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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Precipitation hardening of laser powder bed fusion Ti-6Al-4V

Here, the laser powder bed fusion (PBF-L) additive manufacturing (AM) community has dedicated significant efforts into process optimization and control for defect-free Ti-6Al-4V. As defects become less of an issue for PBF-L Ti-6Al-4V, the processing-structure-properties (PSP) relationships between AM microstructures can now be explored to optimize mechanical properties. Lower temperature aging treatments around 550 °C in wrought Ti-6A-4V have been historically understood to precipitation harden the α phase with an ordered, hexagonal close packed (HCP) α 2 phase. The α 2 phase existed as nanoscale Ti 3 Al precipitates coherent with the parent α phase. The goal of the present investigation was to implement a vacuum heat treatment of 545 °C for 100 hours on PBF-L Ti-6Al-4V. This vacuum heat treatment took place after an initial hot isostatic pressure (HIP) treatment that decomposed the as-built, martensitic microstructure. The vacuum aging successfully produced nanoscale precipitates of α 2 phase within α-laths, confirmed via atom probe tomography (APT). Microstructural-length scale and quasi-static mechanical properties were investigated by nanoindentation and uniaxial tensile tests of miniaturized test specimens. Given the sensitivity of Ti-6Al-4V mechanical properties to small changes in chemistry, all test specimens originated from the same build. The α 2 precipitation resulted in significantly harder α-laths (≈ 2 GPa) as measured via nanoindentation, as well as a relative yield and ultimate tensile strength increase of 60 MPa and 38 MPa, respectively. Analysis of Variance (ANOVA) of the datasets revealed no statistical differences in total elongation between the HIPed and HIPed + aged specimens, indicative of the aging treatment producing a net benefit of strength with no loss in ductility.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An experimental process parameter study on the identification of defects in additively fabricated Al6061 with laser powder bed fusion

Additively fabricated metal parts using laser powder bed fusion (L-PBF) possess sophisticated morphology due to the recurrent use of laser-induced metal powder melting and solidification. The surface and 3D morphology of these parts often include defects in the form of protrusions, depressions, pores, voids, keyholes, or cracks that are known to be influenced by laser scanning paths and layer-to-layer processing. Such inconsistent part quality hampers the extensive adoption of L-PBF. Pores and cracks are detrimental to the fatigue life of the parts and components. Quantifying and controlling part defects and optimizing processing and scanning strategy parameters adaptively in real-time through in situ monitoring systems are highly desired. This study investigates the optimization of experimental process parameters (power, scan velocity, and hatch spacing) and their effects on the cracking and porosity of Al6061 alloy using machine learning techniques. Multi-objective optimization is formulated and conducted to determine the L-PBF parameters that minimize both porosity and crack densities.

36 MATERIALS SCIENCE↗
NASA NTRS1999

Effect of furosemide on pulmonary blood flow distribution in resting and exercising horses

We determined the spatial distribution of pulmonary blood flow (PBF) with 15-micron fluorescent-labeled microspheres during rest and exercise in five Thoroughbred horses before and 4 h after furosemide administration (0.5 mg/kg iv). The primary finding of this study was that PBF redistribution occurred from rest to exercise, both with and without furosemide. However, there was less blood flow to the dorsal portion of the lung during exercise postfurosemide compared with prefurosemide. Furosemide did alter the resting perfusion distribution by increasing the flow to the ventral regions of the lung; however, that increase in flow was abated with exercise. Other findings included 1) unchanged gas exchange and cardiac output during rest and exercise after vs. before furosemide, 2) a decrease in pulmonary arterial pressure after furosemide, 3) an increase in the slope of the relationship of PBF vs. vertical height up the lung during exercise, both with and without furosemide, and 4) a decrease in blood flow to the dorsal region of the lung at rest after furosemide. Pulmonary perfusion variability within the lung may be a function of the anatomy of the pulmonary vessels that results in a predominantly fixed spatial pattern of flow distribution.

