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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

International Space Station Common Cabin Air Assembly Condensing Heat Exchanger Hydrophilic Coating Operation, Recovery, and Lessons Learned

The ability to control the temperature and humidity of an environment or habitat is critical for human survival. These factors are important to maintaining human health and comfort, as well as maintaining mechanical and electrical equipment in good working order to support the human and to accomplish mission objectives. The temperature and humidity of the International Space Station (ISS) United States On-orbit Segment (USOS) cabin air is controlled by the Common Cabin Air Assembly (CCAA). The CCAA consists of a fan, a condensing heat exchanger (CHX), an air/water separator, temperature and liquid sensors, and electrical controlling hardware and software. The CHX is the primary component responsible for control of temperature and humidity. The CCAA CHX contains a chemical coating that was developed to be hydrophilic and thus attract water from the humid influent air. This attraction forms the basis for water removal and therefore cabin humidity control. However, there have been several instances of CHX coatings becoming hydrophobic and repelling water. When this behavior is observed in an operational CHX in the ISS segments, the unit s ability to remove moisture from the air is compromised and the result is liquid water carryover into downstream ducting and systems. This water carryover can have detrimental effects on the ISS cabin atmosphere quality and on the health of downstream hardware. If the water carryover is severe and widespread, this behavior can result in an inability to maintain humidity levels in the USOS. This paper will describe the operation of the five CCAAs within the USOS, the potential causes of the hydrophobic condition, and the impacts of the resulting water carryover to downstream systems. It will describe the history of this behavior and the actual observed impacts to the ISS USOS. Information on mitigation steps to protect the health of future CHX hydrophilic coatings as well as remediation and recovery of the full heat exchanger will be discussed.

Balistreri, Steven F.↗
NASA NTRS2010

Stacked Corrugated Horn Rings

This Brief describes a method of machining and assembly when the depth of corrugations far exceeds the width and conventional machining is not practical. The horn is divided into easily machined, individual rings with shoulders to control the depth. In this specific instance, each of the corrugations is identical in profile, and only differs in diameter and outer profile. The horn is segmented into rings that are cut with an interference fit (zero clearance with all machining errors biased toward contact). The interference faces can be cut with a reverse taper to increase the holding strength of the joint. The taper is a compromise between the interference fit and the clearance of the two faces during assembly. Each internal ring is dipped in liquid nitrogen, then nested in the previous, larger ring. The ring is rotated in the nest until the temperature of the two parts equalizes and the pieces lock together. The resulting assay is stable, strong, and has an internal finish that cannot be achieved through other methods.

Sosnowski, John B.↗
DOE OSTI2025

Small-scale properties from exascale computations of turbulence on a $\mathbf{32\,768^3}$ periodic cube

To study the physics of small-scale properties of homogeneous isotropic turbulence at increasingly high Reynolds numbers, direct numerical simulation results have been obtained for forced isotropic turbulence at Taylor-scale Reynolds number R λ = 2500 on a 32 768 3 three-dimensional periodic domain using a GPU pseudo-spectral code on a 1.1 exaflop GPU supercomputer (Frontier). These simulations employ the multi-resolution independent simulation (MRIS) technique (Yeung & Ravikumar 2020, Phys. Rev. Fluids, vol. 5, 110517) where ensemble averaging is performed over multiple short segments initiated from velocity fields at modest resolution, and subsequently taken to higher resolution in both space and time. Reynolds numbers are increased by reducing the viscosity with the large-scale forcing parameters unchanged. Although MRIS segments at the highest resolution for each Reynolds number last for only a few Kolmogorov time scales, small-scale physics in the dissipation range is well captured – for instance, in the probability density functions and higher moments of the dissipation rate and enstrophy density, which appear to show monotonic trends persisting well beyond the Reynolds number range in prior works in the literature. Attainment of range of length and time scales consistent with classical scaling also reinforces the potential utility of the present high-resolution data for studies of short-time-scale turbulence physics at high Reynolds numbers where full-length simulations spanning many large-eddy time scales are still not accessible. A single snapshot of the 32 768 3 data is publicly available for further analyses via the Johns Hopkins Turbulence Database.

