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At least 937 records · Page 52

Comparison of the Effects of Tool Geometry for Friction Stir Welding Thin Sheet Aluminum Alloys for Aerospace Applications

In this presentation, the results of a recent study on the effect of pin tool design for friction stir welding thin sheets (0.040") of aluminum alloys 2024 and 7075 are provided. The objective of this study was to investigate and document the effect of tool shoulder and pin diameter, as well as the presence of pin flutes, on the resultant microstructure and mechanical properties at both room temperature and cryogenic temperature. Specifically, the comparison between three tools will include: FSW process load analysis (tool forces required to fabricate the welds), Static Mechanical Properties (ultimate tensile strength, yield strength, and elongation), and Process window documenting the range of parameters that can be used with the three pin tools investigated. All samples were naturally aged for a period greater than 10 days. Prior research has shown 7075 may require post weld heat treatment. Therefore, an additional pair of room temperature and cryogenic temperature samples was post-weld aged to the 7075-T7 condition prior to mechanical testing.

Merry, Josh↗

Estimating Alpine Snow Depth by Combining Multi-Frequency Passive Radiance Observations with Ensemble Snowpack Modeling

This paper presents a physically-based snow depth retrieval algorithm adapted for deep mountainous snowpack and airborne multifrequency (10.7, 18.7, 37.0 and 89.0 GHz) passive microwave (PM) radiance observations from a single flight. The algorithm employs a single forecast-analysis cycle of a traditional sequential assimilation scheme. It uses an ensemble of multi-layer snowpack model runs to resolve snow microstructure and melt-refreeze crusts, andmicrowave radiative transfer models to relate snow properties to microwave measurements.Snow depth was retrieved at a 120 m spatial resolution over three 1 km2 Intensive Study Area (ISA) within the Rabbit Ears Meso-Cell Study Area (MSA) from the NASA Cold Land Processes Experiment (CLPX) in Colorado (United States) for one date in February 2003. When evaluated against in situ observations, root mean square error (RMSE) of the snow depth from the assimilation was 13.3 cm for areas with low (<5 %) forest cover, which was a reduction of 48 % in the RMSE compared with the modeled snow depth when the PM observations were not assimilated; indicating a ~5% relative error of the posterior snow depth with respect to the average snow depth (200 cm) measured at these pixels. For pixels with forest cover ranging from 5-15% and 15-30%, results were improved (R2 increased from 0.65 to 0.71 and from 0 to 0.38, respectively) by introducing a forest radiative transfer model during the assimilation.

Airborne Multifrequency↗

Multiscale Modeling of Thermoplastics Using Atomistic-informed Micromechanics

A multiscale model was developed for predicting the thermoelastic behavior of semi-crystalline thermoplastic materials for composite aerospace applications. At the highest scale containing the semi-crystalline spherulite in an amorphous matrix, the generalized method of cells, or high fidelity method of cells, was used to perform the homogenization calculations to obtain the effective properties. Models were developed assuming a cubic, or spherical shape, for the spherulite to understand if the morphology of the spherulite affects the effective thermoelastic properties. The generalized method of cells was used to model at the repeating unit cells at the subscales of the microstructure including the lamellae stacks and granular crystal blocks. The scales are integrated using the multiscale micromechanics method in the NASA Multiscale Analysis Tool. Data from molecular dynamics simulations were used as inputs for the amorphous and crystalline constituents. Convergence studies were performed to determine the best level of discretization for the repeating unit cell at the highest scale. Effective Young’s modulus, shear modulus, Poisson’s ratio, coefficient of thermal expansion, and thermal conductivity were predicted for polyether ether ketone and polyether ketone ketone, and very good agreement between the model utilizing the cubic spherulite and the experimental data, where available, was observed for polyether ketone ketone. Normalization of the data for the bulk polyether ketone ketone, against amorphous data, improved the predictions as compared to experimental data. Overall, the high fidelity method of cells predicted a stiffer response then the generalized method of cells as the crystallinity was increased. The shape of the spherulite had a minimal effect on the predicted bulk properties of the polymers.