NASA Discipline Cardiopulmonary↗
NASA NTRSDate not supplied

Size Effects on Laser Powder Bed Fusion and Laser Powder Directed Energy Deposition GRCop-42 Alloy

Additive manufacturing (AM) plays a significant role in the fabrication of regeneratively cooled rocket engine combustion chambers, where internal channels are used to transport high pressure propellants to keep the engine from overheating. Cooling channels are designed with thin walls between the cooling and combustion sides, experiencing high thermal and mechanical stresses from large temperature gradients and internal pressures. Hence, selecting materials suited for this environment and maintaining a high-quality processing for this critical application is of utmost importance. GRCop-alloys (Cu-Cr-Nb) were developed as an ideal material for combustion chambers due to its high conductivity and high strength at temperature, being employed as a structural member for the hotwall with excellent heat transfer capabilities. GRCop-42 (Cu, 4 at% Cr, 2 at% Nb) has significantly matured using the Laser Powder Bed Fusion (L-PBF) process through microstructure, mechanical and thermophysical properties and evaluations using hot-fire testing. Additionally, Laser Powder Directed Energy Deposition (LP-DED) has demonstrated successful deposition and geometry samples using GRCop-42. While the maturation in properties has focused on bulk material properties from standard test specimens, these cannot be extrapolated to be used in thin walls, as different features (i.e., microstructure, porosity, and surface texture) have a greater effect on thin walls, especially on AM structures built using L-PBF and LP-DED. This presentation provides an overview of the effects introduced by reducing the thickness on the fabrication, microstructure, surface metrology and subsequent mechanical properties of GRCop-42 using L-PBF and LP-DED as well as future work planned for this research.

Gabriel Demeneghi↗
NASA NTRS2026

A Dispersion-Strengthened Low-Density Niobium Alloy and Its Elevated Temperature Mechanical Performance

In response to the elevated-temperature and weight-reduction demands of modern aerospace applications, a novel oxide-dispersion-strengthened low-density niobium alloy (LDNb-ODS) was fabricated using laser powder bed fusion (L-PBF). To overcome powder procurement barriers, L-PBF feedstock was produced by blending commercial Nb521, Ti64, and Cr powder with Y2O3 nanoparticles via resonant acoustic mixing. Following L-PBF and a 1400°C vacuum heat treatment, the alloy achieved a density of 6.73 g/cc and a fine mean grain size of 4.62 µm stabilized by uniform ~30 nm yttria dispersoids. Microstructural analysis revealed a chemically inhomogeneous build with lack-of-fusion defects and a titanium (Ti) shift from a nominal 31.5 wt% in the starting powder blend to 24.8 wt% in the printed part due to preferential Ti loss during printing. Elevated-temperature tensile testing demonstrated that LDNb-ODS maintained a superior specific yield strength of 60-85 MPa/(g/cc) up to 800°C, outperforming nickel-based alloys Ni625, Ni230, and GRX-810. Between 870°C and 950°C, its specific strength surpassed both Ni718 and Ni625. In rapid stress-rupture testing at 1093°C and 20.7 MPa, uncoated LDNb-ODS survived 21.4 hours (a tenfold increase over legacy C-103) while an R512E silicide coating extended rupture life to 84.8 hours, confirming that oxidation accelerates low-stress failure. These findings demonstrate that additive manufacturing of LDNb-ODS provides a viable, lightweight alternative to nickel-based superalloys for high-temperature (>850°C) aerospace components.