intermittency↗
NASA NTRS1992

Model-driven mapping onto distributed memory parallel computers

The author addresses the problem of exploiting the parallelism available in a program to efficiently employ the resources of the target machine in the context of building a mapping compiler for a distributed memory parallel machine. He demonstrates the effectiveness of using execution models to select the best mapping technique from among those available for a given program segment on a particular machine. Through analysis of the execution models for several mapping techniques for one class of programs on a linear processor array, it is shown that selecting the best technique for a particular program instance can make a significant difference in performance. On the other hand, the results of benchmarks from a mapping compiler for the Warp systolic array machine show that the execution models considered are accurate enough to select the best mapping technique for a given program.

Sussman, Alan↗
NASA NTRS1971

An application of cluster detection to scene analysis

Certain arrangements of local features in a scene tend to group together and to be seen as units. It is suggested that in some instances, this phenomenon might be interpretable as a process of cluster detection in a graph-structured space derived from the scene. This idea is illustrated using a class of scenes that contain only horizontal and vertical line segments.

Rosenfeld, A. H.↗
NASA NTRS2000

Gravity Wave Energetics Determined From Coincident Space-Based and Ground-Based Observations of Airglow Emissions

Significant progress was made toward the goals of this proposal in a number of areas during the covered period. Section 5.1 contains a copy of the originally proposed schedule. The tasks listed below have been accomplished: (1) Construction of space-based observing geometry gravity wave model. This model has been described in detail in the paper accompanying this report (Section 5.2). It can simulate the observing geometry of both ground-based, and orbital instruments allowing comparisons to be made between them. (2) Comparisons of relative emission intensity, temperatures, and Krassovsky's ratio for space- and ground-based observing geometries. These quantities are used in gravity wave literature to describe the effects of the waves on the airglow. (3) Rejection of Bates [1992], and Copeland [1994] chemistries for gravity wave modeling purposes. Excessive 02(A(sup 13)(Delta)) production led to overproduction of O2(b(sup 1)(Sigma)), the state responsible for the emission of O2. Atmospheric band. Attempts were made to correct for this behavior, but could not adequately compensate for this. (4) Rejection of MSX dataset due to lack of coincident data, and resolution necessary to characterize the waves. A careful search to identify coincident data revealed only four instances, with only one of those providing usable data. Two high latitude overpasses and were contaminated by auroral emissions. Of the remaining two mid-latitude coincidences, one overflight was obscured by cloud, leaving only one ten minute segment of usable data. Aside from the statistical difficulties involved in comparing measurements taken in this short period, the instrument lacks the necessary resolution to determine the vertical wavelength of the gravity wave. This means that the wave cannot be uniquely characterized from space with this dataset. Since no observed wave can be uniquely identified, model comparisons are not possible.

Source record↗
DOE OSTI2025

Optimization of a Mixed Fleet of Aerial Drones for Medical Supplies: A Case Study of Blood Delivery Logistics

Aerial drones have emerged as an innovative solution for faster transportation of time-sensitive items (e.g., emergency medical supplies), potentially reducing the transmission of contagious diseases and enhancing healthcare availability through contactless autonomous delivery. We study fleet sizing and efficient scheduling of a mixed fleet of drones for delivering time-sensitive medical items having distinct release and due times to minimize the required fleet size and fleet composition, the required number of additional batteries, and the total energy consumption. We continuously track the remaining battery energy of drones to determine the optimal timing for battery replacement, rather than replacing the battery at each node. Using actual drone flight test data, we employed a machine learning (ML) method to estimate the energy consumption of different drone types during flight segments for different operating parameters. We present a novel mixed-integer programming model to efficiently formulate the problem that integrates the estimated energy consumption functions from ML. We propose a new greedy heuristic (GH) algorithm and a customized genetic algorithm (GA) for solving large-scale instances of this problem faster. Results demonstrate that the GH algorithm is substantially faster than the accelerated CPLEX and the GA, while sacrificing the solution quality by a small amount. Results based on an actual blood sample delivery case study from Pendleton, Oregon, United States, show that using a mixed fleet of drones reduces the total cost and total energy consumption up to 18.18% and 28.7%, respectively, compared to using a homogeneous fleet.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
NASA NTRS1973