thermoplastics↗

Advanced Durability and Damage Tolerance Design and Analysis Methods for Composite Structures: Lessons Learned from NASA Technology Development Programs

Aerospace vehicles are designed to be durable and damage tolerant. Durability is largely an economic life-cycle design consideration whereas damage tolerance directly addresses the structural airworthiness (safety) of the vehicle. However, both durability and damage tolerance design methodologies must address the deleterious effects of changes in material properties and the initiation and growth of microstructural damage that may occur during the service lifetime of the vehicle. Durability and damage tolerance design and certification requirements are addressed for commercial transport aircraft and NASA manned spacecraft systems. The state-of-the-art in advanced design and analysis methods is illustrated by discussing the results of several recently completed NASA technology development programs. These programs include the NASA Advanced Subsonic Technology Program demonstrating technologies for large transport aircraft and the X-33 hypersonic test vehicle demonstrating technologies for a single-stage-to-orbit space launch vehicle.

Harris, Charles E.↗

In Situ Observation of Growth Dynamics in DECLIC Directional Solidification Insert Onboard ISS: DSI-R Flight Campaign

The study of solidification microstructure formation is of utmost importance for materials design and processing, as solid-liquid interface patterns largely govern mechanical and physical properties. Pattern selection occurs under dynamic conditions of growth in which the initial morphological instability evolves nonlinearly and undergoes a reorganization process. The dynamic and nonlinear nature of this instability renders in situ observation of the interface an invaluable tool to gain knowledge on the time-evolution of the interface pattern. Transparent organic analogs, which solidify like metallic alloys, allow direct visualization of interface dynamics. Extensive ground-based studies of both metallic and organic bulk samples have established the presence of significant convection during solidification processes that alters the formation of interfacial microstructures. A reduced-gravity environment is therefore mandatory for fluid flow elimination in bulk samples. In the framework of the CNES project MISOL3D (MIcrostrutures de SOLidification 3D) and the NASA projects DSIP (Dynamical Selection of 3D Interface Patterns), SPADES (SPAtiotemporal Evolution of three-dimensional DEndritic array Structures) and CAMUS (ComputAtional Studies of MicrostrUcture Formation During Alloy Solidification in Microgravity), we participated in the development of the Directional Solidification Insert (DSI) of the DEvice for the study of Critical Liquids and Crystallization (DECLIC). The DECLIC-DSI is dedicated to in situ and real-time characterization of solid-liquid interface patterns during directional solidification of transparent alloys in diffusive transport regime. Between April 2010 and March 2011, the first ISS campaign (DSI) explored the entire range of microstructures resulting in unprecedented observations. A second campaign (DSI-R), performed between October 2017 and December 2018, in which the insert contained an alloy of higher solute concentration, allowed to complete the benchmark database. The increase of solute concentration resulted in well-developed dendritic patterns at lower velocities (lower interface curvature and larger tip radius). The microstructure resulting from dendritic growth is dominant in metallurgy so that it is fundamental to understand the mechanisms of its formation. The main aims of this experimental campaign are to understand: the mechanisms of the cell to dendrite transition, the fundamental mechanisms of sidebranching formation, the dependence of dendrite tip shapes on growth conditions, the interaction of primary array and secondary sidebranches, and the influence of subgrain boundaries on the spatiotemporal organization of the array structure. Preparation, analysis and interpretation of the experiments performed onboard ISS are considerably enhanced by experiments performed on ground using thin-samples (Pr. Trivedi’s group) and phase-field simulations of microstructure formation in a diffuse growth regime (Pr. Karma’s group). In this summary, we will present an initial assessment of the results obtained during the DSI-R campaign. Nomenclature Vp: pulling velocity G: thermal gradient L: solidified length rtip: tip curvature radius Acronyms/Abbreviations CADMOS: Centre d'Aide au Développement des activités en Micro-pesanteur et des Opérations Spatiales CNES: Centre National d’Études Spatiales DECLIC: Device for the study of Critical LIquids and Crystallization DSI: Directional Solidification Insert DSI-R: Directional Solidification Insert - Refurbish ISS: International Space Station NASA: National Aeronautics and Space Administration PF: phase-field SCN: Succinonitrile 3D: three-dimensional

