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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Multiuser Collaboration with Networked Mobile Devices

In this paper we describe a multiuser collaboration infrastructure that enables multiple mission scientists to remotely and collaboratively interact with visualization and planning software, using wireless networked personal digital assistants(PDAs) and other mobile devices. During ground operations of planetary rover and lander missions, scientists need to meet daily to review downlinked data and plan science activities. For example, scientists use the Science Activity Planner (SAP) in the Mars Exploration Rover (MER) mission to visualize downlinked data and plan rover activities during the science meetings [1]. Computer displays are projected onto large screens in the meeting room to enable the scientists to view and discuss downlinked images and data displayed by SAP and other software applications. However, only one person can interact with the software applications because input to the computer is limited to a single mouse and keyboard. As a result, the scientists have to verbally express their intentions, such as selecting a target at a particular location on the Mars terrain image, to that person in order to interact with the applications. This constrains communication and limits the returns of science planning. Furthermore, ground operations for Mars missions are fundamentally constrained by the short turnaround time for science and engineering teams to process and analyze data, plan the next uplink, generate command sequences, and transmit the uplink to the vehicle [2]. Therefore, improving ground operations is crucial to the success of Mars missions. The multiuser collaboration infrastructure enables users to control software applications remotely and collaboratively using mobile devices. The infrastructure includes (1) human-computer interaction techniques to provide natural, fast, and accurate inputs, (2) a communications protocol to ensure reliable and efficient coordination of the input devices and host computers, (3) an application-independent middleware that maintains the states, sessions, and interactions of individual users of the software applications, (4) an application programming interface to enable tight integration of applications and the middleware. The infrastructure is able to support any software applications running under the Windows or Unix platforms. The resulting technologies not only are applicable to NASA mission operations, but also useful in other situations such as design reviews, brainstorming sessions, and business meetings, as they can benefit from having the participants concurrently interact with the software applications (e.g., presentation applications and CAD design tools) to illustrate their ideas and provide inputs.

ground operations↗
NASA NTRS1976

Remote sensing of land use and water quality relationships - Wisconsin shore, Lake Michigan

This investigation assessed the utility of remote sensing techniques in the study of land use-water quality relationships in an east central Wisconsin test area. The following types of aerial imagery were evaluated: high altitude (60,000 ft) color, color infrared, multispectral black and white, and thermal; low altitude (less than 5000 ft) color infrared, multispectral black and white, thermal, and passive microwave. A non-imaging hand-held four-band radiometer was evaluated for utility in providing data on suspended sediment concentrations. Land use analysis includes the development of mapping and quantification methods to obtain baseline data for comparison to water quality variables. Suspended sediment loads in streams, determined from water samples, were related to land use differences and soil types in three major watersheds. A multiple correlation coefficient R of 0.85 was obtained for the relationship between the 0.6-0.7 micrometer incident and reflected radiation data from the hand-held radiometer and concurrent ground measurements of suspended solids in streams. Applications of the methods and baseline data developed in this investigation include: mapping and quantification of land use; input to watershed runoff models; estimation of effects of land use changes on stream sedimentation; and remote sensing of suspended sediment content of streams. High altitude color infrared imagery was found to be the most acceptable remote sensing technique for the mapping and measurement of land use types.

Haugen, R. K.↗
NASA NTRS2006

The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-Global Precipitation Estimates at Fine Scales

The TRMM Multi-satellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining multiple precipitation estimates from satellites, as well as gauge analyses where feasible, at fine scales (0.25 degrees x 0.25 degrees and 3-hourly). It is available both after and in real time, based on calibration by the TRMM Combined Instrument and TRMM Microwave Imager precipitation products, respectively. Only the after-real-time product incorporates gauge data at the present. The data set covers the latitude band 50 degrees N-S for the period 1998 to the delayed present. Early validation results are as follows: The TMPA provides reasonable performance at monthly scales, although it is shown to have precipitation rate dependent low bias due to lack of sensitivity to low precipitation rates in one of the input products (based on AMSU-B). At finer scales the TMPA is successful at approximately reproducing the surface-observation-based histogram of precipitation, as well as reasonably detecting large daily events. The TMPA, however, has lower skill in correctly specifying moderate and light event amounts on short time intervals, in common with other fine-scale estimators. Examples are provided of a flood event and diurnal cycle determination.