Low Density Niobium Alloy↗
NASA NTRSDate not supplied

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

GRCop is an alloy family constructed of copper, chromium, and niobium and was developed by NASA for high heat flux applications. GRCop-alloys were specifically formulated for the requirements in channel-cooled main combustion chambers allowing for repeat use in high heat flux environments[1]. GRCop-84 was evolved using additive manufacturing techniques under a NASA development program. To further increase thermal conductivity while maintaining material strength characteristics, the percentage of alloying elements were cut in half and GRCop-42 was developed. In recent years, NASA has successfully additively manufactured GRCop-42 with comparable material characteristics to extrudedGRCop-42 using a Laser Powder Bed Fusion (L-PBF) process. Benefits of this process include fabrication of intricate internal cooling channels as well as a decrease in manufacturing time. However, there are some large disadvantages in using this process. The nature of the powder bed process imposes a strict volume constraint as well as an excessive amount of material inventory required. A Directed Energy Deposition (DED) process addresses these limitations while also speeding up the manufacturing process. With little data on how DED performs with GRCop-42, an investigation into the mechanical properties was conducted. More specifically, Blown Powder Directed Energy Deposition (BPD), was used to compare material properties to that of the L-PBF manufactured GRCop-42. The DED manufactured material was found to have less than 0.1% porosity. Tensile tests concluded that the DED manufactured GRCop-42 had lower tensile strengths at room temperature. The results point towards a process capable of producing fully dense parts capable of meeting mechanical strength requirements with some possible refinement of printing parameters.

GRCop-42↗
NASA NTRS2021

Effect of Temperature History on Thermal Properties of Additively Manufactured C-18150 Alloy Samples

The effects of thermal history on the thermal properties of C-18150 (Cu-1.5Cr-0.5Zr, wt.%) parts made by the laser powder-bed-fusion (L-PBF) additive manufacturing (AM) process with three different fabrication orientations (horizontal, angled, and vertical to the build direction) were investigated. A significant difference in thermal properties between as-fabricated and fully heat-treated L-PBF C-18150 samples was observed, and the mechanisms of such behaviors are discussed.

C-18150↗
NASA NTRS2026

Fatigue Behavior of Laser Powder Bed Fused HAYNES 214: Effects of Different Surface Treatments

In this study, under NASA’s Rapid and Analysis Manufacturing Propulsion Technology (RAMPT) project, effects of different surface post-treatments on surface texture and fatigue behavior of L-PBF Alloy 214 were investigated. Various subtractive SPTs including abrasive flow machining (AFM), machining (M), shot peening (SP), vapormatt (VM), dry electropolishing (DE), chemical milling (CM), chemical-mechanical polishing (CMP), electro chemical (ECP) were applied to study the variations of the surface texture, microstructure and uniaxial fatigue behavior under fully reversed strain-controlled condition at four different strain amplitudes of 0.005, 0.004, 0.003, and 0.0025 mm/mm. The insights gained regarding the relationship between structural and mechanical properties for different SPTs can help establish guidelines for selecting the most effective process to enhance the performance of Laser Powder Bed Fusion (L-PBF) Alloy 214, especially for critical aerospace applications.

Post-Processing↗
DOE OSTI2025

Laser powder bed fusion parameter estimation with k-NN

Abstract Laser powder bed fusion (L-PBF) is a technique within additive manufacturing that uses a high power density laser to build parts from fused powdered metal alloy. This technology is well equipped to produce complex parts with otherwise impossible features, such as hidden voids or lattice structures. Alongside capability, reliability and quality are key characteristics considered when choosing a manufacturing method, and these are gaining attention as this method becomes more prevalent in industry. One main indicator of a stable L-PBF process is consistent melt pool geometry, and the properties of which are likely to determine the quality of the part produced. As computing power and sensing technologies become more advanced, this melt pool geometry could be studied in real time. This work addresses the challenge by leveraging a k-nearest neighbor (k-NN) model to identify key features within melt pool imagery and predict the energy density. The k-NN model was trained on data provided by the National Institute of Standards and Technology (NIST). Data preprocessing was performed on the images to extract features that were used in the k-NN model. This approach was used to accurately infer the energy density of unseen layers within the same part. The algorithm was subsequently tested with unique scan strategies and found to reasonably estimate the energy density of different parts. A fivefold cross validation found the algorithm to be consistently predicting the class of 91.4% of the in situ melt pool images.