Mota, F.L.↗

Microstructure and mechanical properties of bulk yttria-partially-stabilized zirconia

A commercially available bulk 4.5 mole percent yttria-(Y2O3) partially stabilized zirconia (PSZ) was studied by light microscopy, X-ray analysis, microhardness measurement, and fracture toughness testing. The growth of the precipitates and the phase transformations were studied as a function of aging in air at 1500 C. Aging curves were constructed for both the as received and the solution annealed and quenched materials; the curves showed hardness peaks at 1397 and 1517 Kg/sq mm respectively. The rectangular plate shaped tetragonal precipitates were found to have a 110 habit plane. A total of twelve different types of tetragonal precipitates were found. Grinding of the Y2O3 PSZ into powder did not cause a significant amount of metastable tetragonal precipitates to transform into the monoclinc phase, thus indicating that transformation toughening is not a significant mechanism for the material.

Valentine, P. G.↗

Microstructural Study of Micron-Sized Craters Simulating Stardust Impacts in Aluminum 1100 Targets

Various microscopic techniques were used to characterize experimental micro- craters in aluminium foils to prepare for the comprehensive analysis of the cometary and interstellar particle impacts in aluminium foils to be returned by the Stardust mission. First, SEM (Scanning Electron Microscopy) and EDS (Energy Dispersive X-ray Spectroscopy) were used to study the morphology of the impact craters and the bulk composition of the residues left by soda-lime glass impactors. A more detailed structural and compositional study of impactor remnants was then performed using TEM (Transmission Electron Microscopy), EDS, and electron diffraction methods. The TEM samples were prepared by Focused Ion Beam (FIB) methods. This technique proved to be especially valuable in studying impact crater residues and impact crater morphology. Finally, we also showed that InfraRed microscopy (IR) can be a quick and reliable tool for such investigations. The combination of all of these tools enables a complete microscopic characterization of the craters.

Leroux, Hugues↗

Establishing model credibility for process-microstructure-property relationships in additive manufacturing using exascale computing

Additive Manufacturing (AM) of alloys holds significant promise as a disruptive technology in various industries, yet its adoption is often hindered by challenges in achieving consistent part quality. These issues are primarily due to the complex process-microstructure-property (PSP) relationships inherent to AM. Computational models can greatly aid in understanding these relationships, but their widespread impact and adoption has been limited by a lack of validated, open-source, and computationally efficient PSP modeling frameworks and hardware limitations. Here, this study leverages the ExaAM software suite and data from the AMBench-2018 series of laser powder bed fusion (LPBF) benchmark experiments to perform a comprehensive model assessment, including verification, validation, sensitivity analysis, and uncertainty quantification. The RADICAL-EnTK workflow manager was used to perform an ensemble of heat transport, solidification, and mechanical response simulations on the exascale computer Frontier, considering uncertainties in critical model inputs such as laser spot size and nucleation parameters, and consisting of 125 explicit grain structure simulations and 7875 crystal plasticity simulations. For a selected location within the Inconel 625 AMBench-2018 test artifact, sensitivity analysis and uncertainty quantification were performed using the predicted distributions of grain structure and mechanical properties. Qualitative agreement was found between the predicted grain size and texture and the observed AMBench-2018 microstructure, the mean predicted yield stress was within 5% of the experimental measurement mean, and the mean predicted engineering stress at 5% strain was within 10% of the experimental measurement mean. The insights gained from development and validation of the ExaAM PSP modeling framework will help guide future directions for enhancing the credibility and reliability of PSP models in AM, thereby accelerating the adoption of AM technologies in various industries.

