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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Development and Airborne Demonstration of the Concurrent Artificially-Intelligent Spectrometry and Adaptive Lidar System: Advancing Lidar Capabilities for the STV Observing System

We report on the design, build and planned airborne demonstration of a spaceflight-prototype Concurrent Artificially-intelligent Spectrometry and Adaptive Lidar System (CASALS). The CASALS lidar is an Adaptive Wavelength Scanning Lidar (AWSL) operating in push broom mode. The demonstration has three major goals: advance the Technical Readiness Level of the AWSL hardware, validate its measurement performance and mature algorithms and methods needed for the Surface Topography and Vegetation (STV) observing system. AWSL acquires parallel tracks of surface heights by rapidly steering a laser beam across a swath. A 1040nm-centered laser is tuned across 30nm and carved into 2-ns pulses, the pulse energy is fiber amplified and the pulses are dispersed cross-track using a non-mechanical wavelength-to-angle grating. For the spaceflight system the beam will be pointable to 1200 10m footprints across a 7km swath. For the airborne demonstration there will be 256 0.7m footprints across a 110m swath. In both cases the footprints overlap across- and along-track for uniform target illumination. For the airborne demonstration a steering mirror will increase the accessible swath width to 4km. At the receiver, solar radiation is filtered with a narrow-slit grating-spectrometer and the footprints are imaged onto a linear-mode, photon-sensitive HgCdTe APD-array. The received pulses are time-division-multiplexed to a few high-speed analog-to-digital converters to record waveforms. Spaceflight and airborne CASALS are designed to nominally detect 20 photons per pulse and, by averaging 27 overlapping footprints, achieve 2cm flat target range precision and high-quality vegetation structure waveforms The AWSL will be flown in the summer of 2024, along with a Headwall VNIR-SWIR hyperspectral sensor imaging a 4km wide swath, at NEON eddy covariance flux towers in the U.S. mid-Atlantic where high resolution hyperspectral and lidar data, acquired annually, are available for validation.

Guangning Yang↗
NASA NTRSDate not supplied

Testing and Analyses of Advanced Composite Tow-Steered Shells with Cutouts

The structural response of two composite tow-steered shells with small cutouts in end compression is assessed using analyses and experimental measurements. The cylindrical shells were manufactured without cutouts using an automated fiber placement system, where the shells’ fiber orientation angles vary continuously around the shell circumference from ±10 degrees on the axially stiff crown and keel, to ±45 degrees on the shear-stiff sides. The first shell with overlaps has laminate thickness variations on the crown and keel that result from application of all 24 tows during each pass of the fiber placement system. The second shell without overlaps uses the fiber placement system’s tow drop/add capability to achieve a more uniform shell wall thickness. These shells without cutouts were tested in axial compression and buckled elastically. An unreinforced cutout representative of a passenger door on a commercial aircraft fuselage is machined into one side of each shell. Results from nonlinear finite element analysis are compared with their corresponding load, displacement, and strain measurements in prebuckling through stable postbuckling. Results from tests and analyses of shells with large cutouts are also discussed. The very good agreement observed in this study increases confidence in applying tow-steered composites to operational vehicles.

Tow-Steered↗
NASA NTRSDate not supplied

Imbalanced Multi-layer Cloud Classification with Advanced Baseline Imager (ABI) and CloudSat/CALIPSO Data

Clouds at different altitudes play different roles in Earth’s climate. Comprehensive understanding of overlapping clouds is important for climate and weather prediction. The East Pacific region is where El Ni˜no and La Ni˜na originate and where multi-layer clouds frequently occur. The overlap of clouds at different altitudes in this region increases the classification complexity for cloud-based climatological studies. Unlike prior work in cloud layer classification that assumes single layer or two-layer of clouds, in this work, we consider multi-layer cloud classification with 8 cloud-level classes (clear-sky, high, middle, low, high+middle, high+low, middle+low, high+middle+low). We develop and analyze machine learning models on features extracted from satellite images from the East Pacific regions collected by GOES Advanced Baseline Imager (ABI). These are used to classify CloudSat/CALIPSO observed multi-layer clouds. Due to the imbalanced nature of the data, we investigate the adoption of conventional resampling methods, as well as deep learning methods with data augmentation. In our experiments, we utilize the random forest classifier and Multilayer perceptron classifier with data augmentation methods to reduce the class imbalance during training. With these approaches, we achieve a classification accuracy of 83.6% without exploiting any ancillary information.

machine learning↗
NASA NTRS2024

Enabling America on the Space Frontier: The Evolution of NASA’s Commercial Space Development Toolkit

