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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

NASA Conjunction Assessment Risk Analysis (CARA) Ground Systems, Software and Operations Infrastructure Cloud Implementation

The growing number of large-scale constellations and the improvements made in the tracking and detection of resident space objects have contributed to the increase of satellite conjunction events. As a result of the increase of objects in Earth orbit, the timeline for risk analysis computations for satellite collision avoidance is more urgent when conjunctions occur. It is imperative NASA maintains a space environment safety functionality for the agency that allows CARA remote access to the ground system while maintaining redundancy. CARA’s On-premises (On-prem) ground system would no longer be able to meet these access and redundancy requirements, hence the investigation and eventual implementation of a Cloud-based ground station infrastructure as a viable solution. This paper will provide an overview of the principal parts of the Conjunction Assessment (CA) risk analysis process used at CARA, summarize the key drivers towards the Cloud solution, and share key lessons learned that are significant for any operational entity considering a cloud solution for real-time satellite operations to ensure a sustainable space traffic environment for all.

Sustainability↗
NASA NTRS1983

Orbital and cloud cover sampling analyses for multisatellite earth radiation budget experiments

Computer simulations have been performed to determine the geographical and temporal coverage of various satellite orbits and scanning and nonscanning radiometers for earth radiation budget measurements. These results were used to simulate the sampling of a diurnally varying cloud and radiation field for several different satellite systems to estimate errors in regional monthly mean reflected radiation. The combined results indicate that coincient observations with a minimum of one sun-synchronous satellite and a midinclined orbit satellite are needed to obtain the required regional, zonal, and global coverage with sufficient temporal sampling for obtaining accurate estimates of monthly mean reflected solar radiation. Overall, the best sampling capability and lowest errors were obtained with a three-satellite system, i.e., two sun-synchronous satellites with different equatorial crossing times combined with either a 46 or 57-deg orbit satellite. The results from these analyses have been used in defining a joint NASA-NOAA multisatellite mission for an earth radiation budget experiment.

Harrison, E. F.↗
NASA NTRS1995

Remote sounding of surface radiative fluxes in cirrus cloudy conditions

It has been long recognized that radiation and radiation perturbations play a critical role in the climate system. Surface radiative fluxes are useful parameters for monitoring global change, for understanding of the effects of clouds on the radiation field, and for improving parameterization of surface sensible and latent heat fluxes. Monitoring of the radiation budget at the top of the atmosphere has been one of the prime satellite programs for the last 30 years. However, monitoring radiative fluxes at the surface over the globe from space cannot be performed in a direct way at the present time. In particular, since clouds are the prime regulators of the radiative fluxes, uncertainties in the retrieved cloud parameters, which are inputs to radiative transfer models, can introduce significant errors in the computed radiative fluxes. Thus, remote sounding of surface radiative fluxes in cloudy conditions requires the development of both satellite cloud retrieval scheme and radiation models. In this paper, we present results of computed surface radiative fluxes in cirrus cloudy conditions using a cirrus cloud retrieval scheme and a detailed radiative transfer program. Comparisons have been made between the computed surface radiative fluxes and the ground-based radiometer measurements obtained during FIRE-II-IFO, which was carried out near Coffeyville, Kansas, during November and December, 1991.

Ou, S. C.↗
DOE OSTI2024

Emulator of PR‐DNS: Accelerating Dynamical Fields With Neural Operators in Particle‐Resolved Direct Numerical Simulation

Abstract Particle‐resolved direct numerical simulations (PR‐DNS) play an increasing role in investigating aerosol‐cloud‐turbulence interactions at the most fundamental level of processes. However, the high computational cost associated with high resolution simulations poses considerable challenges for large domain or long duration simulation using PR‐DNS. To address these issues, here we present an emulator of the complex physics‐based PR‐DNS developed by use of the data‐driven Fourier Neural Operator (FNO) method. The effectiveness of the method is showcased by presenting turbulence and temperature fields in a two‐dimensional space. The results demonstrate high accuracy at various resolutions and the emulator is two orders of magnitude cheaper in terms of computational demand compared to the physics‐based PR‐DNS model. Furthermore, the FNO emulator exhibits strong generalization capabilities for different initial conditions and ultra‐high‐resolution without the need to retrain models. These findings highlight the potential of the FNO method as a promising tool to simulate complex fluid dynamics problems with high accuracy, computational efficiency, and generalization capabilities, enhancing our understanding of the aerosol‐cloud‐precipitation system.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Improving the Capabilities and Computational Efficiency of the RTE+RRTMGP Radiation Code (Final Report)

