Search NASA⌕ Search

SEARCH · Search NASA

Results for “MANUFACTURABILITY”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Creep suppression and fatigue in bio-based composites manufactured via conventional and large format additive manufacturing processes

The emergence of novel extrusion-based additive manufacturing (AM) processes has prompted the development of new thermoplastic composite feedstocks, and broadening sustainability initiatives have driven the development of bio-based and recyclable material for AM feedstocks. Poly(lactic acid) (PLA) with wood flour (WF) is one composite system that has been demonstrated in numerous AM applications, as well as traditional processing methods (i.e., compression and injection molding); however, there has been a need to understand how the variation in processing methodology impacts the material performance of these bio-based feedstocks from a fundamental perspective, with particular emphasis on creep for an extended application use-life. Herein, PLA/WF is explored as a feedstock material for large format additive manufacturing (LFAM) and the performance of additively manufactured materials is compared to those produced via more traditional processing methods. It is also demonstrated that the addition of WF decreases the material’s coefficient of thermal expansion (CTE) while increasing its Young’s modulus, susceptibility to water uptake, and creep fatigue resistance. Essentially, the addition of 20 wt% WF results in a 92 % decrease in rubbery regime CTE while simultaneously resulting in a 14 % increase in modulus, 190 % increase in water uptake, and a 31 % decrease in residual strain after cyclic creep tests. The processing method was also found to play a large role in the final part performance, with the printed material increasing the crystallinity by 183 % and 214 % compared to its compression and injection molded counterparts. Furthermore, the porosity of printed samples increased by two orders of magnitude compared to samples prepared via traditional processing methods.

36 MATERIALS SCIENCE↗
DOE OSTI2021

On the additive manufacturing (3D printing) of viscoelastic materials and flow behavior: From composites to food manufacturing

Additive manufacturing (AM) or more commonly known as 3D-printing has gained much ground in industrial manufacturing because of its breakthrough in rapid prototyping and processes. To date, the 3D-printing market has grown significantly and is poised for growth in line with digitization of manufacturing. Furthermore, the main objective of this review article focuses on the viscoelastic behavior (viscous solution) of 3D printing materials at ambient conditions, which are not essentially under melt-flow or higher temperatures. The initial section reviews the basic concepts on viscosity and viscoelastic phenomenon, with emphasis on the preferred conditions a viscous material should have prior to 3D-printing. Several examples of structures formed from viscoelastic materials through 3D-printing are also detailed, as well as the various curing techniques for different printed objects or models. While there is much interest on industrial applications, the last part surveys various food formulations used for 3D-printing.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Industrial Deployment of Computer Aided Manufacturing Software for Hybrid Advanced Manufacturing

GibbsCAM, 3D Systems’ software product, is a full-featured CAM system that provides powerful CNC programming, capabilities, and solutions, delivering high quality parts without sacrificing ease of use. Oak Ridge National Laboratory (ORNL) collaborated with GibbsCAM to evaluate their toolpath generating software being developed for both blown powder and hybrid CNC/additive manufacturing machinery. The current approach in toolpath solutions for additive manufacturing is to utilize subtractive toolpaths created by existing CAM software and reversing it for additive manufacturing applications. GibbsCAM is working to develop a full solution to mitigate the challenges that arise with this approach and deploy a fully customized solution for producing quality, reliable components for a range of different DED systems. When successful, this will be an automated solution deployed through a future release of GibbsCAM software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Multi-scale characterization of supersolidus liquid phase sintered H13 tool steel manufactured via binder jet additive manufacturing

Additive manufacturing (AM) of H13 tool steel by binder jet 3D printing (BJ3DP) followed by pressureless supersolidus liquid phase sintering (SLPS) provides a low-cost alternative manufacturing method for components with intricate geometric features. However, the microstructure-mechanical property relationships for BJ3DP-SLPS produced H13 tool steel are not well understood, which makes it challenging to develop printing and post-processing methods that maximize part performance. In this work, we leverage atom probe tomography and transmission electron microscopy along with thermodynamic calculations to rationalize the microstructure-mechanical property relationships in as-sintered BJ3DP H13 tool steel. Here, we report for the first time, the presence of a continuous eutectic film-like carbide in H13 along with the more commonly observed cuboidal MX carbides in the prior liquid channels of the microstructure. Further, atom probe tomography revealed the interconnected nature of the MX carbides that appear to be discrete in two-dimensional micrographs. These continuous eutectic carbides and interconnected MX carbides result in brittle failure of the material. Characterization of these microstructural features will be critical in developing appropriate post-processing heat treatments for the improved mechanical performance of BJ3DP H13.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermal Management System for an Electric Machine with Additively Manufactured Hollow Conductors with Integrated Heat Pipes: Preprint

