SEARCH · Engineering Papers

Results for “Additively Manufacturing”

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.

SourceResearch connectionFrom yearThrough year

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

At least 199 records · Page 11

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Development of HPC based phase field simulations tool for modification of alloy morphology to enhance material properties during additive manufacturing (AM) process

Currently, additive manufacturing (AM) technology is extensively used to manufacture aerospace components because of the unique advantages of the technique in producing custom designs, complex geometries in a near-net fashion that significantly reduces the manufacturing cost, and improved energy efficiency. However, the thermodynamic properties of existing aerospace alloys and the thermal conditions that prevail in most of the powder-bed based additive manufacturing processes lead to undesirable columnar / columnar-dendritic microstructures that promote solidification cracking during the process, and the development of anisotropy in the mechanical properties of the as-built components. Time consuming, energy-intensive post AM treatments are required to recover the mechanical properties of the wrought components for which the existing alloy compositions were designed for. However, novel alloy compositions, that exploit the AM thermal conditions to produce fine, equiaxed grain structures in the as-built condition, with mechanical properties equal to or exceeding those of the wrought work-horse alloy, Ti-6Al-4V has recently been demonstrated in Ti-Cu alloys. Significant energy savings up to 66% can be obtained for a typical aerospace component through digitally designing the AM process, process parameters, and alloy composition. The current project focused on developing a fundamental understanding of the evolution of the columnar to equiaxed transition (CET) occurring during solidification under AM thermal conditions in Ti-Cu and Ti-Cu-X alloys using high-fidelity phase field (PF) simulations using the leadership class computing facilities that exist in the national laboratories. The simulations were able to capture the effect of alloy and process conditions on CET, and clearly showed the beneficial effect of a ternary solute addition to Ti-Cu binary alloys on CET. The simulations indicated that bulk nucleation in the liquid ahead of the solidifying epitaxial front was promoted by a large, transient, thermal undercooling promoted by the mismatch between the growth rate of the dendrite tips in the epitaxial front and the imposed solidification rate. AM experiments performed at Raytheon Technologies Research Center using the same thermal conditions used in the PF simulations indicated the formation of equiaxed grains, although the grain size was bigger than the ones reported in the literature. On the other hand, the equiaxed grain size predicted by PF simulations were smaller than the grain size of Ti-Cu alloys reported in the literature. The industry will follow up the existing work in a future program that would involve further optimization of the process for the Ti-Cu-X alloys to demonstrate the application of the process and the alloy to a specific aerospace component.

36 MATERIALS SCIENCE↗

DOE OSTI2020

3D Characterization of the Columnar-to-Equiaxed Transition in Additively Manufactured Inconel 718

Additive manufacturing (AM) provides enormous processing flexibility, enabling novel part geometries and optimized designs. Access to a local heat source further permits the potential for local microstructure control on the scale of individual melt pools, which can enable local control of part properties. In order to design tailored processing strategies for target microstructures, models predicting the columnar-to-equiaxed transition must be extended to the high solidification velocities and complex thermal histories present in AM. Here, we combine 3D characterization with advanced modeling techniques to develop a more complete understanding of the solidification process and evolution of microstructure during electron beam melting (EBM) of Inconel 718. Full calibration of existing microstructure prediction models demonstrates the differences between AM processes and more conventional welding techniques, underlying the need for accurate determination of key parameters that can only be measured directly in 3D. The ability to combine multisensor data in a consistent 3D framework via data fusion algorithms is essential to fully leverage these advanced characterization approaches. Thermal modeling provides insight on microstructure development within isolated solidification events and demonstrates the role of Marangoni effects on controlling solidification behavior.

Polonsky, Andrew↗

DOE OSTI2023

Invertible neural networks for real-time control of extrusion additive manufacturing

Material extrusion additive manufacturing (AM) has enabled an elegant fabrication pathway for a vast material library. Nonetheless, each material requires optimization of printing parameters generally determined through significant trial-and-error testing. To eliminate arduous, iteration-based optimization approaches, many researchers have used machine learning (ML) algorithms which provide opportunities for automated process optimization. Here, in this work, we demonstrate the use of an ML-driven approach for real-time material extrusion print-parameter optimization through in-situ monitoring of printed line geometry. To do this, we use deep invertible neural networks (INNs) which can solve both forward and inverse, or optimization, problems using a single network. By combining in-situ computer vision and deep INNs, the printing parameters can be autonomously optimized to print a target line width in 1.2 s. Furthermore, defects that occur during printing can be rapidly identified and corrected autonomously. The methods developed and presented in this work eliminate user-intensive, time-consuming, and iterative parameter discovery approaches that currently limit accelerated implementation of extrusion-based AM processes. Furthermore, the presented approach can be generalized to provide real-time monitoring and optimization pathways for increasingly complex AM environments.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Recycling of CF-ABS machining waste for large format additive manufacturing

