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At least 1,351 records · Page 75

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NASA NTRSDate not supplied

Space Launch System Base Aerothermodynamics Post-Flight Reconstruction for Artemis I

Artemis I was the first uncrewed integrated test flight of the NASA heavy-lift, human-rated, exploration-class launch vehicle, Space Launch System (SLS), and Orion spacecraft. Artemis I successfully launched from Pad39B at NASA Kennedy Space Center on November 16th, 2023. The integrated test flight is composed of launch and ascent of the SLS vehicle from lift-off to RS-25 main engine cut-off (MECO), interim cryogenic propulsion stage (ICPS) in-space flight and Orion’s trajectory around the moon and landing in the Pacific Ocean which occurred on December 11th, 2023. The SLS total thrust of 8,800,000 lbf is powered by four LOX/LH2 RS-25 engines and two 5-segment solid rocket boosters. As a result, base flow environments for this vehicle are highly complex and extreme. SLS base aerothermodynamics covers rocket plume-induced convection and radiation of the vehicle’s aft region during powered flight from lift-off to MECO. This work discusses the SLS base flow physics observed during Artemis I and comparisons of post-flight reconstruction with pre-flight models and Space Shuttle data. This is the first time in-depth base heating flight reconstruction has been investigated for an exploration-class launch vehicle since the Saturn V Program.

aerothermodynamics↗

NASA NTRSDate not supplied

Space Launch System Base Aerodynamics Post-Flight Reconstruction for Artemis I

Artemis I was the first uncrewed integrated test flight of the NASA heavy-lift, human-rated, exploration-class launch vehicle, Space Launch System (SLS), and Orion spacecraft. Artemis I successfully launched from Pad39B at NASA Kennedy Space Center on November 16th, 2022. The integrated test flight was composed of launch and ascent of SLS vehicle from lift-off to RS-25 main engine cut-off (MECO), interim cryogenic propulsion stage (ICPS) in-space flight and Orion’s trajectory around the moon and landing in the Pacific Ocean which occurred on December 11th, 2022. The SLS total thrust of 8,800,000 lbf was powered by four LOX/LH2 RS-25 engines and two 5-segment solid rocket boosters. As a result, the base flow field had highly complex phenomena and regimes. SLS base aerodynamics covers vehicle base pressure and integrated axial force during powered flight from lift-off to MECO. This work discusses the SLS base flow physics observed during Artemis I and comparisons of post-flight reconstruction with pre-flight models and Space Shuttle data. This was the first time in-depth base aerodynamics flight reconstruction has been investigated for an exploration-class launch vehicle since the Saturn V Program.

aerothermodynamics↗

NASA NTRSDate not supplied

Space Launch System Base Aerothermodynamics Post-Flight Reconstruction for Artemis I

aerothermodynamics↗

NASA NTRSDate not supplied

Base Aerodynamics Post-Flight Reconstruction for Artemis I

Artemis I was the first uncrewed integrated test flight of the NASA heavy-lift, human-rated, exploration-class launch vehicle, Space Launch System (SLS), and Orion spacecraft. Artemis I successfully launched from Pad39B at NASA Kennedy Space Center on November 16th, 2022. The integrated test flight was composed of launch and ascent of SLS vehicle from lift-off to RS-25 main engine cut-off (MECO), interim cryogenic propulsion stage (ICPS) in-space flight and Orion’s trajectory around the moon and landing in the Pacific Ocean which occurred on December 11th, 2022. The SLS total thrust of 8,800,000 lbf was powered by four LOX/LH2 RS-25 engines and two 5-segment solid rocket boosters. As a result, the base flow field had highly complex phenomena and regimes. SLS base aerodynamics covers vehicle base pressure and integrated axial force during powered flight from lift-off to MECO. This work discusses the SLS base flow physics observed during Artemis I and comparisons of post-flight reconstruction with pre-flight models and Space Shuttle data. This was the first time in-depth base aerodynamics flight reconstruction has been investigated for an exploration-class launch vehicle since the Saturn V Program.

