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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Streamline-Traced, External-Compression Supersonic Inlets for Mach 2

A computational study was performed to explore the aerodynamic design and performance of streamline-traced, external-compression (STEX) inlets for Mach 2.0. The performance metrics included inlet flow rates, total pressure recovery, and total pressure distortion. The study explored the use of round and flattened capture cross-sections and a bleed slot. The design of the inlet and generation of the inlet geometry was performed using the Supersonic Inlet Design and Analysis(SUPIN) Tool. Computational grids were generated, and methods of computational fluid dynamics (CFD) were applied to solve the three-dimensional, turbulent flow through the inlets using the Wind-US CFD flow solver. It was found that the use of a bleed slot with about 5% bleed resulted in an inlet total pressure recovery of 95% at Mach 2 with acceptable radial and circumferential total pressure distortion. It was also found that there was only a slight decrease in performance between a round and flattened capture cross-section. This suggests that the use of streamline tracing offers flexibility in shaping the inlet capture cross-section for a more favorable integration with an aircraft wing or fuselage. This flexibility and the good performance of the inlet provides a novel inlet design for future commercial supersonic aircraft.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Streamline‐Traced, External‐Compression Supersonic Inlets for Mach 2

A computational study was performed to explore the aerodynamic design and performance of streamline-traced, external‐compression (STEX) inlets for Mach 2.0. The performance metrics included inlet flow rates, total pressure recovery, and total pressure distortion. The study explored the use of round and flattened capture cross‐sections and a bleed slot. The design of the inlet and generation of the inlet geometry was performed using the Supersonic Inlet Design and Analysis (SUPIN) Tool. Computational grids were generated, and methods of computational fluid dynamics (CFD) were applied to solve the three dimensional, turbulent flow through the inlets using the Wind‐US CFD flow solver. It was found that the use of a bleed slot with about 5% bleed resulted in an inlet total pressure recovery of 95% at Mach 2 with acceptable radial and circumferential total pressure distortion. It was also found that there was only a slight decrease in performance between a round and flattened capture cross‐section. This suggests that the use of streamline tracing offers flexibility in shaping the inlet capture cross‐section for a more favorable integration with an aircraft wing or fuselage. This flexibility and the good performance of the inlet provides a novel inlet design for future commercial supersonic aircraft.

Computational Fluid Dynamics↗
NASA NTRS2023

Temperature Effect on Silicate Melt-Sulfide-Metal Trace Element Partitioning in the Presence of Sulfur Under Reduced Conditions

The reduced nature of Mercury, enstatite chondrites, and the aubrite parent bodies (APB) have raised many questions regarding the geochemical behavior of typically lithophile, heat-producing, and rare-earth elements (REE) in magmas at low oxygen fugacity (fO2). Due to decreasing O availability at these low fO2, and an abundance of S(sup 2(-)), sulfur (S) acts as an important anion that changes the partitioning behavior of many elements and modifies the physical properties of silicate melts. Preliminary observations suggest that major and minor elements exhibit different geochemical affinities in highly reduced, S-rich systems compared to terrestrial rocks. The speciation and bonding environment of S, dictated by P/T/fO2 conditions, may strongly influence the degree to which S affects partitioning behavior. Here we investigate the partitioning behavior of major, minor, and trace elements between silicate melt, sulfide melt, and metal as well as the coordination chemistry of S in highly reduced silicate melts. Our work is focused on investigating solely the entropy-dependent temperature effect on partitioning of elements for which we currently have MESSENGER data (K, Na, Th, U, Si, Mg, Fe, Ti, Ca, Al, Cr, Mn, S, Cl) as well as a host of geochemically relevant trace elements such as REEs (P, Co, Ni, Mo, Ce, Nd, Sm, Eu, Gd, Dy, Yb). Previous studies in which temperature, pressure, and fO2 were co-varied found that as fO2 decreases, heat-producing elements U and Th become more chalcophile, while K becomes less chalcophile. Concurrently, nominally lithophile elements Mg and Ca become more chalcophile and were observed as minor elements in exsolved sulfides and bonded with S species in silicate melt. These studies, however, could not disentangle entropic effects from changes in the fO2. New temperature-dependent partitioning data from our work will be used to determine which elements are most likely to retain their lithophile character and hence be incorporated into silicates, and which elements are likely contained within the sulfide (chalcophile) and metal core (siderophile), setting the stage for the thermal and magmatic evolution of reduced planetary bodies.