Huffman, George J.↗
NASA NTRS1987

The quadrupole gravitational lens

An asymmetric lens made of a spherically symmetric galaxy and a quadrupole tidal part allows a very simple pictorial examination of the multiplicity and positions of the images, for any mass density profile. The lens equations can be reduced to one equation in one variable. In the special case of a singular isothermal sphere with a tide (SIST), the lens properties are described by five parameters. Two parameters determine the angular scale and orientation, while three determine the configuration of the images. A comprehensive investigation of the SIST lens is performed, including the variation of the configurations with the parameter values, the critical surfaces in the parameter space, and the extremal solutions. Analytic expressions are derived for the SIST parameters, and additional image positions, in the case when the intensity ratio and positions relative to the galaxy for two of the images are given as input. Quadrupole lenses with a point mass and a pseudoisothermal sphere as the main part are also described in terms of direction diagrams. A direct relation between deflection profile and rotational velocity is derived.

Kovner, Israel↗
DOE OSTI2022

Downscaling atmospheric chemistry simulations with physically consistent deep learning

Abstract. Recent advances in deep convolutional neural network (CNN)-based super resolution can be used to downscale atmospheric chemistry simulations with substantially higher accuracy than conventional downscaling methods. This work both demonstrates the downscaling capabilities of modern CNN-based single image super resolution and video super-resolution schemes and develops modifications to these schemes to ensure they are appropriate for use with physical science data. The CNN-based video super-resolution schemes in particular incur only 39 % to 54 % of the grid-cell-level error of interpolation schemes and generate outputs with extremely realistic small-scale variability based on multiple perceptual quality metrics while performing a large (8×10) increase in resolution in the spatial dimensions. Methods are introduced to strictly enforce physical conservation laws within CNNs, perform large and asymmetric resolution changes between common model grid resolutions, account for non-uniform grid-cell areas, super-resolve lognormally distributed datasets, and leverage additional inputs such as high-resolution climatologies and model state variables. High-resolution chemistry simulations are critical for modeling regional air quality and for understanding future climate, and CNN-based downscaling has the potential to generate these high-resolution simulations and ensembles at a fraction of the computational cost.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Infrared analysis of LMC superbubbles

Researchers are analyzing three superbubbles in the Large Magellanic Cloud (LMC), cataloged by Meaburn (1980) as LMC-1, LMC-4 (a.k.a. Shapley Constellation III), and LMC-5. Superbubbles are the largest infrared sources in the disks of external galaxies. Their expansion requires multiple supernovae from successive generations of star formation. In LMC superbubbles, the grains swept up by shocks and winds represent an interstellar medium (ISM) whose abundances are quite different from the Galaxy. By applying the Dwek (1986) grain model, we can derive the composition and size spectrum of the grains. The inputs to this model are the dust emission in the four Infrared Astronomy Satellite (IRAS) bands and the interstellar radiation field (ISRF) that provides the heating. The first step in the project is to derive the ISRF for star-forming regions on the periphery of superbubbles. Researchers are doing this by combining observations at several wavelengths to determine the energy budget of the region. They will use a UV image to trace the ionizing stellar radiation that escapes, an H alpha image to trace the ionizing stellar radiation that is absorbed by gas, and the four IRAS images to trace the stellar radiation, both ionizing and non-ionizing, that is absorbed by dust. This multi-wavelength approach has the advantages that we do not have to assume the shape of the IMF or the extinction of the source.