Large format additive manufacturing (LFAM) necessitates the use of short fiber thermoplastic composites, such as carbon fiber filled acrylonitrile butadiene styrene, to enable printing. Currently, when LFAM parts are machined into their final shape, the machining scrap (i.e., small flake like particles and offcuts) is landfilled. Previous studies have demonstrated the viability of recycling end-of-life LFAM parts by shredding and optionally re-compounding the material back into pellets. However, there is little understanding of the value and performance of recycled material made from LFAM machining scrap, which if pursued could motivate more broad recycling of this waste stream. In this study, recycled in-process machining scrap is explored as an LFAM feedstock source. Herein, it is found that the primary degradation mechanism of the recycled material is significant fiber length attrition during surface machining. While this fiber attrition negatively impacts the mechanical performance of the material in the print direction, it seems that the changes in processing behaviors and print quality, namely the surface roughness of the printed structure associated with shorter fiber lengths, is beneficial to interlayer adhesion. The tensile strength and elastic modulus of the recycled material, in the print direction, decreased 11% and 31% respectively compared to the pristine material. However, in the layer-wise direction it was found that the recycled material exhibited no significant change in elastic modulus and a significant 21% increase in tensile strength – a surprising result. In conclusion, this work indicates that machining waste could be a viable material stream for recycled LFAM feedstock materials.

42 ENGINEERING↗

DOE OSTI2025

Using the optimal combined index weight ratio to improve the probability of anomaly detection in big area additive manufacturing

Big Area Additive Manufacturing (BAAM) of composites requires significant time, energy, and material, so it is critical to reduce production inefficiencies to make functional parts without multiple iterations. Statistical process control coupled with Principal Component Analysis (PCA) is a powerful technique that provides a quick, computationally inexpensive, and intuitive way for operators to detect defects that form in a manufacturing process without massive datasets. Recently, a combined index that is a weighted sum of the Hotelling's T 2 and squared residual error statistics has been proposed that can be monitored in one chart, improving interpretation accuracy and simplicity. However, the literature does not offer a formal method to optimise the weights. Here, we introduce two new approaches to the traditional weight selection approach using simulated and BAAM image data. Approach 1 uses a theoretically motivated optimum inspired by probabilistic principal component analysis. Approach 2 systematically varies the ratio of the weights to find the optimum. We show that approach 1 delivers optimal anomaly detection performance in select cases while approach 2 fares better in practice. Surprisingly, we also show that choosing a more complex PCA model has a minimal negative impact on anomaly detection performance compared to a more simplistic model.

3-dimensional printing↗

DOE OSTI2025

LatticeAnalytics: Strut-Level Visualization and Inspection of Additively Manufactured Lattice Structures

Additive manufacturing (AM) is revolutionizing the production of custom components with complex internal geometries, essential for high-performance applications in diverse fields such as medicine and defense. These AM parts optimize strength while minimizing weight by utilizing internal lattice structures consisting of large quantities of small interconnected struts. However, the complexity of these structures, combined with the challenges of using X-ray Computed Tomography (XCT) data, makes validation of part reliability difficult. This ultimately inhibits the development of novel parts for our collaborating material scientists. Here, we introduce LatticeAnalytics, a novel framework specifically designed for visual inspection of defects in these lattice structures. Our framework offers an end-to-end solution that includes the data management of XCT scans, enables remote access for geographically dispersed teams through a web-based dashboard, and incorporates novel visualizations. Our analysis is facilitated by a coarse alignment between the lattice’s nominal model, a spatial graph, and the XCT data. We employ a simple VR-based approach for fast and rough alignment, followed by an offline registration and identification of the struts. With the nodes and struts aligned and identified in the volume, our framework allows querying of subvolumes containing a single strut at multiple resolutions. This avoids computation over the entire lattice and also allow for easy parallelization of down-stream computations, such as strut-specific metrics. To depict a fast overview of the strut quality, we introduce two innovative visual encodings, crucial for our collaborators’ research in creating novel AM parts: the Contour View and the Roughness Map, which depict critical geometrical and surface features of individual struts in standardized two 2D views. We evaluated the integrated system through expert interviews. The feedback confirms the framework’s practicality and its effectiveness in enhancing current inspection workflows. It solves major bottlenecks for our collaborators, ultimately helping them create novel parts with advanced properties.