B A Anzures↗
NASA NTRSDate not supplied

Effect of Pressure on Trace Element Activity Coefficients in Metal-Silicate Systems

The partitioning of trace elements between metal and silicate melts serves as the foundation for understanding the differentiation of a planetary body into a metallic core and silicate mantle. Element activity influences metal-silicate partitioning behavior. Activity coefficients are directly dependent on composition and temperature, and can be indirectly dependent on oxygen fugacity and pressure. Distinguishing the effect of pressure from other variables on the activity coefficients and partitioning is important for understanding the chemical evolution of different planetary bodies during differentiation. In this study, we investigated the influence of pressure on the activity coefficients of Cu, Mo, Pd, Pt, As, Sb, and Bi in Fe-Si metallic liquids. All of these elements exhibit moderate to high activity coefficients in Fe-Si liquids at low pressure, which significantly controls their metal-silicate partitioning behavior. Identifying whether this strong dependence persists at higher pressures is critical to modeling and understanding the chemical consequences of core formation. New experiments at 10 GPa were used to derive activity coefficients for these metals which can be compared to activity coefficients determined at 1 GPa. Experiments were conducted at 10 GPa and 2373K using a 10/5 assembly in the 880-ton multi-anvil press at NASA Johnson Space Center. The standard 10/5 COMPRES assembly was slightly modified to accommodate a sample capsule machined from single-crystal MgO that minimizes melt percolation out of the sample volume during the experiment. Experiment starting materials were comprised of 70 wt.% Knippa basalt and 30 wt.% metal. The metal mixture (~85 wt.% Fe) was created by adding the elements of interest (Cu, Mo, Pd, Pt, As, Sb, Bi) to Fe metal powder. Varied amounts of Si metal (0-10 wt.% Si) were added to the metal-silicate mixtures to generate a systematic series of starting materials. For each element, an epsilon interaction parameter in Fe-Si liquid was derived from the results of our 0-10 wt.% Si metal series. To investigate whether pressure influences the trace element activity coefficients in the 1-10 GPa pressure range, we compared our results at 10 GPa to those at 1-4 GPa [1-3]. Our results can also be directly compared to interaction parameters for Au, P, V, Mn, Ga, Zn, Cd, Sn, W, Pb, and Nb previously determined at 10 GPa and 2373K following the same methods [4]. Combined, this suite of interaction parameters will directly inform metal-silicate partitioning between 1 and 10 GPa, and assess whether these values can be extrapolated to modeling differentiation processes at pressures >10 GPa.

Kelsey Prissel↗
NASA NTRSDate not supplied

All-sky Retrieval of Atmospheric Temperature, Water Vapor, Clouds, Trace Gases, and Surface Properties from Operational Hyperspectral IR Sounders

Operational IR sounders such AIRS, CrIS, and IASI provide high quality hyperspectral measurements for weather and climate applications. We will describe a new all-sky Single Field-of-view Sounder Atmospheric Product (SiFSAP). The uniqueness of this product is that it uses all available channels from hyperspectral sounders and the optimal estimation retrieval is done at a single FOV spatial resolution. The SiFSAP includes atmospheric temperature, water vapor, clouds, trace gases, surface skin, and surface emissivity and will be produced operationally at NASA GES DISC. We will describe the core component of the SiFSAP algorithm, which is the Principal Component-based Radiative Transfer Model (PCRTM), and will show example applications of the SiFSAP product for various atmospheric weather and dynamics studies. We also describe a new Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides fast and accurate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

pcrtm↗
NASA NTRSDate not supplied

Ammonia-Removal Efficiency By Full-Scale Carbon-Based Trace-Contaminant Sorbent Monoliths Integrated With the Rapid-Cycle Amine (RCA) Swing Bed