Verter, Fran↗
DOE OSTI2022

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

Finding actionable trends in laser-based metal additive manufacturing process monitoring data is challenging owing to the diversity and complexity of the underlying physical interactions. A single monitoring solution that captures a particular process phenomenon, such as a photodiode that tracks melt pool intensity, is not alone capable of evaluating process stability or detecting flaw formation with sufficient precision for routine application in industry. In this work, to improve flaw detection performance, we adopted a data fusion approach that captures multiple process phenomena. To demonstrate this, we acquired data from laser powder bed fusion (LPBF) builds of cylindrical specimens produced with different laser spot sizes, emulating defocusing due to process faults such as thermal lensing. The resulting specimens had porosity of varying types and severity, quantified by post-build non-destructive X-ray computed tomography, Archimedes density measurements, and destructive metallographic characterization. During the build, the melt pool state was monitored with two coaxial high-speed video cameras and a temperature field imaging system. Physically intuitive low-level melt pool signatures, such as melt pool temperature, shape and size, and spatter intensity were extracted from this high-dimensional, image-based sensor data. These process signatures were subsequently used as input features in relatively simple machine learning models, such as a support vector machine, which were trained to detect laser defocusing, and in addition, predict porosity type and severity. The results show that the data fusion approach significantly enhanced system performance by reducing the overall false positive rate from ~ 0.1 to ~ 0.001 without sacrificing the true positive rate (~0.90). These results were at par with a black-box, deep machine learning approach (convolutional neural network).

36 MATERIALS SCIENCE↗
DOE OSTI2020

System-Independent X-Ray Characterization

We have developed a method for image reconstruction and analysis of dual-energy X-ray scans that has been demonstrated to yield a physically intuitive characterization of materials (by electron density and effective atomic number) in a system-independent way. Our methodology stands in contrast to common practice of reconstructing images to yield linear attenuation coefficients, which depend strongly on system spectral response. At the core of our method, a technique called dual-energy decomposition is used to generate spectral energy-independent characterizations of the attenuation properties of a material. Inputs to this decomposition include system spectral response estimates and dual-energy X-ray projection data. X-ray cross-section tables are used to convert decomposition results to physical feature estimates (electron density, effective atomic number). Our method currently works best for materials with atomic numbers below 22 (titanium). In prior work for DHS, we demonstrated in a controlled, no-clutter environment that the decomposition technique could be applied to scans of a well-characterized materials on multiple systems with different X-ray spectral responses. In cases where LAC values showed a standard deviation of as much as 20% of mean value, application of our method yielded results with standard deviations as low as 1–3% of mean value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2011

Current Closure in the Auroral Ionosphere: Results from the Auroral Current and Electrodynamics Structure Rocket Mission

The Auroral Current and Electrodynamics Structure (ACES) mission consisted of two sounding rockets launched nearly simultaneously from Poker Flat Research Range, AK on January 29, 2009 into a dynamic multiple-arc aurora. The ACES rocket mission was designed to observe electrodynamic and plasma parameters above and within the current closure region of the auroral ionosphere. Two well instrumented payloads were flown along very similar magnetic field footprints, at different altitudes, with small temporal separation between both payloads. The higher altitude payload (apogee 360 km), obtained in-situ measurements of electrodynamic and plasma parameters above the current closure region to determine the input signature. The low altitude payload (apogee 130 km), made similar observations within the current closure region. Results are presented comparing observations of the electric fields, magnetic components, and the differential electron energy flux at magnetic footpoints common to both payloads. In situ data is compared to the ground based all-sky imager data, which presents the evolution of the auroral event as the payloads traversed through magnetically similar regions. Current measurements derived from the magnetometers on the high altitude payload observed upward and downward field-aligned currents. The effect of collisions with the neutral atmosphere is investigated to determine it is a significant mechanism to explain discrepancies in the low energy electron flux. The high altitude payload also observed time-dispersed arrivals in the electron flux and perturbations in the electric and magnetic field components, which are indicative of Alfven waves.

Kaeppler, S. R.↗
NASA NTRS2012

Current Closure in the Auroral Ionosphere: Results from the Auroral Current and Electrodynamics Structure Rocket Mission