Miao, Haichao [Lawrence Livermore National Laborat↗

DOE OSTI2020

Material Developments for 3D/4D Additive Manufacturing (AM) Technologies

Additive Manufacturing (AM), or 3D printing, is a unique technology in which structurally complex objects can be easily manufactured. While AM allows for the creation of intricate 3D objects, these objects are inactive and motionless. With recent incorporation of a “pre-programmed functionality’’ to the 3D printed objects, a new concept has emerged, 4D printing. Specifically, the 4D printing technology enables a static 3D printed object to change its shape, functionality or property over time upon exposure to a specific stimulus such as heat, stress, light, pH, and moisture, etc. We designed and produced compact 3D/4D printable materials that can be used as (a) structural components of the unmanned aerial vehicles (UAVs), and (b) as hydrogen storage materials that supply hydrogen to a fuel cell to expand the operational reach, namely flight time, and endurance of the UA Vs.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Material Developments for 3D/4D Additive Manufacturing (AM) Technologies

Additive Manufacturing (AM), or 3D printing, is a unique technology in which structurally complex objects can be easily manufactured. While AM allows for the creation of intricate 3D objects, these objects are inactive and motionless. With recent incorporation of a “pre-programmed functionality” to the 3D printed objects, a new concept has emerged, 4D printing. Specifically, the 4D printing technology enables a static 3D printed object to change its shape, functionality or property over time upon exposure to a specific stimulus such as heat, stress, light, pH, and moisture, etc. We designed and produced compact 3D/4D printable materials that can be used as (a) structural components of the unmanned aerial vehicles (UAVs), and (b) as hydrogen storage materials that supply hydrogen to a fuel cell to expand the operational reach, namely flight time, and endurance of the UAVs.

08 HYDROGEN↗

NASA NTRS2021

The Effect of Composition on Microstructure and Properties for Additively Manufactured Superalloy 718

Additive manufacturing (AM) represents an exciting new approach towards producing metallic aerospace components. The ability to make complex geometries that were impossible to create using conventional manufacturing methods has sparked interest from the aerospace community, including NASA. The use of AM components for crucial and human rated space missions necessitates a full characterization of the differences between AM and more conventional wrought and cast processes. For this study, sixteen different commercially available superalloy 718 powder feedstocks were obtained, built using laser powder bed fusion(L-PBF), and microstructurally and mechanically analyzed. These measurements revealed a wide range of build qualities and microstructures despite all powder lots falling within the 718chemical specification and being processed using the same prescribed build and heat treatment parameters. Statistical analysis found a strong correlation of the amount of carbon in the powder with the final grain size and strength of the heat-treated 718 part. Ultimately, this study highlights the need of a refined superalloy 718 chemical specification for powder lots to be used in AM.

Timothy M Smith↗

NASA NTRSDate not supplied

Simultaneous Orthogonal Imaging for Cold Flow Characterization of Additively Manufactured Injector Elements

Additively manufactured (AM) injectors have the potential to improve characteristic velocity (C*) performance beyond the 90-97% of theoretical C* performance seen by traditionally manufactured (TM) combustion device injectors. Maximized C* performance yields high overall combustion efficiency in all types of combustion devices, particularly liquid rocket engines (LREs) and rotating detonation rocket engines (RDREs). A high degree of propellant atomization and mixedness is required to achieve maximum C* performance and therefore high overall combustion efficiency. This study focused on measuring and comparing the performance of different novel AM injector elements over a broad range of operating conditions under high pressure, cold flow. As part of this work, a high pressure, cold flow experimental spray facility was designed to measure each element’s injector spray patterns under pressures ranging from 50 to 1000 psig and stiffness ratios from 0.5 to 2.0. Preliminary results are presented from orthogonal, simultaneous imaging comparing atomization and spray geometry between quad, trio, pentad, slotted, and triplet impingers in gas-liquid flow.

Ari D Goldman↗

NASA NTRSDate not supplied

Additive Manufacturing at NASA

Additive Manufacturing (AM) is certainly changing the space industry and providing new opportunities to travel to low earth orbit and explore our universe. New design opportunities –not previously possible –for new high performance metal alloys, light-weighting, managing thermal, structural, and dynamic loads are being enabled by AM. This presentation will showcase the vast portfolio of NASA’s AM activities in the last 12 years; transportation from Earth to Destination, Habitat at Destination, Lander from Station to Surface, and Science mission spacecrafts. NASA’s technical excellence is being leveraged heavily in the AM community thru collaborative projects, partnership agreements, tech transfer program. Challenges as well as opportunities will be discussed.

