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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Pressure-based process monitoring of direct-ink write material extrusion additive manufacturing

As additive manufacturing (AM) has become a reliable method for creating complex and unique hardware rapidly, the quality assurance of printed parts remains a priority. In situ process monitoring offers an approach for performing quality control while simultaneously minimizing post-production inspection. For extrusion printing processes, direct linkages between extrusion pressure fluctuations and print defects can be established by integrating pressure sensors onto the print head. In this work, the sensitivity of process monitoring is tested using engineered spherical defects. Pressure and force sensors located near an ink reservoir and just before the nozzle are shown to assist in identification of air bubbles, changes in height between the print head and build surface, clogs, and particle aggregates with a detection threshold of 60–70% of the nozzle diameter. Visual evidence of printed bead distortion is quantified using optical image analysis and correlated to pressure measurements. Importantly, this methodology provides an ability to monitor the quality of AM parts produced by extrusion printing methods and can be accomplished using commonly available pressure-sensing equipment.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Material extrusion additive manufacturing of wood pulp-reinforced epoxy composites

Direct ink writing (DIW) is an extrusion-based form of 3D-printing that has gained popularity over the last decade. DIW uses thixotropic fluid extrusion to form a particular shape. In order to form stable structures, the rheology of the paste is important to allow for extrusion from the syringe, stability of the growing print, and prevention of unwanted seeping flow during jog moves. In this work, we use wood pulp as a bio-based filler that can provide shear thinning properties to the ink, which produces a stable ink for DIW processing. Additionally, the filler imparts improved mechanical and thermal performance compared to neat resin. The wood pulp provided the shear thinning behavior necessary for DIW printing, and pulp loadings greater than 6 wt%, provided sufficient yield stress so that the composite could self-support during printing. Nanoclay was utilized to further improve ink rheology and appearance to enable larger scale printing. Overall, this work showed successful DIW of an epoxy resin with a sustainable filler improving its stiffness and thermal properties and provides an avenue for further development of bio-based inks for DIW towards various applications.

Lamm, Meghan E. [Oak Ridge National Laboratory (OR↗
DOE OSTI2023

Low density syntactic foams via material extrusion additive manufacturing

An ink formulation for additive manufacturing of low density syntactic foams is described. The ink formulation can include a thermoset resin, a curing agent suitable for use with the thermoset resin, a plurality of hollow spheres, such as glass microballoons, one or more solvents, and one or more non-hollow, viscosity modifying filler. Also described are a method of preparing the ink formulation, a method of preparing three-dimensional objects comprising low density syntactic foams, and the three-dimensional objects prepared thereby.

Compton, Brett Gibson↗
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

Machine learning informed control systems for extrusion printing processes

Systems and methods for controlling a material extrusion device to extrude a filament of an ink are provided. An extrusion printing control system collects from one or more sensors measurements representing an internal state of material extrusion processing during extrusion of the filament. In addition, the system collects an image of the filament as the filament is extruded. The system applies a classifier to the collected image to generate an image-derived state characterizing the filament. Based on the internal state and the image-derived state, the system estimates a derived state using a model. The system determines control parameters using the model to achieve a desired quality of the filament by minimizing a cost function based on the internal state, the image-derived state, the derived state, and constraints of the material extrusion device. Finally, the system provides the control parameters to a controller of the material extrusion device.

Howell, Brian↗
DOE OSTI2023

1. Introduction to Additive Manufacturing

Additive manufacturing (AM) is the process of constructing an object by adding layer upon layer of material in specific locations, to build the object into its final shape. There are many different AM processes that can be used to add layers of material, such as extrusion, material jetting, and sheet lamination. All of the AM processes are a form of digital fabrication because the object to be constructed must first be modeled with a computer. The modeled object must be converted into machine instructions that an AM system can use to construct the object. This chapter serves as an introduction to the many different AM processes. Subsequent chapters will explore the intricacies of creating machine instructions for the AM processes introduced here.

Macdonald, Eric↗
DOE OSTI2023

Extrusion parameter control optimization for DIW 3D printing using image analysis techniques

Material extrusion is a well-recognized facet of additive manufacturing that involves the fabrication of parts through the deposition of structural material from an extrusion head from a bulk supply. In the subdivision of Direct Ink Writing (DIW) additive manufacturing, challenges arise when the structural material is flowable, synchronous extrusion control and tool movement becomes critical for achieving high-quality parts with low defect populations. DIW techniques are most used in laboratory settings using expensive custom instruments and may require specialized 3D slicing software. Here, in this study, the fabrication of an inexpensive, consumer-friendly progressive cavity pump dispensing system is detailed, in which can create high-quality parts by executing G-code commands produced from a commercial slicing software. The precision and repeatability of the movement-synchronized material extrusion is demonstrated through a series of optimization schemes, entailing the alteration of various control parameters, which directly affect the extrusion properties demonstrated during a print. In situ diagnostics were implemented to evaluate the results of the established optimization experiment. Using a machine vision technique, images of the optimization prints are processed. Following this, a supervised machine learning model was trained to autonomously judge whether or not the extrusion parameters produced a passing or failing result. The machine learning scheme serves as a preliminary benchmark for future layer-by-layer evaluation of more complex DIW parts. The construction of the printer and development of in situ characterization capabilities demonstrates the ability for this printer to create high-fidelity DIW parts for a fraction of the price of other systems.