The Auroral Current and Electrodynamics Structure (ACES) mission consisted of two sounding rockets launched nearly simultaneously from Poker Flat Research Range, AK on January 29, 2009 into a dynamic multiple-arc aurora. The ACES rocket mission was designed to observe electrodynamic and plasma parameters above and within the current closure region of the auroral ionosphere. Two well instrumented payloads were flown along very similar magnetic field footprints, at different altitudes, with small temporal separation between both payloads. The higher altitude payload (apogee 360 km), obtained in-situ measurements of electrodynamic and plasma parameters above the current closure region to determine the input signature. The low altitude payload (apogee 130 km), made similar observations within the current closure region. Results are presented comparing observations of the electric fields, magnetic components, and the differential electron energy flux at magnetic footpoints common to both payloads. In situ data is compared to the ground based all-sky imager data, which presents the evolution of the auroral event as the payloads traversed through magnetically similar regions. Current measurements derived from the magnetometers on the high altitude payload observed upward and downward field-aligned currents. The effect of collisions with the neutral atmosphere is investigated to determine if it is a significant mechanism to explain discrepancies in the low energy electron flux. The high altitude payload also observed time-dispersed arrivals in the electron flux and perturbations in the electric and magnetic field components, which are indicative of Alfven waves.

Kaeppler, S. R.↗
NASA NTRS2004

Fossil Signatures Using Elemental Abundance Distributions and Bayesian Probabilistic Classification

Elemental abundances (C6, N7, O8, Na11, Mg12, Al3, P15, S16, Cl17, K19, Ca20, Ti22, Mn25, Fe26, and Ni28) were obtained for a set of terrestrial fossils and the rock matrix surrounding them. Principal Component Analysis extracted five factors accounting for the 92.5% of the data variance, i.e. information content, of the elemental abundance data. Hierarchical Cluster Analysis provided unsupervised sample classification distinguishing fossil from matrix samples on the basis of either raw abundances or PCA input that agreed strongly with visual classification. A stochastic, non-linear Artificial Neural Network produced a Bayesian probability of correct sample classification. The results provide a quantitative probabilistic methodology for discriminating terrestrial fossils from the surrounding rock matrix using chemical information. To demonstrate the applicability of these techniques to the assessment of meteoritic samples or in situ extraterrestrial exploration, we present preliminary data on samples of the Orgueil meteorite. In both systems an elemental signature produces target classification decisions remarkably consistent with morphological classification by a human expert using only structural (visual) information. We discuss the possibility of implementing a complexity analysis metric capable of automating certain image analysis and pattern recognition abilities of the human eye using low magnification optical microscopy images and discuss the extension of this technique across multiple scales.

Hoover, Richard B.↗
NASA NTRS2013

A Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products

Identification of clear-sky snow and ice is an important step in the production of cryosphere radiation budget products, which are used in the derivation of long-term data series for climate research. In this paper, a new method of clear-sky snow/ice identification for Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. The algorithm's goal is to enhance the identification of snow and ice within the Clouds and the Earth's Radiant Energy System (CERES) data after application of the standard CERES scene identification scheme. The input of the algorithm uses spectral radiances from five MODIS bands and surface skin temperature available in the CERES Single Scanner Footprint (SSF) product. The algorithm produces a cryosphere rating from an aggregated test: a higher rating corresponds to a more certain identification of the clear-sky snow/ice-covered scene. Empirical analysis of regions of interest representing distinctive targets such as snow, ice, ice and water clouds, open waters, and snow-free land selected from a number of MODIS images shows that the cryosphere rating of snow/ice targets falls into 95% confidence intervals lying above the same confidence intervals of all other targets. This enables recognition of clear-sky cryosphere by using a single threshold applied to the rating, which makes this technique different from traditional branching techniques based on multiple thresholds. Limited tests show that the established threshold clearly separates the cryosphere rating values computed for the cryosphere from those computed for noncryosphere scenes, whereas individual tests applied consequently cannot reliably identify the cryosphere for complex scenes.

Radkevich, Alexander↗
DOE OSTI2023

Universal linear intensity transformations using spatially incoherent diffractive processors

