR, high level specifications of the application are translated to materials capability requirements. Subsequently, at-temperature materials testing is conducted on as-printed and sintered additively manufactured coupons. Data from the coupons are compared against cast and wrought SS316L data obtained from the literature. Results show that the tensile properties from the BJ process compare well against cast properties. Furthermore, a baseline analysis of creep testing data is established for the BJ process, and insights are drawn from the results towards future improvements of the process.

14 SOLAR ENERGY↗
DOE OSTI2023

Additive manufacturing process parameter determination for a new Fe-C-Cu alloy

As a potential replacement for stainless steel alloys commonly used to print parts with laser powder bed fusion, a new Cu precipitation strengthened ferrous alloy, with composition Fe-0.2C-6Cu (wt%), was recently developed. This material is Co- and Ni-free, printable, has mechanical properties comparable to that of high strength stainless steels (approximately 1300 MPa UTS), and is cost-advantaged relative to existing low-alloy steels for additive manufacturing of parts with complex shapes. To gain traction for broader application, optimal laser powder bed fusion (LPBF) processing conditions to produce nearly defect-free parts without compromising mechanical strength are needed. Here, an optimal processing window based upon laser speeds that achieve minimal porosity was quantified via comparisons of measured melt pool penetration, scan speeds, printed material density and laser beam energy density on a commercial LPBF unit operating at 350 W, 80 μm hatch spacing, and 50 μm layer thickness based upon optimal parameters for 17-4PH. Furthermore, the window is 300 to 500 mm/s to achieve >99.8 % dense Fe-0.2C-6Cu (wt%) specimens. Other defects such as burning, spatter, and lack of fusion were also avoided in this window. The window was validated with in-situ synchrotron X-ray imaging that enabled visualization of the vapor cavity, melting, and solidification during a single laser track scan on a miniature powder bed sample. In addition, in-situ infrared imaging provided temperature fields, cooling rate and solidification range, and confirmed minimal printing defects and spatter within the processing window.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Warpage-Resistant, Under-Extrusion-Free, High-Surface-Quality Additive Manufacturing Process for Polyethylene-Based Composite Radiation Shielding Material

Polyethylene (PE) is one of the best shielding materials for primary space radiation due to its high hydrogen content. For effective secondary neutron shielding, boron-rich fillers are incorporated to enhance performance. The semicrystalline nature and high thermal expansion coefficient of PE impede its adoption for in situ additive manufacture in space via the fused deposition modeling (FDM) 3D printing. Here, we developed an optimized PE blend to mitigate the effects of under-extrusion and warpage. Guided by studies on extrusion and warpage, we developed an optimal set of printing parameters for the proposed PE blend. The optimum PE blend─both in its pure form and when doped with fillers─has been tested on different FDM printers. The printed structures exhibit high and uniform density, smooth surfaces, no warpage, and competitive mechanical properties. The FDM-printed plates demonstrate efficient shielding from thermal neutrons, predicted via modeling and confirmed experimentally using extended Q-range small-angle neutron scattering.

additive manufacturing↗
DOE OSTI2024

Indirect additive manufacturing process for fabricating bonded soft magnets

A bonded soft magnet object comprising bonded soft magnetic particles of an iron-containing alloy having a soft magnet characteristic, wherein the bonded soft magnetic particles have a particle size of at least 200 nm and up to 100 microns. Also described herein is a method for producing the bonded soft magnet by indirect additive manufacturing (IAM), such as by: (i) producing a soft magnet preform by bonding soft magnetic particles with an organic binder, wherein the magnetic particles have an iron-containing alloy composition with a soft magnet characteristic, and wherein the particles of the soft magnet material have a particle size of at least 200 nm and up to 100 microns; (ii) subjecting the preform to an elevated temperature sufficient to remove the organic binder to produce a binder-free preform; and (iii) sintering the binder-free preform at a further elevated temperature to produce the bonded soft magnet.

Paranthaman, Mariappan Parans↗
DOE OSTI2022

Development of a concurrent coupled Atomistic - Continuum model to predict the defect and grain structure for Additive Manufacturing process [Slides]

Development of a coupled atomistic-continuum model for metal AM process. Two-way coupling between atomistic (heat flux) and continuum (temperature) domain. Identification of grain and dislocation structure at the atomistic domain. Conversion of dislocation data from discrete atomistic to density form at the continuum. Obtain the spatial distribution of grain structure and dislocation density in additively manufactured metal polycrystal material.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Recent advancements in high performance polymer electrolyte fuel cell electrode fabrication – Novel materials and manufacturing processes

The global effort to introduce polymer electrolyte fuel cells for clean and renewable energy to the market is increasing the demand for high performance, robust and affordable membrane electrode assemblies (MEAs). There is not yet a standard method for large scale production of MEAs, or the methods employed are generally unsatisfactory in terms of quality and performance. A large number of published data of newly developed catalyst and electrolyte materials, claim to improve the state of the art, but are often not fully comparable due to different experimental studies and experimental designs. This article summarizes the trends in material developments and emerging MEA-manufacturing techniques. The materials and techniques are systematically compared in terms of cell performance and scalability. Current and future scientific challenges are identified and analysed based on published findings over the past five years. Finally, the results of the cited papers have been quantitatively compared to each other and to the internal benchmarks used in each cited work to provide a complete picture of the state of the art in PEFC MEA manufacturing.

25 ENERGY STORAGE↗
DOE OSTI2021

Advances in Processing, Manufacturing, and Applications of Magnetic Materials

Magnetic materials are increasingly important for many green energy technologies. Probably, the best known of these are permanent magnets. They are used to supply a magnetic field and are widely used in actuators, motors, generators, data storage, and sensors. These are “hard magnets,” meaning that they retain a large permanent magnetization (difficult to be demagnetized), which is what makes them so useful in motors where an opposing magnetic field can be used to push against them. A coercivity (resistance to demagnetization) of ~400 Oe (32,000 A/m) or more is typically the threshold value for a hard magnet and is typical of isotropic sintered ferrite (SrFe 12 O 19 ) such as found in many “refrigerator magnets.” Comparably important soft magnets are useful for directing magnetic fields and can be very easily (de)magnetized. As such, they typically have a coercivity < 12.5 Oe (1000 A/m), and specialized very soft magnets can have coercivities < 0.00125 Oe (1 A/m). Some common applications include coil cores, transformer cores, and magnetic shielding. Additionally, they are important for many AC electrical applications such as inductors, filters, and resonators, particularly at high frequencies up to and including microwaves.

36 MATERIALS SCIENCE↗