This paper discusses steps taken to size a thermal management system for an aircraft propulsion electric machine containing additively manufactured coils integrated with heat pipes aimed at boosting its specific power. Experimental setups are used to size and characterize heat pipes for the application and 3D thermal FEA is used to determine optimum heat transfer coefficient of convective boundaries. Geometric details of fin-based surface area enhancement required to reach target combined overall heat transfer coefficient (U) and surface area (A) performance (UA) in W/K, is worked out for relevant boundaries and the resulting UA is verified in 3D thermal FEA. Thermal management system's UA (by extension specific power) sensitivity to coolant temperature is explored and temperature distribution plots of optimized machine components are presented and discussed.

additive manufacturing↗
DOE OSTI2022

Design optimization of an additively manufactured prototype recuperator for supercritical CO 2 power cycles

Supercritical CO 2 (sCO 2 ) power cycles are being developed due to their potential for high efficiency and reduced capital cost. It is necessary that these recuperators operate at high pressures and temperatures, up to 30 MPa and 900 K, with effectiveness values > 95% and pressure drops <1% to achieve high cycle efficiencies. Moreover, it is also necessary to have reasonable cost recuperators to control the capital costs of the sCO 2 power cycles. In this study, a Plate Pin-Fin (PPF) heat exchanger has been proposed as an sCO 2 recuperator. This preliminary recuperator design leverages capabilities enabled by additive manufacturing. Although the PPF design has characteristics similar to those of a plate heat exchanger, small diameter and relatively long fins are used to increase surface area, enhance heat transfer, and provide structural support for the partition plates that separate the fluid streams. Existing correlations for heat transfer and pressure drop were adapted for the PPF heat exchanger. These correlations were implemented in a 1D analytical model and used for the optimization of a 5-kW th high temperature recuperator for an indirect sCO 2 cycle by varying the design parameters to minimize the quantity of material required. A 3D conjugate heat transfer numerical simulations were conducted to validate the heat transfer and pressure loss correlations. A steepest descent method was used to minimize heat exchanger mass for a 5-kW prototype recuperator subject to a maximum specified pressure drop. Additionally, the design analysis indicated that an optimum PPF recuperator would be attained for the minimum allowable pin transverse spacing, minimum pin width, minimum pin height and near maximum cell aspect ratio. Moreover, at a low material requirement of 0.216 kg/kW and a pressure drop, which is almost five times lower than the allowable pressure drop design target, the optimized PPF heat exchanger has the high potential to be an alternative to a printed circuit heat exchanger, which is a conservative design basis for the current state-of-the-art sCO 2 recuperators.

42 ENGINEERING↗
DOE OSTI2025

Comparison of three measurement modalities for 3D characterization of manufactured features and process-induced porosity in titanium alloy additively manufactured parts

Nondestructive characterization of internal features and defects within complex components is vital for many industrial applications, particularly with the advent of additive manufacturing (AM) technologies. However, community understanding of the limitations of nondestructive methods such as X-ray Computed Tomography (CT) can be limited in certain industrial sectors as these may be emergent applications. In this paper, we investigate the limits of X-ray CT measurements and compare extracted data with mechanical polishing serial sectioning (MPSS) and confocal laser scanning microscopy (CLSM). The test object is an additively manufactured titanium alloy disk that contains both process-induced porosity and machined features, including focused ion beam milled features designed to probe the resolution limits of X-ray CT. Results show that each of these characterization techniques has advantages and disadvantages. We compare data acquisition times, spatial resolution, geometric measurement accuracy and defect visualization fidelity across these modalities to establish a practical framework.