Abstract Under spatially coherent light, a diffractive optical network composed of structured surfaces can be designed to perform any arbitrary complex-valued linear transformation between its input and output fields-of-view (FOVs) if the total number ( N ) of optimizable phase-only diffractive features is ≥~2 N i N o , where N i and N o refer to the number of useful pixels at the input and the output FOVs, respectively. Here we report the design of a spatially incoherent diffractive optical processor that can approximate any arbitrary linear transformation in time-averaged intensity between its input and output FOVs. Under spatially incoherent monochromatic light, the spatially varying intensity point spread function ( H ) of a diffractive network, corresponding to a given, arbitrarily-selected linear intensity transformation, can be written as H ( m , n ; m ′, n ′) = | h ( m , n ; m ′, n ′)| 2 , where h is the spatially coherent point spread function of the same diffractive network, and ( m , n ) and ( m ′, n ′) define the coordinates of the output and input FOVs, respectively. Using numerical simulations and deep learning, supervised through examples of input-output profiles, we demonstrate that a spatially incoherent diffractive network can be trained to all-optically perform any arbitrary linear intensity transformation between its input and output if N ≥ ~2 N i N o . We also report the design of spatially incoherent diffractive networks for linear processing of intensity information at multiple illumination wavelengths, operating simultaneously. Finally, we numerically demonstrate a diffractive network design that performs all-optical classification of handwritten digits under spatially incoherent illumination, achieving a test accuracy of >95%. Spatially incoherent diffractive networks will be broadly useful for designing all-optical visual processors that can work under natural light.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Statistics of Wide Pre-main-sequence Binaries in the Orion OB1 Association

Statistics of low-mass pre-main-sequence binaries in the Orion OB1 association with separations ranging from 0."6 to 20" (220 to 7400 au at 370 pc) are studied using images from the VISTA Orion mini survey and astrometry from Gaia. The input sample based on the CVSO catalog contains 1137 stars of K and M spectral types (masses between 0.3 and 0.9 M ⊙ ), 1021 of which are considered to be association members. There are 135 physical binary companions to these stars with mass ratios above ~0.13. The average companion fraction is 0.09 ± 0.01 over 1.2 decades in separation, slightly less than, but still consistent with, the field. We found a difference between the Ori OB1a and OB1b groups, the latter being richer in binaries by a factor of 1.6 ± 0.3. No overall dependence of the wide-binary frequency on the observed underlying stellar density is found, although in the Ori OB1a off-cloud population, these binaries seem to avoid dense clusters. The multiplicity rates in Ori OB1 and in sparse regions like Taurus differ significantly, hinting that binaries in the field may originate from a mixture of diverse populations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2022

A Novel Machine Learning-Based Gap-Filling of Fine-Resolution Remotely Sensed Snow Cover Fraction Data By Combining Downscaling and Regression

Satellite-based remotely sensed observations of snow cover fraction (SCF) can have data gaps in spatially distributed coverage from sensor and orbital limitations. We mitigate these limitations in the example fine-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) data by gap-filling using auxiliary 1-km datasets that either aid in downscaling from coarser-resolution (5 km) MODIS SCF wherever not fully covered by clouds, or else by themselves via regression wherever fully cloud covered. This study’s prototype predicts a 1-km version of the 500-m MOD10A1 SCF target. Due to noncollocatedness of spatial gaps even across input and auxiliary datasets, we consider a recent gap-agnostic advancement of partial convolution in computer vision for both training and predictive gap-filling. Partial convolution accommodates spatially consistent gaps across the input images, effectively implementing a two-dimensional masking. To overcome reduced usable data from noncollocated spatial gaps across inputs, we innovate a fully generalized three-dimensional masking in this partial convolution. This enables a valid output value at a pixel even if only a single valid input variable and its value exist in the neighborhood covered by the convolutional filter zone centered around that pixel. Thus, our gap-agnostic technique can use significantly more examples for training (∼67%) and prediction (∼100%), instead of only less than 10% for the previous partial convolution. We train an example simple three-layer legacy super-resolution convolutional neural network (SRCNN) to obtain downscaling and regression component performances that are better than baseline values of either climatology or MOD10C1 SCF as relevant. Our generalized partial convolution can enable multiple Earth science applications like downscaling, regression, classification, and segmentation that were hindered by data gaps.