Jung, Patrick (ORCID:0000000267890859)↗
DOE OSTI2024

Efficient sensitivity analysis of the thermal profile in powder bed fusion of metals using hypercomplex automatic differentiation finite element method

Rapid cyclic temperature fluctuation occurring in powder bed fusion of metals using a laser beam (PBF-LB/M) influences the formation of flaws in printed parts. Consequently, there is a pressing need to enhance the quality of printed parts by developing innovative methodologies that can predict thermal histories and help uncover the intricate relationships between process parameters and thermal profiles. Sensitivity Analysis (SA) emerges as an essential tool for this, offering the potential for process optimization and enhanced quality control. Nonetheless, conventional SA methodologies often incur in excessive computational costs and potential numerical approximation errors. Here, to address this technical challenge, we present a novel method for SA that integrates the HYPercomplex-based Automatic Differentiation (HYPAD) technique with transient thermal simulations conducted via the finite element method (FEM). Leveraging this methodology, we efficiently and accurately perform SA for PBF-LB/M processes in a post-processing step. Compared to traditional methods like Finite Differences (FD), HYPAD-FEM required 96 % less computational time for obtaining sensitivities for 22 process parameters, under a comparative study conducted within the context of the 2018–02 AM benchmark of the National Institute of Standards and Technology. In summary, HYPAD-FEM offers superior efficiency and accuracy in SA over conventional methods, delivering the best sensitivity of a model without the need for step-size selection and problem or parameter-based implementations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Temperature-dependent mechanical properties and crystal plasticity parameters for additively manufactured Haynes-214 alloy: Experiments and numerical modeling

Our experimental mechanical testing data demonstrated that the additively manufactured (AM) laser powder bed fusion (L-PBF) Haynes-214 alloy exhibits non-linear mechanical properties as the temperature rises from ambient to 870 °C. Crystal plasticity (CP) simulations provide an effective approach to gaining deeper insights into microstructure-property linkages under thermomechanical loading. This method can reduce the need for costly high-temperature mechanical testing while accounting for the effects of crystallographic texture and grain morphology on the mechanical behavior of AM materials. However, calibrating a CP model is time-consuming because individual simulations are computationally expensive and hundreds (or more) of iterations over parameter sets may be required. To address this issue, we have designed a machine learning-differential evolution (ML-DE) CP framework that can accurately interpolate the tensile properties of AM L-PBF Haynes-214 alloy across a wide temperature range from ambient to 870 °C, with minimal reliance on experimental data. The framework uses electron backscatter diffraction (EBSD) measurements to generate statistically equivalent microstructural volume elements to serve as inputs to the CP modeling framework. Stress–strain curves were generated from 1000 CP simulations, which serve as the training data set for the three ML regression algorithms explored: linear, extra-trees, and multi-layer perceptron. These three regression models were independently evaluated to compare their efficiency and identify the most suitable algorithm for the given problem. Results revealed that the extra-trees ML regressor outperforms the other models in both qualitative and quantitative aspects with an R 2 of 0.98. Subsequently, the differential evolution optimization approach is employed to calibrate the ML-based CP material parameters with experimental results obtained at various temperatures. Finally, temperature-dependent CP material parameters are formulated. The effectiveness and efficiency of the designed framework are validated through comparison with experimental results, demonstrating a high degree of agreement. These calibrated parametric constitutive equations enable further use of the CP model to study the deformation behavior of this alloy under a wide range of thermo-mechanical loading conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Establishing an acoustic-property relationship in laser powder bed fusion with machine learning

Quality control of Laser Powder Bed Fusion (PBF-LB) additively manufactured parts is an important hurdle inhibiting the technology’s use structural applications. Acoustic monitoring of the laser powder bed fusion process can detect defects in-situ that are known to degrade mechanical properties. However, processing-structure-property (PSP) relationships are required to extrapolate from detected defects to part performance. Here, this study explores how acoustics may be a suitable signature linking processing conditions to properties, thus effectively substituting for structure in the PSP relationship. Establishing such a relationship would enable a part’s mechanical performance to be directly predicted from its acoustic signature, reducing the need for destructive testing or microstructural analysis to ensure a part will meet performance requirements. One hundred CoCrFeMnNi high entropy alloy tensile bars were printed across 13 process conditions in a series of 6 prints. The acoustic signatures of these tensile bars were used to train machine learning models to predict each part’s mechanical properties. By using both process information and acoustic information to predict mechanical properties, yield strength was predicted 18% more accurately and ductility to failure was predicted 10% more accurately than is achieved when using duplicate parts to predict part performance. Finally, individual acoustic frequencies were investigated to determine why acoustic signatures improve mechanical property predictions and the potential physical origins of these signatures. This work demonstrates how blending acoustics, process information, and machine learning can provide in-situ diagnostics of mechanical properties and improve the reliability of the PBF-LB process.