aerothermodynamics↗

DOE OSTI2026

Quantum block encoding for one-pair semiseparable matrices

Quantum block encoding (QBE) is a crucial step in the development of most quantum algorithms, as it provides an embedding of a given matrix into a suitable larger unitary matrix. Historically, the development of efficient techniques for QBE has mostly focused on sparse matrices; less effort has been devoted to data-sparse (e.g., rank-structured) matrices. In this work we examine a particular case of rank structure, namely, one-pair semiseparable matrices. We present a new block encoding approach that relies on a suitable factorization of the given matrix as the product of triangular and diagonal factors. To encode the matrix, the algorithm needs $2\log(N)+7$ ancillary qubits. Assuming that the data input oracles can be implemented with polylogarithmic depth, or that a QRAM input model is available, our proposed method requires $\mathcal{O}({\rm polylog} (N))$ time and has an error of $\mathcal{O}(N^2)$, where $N$ is the matrix size.

Antonioli, Giacomo [Pisa U.; CERN] (ORCID:00090000↗

DOE OSTI2016

Corrosion-induced microstructural developments in 316 stainless steel during exposure to molten Li 2 BeF 4 (FLiBe) salt

The microstructural evaluation and characterization of 316 stainless steel samples that were tested in molten Li 2 BeF 4 (FLiBe) salt were investigated in this study for evaluating its performance in high-temperature molten fluoride salts. Recently, 316 stainless steel and FLiBe salt are being actively considered as the main structural alloy and primary coolant of fluoride salt-cooled high-temperature reactor (FHR), a leading nuclear reactor concept for the next generation nuclear plants (NGNP). In support of the materials development for the FHR, high-temperature corrosion tests of 316 stainless steel in molten FLiBe salt at 700°C have been conducted in both bare graphite crucibles and 316 stainless steel-lined crucibles in an inert atmosphere for up to 3000 hours. The microstructure of the tested samples was comprehensively characterized using scanning electron microscopy (SEM) in conjunction with energy dispersive x-ray spectroscopy (EDS) and electron backscatter diffraction (EBSD), and scanning transmission electron microscopy (STEM) with EDS. In addition to the noticeable intergranular corrosion attack on surface, the corrosion in terms of the Cr depletion along high angle grain boundaries (15-180º) extended to 22µm in depth after 3000-hour exposure to molten FLiBe salt in graphite crucible. The coherent Σ3 grain boundary appeared high resistance to the Cr depletion. The substantial Cr depletion from the near-to-surface layer induced phase transformation from γ-martensite to α-ferrite phase (FeNi x ) during corrosion at 700ºC. Furthermore, the presence of graphite in the molten salt doubled the corrosion attack depth and led to the formation of round Mo2C, hexagonal Cr 7 C 3 and needle-like Al 4 C 3 phase within the alloy as deep as 50 µm after 3000-hour corrosion testing. Based on the microstructural analysis, the corrosion mechanisms of 316 stainless steel in molten FLiBe salt in different corrosion crucibles were illuminated through schematic diagrams. Additionally, a thermal diffusion controlled corrosion model was developed and validated by experimental data for predicting the long-term corrosion attack depth.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Water level data collected in the Rifle Floodplain, Colorado, USA

Waterlevel data from 28 instrumented wells at the Old Rifle field site. This waterlevel data was calculated from vented pressure transducers which were deployed in these wells. For this calculation the TOC (Top of Casing), depth to transducer and water column above the transducer were used. The transducer data was obtained through the DOE LM Soars system. The raw data from this system are provided in a companion datapackage

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Street-level temperature estimation using graph neural networks: Performance, feature embedding and interpretability