Additive manufacturing↗

Uncertainty Quantification for Dissimilar Material Joints Under Corrosion Environment

Abstract Self-Piercing Riveting (SPR) is one of the most commonly used methods for joining dissimilar materials in the automotive industry. These joints are popular due to their adaptability, high performance and short cycle time. However, since these joints involve two dissimilar materials, they are susceptible to galvanic corrosion in the presence of an electrolyte which is driven by the difference in the equilibrium potential of the metals. This can affect the safety and resilience of these joints. In this paper, we focus on galvanic corrosion in Al-Fe SPR joints. A Machine learning (ML) based surrogate model, which is based off of FE simulations, for statistical corrosion analysis is developed. This model enables the resilience and reliability analysis of SPR joints under corrosion environment. In this study, first a physics-based finite element (FE) corrosion model has been developed to simulate the galvanic corrosion between a Fe cathode and an Al anode of a SPR joint. This model takes into account the effect of the crystal microstructure of the Al anode and the precipitation of the corrosion product. Several geometric and environmental factors including crevice gap, roughness of anode, conductivity, pH and the temperature of the electrolyte that effect corrosion are investigated. A thorough Uncertainty Quantification (UQ) analysis is conducted for the overall corrosion behavior of the Fe-Al SPR joints using a novelistic Probabilistic Confidence-Based Adaptive Sampling (PCAS) technique. PCAS is used to train the surrogate model by identifying the critical sampling points and thus reducing the overall computational costs. It is found that the electrolyte temperature has the largest effects on the material loss and needs to be managed closely for better corrosion control. By understanding the corrosion performance and resultant uncertainty impact on SPR joints, the reliability and resilience of these joints can be improved.

36 MATERIALS SCIENCE↗

Synthesis and behavior of bulk iron nitride soft magnets via high-pressure spark plasma sintering

Abstract In this study, dense bulk iron nitrides (Fe x N) were synthesized for the first time ever using spark plasma sintering (SPS) of Fe x N powders. The Fe 4 N phase of iron nitride in particular has significant potential to serve as a new soft magnetic material in both transformer and inductor cores and electrical machines. The density of SPSed Fe x N increased with SPS temperature and pressure. The microstructure of the consolidated bulk Fe x N was characterized with X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and superconducting quantum interference device (SQUID) magnetometry. XRD revealed a primary phase of Fe 4 N with secondary phases of Fe 3 N and metallic iron. Finite element analysis (FEA) was also applied to investigate and explain localized heating and temperature distribution during SPS. The effects of processing on interface bonding formation and phase evolution were investigated and discussed in detail to provide insight into fundamental phenomena and microstructural evolution in SPSed Fe x N. Graphic abstract

36 MATERIALS SCIENCE↗

Effect of polycyclosilane microstructure on thermal properties

Thermal characterization of polysilanes has focused on the influence of organic side chains, whereas little is understood about the influence of silane backbone microstructure on thermal stability, phase properties, and pyrolysis. To address this knowledge gap, we prepared three distinct polycyclosilanes: linear polymers synthesized from the cyclosilane building blocks 1,4Si 6 and 1,3Si 6 , as well as a cyclic polymer of 1,3Si 6 . Thermal properties across the temperature range 25 to 600 °C were investigated using differential scanning calromietry (DSC) and thermogravimetric analysis (TGA). We found differences between linear and cyclic materials, including a phase transition unique to the cyclic polymer and lower rates of mass loss during pyrolysis. Density functional theory (DFT) calculations provided insight into microstructure-dependent pyrolysis.

36 MATERIALS SCIENCE↗

Utilization of the Critic Subnetwork of a Generative Adversarial Network as Detector of Morphological Material Change in Image Data

The resolution of computed tomography (CT) has become high enough to monitor morphological changes due to aging in materials in long-term applications. For this work, we explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect; but both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗

Chemical and Microstructural Changes in Metallic and Ceramic Materials Exposed to Venusian Surface Conditions