Acoustic emission↗
DOE OSTI2024

Microstructural effects on the rotating bending fatigue behavior of Ti–6Al–4V produced via laser powder bed fusion with novel heat treatments

The rotating bending fatigue (RBF) behavior (fully reversed, R = -1) of additively manufactured (AM) Ti–6Al–4V alloy produced via laser powder bed fusion (PBF-L) was investigated with respect to different microstructures achieved through novel heat treatments. The investigation herein seeks to elucidate the effect of microstructure by controlling variables that can affect fatigue behavior in Ti–6Al–4V, such as chemistry, porosity, and surface roughness. In order to control these variables, different hot isostatic pressing (HIP) treatments at 800 °C, 920 °C, and 1050 °C with a 920 °C temper were applied to three sets of Ti–6Al–4V cylinders that originated from the same PBF-L build, such that there were 30 tests per condition. After HIP treatment, the specimens were machined and tested. The highest runout stress was achieved after sub-β transus HIP at 800 °C for 2 h at 200 MPa of pressure. A significant drop in fatigue strength was attributed to large prior-β grains and grain boundary α resulting from super-β transus HIP treated specimens. In conclusion, for the sub-β transus HIP specimens, differences in fatigue strength were attributed to α lath thickness, relative dislocation density, and dislocation boundary strengthening.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Very high cycle fatigue characteristics of laser beam powder bed fused AlSi10Mg: A systematic evaluation of part geometry

This study explores the influence of geometry and part size on defect distribution, melt pool size, and mechanical characteristics in laser beam powder bed fused (LB-PBF) AlSi10Mg. Five distinct geometries—hourglass, small rod, small block, large block, and large rod—were fabricated under identical process parameters. Fully reversed ultrasonic fatigue testing, operating at a frequency of 20 kHz, was conducted to assess the very high cycle fatigue properties. The findings indicated that part geometry had a major impact on the fatigue properties of the material in the very high cycle fatigue regime. Specimens machined from large rods and large blocks had the lowest porosity and highest fatigue resistance. Microstructural analysis indicated that hourglass, small rod, and small block specimens had shallower melt pools and overlap depths compared to other geometries. This observation suggests a higher cooling rate in specimens with smaller cross-sectional areas, leading to the increased presence of entrapped gas pores and a lack of fusion defects. Understanding the relationship between part geometry and fatigue properties in LB-PBF components offers insights for optimizing design and manufacturing processes in additive manufacturing applications.

AlSi10Mg↗
DOE OSTI2025

Simulated effect of defect volume and location on very high cycle fatigue of laser beam powder bed fused AlSi10Mg

This study quantifies the interaction between volumetric defect location and size on the very high cycle fatigue (VHCF) of laser beam powder bed fused (LB-PBF) AlSi10Mg. Crystal plasticity finite element method (CPFEM) simulations were used to investigate the effects of defect location and size on the driving force for crack initiation. The CPFEM model was calibrated against uniaxial and cyclic experimental data of LB-PBF AlSi10Mg. Defect characteristics were informed by experimental data from the specimens produced in various geometries to create realistic representative volume elements (RVEs) with equivalent volume fractions of defects. By embedding defects of varying sizes and locations within the RVEs, fatigue indicator parameters (FIPs) were calculated to analyze the impact of defects’ characteristics on fatigue performance. Different combinations of defect volume and locations were generated for various microstructure instantiations, providing insight into extreme value fatigue responses. Larger defect volumes located on free surfaces consistently generated the highest FIPs, suggesting defect size and boundary proximity intensify stress concentration effects. RVEs with multiple smaller defects produced lower FIPs than those with single large critical defects. These findings underscore the critical role of defect characteristics on fatigue life, providing a foundation for future predictive modeling in fatigue-sensitive AM applications.