Estimating street-level air temperature is a challenging task due to the highly heterogeneous urban surfaces, canyon-like street morphology, and the diverse physical processes in the built environment. Though pioneering studies have embarked on investigations via data-driven approaches, many questions remain to be answered. Here, in this study, we leveraged an innovative framework and redefined the street-level temperature estimation problem using Graph Neural Networks (GNN) with spatial embedding techniques. The results showed that GNN models are more capable and consistent of estimating street-level temperature among tested locations, benefiting from its unique strength in handling extensive data over unstructured graph topology. In addition, we conducted in-depth analysis of feature importance to enhance the model interpretability. Among the urban features analyzed in this study, the time-variant canopy density and meter-level land use data emerge as crucial factors. Our findings highlight GNN 's high potential in capturing the complex dynamics between urban elements and their impacts on microclimate, thus offering valuable insights for comprehensive urban data collection and urban climate modeling in general. Collectively, this study also contributes to urban planning and policy by providing avenues to enhance city resilience against climate change, thereby advancing the agenda for environmental stewardship and urban sustainability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Cosmogenic nuclide and solute flux data from central Cuban rivers emphasize the importance of both physical and chemical mass loss from tropical landscapes

We use 25 new measurements of in situ produced cosmogenic 26 Al and 10 Be in river sand, paired with estimates of dissolved load flux in river water, to characterize the processes and pace of landscape change in central Cuba. Long-term erosion rates inferred from 10 Be concentrations in quartz extracted from central Cuban river sand range from 3.4–189 Mg km –2 yr –1 (mean 59, median 45). Dissolved loads (10–176 Mg km –2 yr –1 ; mean 92, median 97), calculated from stream solute concentrations and modeled runoff, exceed measured cosmogenic- 10 Be-derived erosion rates in 18 of 23 basins. This disparity mandates that in this environment landscape-scale mass loss is not fully represented by the cosmogenic nuclide measurements. The 26 Al / 10 Be ratios are lower than expected for steadystate exposure or erosion in 16 of 24 samples. Depressed 26 Al/ 10 Be ratios occur in many of the basins that have the greatest disparity between dissolved loads (high) and erosion rates inferred from cosmogenic nuclide concentrations (low). Depressed 26 Al/ 10 Be ratios are consistent with the presence of a deep, mixed, regolith layer providing extended storage times on slopes and/or burial and extended storage during fluvial transport. River water chemical analyses indicate that many basins with lower 26 Al/ 10 Be ratios and high 10 Be concentrations are underlain at least in part by evaporitic rocks that rapidly dissolve. Our data show that when assessing mass loss in humid tropical landscapes, accounting for the contribution of rock dissolution at depth is particularly important. In such warm, wet climates, mineral dissolution can occur many meters below the surface, beyond the penetration depth of most cosmic rays and thus the production of most cosmogenic nuclides. Our data suggest the importance of estimating solute fluxes and measuring paired cosmogenic nuclides to better understand the processes and rates of mass transfer at a basin scale.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Space Launch System Liftoff and Separation Dynamics Analysis Tool Chain

A flexible, hierarchical tool chain that is being applied to NASA’s Space Launch System (SLS) for critical dynamics phenomena is described. This tool chain, called CLVTOPS, is used to investigate lateral liftoff movement of the vehicle as it departs and clears the mobile launch tower and separation of the two solid rocket boosters without collision with the core stage and payload. The toolset’s architecture was configured to take advantage of a modern software-engineering approach for maximum flexibility and utilization of open-source simulations and associated tools. As opposed to a “monolithic” approach, scripting languages were used to “bind” together a tool chain to configure and organize input data, execute and produce analysis results, and post-process these results to facilitate a rapid iterative analysis process to quickly address issues and pursue alternatives with emphasis on analysis automation. Key capabilities in the tool chain include processing and mining of very large data sets, a wide range of graphical depictions, and high-fidelity, physics-based simulations. The paper begins with a problem description and the motivation for liftoff and separation dynamics analysis followed by a historical survey of dynamics analyses for previous NASA human-rated launch vehicles. Details of the tool chain and its components are then introduced divided, first, into description of the scripting language architecture used to “bind” the simulation tools, programs, and scripts together and, second, the physics models and simulations. Representative analyses and data products are shown for liftoff and booster separation dynamics that provide in-depth insight to the tool chain’s capabilities. Supporting activities such as simulation tool chain verification, version archiving and data management, and training are addressed. The paper concludes with case examples on how the tool chain can be tailored to related aerospace dynamics analyses, both large and small. These patterns and techniques for SLS dynamics tool construction can be applied for other aerospace simulations.