Soni Yatheendradas↗
NASA NTRS2010

Temporal laser pulse manipulation using multiple optical ring-cavities

An optical pulse stretcher and a mathematical algorithm for the detailed calculation of its design and performance is disclosed. The optical pulse stretcher has a plurality of optical cavities, having multiple optical reflectors such that an optical path length in each of the optical cavities is different. The optical pulse stretcher also has a plurality of beam splitters, each of which intercepts a portion of an input optical beam and diverts the portion into one of the plurality of optical cavities. The input optical beam is stretched and a power of an output beam is reduced after passing through the optical pulse stretcher and the placement of the plurality of optical cavities and beam splitters is optimized through a model that takes into account optical beam divergence and alignment in the pluralities of the optical cavities. The optical pulse stretcher system can also function as a high-repetition-rate (MHz) laser pulse generator, making it suitable for use as a stroboscopic light source for high speed ballistic projectile imaging studies, or it can be used for high speed flow diagnostics using a laser light sheet with digital particle imaging velocimetry. The optical pulse stretcher system can also be implemented using fiber optic components to realize a rugged and compact optical system that is alignment free and easy to use.

Nguyen, Quang-Viet↗
NASA NTRS2018

More Efficient Precipitation Rate Data Acquisition with the STORM Swath-Based Analysis Tool

A multitude of locations exist for acquiring satellite-derived precipitation rate data. Because the volume of data exceeds what can reasonably be analyzed manually, online tools have been developed to help researchers make more informed data acquisition decisions. Some interfaces provide sample images generated from prioritized variables to enable efficient visual inspection, while others include the ability to subset geographically to reduce the volume of the data to the area of interest. Building upon such value-added services is the STORM (the NASA Precipitation Processing System (PPS) data product ordering system) Swath-Based Analysis Tool (https://storm.pps.eosdis.nasa.gov/storm/Analysis.jsp). With it, users can compare overflights of multiple precipitation satellites simultaneously and from this make determinations about which swaths will best serve their research. They can preview these overflights with two distinct visualization tools. Finally, they can then download geographically subset swaths that have precipitation rate characteristics matching their research needs. A user starts by making up to six selections. They then select their date range of interest going back to 1997. Finally, they select a geographical region either by inputting latitude-longitude corners of a rectangle or drawing that rectangle on an interactive map. The system processes each file, determining aggregate statistics about the precipitation rates within the selected region as observed by each instrument. These statistical values are added to a time series graph as a "time remaining" counter is continuously updated. The chart is fully interactive, with detailed values displayed upon mouseover, and numerous options available upon clicking each point. Since the user is likely to need the relevant files for their own research, they can generate an order from their request. All files are geographically subset to the region of interest, and the user can use the statistical values to limit which files are added to the order. This flexibility helps to ensure researchers are only downloading the files they need for their work, making for a more efficient process both from a time-consumption and a storage perspective. This paper will introduce the Swath-Based Analysis Tool and explore its numerous features. It will discuss several use cases for precipitation scientists.

remote sensing↗
NASA NTRS2011

A Rocket-Base Study of Auroral Electrodynamics Within the Current Closure Ionosphere

The Auroral Current and Electrodynamics Structure (ACES) mission consisted of two sounding rockets launched nearly simultaneously from Poker Flat Research Range, AK on January 29, 2009 into a dynamic multiple-arc aurora. The ACES rocket mission, in conjunction with the PFISR Radar, was designed to observe the three-dimensional current system of a stable auroral arc system. ACES utilized two well instrumented payloads flown along very similar magnetic field footprints, at various altitudes with small temporal separation between both payloads. ACES High, the higher altitude payload (apogee 360 km), took in-situ measurements of the plasma parameters above the current closure region to provide the input signature into the lower ionosphere. ACES Low, the low-altitude payload (apogee 130 km), took similar observations within the current closure region, where cross-field currents can flow. We present results comparing observations of the electric fields, magnetic fields, electron flux, and the electron temperature at similar magnetic footpoints between both payloads. We further present data from all-sky imagers and PFISR detailing the evolution of the auroral event as the payloads traversed regions connected by similar magnetic footpoints. Current measurements derived from the magnetometers on both payloads are further compared. We examine data from both PFISR and observations on the high-altitude payload which we interpreted as a signature of electron acceleration by means of Alfv n waves. We further examine all measurements to understand ionospheric conductivity and how energy is being deposited into the ionosphere through Joule heating. Data from ACES is compared against models of Joule heating to make inferences regarding the effect of collisions at various altitudes.

Kaeppler, Stephen R.↗