AlSi10Mg↗
DOE OSTI2025

Effect of threshold parameters on infrared segmentation methods for porosity detection in electron beam powder bed fusion

In-situ process monitoring has seen significant interest in additive manufacturing to address qualification and certification goals. This is especially prevalent in metal powder bed fusion processes such as electron beam powder bed fusion (PBF-EB), with layer-wise infrared imaging being commonly used to detect defects. Here, this work compares two different segmentation methods (static thresholding and statistical thresholding) used for detecting porosity from in-situ infrared imaging data for PBF-EB. Samples were manufactured at a variety of focus offset values to induce porosity. Then, the segmented infrared images were compared to ex-situ X-ray computed tomography scans, which served as a ground-truth reference for objective evaluation. Through this analysis framework, the influential parameters, static threshold and N-value (number of standard deviations above the mean pixel value), respectively, for both image segmentation methods were analyzed and compared for their effects on porosity detection. With optimal parameter settings, the two methods had similar porosity detection performance, but the statistical method performed better under a larger variety of parameter settings.

Infrared imaging↗
DOE OSTI2026

Process-level cost analysis of hybrid manufacturing pathways for aerospace structural components

Hybrid manufacturing is a promising route for producing complex aerospace components, yet systematic cost benchmarking across multiple additive-subtractive pathways remains limited. This study presents a comprehensive process-based cost analysis of seven hybrid manufacturing routes, including laser powder bed fusion (L-PBF), powder- and wire-directed energy deposition (DED), wire arc additive manufacturing (WAAM), additive friction stir deposition (AFSD), metal binder jetting (MBJ), and agility forging, followed by scanning and finish machining. Parametric cost models incorporating direct material, labor, and energy costs were developed. L-PBF results are discussed in detail for a pickle fork component and directly compared with commercial pricing. Across all hybrid routes, labor emerged as the dominant cost driver, contributing more than 70% of total manufacturing cost in some cases. AFSD exhibited the lowest cost for aluminum components, with MBJ being its 316 L stainless steel counterpart, after accounting for geometric scaling. Benchmarking against industrial quotes suggests that hybrid manufacturing can achieve cost levels comparable to those of commercial services, although labor-intensive processes exhibit greater deviation. The analysis highlights automation of material handling, setup, and supervision as key opportunities for improving economic competitiveness. Overall, the proposed framework provides a quantitative basis for evaluating and optimizing hybrid manufacturing pathways for aerospace applications.

Baruah, Sweta [ORNL] (ORCID:0009000174256207)↗
DOE OSTI2024

Active interlocking metasurfaces enabled by shape memory alloys

Interlocking metasurfaces (ILMs) are a newly developed joining technology that relies on arrays of interlocking features that transmit force and constrain motion between adjoining bodies in one or more directions. This study explores harnessing the shape memory effect (SME) in Nickel-Titanium shape memory alloys (NiTi SMAs) in structures fabricated using additive manufacturing (AM) to advance the development of active ILMs by creating unit cells that open or close at specific temperatures. The study encompasses designing and fabricating two distinct interlocking array configurations using near-equiatomic NiTi powder and the laser powder bed fusion (L-PBF) AM technique, following a previously developed AM process optimization framework to manufacture defect-free parts. To guide the design process, finite element analysis (FEA) was employed to predict strain values during engage-disengage cycles. The martensitic transformation characteristics of the ILMs were characterized. Thermomechanical testing revealed that the ILMs demonstrate high locking force once engaged, coupled with complete shape recovery and good cyclic stability. Digital image correlation (DIC) was also employed to validate the FEA predictions during the engage-disengage cycles. The results indicate that NiTi SMA-based ILMs can be designed and fabricated into complex shapes using L-PBF. By leveraging the SME, the functionality of an ILM can be improved upon. The combination of computational modeling, additive manufacturing, and thermomechanical and physical property characterization provides a framework for designing future ILMs out of active materials.

Additive manufacturing↗