Results are presented on full-scale performance testing of vacuum-regenerable, carbon based sorbent monoliths for trace-contaminant (TC) removal integrated with the Rapid-Cycle Amine (RCA) swing bed for use in the Portable Life Support System (PLSS) during Extravehicular Activities (EVAs). The current state-of-art in TC-control technology involves the use of a packed bed of acid-impregnated granular charcoal, which is difficult to regenerate. The carbon-based sorbent under development in this project can be regenerated by exposure to vacuum at room temperature. Data on cyclic sorption-desorption of ammonia, which is a major TC of concern, were collected in a simulated PLSS ventilation loop which involved the RCA placed upstream of the Trace Contaminant Control System (TCCS). Results of testing involving pressure-swing operation of the integrated TCCS/RCA system indicate ammonia-removal efficiency exceeding 80% throughout multiple sorption-desorption cycles. This paper presents an overview of the TCCS research, the favorable results obtained, and provides insight into future work needed to further the technology development.

Marek A Wójtowicz↗
NASA NTRSDate not supplied

Tracking the Hunga Tonga-Hunga Ha’apai Eruption Stratospheric Aerosol and Trace Gas Plumes Using Machine Learning

The Hunga Tonga-Hunga Ha’apai (HTHH) submarine volcano had an explosive eruption phase on January 15, 2022, that thrusted ash, gases, and water vapor through the troposphere and into the stratosphere. The stratospheric volcanic plume included aerosol precursor gases such as SO2 and H2S as well as anomalously high water vapor concentrations due to the submarine oceanic origin. With these atmospheric constituents, the sulfuric gases and water vapor formed sulfate (SO4) particles via gas-to-particle reactions and these aerosols likely increased in size due to hygroscopic growth within anomalously humid regions. Strong easterlies and gravity waves propagated the volcanic impacts throughout the stratosphere. Orbital and suborbital passive sensor retrievals detected changes in the aerosol and trace gas characteristics within the atmospheric column for cloud-free regions over the southern hemisphere. While the CALIPSO lidar can detect aerosol layers in the stratosphere, passive sensors such as MODIS retrieved the total column aerosol abundance and characteristics. Previous studies used manual tracking methods to determine volcanic plume positions and compared them to ground observations. In this study, we examine the machine learning (ML) approaches including segmentation, object detection, and object tracking to identify and track aerosol and trace gas plumes using orbital and suborbital sensor data. This ML implementation strives to provide a more systematic approach to separate total column effects from those of the stratosphere. Similar ML tracking may be useful for stratospheric impact events observed historically by CALIPSO and in the future with EarthCare and the Atmosphere Observing System (AOS) lidar-capable missions.

Rhys Leahy↗
DOE OSTI2026

Accelerating laser ray tracing in high fidelity physics simulations of laser melting using squeeze U-net

Laser melting is a core component of the ongoing industrial revolution, dubbed Industry 4.0, as lasers facilitate fast and precise melting and fusion in advanced manufacturing. There is a strong need to optimize the laser process using simulations. However, this has proven challenging as high fidelity simulations are needed for predictive modeling and this is currently prohibitively expensive even when run on hundreds of processors on high performance computers. The challenge is capturing complex physics of laser material interaction, fluid dynamics, thermal physics and material phase transformations at various length and time scales. To close this technological gap, we modified a squeeze U-net to accelerate the laser ray tracing component of such high fidelity models by ~4x–40x while preserving the core physics principle of conservation of energy with 97% accuracy. This approach enables the accurate modeling of global laser energy absorption as a function of local surface temperatures and complex surface topologies, which govern the reflection directions and energy losses of laser rays upon interacting with the material surface.