42 ENGINEERING↗
DOE OSTI2024

Methodology to determine printability criteria of highly concentrated pastes through rheological characterization

Material extrusion is an additive manufacturing technique that enables the creation of reproducible and complex hardware by depositing a viscous, shear-thinning ink onto a substrate in a custom-pattern via extrusion through a syringe. Here, the ability of an ink to be extruded onto a substrate in many layers, and maintain the desired shape is what defines the printability. Printability is often investigated by formulating, printing, and postmortem analysis of final parts in an iterative manner. Investigations of printability through rheological characterization have often been concerned with inks that straddle the line between printable and too thin, leaving out an entire class of inks that are highly-filled pastes, where extrudability is the limiting factor. Highly-filled pastes continue to pose issues for researchers as the effect of filler morphology, size, loading, and packing fraction on the ink rheology and corresponding printability is not understood. While traditional rheological characterizations may be useful for some inks, we show that protocols utilizing steady-shear, or large-amplitude oscillatory shear are difficult and unreliable for highly-filled pastes. Through transient rheology paired with real-time images we show that each traditional protocol produces inhomogeneous deformations that violate the assumptions that underly common rheological definitions. Instead, we demonstrate metrics measured with small-amplitude oscillatory shear that are correlated to the printability of various ink formulations ranging in loading. The rheological measures that accurately predict the printability of the inks are the axial stress measured at small amplitudes, and the critical stress amplitude above which rheological characterizations become impossible. In addition, we estimate the maximum packing fraction for each filler, based on the exponent common to hard sphere models, and show that the printability of each ink can be predicted by the ratio of the packing fraction to the theoretical maximum. We show how small-amplitude oscillatory shear allows users to develop printability criteria for any ink to enhance the workflow in the development of new inks, increase the performance of material extrusion printing, and improve the stability of printed parts, with less wasted time and materials.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Using Additive Manufacturing to Print a CubeSat Propulsion System

CubeSats are increasingly being utilized for missions traditionally ascribed to larger satellites CubeSat unit (1U) defined as 10 cm x 10 cm x 11 cm. Have been built up to 6U sizes. CubeSats are typically built up from commercially available off-the-shelf components, but have limited capabilities. By using additive manufacturing, mission specific capabilities (such as propulsion), can be built into a system. This effort is part of STMD Small Satellite program Printing the Complete CubeSat. Interest in propulsion concepts for CubeSats is rapidly gaining interest-Numerous concepts exist for CubeSat scale propulsion concepts. The focus of this effort is how to incorporate into structure using additive manufacturing. End-use of propulsion system dictates which type of system to develop-Pulse-mode RCS would require different system than a delta-V orbital maneuvering system. Team chose an RCS system based on available propulsion systems and feasibility of printing using a materials extrusion process. Initially investigated a cold-gas propulsion system for RCS applications-Materials extrusion process did not permit adequate sealing of part to make this a functional approach.

electric propulsion systems↗
DOE OSTI2024

Planar slicing for nonextrusion AM processes

Extrusion-based AM processes, including material extrusion and directed energy deposition, construct objects by continuously depositing a relatively small amount of molten feedstock to a specific location. Nonextrusion AM processes, on the other hand, tend to form each layer by linearly or areally projecting either energy onto a vat of photocurable liquid or a binding agent into a bed of loose powder. Such systems vary significantly from extrusion-based AM processes but do share similarities. The general approach to path planning is the same, but nonextrusion processes typically favor the use of bitmap representations, instead of polygons, for pathing computation and do not use a g-code file to command the printer. In this chapter, a high-level discussion of these differences will be covered.

Macdonald, Eric↗
DOE OSTI2022

Sealability Qualification of Material Extruded Zytel Gaskets at Extreme Temperatures

In this work, an in-depth qualification of additively manufactured Zytel for gasketing proton exchange membrane fuel cells (PEMFC’s) subject to extreme temperature conditions. The temperature cycling of the PEMFC from 55°C to 100°C accelerates the deterioration of these gaskets compared to that of conventional operation. The additive manufacturing process employed to print these gaskets is material extrusion using Zytel filament. In order to see the effects of the temperature of interest on the printed specimen, each specimen was thermally soaked and then charactered and tested according to ASTM standard F37B. ASTM F37B tests a materials ability to seal and maintain it while bearing both a compressive load and internal pressure load to simulate being in static operation. This process of thermally soaking and sealability testing is shown to show the validity of both this material and additive manufactured components for other applications as well. It is observed that soaking the gaskets at 100°C corrects some of the defects that are present after printing such as missing layers and small voids on the surface of the samples. This allowed for the hot soaked materials to perform better than the samples at room temperature and cold soaked.

Sealability↗