This report details progress on the RTE+RRTMGP radiation codes made during the period of performance. RTE+RRTMGP is a set of codes for computing radiative fluxes in planetary atmospheres. RRTMGP uses a k-distribution to provide an optical description (absorption and possibly Rayleigh optical depth) of the gaseous atmosphere, along with the relevant source functions, on a pre-determined spectral grid given temperatures, pressures, and gas concentration. RTE computes fluxes given spectrally-resolved optical descriptions and source functions. Spectrally-resolved fluxes are summarized (“reduced”) via a user extensible class. The initial release of the code and the design choices are described in Pincus et al. 2019; the codes are available on Github. Although RRTMGP was based on current (at the time) empirical spectroscopic data, RTE and RRTMGP were developed in large part to modernize software practices. The design focused on flexibility broadly interpreted: by separating code from data and allowing data to drive computation; in coupling to the host model (e.g. the coupling of clouds to radiative fluxes is user-controlled); with respect to programming languages (computational tasks are accessed via widely-compatible C interfaces); and with respect to hardware (the codes run on a range of CPU and GPU architectures). The code also puts an emphasis on modularity and clarity. RTE+RRTMGP v1.0 was released in September 20219. This award supported the evolution of the RTE+RRTMGP code base to support greater flexibility, accuracy, and efficiency.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Program listing for the REEDM (Rocket Exhaust Effluent Diffusion Model) computer program

The program listing for the REEDM Computer Program is provided. A mathematical description of the atmospheric dispersion models, cloud-rise models, and other formulas used in the REEDM model; vehicle and source parameters, other pertinent physical properties of the rocket exhaust cloud and meteorological layering techniques; user's instructions for the REEDM computer program; and worked example problems are contained in NASA CR-3646.

Bjorklund, J. R.↗
DOE OSTI2021

Improving the prediction of DNI with physics-based representation of all-sky circumsolar radiation

Direct normal irradiance (DNI) is often interpreted differently in ground measurements and forecasts using numerical weather prediction (NWP) models, leading to substantial bias in DNI forecasting especially under cloudy-sky conditions. To mitigate the bias, we use the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) to conduct physics-based simulations of solar radiation in the circumsolar region. The DNI is quantified using the sum of the radiation along the sun direction and the scattered radiation within the circumsolar region. FARMS-DNI is coupled with the Weather Research and Forecasting model with solar extensions (WRF-Solar) to predict day-ahead DNI in 9-km pixels over an extended domain covering the contiguous United States. The DNI forecasts for the entire year of 2018 are validated using surface-based observations at the Atmospheric Radiation Measurement (ARM) and Surface Radiation Budget Network (SURFRAD) sites and a satellite-based solar radiation product developed by the procedure of the National Solar Radiation Data Base (NSRDB). The results show that the WRF-Solar coupled with the conventional Beer-Bouguer-Lambert law underestimes the overall DNI forecasts by 30%-60%, which is a joint effect of the uncertainties in computing the circumsolar radiation and forecasting cloud properties. This bias is significantly reduced by using FARMS-DNI.

14 SOLAR ENERGY↗
DOE OSTI2022

Semantic Property Graph for Scalable Knowledge Graph Analytics

Graphs are a natural and fundamental representation to describe entities, relationships, activities, and evolution of complex systems. Many domains such as communication, citation, procurement, biology, social media, and transportation can be modeled as a set of entities and their relationships. Resource Description Framework (RDF) and Labeled Property Graph (LPG) are two of the most used data models to encode information in a graph. Both models are similar in terms of using basic graph elements such as nodes and edges but differ in terms of the modeling approach, expressibility, serialization, and target applications. RDF is a flexible data exchange model for expressing information about entities but it tends to a have high memory footprint and inefficient storage, which does not make it a natural choice to perform scalable graph analytics. In contrast, LPG has gained traction as a reliable model to perform scalable graph analytic tasks such as sub-graph matching, network alignment, and real-time knowledge graph query. It provides efficient storage, fast traversal, and flexibility to model various real-world domains. At the same time, the LPG lacks the support of a formal knowledge representation such as an ontology to provide automated knowledge inference. We propose Semantic Property Graph (SPG) as a logical projection of reified RDF into the LPG model. SPG continues to use RDF ontology to define the type hierarchy of the projected graph and validate it against a given ontology. We present a framework to convert reified RDF graphs into SPG using two different computing environments. We also present cloud-based graph migration capabilities using Amazon Web Services.