Computer science↗
DOE OSTI2024

Hutchinson Trace Estimation for high-dimensional and high-order Physics-Informed Neural Networks

Physics-Informed Neural Networks (PINNs) have proven effective in solving partial differential equations (PDEs), especially when some data are available by seamlessly blending data and physics. However, extending PINNs to high-dimensional and even high-order PDEs encounters significant challenges due to the computational cost associated with automatic differentiation in the residual loss function calculation. Herein, we address the limitations of PINNs in handling high-dimensional and high-order PDEs by introducing the Hutchinson Trace Estimation (HTE) method. Starting with the second-order high-dimensional PDEs, which are ubiquitous in scientific computing, HTE is applied to transform the calculation of the entire Hessian matrix into a Hessian vector product (HVP). This approach not only alleviates the computational bottleneck via Taylor-mode automatic differentiation but also significantly reduces memory consumption from the Hessian matrix to an HVP’s scalar output. We further showcase HTE’s convergence to the original PINN loss and its unbiased behavior under specific conditions. Comparisons with the Stochastic Dimension Gradient Descent (SDGD) highlight the distinct advantages of HTE, particularly in scenarios with significant variability and variance among dimensions. We further extend the application of HTE to higher-order and higher-dimensional PDEs, specifically addressing the biharmonic equation. By employing tensor-vector products (TVP), HTE efficiently computes the colossal tensor associated with the fourth-order high-dimensional biharmonic equation, saving memory and enabling rapid computation. The effectiveness of HTE is illustrated through experimental setups, demonstrating comparable convergence rates with SDGD under memory and speed constraints. Additionally, HTE proves valuable in accelerating the Gradient-Enhanced PINN (gPINN) version as well as the Biharmonic equation. Overall, HTE opens up a new capability in scientific machine learning for tackling high-order and high-dimensional PDEs.

Curse of dimensionality↗
DOE OSTI2024

Understanding Trace Iron and Chromium Incorporation During Gibbsite Crystallization and Effects on Mineral Dissolution

Incorporation of pollutants, e.g., heavy metals, or critical elements, e.g., lithium, as impurities in mineral phases can significantly affect their mobility or sequestration in the environment. Even when present at low concentrations, impurities can alter the solubility and reactivity of the host mineral. Here, in this study, we investigate the incorporation of trace amounts of iron (Fe 3+ ) and chromium (Cr 3+ ) during the crystal growth of the aluminum (Al 3+ ) hydroxide, gibbsite, a major component of bauxite ores, an important soil mineral, and a dominant mineral phase in stored radioactive wastes. Using a comprehensive suite of analytical techniques, we show that both Cr 3+ and Fe 3+ can be incorporated into the gibbsite lattice during coprecipitation by replacing Al 3+ in octahedral sites. These small amounts are consistent with limited to no structural isomorphism shared between Al 3+ and Cr 3+ /Fe 3+ hydroxide precipitates, nor room temperature miscibility of their isostructural M 2 O 3 oxide forms, in contrast with oxyhydroxide forms where Al 3+ and Fe 3+ share similar structural topologies. Despite the limited uptake of Cr 3+ /Fe 3+ , we show that these impurities have significant implications for gibbsite dissolution behavior. The limited uptake of Cr 3+ /Fe 3+ (e.g. 0.43% Cr 3+ and 0.4% Fe 3+ ), we show that these impurities have significant implications for gibbsite dissolution behavior and subsequent reactivity in complex environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Mantaray: A Rust Package for Ray Tracing Ocean Surface Gravity Waves

Ocean surface gravity waves are an important component of air-sea interaction, influencing energy, momentum, and gas exchanges across the ocean-atmosphere interface. In specific applications such as refraction by ocean currents or bathymetry, ray tracing provides a computationally efficient way to gain insight into wave propagation. In this paper, we introduce Mantaray, an open-source software package implemented in Rust, with a Python interface, that solves the ray equations for ocean surface gravity waves. Mantaray is designed for performance, robustness, and ease of use. The package is modular to facilitate further development and can currently be applied to both idealized and realistic wave propagation problems (Fig. 1).

16 TIDAL AND WAVE POWER↗