Additive manufacturing↗
DOE OSTI2020

Fabrication of UN-Mo CERMET Nuclear Fuel Using Advanced Manufacturing Techniques

Ceramic-metallic nuclear fuels are a candidate fuel for nuclear thermal propulsion systems due to their high heat transport properties, which are necessary in very high-temperature environments. The conventional fabrication of uranium nitride–molybdenum fuel has been thoroughly studied in the past, but modern manufacturing techniques have presented a unique opportunity for further development within this field. This work demonstrates the use of advanced manufacturing techniques to produce nuclear fuel pellets composed of uranium nitride microspheres encased in a molybdenum matrix. Binder jetting is used to print molybdenum disks that are filled with uranium nitride microspheres and afterward sintered using spark plasma sintering. Two fuel pellets were fabricated to demonstrate the methodology and to provide a baseline analysis of the effects of temperature and pressure processing conditions. Characterization of the sintered fuel pellets includes detailed microstructural analysis and thermal conductivity measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Traction Motor Design Trade-Offs with Additively Manufactured Anisotropic Bonded Magnets

Extrusion based big area additive manufacturing (BAAM) has been previously demonstrated for the fabrication of dense anisotropic bonded magnets. This paper reports on design trade-offs when such magnets are employed in a motor designed for electric vehicle applications. An external rotor fractional slot permanent magnet synchronous machine designed with sintered dysprosium free magnets rated for 100kW peak and 50kW continuous power is used as the baseline. The impact of using the bonded BAAM magnets on the motor and inverter volumes, motor loss and cooling systems as well as demagnetization margins is evaluated. It is found that although the motor power density reduces due to the lower energy product of the BAAM magnets, there are other system level benefits including reductions in the cooling system requirement, lower inverter rating and volume, decrease in short circuit current and improved demagnetization marains.

additive manufacturing↗
DOE OSTI2020

Cost-Effective Additive Manufacturing of Ambient Pressure-Dried Silica Aerogel

The conventional manufacturing processes for aerogel insulation materials mostly rely on the supercritical drying, which suffers from issues of massive energy consumption, high-cost equipment, and prolonged processing time. Considering the large market demand for the aerogel insulation material in the next decade, a cost-effective and scalable fabrication technique is highly desired. In this paper, a direct ink writing (DIW) method is used to three-dimensionally fabricate the silica aerogel insulation material, followed by room-temperature and ambient pressure drying. Compared with the supercritical drying and freeze-drying techniques, the reported method significantly reduces the fabrication time and costs. The cost-effective DIW technique offers the capability to print complex hollow internal structures, coupled with the porous aerogel structure, it is found to be beneficial for the thermal insulation property. In this work, the addition of fiber to the ink assures the durability of the fabricated product, without sacrificing the thermal insulation performance. The foam ink preparation methods and the printability are demonstrated in this paper, along with the printing of complex three-dimensional geometries. The thermal insulation performance of the printed objects is characterized, and the mechanical properties were also examined. The proposed approach is found to have a 56% reduction in the processing time. The printed silica aerogels exhibit a low thermal conductivity of 0.053 W m –1 K –1 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Distributed heterogeneous compute infrastructure for the study of additive manufacturing systems

We present the current status of a large-scale computing framework to address the need of the multidisciplinary effort to study chemical dynamics. Specifically, we are enabling scientists to process and store experimental data, run large-scale computationally expensive high-fidelity physical simulation, and analyze these results using the state-of-the-art data analytics tools, machine learning, and uncertainty quantification methods using heterogeneous computing resources, such as CPU and GPU cluster. The framework can integrate or abstract out multiple domains based on roles. In order to develop this framework, we have leveraged an existing framework coupled with in-house heterogeneous computing resources. We present the results of using this framework on a single metadata triggered workflow to accelerate an additive manufacturing use case.

heterogeneous computing, hpc, workflows, reproduci↗
DOE OSTI2022

Environmental Benefits of Closing the Solar Manufacturing and Recycling Loop: Preparation of Solar Manufacturing Inventories

The cumulative global solar panel waste stream is projected to reach between 60 and 78 million tonnes by 2050. Steps towards developing, demonstrating, and implementing processes that recover glass, metals, and semiconductor materials from end-of-life solar panels have already been taken. However, these processes result in the downcycling of most secondary solar materials. Critically, the costs and benefits of capturing these secondary materials for use in new solar panels are unknown. To evaluate the environmental benefit associated with solar material recycling and reuse in next generation panels, prior inventories must be updated and prepared for integration with recycling processes to examine the benefit of closing the material loop between solar panel end-of-life and new panel manufacturing. This current work describes steps taken to upgrade existing inventories that detail the manufacturing of cadmium-telluride (CdTe) panels from the Ecoinvent -v2.2 life cycle inventory database to Ecoinvent -v3. During this update, material inventories were modified to capture different realistic material supply chains within the constraints of Ecoinvent -v3. Materials discussed in detail in this work include primary flat glass, aluminum, steel, copper, and CdTe. This work demonstrated that environmental indicators such as embodied carbon, acidification, and terrestrial eutrophication associated with solar panel production can be reduced by 25% to over 40% through improved primary material sourcing.