6DOF↗

NASA NTRS1987

Thematic mapper research in the earth sciences: Small scale patches of suspended matter and phytoplankton in the Elbe River Estuary, German Bight and Tidal Flats

A Thematic Mapper (TM) field experiment was followed by a data analysis to determine TM capabilities for analysis of suspended matter and phytoplankton. Factor analysis showed that suspended matter concentration, atmospheric scattering, and sea surface temperature can be retrieved as independent factors which determine the variation in the TM data over water areas. Spectral channels in the near infrared open the possibility of determining the Angstrom exponent better than for the coastal zone color scanner. The suspended matter distribution may then be calculated by the absolute radiance of channel 2 or 3 or the ratio of both. There is no indication of whether separation of chlorophyll is possible. The distribution of suspended matter and sea surface temperature can be observed with the expected fine structure. A good correlation between water depth and suspended matter distribution as found from ship data can now be analyzed for an entire area by the synoptic view of the TM scenes.

Grassl, H.↗

NASA NTRS1986

Voyager 2 photopolarimeter experiment - Evidence for tenuous outer ring material at Saturn

Voyager 2 photopolarimeter data are employed to characterize two regions of optically thin material outside the Saturn F ring. The study consists of a statistical analysis of optical depth value fluctuations caused by occultations of starlight from Delta Sco as viewed through the material. One the optically thin regions surrounds the orbital semimajor axis of the outer F ring shepherd satellite Pandora and the other thin region lies 144,090 km farther outward. The first region, with an optical depth of 0.008-0.016, is about 200 km in radius and the second, with an optical depth of 0.005-0.013, is about 1000 km in radial width. The data had a resolution of 0.5 km.

Graps, A. L.↗

DOE OSTI2017

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

Wetlands are one of the most significant natural sources of methane (CH 4 ) to the atmosphere. They emit CH 4 because decomposition of soil organic matter in waterlogged anoxic conditions produces CH 4 , in addition to carbon dioxide (CO 2 ). Production of CH 4 and how much of it escapes to the atmosphere depend on a multitude of environmental drivers. Models simulating the processes leading to CH 4 emissions are thus needed for upscaling observations to estimate present CH 4 emissions and for producing scenarios of future atmospheric CH 4 concentrations. Aiming at a CH 4 model that can be added to models describing peatland carbon cycling, we composed a model called HIMMELI that describes CH 4 build-up in and emissions from peatland soils. It is not a full peatland carbon cycle model but it requires the rate of anoxic soil respiration as input. Driven by soil temperature, leaf area index (LAI) of aerenchymatous peatland vegetation, and water table depth (WTD), it simulates the concentrations and transport of CH 4 , CO 2 , and oxygen (O 2 ) in a layered one-dimensional peat column. Here, we present the HIMMELI model structure and results of tests on the model sensitivity to the input data and to the description of the peat column (peat depth and layer thickness), and demonstrate that HIMMELI outputs realistic fluxes by comparing modeled and measured fluxes at two peatland sites. As HIMMELI describes only the CH 4 -related processes, not the full carbon cycle, our analysis revealed mechanisms and dependencies that may remain hidden when testing CH 4 models connected to complete peatland carbon models, which is usually the case. Our results indicated that (1) the model is flexible and robust and thus suitable for different environments; (2) the simulated CH 4 emissions largely depend on the prescribed rate of anoxic respiration; (3) the sensitivity of the total CH 4 emission to other input variables is mainly mediated via the concentrations of dissolved gases, in particular, the O 2 concentrations that affect the CH 4 production and oxidation rates; (4) with given input respiration, the peat column description does not significantly affect the simulated CH 4 emissions in this model version.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Accelerated Depth Computation for Surface Boxplots with Deep Learning