Alison Park↗

NASA NTRSDate not supplied

Mitigating Grazing Flow Impedance Eduction Errors in Additively Manufactured Porous Liners

Additively manufactured porous metamaterials, including triply periodic minimal surface (TPMS) cores, are promising candidates for aeroengine liners but often behave as extended-reacting treatments under grazing flow. Standard impedance eduction procedures assume locally-reacting behavior and can yield physically inconsistent results for such materials. This study evaluates internal partitions (thin solid walls inserted at regular intervals along the liner’s streamwise extent) as a means of suppressing internal streamwise propagation to improve eduction consistency. Six TPMS configurations were tested in the NASA Langley Grazing Flow Impedance Tube (GFIT) at partition spacings of 4′′, 2′′, and 1′′, as well as unpartitioned, and at Mach numbers up to 0.3. For most geometries, 2′′ partition spacing eliminated impedance discontinuities and substantially improved Prony correlation, though effectiveness varied with core topology. Partitions also altered the acoustic response of the liners: resistance increased, resonance frequencies shifted downward, and peak attenuation decreased while bandwidth broadened in some cases. Because partitions modify the liner itself, the educed impedance characterizes the partitioned system rather than the original unpartitioned core. These results establish partitioning as a practical pathway toward liners that are more compatible with standard eduction methods, while demonstrating that the intervention is itself an acoustic design change.

liners↗

DOE OSTI2020

System and method for controlling an energy beam of an additive manufacturing system

An additive manufacturing system includes an energy beam generator that generates an energy beam to melt and fuse raw materials for a part and a computing device that controls operation of the energy beam generator. The computing device includes a memory element that stores or access a three-dimensional model of the part, and a processing element that receives at least a portion of the three-dimensional model and controls a parameter of the energy beam generator according to a gradient function so as to apply a variable amount of heat to the raw material that forms an overhang on the part.

42 ENGINEERING↗

DOE OSTI2024

Testing Protocol Development for the Fracture Toughness of Parts Built with Big Area Additive Manufacturing

The mechanical testing of additively manufactured parts has largely relied on the existing standards developed for traditional manufacturing. While this approach leverages the investment made in current standards development, it inaccurately assumes that the mechanical response of additive manufacturing (AM) parts is identical to that of parts manufactured through traditional processes. When considering thermoplastic, material extrusion AM, the differences in response can be attributed to an AM part’s inherent inhomogeneity caused by porosity, interlayer zones, and surface texture. Additionally, the interlayer bonding of parts printed with large-scale AM is difficult to adequately assess, as much testing is performed such that stress is distributed across many layer interfaces; therefore, the lack of AM-specific standards to assess interlayer bonding is a significant research gap. To quantify interlayer bonding via fracture toughness, double cantilever beam (DCB) testing has been used for some AM materials, and DCB has been generally used for a variety of materials including metal, wood, and laminates. Mode I DCB testing was performed on thermoplastic matrix composites printed with Big Area Additive Manufacturing (BAAM). Of particular interest was the notch shape and deflection speed during testing. The results examine the differences when using two notch types and three deflection speeds. The testing method introduced by the following paper differentiates itself from the ones described in the standards used by modernizing the methodology. This was conducted with the introduction of Digital Image Correlation (DIC) to gather displacement and load data simultaneously without human intervention.

Polymer Science↗

DOE OSTI2021

Adhesion of Titanium Coatings on Additively Manufactured Stainless Steel [Slides]

Additive manufacturing can improve fuel cell development by increasing design development speed, enabling complex designs through more flexible fabrication, and reducing wasted excess material. The goal of the project is to develop a process for strongly adhering a coating of titanium to additively manufactured stainless steel.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Fundamental Path Optimization Strategies for Extrusion-based Additive Manufacturing

Extrusion-based additive manufacturing processes begin with a software program, called a slicer, that generates layer geometry and fits toolpaths to each layer to define where material is to be extruded or deposited. Before the toolpaths are output as g-code for the additive manufacturing system to execute, the toolpaths should be optimized. Many complex optimization approaches using graph theory, Chinese postman problem, and other complex mathematical models exist, but these approaches are rarely used in daily printing operations and are not available through common slicing programs such as Cura and PrusaSlicer. Instead, path planning and optimization typically revolves around simpler, fully automated approaches such as inside out and next closest. This paper will explore the fundamental optimization strategies for toolpath planning and document a new implementation, available via open-source slicing software, that allows for greater control of the path planning process.

Roschli, Alex [ORNL] (ORCID:0000000213084632)↗

DOE OSTI2023

Systems and methods for additive manufacturing magnetic solenoids

Systems and methods for forming a magnetically-enabled part via additive manufacturing. The method includes depositing a layer of additive manufacturing material on a build plate, melting or sintering the layer of additive manufacturing material, depositing additional layers of additive manufacturing material on previous layers of additive manufacturing material, the additive manufacturing material of at least some of the additional layers being magnetically permeable, and melting or sintering the additional layers of additive manufacturing material such that the magnetically-enabled part has a transition region including at least some of the magnetically permeable additive manufacturing material.

Hatch, Jonathan Douglas↗

DOE OSTI2024

Systems and methods for additive manufacturing magnetic solenoids

Hatch, Jonathan Douglas↗