Purohit, Sumit↗
DOE OSTI2021

Cyber-Physical System Implementation for Manufacturing With Analytics in the Cloud Layer

Effective and efficient modern manufacturing operations require the acceptance and incorporation of the fourth industrial revolution, also known as Industry 4.0. Traditional shop floors are evolving their production into smart factories. To continue this trend, a specific architecture for the cyber-physical system is required, as well as a systematic approach to automate the application of algorithms and transform the acquired data into useful information. This work makes use of an approach that distinguishes three layers that are part of the existing Industry 4.0 paradigm: edge, fog, and cloud. Each of the layers performs computational operations, transforming the data produced in the smart factory into useful information. Trained or untrained methods for data analytics can be incorporated into the architecture. A case study is presented in which a real-time statistical control process algorithm based on control charts was implemented. The algorithm automatically detects changes in the material being processed in a computerized numerical control (CNC) machine. The algorithm implemented in the proposed architecture yielded short response times. The performance was effective since it automatically adapted to the machining of aluminum and then detected when the material was switched to steel. The data were backed up in a database that would allow traceability to the line of g-code that performed the machining.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Berkeley eXtensible Environment (BXE) v3

The Berkeley eXtensible Environment (BXE) provides a cloud environment for hardware designers and computer architects to design, build, and simulate their custom architectures on an on-premises FPGA cluster. Utilizing the Chipyard, MoSAIC, and FireSim frameworks, users are provided an environment where they can assemble SoC designs from an existing library of components or import their own source code. Once their designs are ready, they can utilize the FireSim framework provided by BXE to deploy and simulate their designs on the FPGA. Users aren't limited to a single FPGA; they can deploy multiple instances across multiple FPGAs, acting like a rack of servers, or partition their large design across multiple FPGAs, ganging multiple FPGAs into a single simulated system.

Fatollahi-Fard, Farzin↗
DOE OSTI2025

High-Spectral Resolution Lidar (HSRL) Instrument Handbook

High-spectral-resolution lidar (HSRL) systems provide vertical profiles of optical depth, backscatter cross-section, depolarization, and backscatter phase function. All HSRL measurements are calibrated by reference to molecular scattering, which is measured at each point in the lidar profile. Like the Raman lidar (RL), but unlike simple backscatter lidars such as the micropulse lidar (MPL), this enables the HSRL to measure backscatter cross-sections and optical depths without prior assumptions about the scattering properties of the atmosphere. The depolarization observations allow robust discrimination between ice and water clouds. Rigorous error estimates can be computed for all measurements. A very narrow angular field of view reduces multiple scattering contributions. The small field of view, coupled with a narrow optical bandwidth, nearly eliminates noise due to scattered sunlight. The laser transmitter is a diode-pumped, frequency-doubled Nd:YAG laser. Narrow-band, single-frequency operation is provided by injection seeding with a single-frequency, cw-diode-pumped diode laser. The main laser cavity is maintained in resonance with the seed laser by adjusting the cavity length to minimize the time between the Q-switch trigger and the emission of the laser pulse. The emission wavelength is tuned via temperature control of the seed laser crystal and is locked to line #1109 of the iodine absorption spectra. Locking is accomplished by minimizing the transmission through a 2-cm-long iodine absorption cell. Use of a high-repetition-rate laser and expansion of the transmitted beam through a 400-mm telescope reduces the transmitted energy density to eye-safe levels. It is possible to look directly into the output beam without hazard. The receiver and transmitter use the same afocal telescope, simplifying the maintenance of stable alignment of the transmitter and receiver although the angular FOV is only 100 μrad. The small FOV and the 4-kHz repetition rate also limit the near-field signal strength, making it possible to record continuous profiles that start at an altitude of ~100 m and extend to 30 km using photon counting detectors. The small FOV also suppresses multiple scattering contributions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstrated in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which constitutes the core content of the metrics and diagnostics package in section 2, and a user's guide documenting the workflow/structure of the version 1.0 codes, and including step-by-step instruction for running the package in section 3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

2021 GeoAI Workshop Report: The Trillion Pixel Challenge

The convergence of geospatial big data with advancements from artificial intelligence, cloud infrastructure, and high-performance computing continues to revolutionize mapping and analysis of Earth's surface in unprecedented detail. Rapid innovations in sensing technologies will soon collect geospatial data in even higher resolution and throughput. These developments offer the potential for breakthroughs in science, policy, and national security via end-to-end GeoAI systems that can provide fresh insights into how humans occupy and alter their environment over time. At the 2021 GeoAI Trillion Pixel workshop, international subject matter experts from government, academia, industry, and nonprofit organizations gathered virtually to discuss the Trillion Pixel GeoAI Challenge. The event focused on six major themes currently influencing scientific innovation and breakthroughs. Particular focus was paid to societal impacts. As an additional takeaway message, the gathering identified remaining application gaps and challenges that are in need of stronger community partnerships and collaborations.