CdTe solar panels↗
DOE OSTI2023

Using defects as a ‘fossil record’ to help interpret complex processes during additive manufacturing: as applied to raster-scanned electron beam powder bed additively manufactured Ti–6Al–4V

Abstract Defects in parts produced by additive manufacturing, instead of simply being perceived as deleterious, can act as important sources of information associated with the complex physical processes that occur during materials deposition and subsequent thermal cycles. Indeed, they act as materials-state ‘fossil’ records of the dynamic AM process. The approach of using defects as epoch-like records of prior history has been developed while studying additively manufactured Ti–6Al–4V and has given new insights into processes that may otherwise remain either obscured or unquantified. Analogous to ‘epochs,’ the evolution of these defects often is characterized by physics that span across a temporal length scale. To demonstrate this approach, a broad range of analyses including optical and electron microscopy, X-ray computed tomography, energy-dispersive spectroscopy, and electron backscatter diffraction have been used to characterize a raster-scanned electron beam Ti–6Al–4V sample. These analysis techniques provide key characteristics of defects such as their morphology, location within the part, complex compositional fields interacting with the defects, and structures on the free surfaces of defects. Observed defects have been classified as banding, spherical porosity, and lack of fusion. Banding is directly related to preferential evaporation of Al, which has an influence on mechanical properties. Lack-of-fusion defects can be used to understand columnar grain growth, fluid flow of melt pools, humping, and spattering events. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2021

A High-Throughput Method to Define Additive Manufacturing Process Parameters: Application to Haynes 282

This paper demonstrates how an analytical and experimental method can be used to rapidly define the 45 additive manufacturing settings for a new alloy where the process parameters were previously unknown. A nickel-based superalloy, Haynes 282, was chosen for the analysis. An experimental matrix of focused processing parameters was predicted with a dimensionless number and 100 samples were printed using the Selective Laser Melting technique. High-throughput measurements validated the predicted process conditions needed to achieve desired density and hardness. The whole process was completed in 16 hours. The new technique was confirmed with analytical processing maps adopted by the metal additive manufacturing community. With the predicted set of process parameters, microstructural characterizations and tensile testing were used to confirm the predictions. The resultant as-fabricated microstructures have refined length scales of both microsegregation and secondary phase distributions. As a result, the mechanical properties were comparable within the predicted processing window and exhibited high strength and high ductility.

Laser Material Processing↗
DOE OSTI2024

Residual stress accumulation in large-scale Ti-6Al-4V wire-arc additive manufacturing

Large-scale additive manufacturing (AM) is of interest in the manufacturing industry to produce components of dimensions on the order of hundreds of millimeters to meters in scale. Wire-arc AM (WAAM) of Ti-6Al-4V (Ti64) is an attractive technique for large-scale AM in the aerospace industry, give the high strength-to-weight ratio of the material and high deposition rate of the process. However, due to the large scale, significant distortion and residual stresses are developed in the material during deposition and cooling, potentially leading to part failure. WAAM of a prototypical large-scale Ti64 machine tool component is studied in this work via finite element analysis (FEA). Element activation/deactivation technique is employed to simulate deposition and the resulting distortion and residual stress (RS) predictions are analyzed to evaluate the possibility of crack formation. Significant distortion (∼10 mm) and RS (>1300 MPa) is predicted, suggesting the formation of cracks and possible crack propagation into the build region. Incorporation of fillets significantly reduces RS concentration regions, thus reducing the possibility of part failure. Material deposition sequence also affects the RS pattern in the build.

Mathews, Ritin↗
DOE OSTI2020

Real-Time Defect Correction in Large-Scale Polymer Additive Manufacturing via Thermal Imaging and Laser Profilometer

Defects can result in a failed part and are costly in terms of time and material. This cost is even greater in the context of large-scale additive manufacturing where the objects can be very large. As a result, a great deal of research has focused on defect identification and mitigation. To address defects during object construction, researchers at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility investigated an in-situ control system comprised of two sensors: a thermal camera and laser profilometer. This control system adjusted material flow and build speed to mitigate three types of defects: low layer times, underfill, and overfill. Several test objects were constructed. The control system was found to adjust build parameters to handle low layer times of approximately 15 seconds and height deviations from -100% underfill (the absence of a layer) to 50% overfill. Within two layers, height deviations could be returned to within 10% of the expected layer height. Further, preliminary results suggest the system can compensate for uneven build surfaces.

Borish, Michael↗