Functional depth is a well-known technique used to derive descriptive statistics (e.g., median, quartiles, and outliers) for 1D data. Surface boxplots extend this concept to ensembles of images, helping scientists and users identify representative and outlier images. However, the computational time for surface boxplots increases cubically with the number of ensemble members, making it impractical for integration into visualization tools. In this paper, we propose a deep-learning solution for efficient depth prediction and computation of surface boxplots for time-varying ensemble data. Our deep learning framework accurately predicts member depths in a surface boxplot, achieving average speedups of 6X on a CPU and 15X on a GPU for the 2D Red Sea dataset with 50 ensemble members compared to the traditional depth computation algorithm. Our approach achieves at least a 99% level of rank preservation, with order flipping occurring only at pairs with extremely similar depth values that pose no statistical differences. This local flipping does not significantly impact the overall depth order of the ensemble members.

Han, Mengjiao↗

NASA NTRS1975

NiCd battery reliability for shuttle serviced spacecraft

Data from life-cycle testing of 22-cell NiCd batteries designed for shuttle-service spacecrafts are analyzed, first by averaging battery cycle lives as a function of temperature and depth of discharge, and then by calculating single cell failure and survival probabilities as a function of temperature, depth of discharge, and number of operating cycles. The single cell data are used to calculate battery survival probabilities. A mathematical failure model which is a function of the quantity of charge through the battery and the temperature is characterized, suggesting a predictive capability for accurate estimation of energy storage subsystem life and performance of accelerated tests. The failure mechanism described is apparently independent of most charge-discharge parameters and common to most cell sizes.

Eliason, J.↗

NASA NTRS1979

Mercurian crater rim heights and some interplanetary comparisons

Rim height (Re) data have been gathered through shadow measurements for 30 fresh mercurian craters with diameters (D) between 2.6 and 39 km. Small mercurian craters (i.e., those less than about 16 km in diameter) have higher rims than do lunar craters of the same diameter; on the basis of Re/D measurements alone, however, mercurian craters larger than about 16 km appear to be indistinguishable from their lunar counterparts (those greater than about 21 km in diameter). Apparent crater depths (Ra, the crater depth measured from the initial target surface) derived from empirical data allude to a decrease in Ra/D with calculated modal impact velocity. This is consistent with the hypothesis that higher impact velocities place the effective depth of burst of the event closer to the surface, thus causing a shallower crater.

Cintala, M. J.↗

NASA NTRS2021

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗

NASA NTRS2000

Vertical Distributions of PH3 in Saturn from Observations of Its 1-0 and 3-2 Rotational Lines

Far-infrared Fourier-transform spectrometer measurements of the 1-0 and 3-2 PH3 transitions in Saturn's disk near 267 and 800 GHz (8.9 and 26.7/cm), respectively, were analyzed simultaneously to derive a global mean profile for the PH3 vertical mixing ratio between 100 and 600 mbar total pressure. The far-infrared spectrum is relatively free from spectral interlopers, suffers minimal absorption or scattering by atmospheric particulates, and contains intrinsically weak PH3 lines that are sensitive to a range of atmospheric depths. The combined spectra are inconsistent with a uniform tropospheric mixing ratio, even with a stratospheric cut-off. They are consistent with a volume mixing ratio of PH3 that drops from 1.2 x 10(exp -5) at 645 mbar pressure to a value of 4.1 x 10(exp -7) at 150 mbar pressure, a decrease that is linear is log abundance vs log pressure. The mixing ratio could drop even more quickly at atmospheric pressures below 150 mbar and still be consistent with the data. The mixing ratio may well remain constant with depth for pressures above 630 mbar. The maximum PH3 mixing ratio in this model is consistent with a [P]/[H] ratio in the deep atmosphere that is about a factor of 10 higher than solar composition. Such a model is consistent with rapid mixing up to the radiative-convective boundary and transport by, for example, vertical waves just above this boundary. In the best fitting model, the eddy diffusion coefficient is approximately 10(exp 4) sq cm near 630 mbar, and it must increase with altitude. The predominant PH3 loss mechanisms are direct photolysis by UV radiation and scavenging by H atoms produced by the photolysis.

Orton, G. S.↗