Throughout NASA’s history, the Agency has supported the development and growth of the U.S. commercial space sector via various mechanisms that have nurtured the technology, companies, people, and ideas driving an industry that today is a significant contributor to the American and global economies. This report identifies 17 such mechanisms and qualitatively examines how they have been applied across four distinct periods in NASA’s history: 1915–1960, which covers NASA’s predecessor, the National Advisory Committee on Aeronautics (NACA), and NASA’s pre-Apollo years; 1961–1980, the Apollo era; 1981–2010, the Space Shuttle era; and 2011–present, the post-Shuttle commercial era. These eras are defined by dominant technologies, programs, or economic trends. Not all 17 mechanisms were applied during each era; some are relatively recent conceptions, while others have been used throughout the history of NASA and NACA. Additionally, there is inevitably some overlap between the mechanisms; this overlap adds an element of subjectivity to the categorizations in this report. In most eras, and for most mechanisms, there are far more examples than can reasonably be summarized in a single document. Therefore, this report should not be considered an exhaustive review of every iteration of any given mechanism’s implementation. Finally, with many of these mechanisms, such as contracts, commercial space capabilities sometimes resulted as a serendipitous by-product rather than a planned outcome.

economic policy↗
NASA NTRSDate not supplied

A Machine Learning Framework for Error Compensation in Radiative Transfer Calculations

Radiative heat transfer influences the amount of heat flux transferred to the surface of the hypersonic vehicle, which is essential to evaluate the performance of thermal protection systems. The radiative heat flux is found to be computationally prohibitive while accounting for the variation in spatial, angular, and spectral domains. A new methodology has been recently developed to alleviate the cost of computation in the spectral domain by constructing flow-agnostic reduced-order models (ROMs). The developed spectral ROM databases provide grouping strategies that account for non-equilibrium absorption and emission as well as interaction between disparate species due to spectral overlap in associated radiative processes. However, the developed ROMs need to be optimized for a specific combination of interacting gas species and would need to re-calibrated in case individual species are added/omitted. In this work, we use various machine learning (ML) techniques to approximate the radiative intensities determined by a ROM optimized for a specific gas mixture. The ML model relies on the ROM databases developed for a single species which ignores any spectral overlap. Thus, radiation evaluation starts with a simple summation of radiative intensities predicted using these non-calibrated ROMs for the contributing species. The ML framework then provides a correction to account for the interplay in the frequency, i.e., emission of photons by one species and absorption by another, and yields mixture-specific radiation fields. Once trained on the individual ROM databases, the ML framework offers instantaneous corrections that serves as a time/cost effective alternative to the optimization of ROMs for a specific gas mixture. The ML framework is trained on both the high fidelity and ROM evaluated line of sight (LOS) data from Orion, Stardust, and FIRE II cases to obtain a general purpose correction model for earth re-entry scenarios when radiation contributions from both atomic nitrogen and atomic oxygen are considered. A geometric length scale parameter is used in the training process to account for errors introduced in the ROM databases as a consequence of high optical thickness. The efficacy of the ML framework is underscored through extensive analysis of train and test errors with respect to all the re-entry scenarios. The applicability of such an ML framework was further corroborated by embedding it in a state-of-the-art US3D - NERO system for determining the radiative heat flux transferred to the hypersonic vehicle surface.

Radiation↗
NASA NTRS2006

Towards Determination of Visual Requirements for Augmented Reality Displays and Virtual Environments for the Airport Tower

The visual requirements for augmented reality or virtual environments displays that might be used in real or virtual towers are reviewed wi th respect to similar displays already used in aircraft. As an example of the type of human performance studies needed to determine the use ful specifications of augmented reality displays, an optical see-thro ugh display was used in an ATC Tower simulation. Three different binocular fields of view (14 deg, 28 deg, and 47 deg) were examined to det ermine their effect on subjects# ability to detect aircraft maneuveri ng and landing. The results suggest that binocular fields of view much greater than 47 deg are unlikely to dramatically improve search perf ormance and that partial binocular overlap is a feasible display tech nique for augmented reality Tower applications.

NATO FURNISHED↗
NASA NTRS2014

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.

CALIOP and MODIS↗
NASA NTRS1965

Hydromagnetic whistlers.

Hydromagnetic whistlers considered as overlapping wavetrains generated by particle interaction and propagating along field aligned paths in magnetosphere

PLASMA-PARTICLE INTERACTION↗
NASA NTRS1968

Low friction servo valve

Valve was developed using air bearings which provide frictionless operation. The servo valve is of the flat plate type with rectangular meter openings. Fluid bearings support the metering plate. The overlap is adjustable by means of a variable hinge block support.

Dustin, M. O.↗