The chemical and microstructural behavior of steels (304, 310, 316, and 1018), nickel-based alloys (beta-NiAl, G30, and 625), gold, coatings (4YSZ, SilcoNert(TradeMark) 1040 (SilcoTek Co.), Dursan(TradeMark) (SilcoTek Co.), and porcelain), and bulk ceramics (alpha-Al2O3, fused quartz, beta-SiC, and alpha-Si3N4) were probed after exposure to supercritical fluid with temperature, pressure, and composition mimicking the Venus lower atmosphere. Exposures were carried out in the Glenn Extreme Environments Rig (GEER) chamber with the Venusian gas mixture (96.5% CO2, 3.5% N2, 30 ppm H2O, 150 ppm SO2, 28 ppm CO, 15 ppm OCS, 3 ppm H2S, 0.5 ppm HCl, and 5 ppb HF) at 92 bar (1330 psi) and 467 C (873 F) for durations of 10 and 42 days. An additional 21-day exposure was done to stainless steel uncoated and coated with SilcoNert(TradeMark) and Dursan(TradeMark). Samples were characterized before and after the experiment by gravimetric analysis, X-ray diffraction, X-ray photoelectron and Auger electron spectroscopies, and cross section electron microscopy analysis. All steels exposed for 10 and 42 days formed double-layered scales consisting mainly of metal (Cr, Fe, Ni) oxides and sulfides showing different chemistry, microstructure, and crystalline phases. The alloys G30 and 625 formed double-layered scales consisting mainly of nickel sulfides. After 10 days, the beta-NiAl exhibited no detectable scale, suggesting only a very thin film was formed. The 304 and 316 stainless steels coated with 4YSZ that were exposed for 10 and 42 days exhibited no significant oxidation. Steel 1018 coated with 4YSZ exhibited a corrosion scale of iron and/or chromium oxide formed at the base of the alloy. The 304 steel coated with porcelain did not exhibit corrosion, although the coating exhibited recession. SilcoNert(TradeMark) exposed for 10 and 42 days exhibited recession, although no oxidation was found to occur at the base of the alloy. Stainless steel 316 coated with Dursan(TradeMark)  exhibited corrosion at the base of the alloy. All ceramics tested showed no clear evidence of reaction. The weight-gain-per-area performance of the materials exposed in the GEER for 10 and 42 days are reported from the lowest to the highest weight gain per area as follows: gold did not exhibit any weight change; nickel-based alloys: beta- NiAl < G30 < 625; steels: 304 < 310 < 316 < 1018; ceramics: considering the experimental uncertainties, no weight change was observed for all ceramics of this work (alpha-Al2O3, Si3N4, SiC, and amorphous SiO2).

Costa, Gustavo C. C.↗

Formation of the {gamma}ʹʹʹ-Ni2(Cr, Mo, W) phase during a two-step aging heat treatment in HAYNES® 244® Alloy

Precipitation hardening is the dominant method of achieving high strength in most Ni-based superalloys. The formation of nanoscale precipitates during thermal exposure is often studied to determine the optimal methods of attaining high strength. The commercial Ni-based superalloy, HAYNES® 244® alloy, is strengthened through a novel -Ni2(Cr, Mo, W) intermetallic phase that forms during a two-step aging cycle. The precipitation kinetics of this intermetallic phase are sluggish for single-step aging in comparison to the γʹ phase in precipitation-strengthened Ni-based alloys, but a two-step aging treatment has shown to reliably harden the alloy and improve high-temperature properties compared to a single-step aging heat treatment. To investigate the formation and coarsening of this phase, heat-treated samples of the 244 alloy were analyzed with high-energy in situ and ex situ X-ray techniques such as small angle X-ray scattering and wide angle X-ray scattering as well as Vickers micro-hardness, electron microscopy, and atom probe tomography. The relationship between hardness, aging parameters, and microstructure evolution is discussed. The enthalpy of formation and precipitate solvus temperature were determined with high-temperature differential scanning calorimetry and dilatometry analysis.

Ni-based Superalloys↗

Tuning gas separation performance of polyimide membranes with macrocyclic crown ether units