58 GEOSCIENCES↗
NASA NTRS1972

Photogrammetric calibration of the NASA-Wallops Island image intensifier system

An image intensifier was designed for use as one of the primary tracking systems for the barium cloud experiment at Wallops Island. Two computer programs, a definitive stellar camara calibration program and a geodetic stellar camara orientation program, were originally developed at Wallops on a GE 625 computer. A mathematical procedure for determining the image intensifier distortions is outlined, and the implementation of the model in the Wallops computer programs is described. The analytical calibration of metric cameras is also discussed.

Harp, B. F.↗
NASA NTRS1977

Analytic studies of local-severe-storm observables by satellites

Attention is concentrated on the exceptionally violet whirlwind, often characterized by a fairly vertical axis of rotation. For a cylindrical polar coordinate system with axis coincident with the axis of rotation, the secondary flow involves the radial and axial velocity components. The thesis advanced is, first, that a violent whirlwind is characterized by swirl speeds relative to the axis of rotation on the order of 90 m/s, with 100 m/s being close to an upper bound. This estimate is based on interpretation of funnel-cloud shape (which also suggests properties of the radial profile of swirl, as well as the maximum magnitude); an error assessment of the funnel-cloud interpretation procedure is developed. Second, computation of ground-level pressure deficits achievable from typical tornado-spawning ambients by idealized thermohydrostatic processes suggests that a two-cell structure is required to sustain such large speeds.

Dergarabedian, P.↗
NASA NTRS1978

Rain scavenging of solid rocket exhaust clouds

An explicit model for cloud microphysics was developed for application to the problem of co-condensation/vaporization of HCl and H2O in the presence of Al2O3 particulate nuclei. Validity of the explicit model relative to the implicit model, which has been customarily applied to atmospheric cloud studies, was demonstrated by parallel computations of H2O condensation upon (NH4)2 SO4 nuclei. A mesoscale predictive model designed to account for the impact of wet processes on atmospheric dynamics is also under development. Input data specifying the equilibrium state of HC1 and H2O vapors in contact with aqueous HC1 solutions were found to be limited, particularly in respect to temperature range.

Dingle, A. N.↗
NASA NTRS1978

A survey of interstellar H I from L-alpha absorption measurements. II

This paper presents interstellar H I column densities, mean H I space densities, total neutral hydrogen column densities, and total mean hydrogen space densities toward 100 stars surveyed in the L-alpha region with the U2 detector of the Copernicus satellite. The data for 47 stars are compared with OAO 2 results, and ratios of gas to E(B-V) color excess are computed for 30 'intercloud' stars, 45 'cloud' stars, and the combined sample of 75 stars. A definitive value of 5.8 x 10 to the 21st power atoms/sq cm per mag is obtained for the mean ratio of total neutral hydrogen to color excess, indicating that this ratio seems to be a constant, independent of location in the sky, except possibly toward stars with anomalous extinction. The anomalous ratio determined for Rho Oph is examined, and the galactic distribution of neutral hydrogen is evaluated. The following values are estimated for matter in the galactic plane within 500 pc of the sun: a total mean hydrogen space density of 1.15 atoms/cu cm, a mean H2 space density of 0.143 molecule/cu cm (possibly a lower limit), and a mean H I space density of 0.86 atom/cu cm (a possible overestimate).

Bohlin, R. C.↗
NASA NTRS1984

Solar reflection from interacting and shadowing cloud elements

An attempt is made to relate the reflection from a broken cloud field to that from a plane parallel cloud of the same optical properties by using Monte Carlo simulations for a very simple model of an array of regularly spaced, infinitely long bar clouds. Reflection from the array is represented by an effective cloud fraction, and it is shown that for many cases this may be obtained by treating the cloud elements to be noninteracting azimuthally symmetric reflectors. The effective cloud fraction is a function of solar zenith angle, the aspect ratio of the individual cloud elements, and the normal or zenith cloud fraction of the array. Model computations for reflection from an array of randomly distributed identical cylinders are also presented as an example of a possible application of this technique.

HARSHVARDHAN↗