Membrane-based gas separation is an energy-efficient alternative to conventional thermally-driven separation processes. However, polymer membranes face the permeability-selectivity trade-off challenge, which stems from the broad size distribution of free volume voids. Here, this study reports a molecular design strategy to address this challenge through incorporating macrocyclic crown ether (CE) moieties into the backbone of Matrimid® polyimide, a commercial gas separation membrane. A series of CE-containing Matrimid®-like copolyimides were synthesized with systematically varied CE molar contents ranging from 3 to 20%. These copolyimides formed ductile, defect-free thin films suitable for membrane fabrication. Gas permeation tests revealed a non-monotonic relationship between permeability/selectivity and CE content. Notably, the copolyimide with only 5% CE demonstrated a 61% increase in CO 2 /CH 4 selectivity and a 13% increase in CO 2 permeability relative to pristine Matrimid®. Higher CE contents did not yield further performance improvements, which is likely due to the competing effects of chain packing disruption and π–π interactions among CE moieties at high content. This hypothesis was supported by wide-angle X-ray scattering (WAXS) analysis, density measurements, and fractional free volume calculations. These findings highlight the potential of macrocyclic crown ether incorporation strategies in fine tuning the microstructure of commercial polyimide gas separation membranes to surpass the traditional permeability-selectivity trade-off.

CO2 separation↗

Effect of heat treatments on superconducting properties and connectivity in K-doped BaFe2As2

Abstract Fe-based superconductors and in particular K-doped BaFe 2 As 2 (K-Ba122) are materials of interest for possible future high-field applications. However the critical current density ( J c ) in polycrystalline Ba122 is still quite low and connectivity issues are suspected to be responsible. In this work we investigated the properties of high-purity, carefully processed, K-Ba122 samples synthesized with two separate heat treatments at various temperatures between 600 and 825 °C. We performed specific heat characterization and T c -distribution analysis up to 16 T and we compared them with magnetic T c and J c characterizations, and transmission-electron-microscopy (TEM) microstructures. We found no direct correlation between the magnetic T c and J c , whereas the specific heat T c -distributions did provide valuable insights. In fact the best J c -performing sample, heat treated first at 750 °C and then at 600 °C, has the peak of the T c -distributions at the highest temperatures and the least field sensitivity, thus maximizing H c2 . We also observed that the magnetic T c onset was always significantly lower than the specific heat T c : although we partially ascribe the lower magnetization T c to the small grain size (< λ , the penetration depth) of the K-Ba122 phase, this behaviour also implies the presence of some grain-boundary barriers to current flow. Comparing the T c -distribution with J c , our systematic synthesis study reveals that increasing the first heat treatment above 750 °C or the second one above 600 °C significantly compromises the connectivity and suppresses the vortex pinning properties. We conclude that high-purity precursors and clean processing are not yet enough to overcome all J c limitations. However, our study suggests that a higher temperature T c -distribution, a larger H c2 and a better connectivity could be achieved by lowering the second heat treatment temperature below 600 °C thus enhancing, as a consequence, J c .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Experimental and theoretical examination of shock-compressed copper through the fcc to bcc to melt phase transitions

Recent studies show a face-centered cubic (fcc) to body-centered cubic (bcc) transformation along the shock Hugoniot for several metals (i.e., Cu, Au, and Ag). Here, we combine laser-shock compression of Cu foils on nanosecond timescales with in situ x-ray diffraction (XRD) to examine the microstructural changes with stress. We study the fcc phase and the phase transition from fcc to bcc (pressures greater than 180 GPa). Textural analysis of the azimuthal intensities from the XRD images is consistent with transformation into the bcc phase through the Pitsch-distortion mechanism. We use embedded atom model molecular dynamics simulations to determine the stability of the bcc phase in pressure–temperature space. Finally, our results indicate that the bcc phase is stabilized only at high temperatures and remains stable at pressures greater than 500 GPa.

36 MATERIALS SCIENCE↗

Decoding diffraction and spectroscopy data with machine learning: A tutorial

This Tutorial provides a step-by-step guide on how to apply supervised machine-learning techniques to analyze diffraction and spectroscopy data. This Tutorial details four models—a reconstruction-focused model, a regression-focused model, a hybrid reconstruction/regression model, and a multimodal model—that use x-ray diffraction profiles and vibrational density of states spectra to predict various microstructural descriptors. In this Tutorial, we cover data pre-processing steps, constructions of the models via dimensionality reduction and regression, training, and analysis of these models. Comparisons of the model’s performance are provided, highlighting the strength and weakness of the various approaches utilized.

36 MATERIALS SCIENCE↗