Severe weather study

Current methods of severe weather information dissemination and the impact of this information on the general public are studied. The study is based on the responses of the general public and the local broadcasters to a severe weather incident which occurred on August 14, 1972 in the Dane County-Madison Metropolitan area. The results of the study were somewhat startling. From the sample, for instance, it was found that 45% of the Dane County population was not aware of the severe thunderstorm warning. In this case this may or may not have been critical, but had the storm been extremely severe or had a tornado and flooding been associated with the storm, a large segment of the population would have been in great danger. What this study has shown, is that the real problem with the dissemination of severe weather information is not the lack of it, but the inability to transfer it in useful form to an overwhelming majority of the general public.

Mills, C. J.↗
DOE OSTI2022

ASDFL: An adaptive super‐pixel discriminative feature‐selective learning for vehicle matching

Abstract There are a large number of cameras in modern transportation system that capture numerous vehicle images continuously. Therefore, automatic analysis of these vehicle images is helpful for traffic flow management, criminal investigations and vehicle inspections. Vehicle matching, which aims to determine whether two input images depict an identical vehicle, is one of the core tasks in vehicle analysis. Recent relevant studies have focused on local feature extraction instead of global extraction, since local details can provide crucial cues to distinguish between cars. However, these methods do not select local features; that is, they do not assign weights to local features. Therefore, in this research, we systematically study the vehicle matching task, and present a novel annotation‐free local‐based deep learning method called Adaptive super‐pixel discriminative feature‐selective learning (ASDFL) to address this issue. In ASDFL, vehicle images are segmented into clusters of super‐pixels of similar size by considering the location and colour similarities of pixels without using any component‐level annotation. These super‐pixels are deemed to be the virtual components of vehicles. Moreover, a convolutional neural network is used to extract the deep features of these virtual components. Thereafter, an instance‐specific mask generation module driven by the extracted global features is enhanced to produce a mask to select the most distinctive virtual components of each vehicle image pair in the feature space. Finally, the vehicle matching task is accomplished by classifying the selected virtual component features of each imaged vehicle pair. Extensive experiments on two popular vehicle identification benchmarks demonstrate that our method is 1.57% and 0.8% more accurate than the previous baselines in a vehicle matching task on the VeRi and VehicleID datasets, respectively, which demonstrates the effectiveness of our method.

Qin, Rong↗
NASA NTRS1993

Learning fuzzy information in a hybrid connectionist, symbolic model

An instance-based learning system is presented. SC-net is a fuzzy hybrid connectionist, symbolic learning system. It remembers some examples and makes groups of examples into exemplars. All real-valued attributes are represented as fuzzy sets. The network representation and learning method is described. To illustrate this approach to learning in fuzzy domains, an example of segmenting magnetic resonance images of the brain is discussed. Clearly, the boundaries between human tissues are ill-defined or fuzzy. Example fuzzy rules for recognition are generated. Segmentations are presented that provide results that radiologists find useful.

Romaniuk, Steve G.↗
NASA NTRS1999

An Evaluation of the Quality of Halogen Occultation Experiment Ozone Profiles in the Lower Stratosphere

The archived ozone profiles from the Halogen Occultation Experiment (HALOE) have already been corrected for the effects of the spectrally varying, interfering absorption due to aerosols composed of aqueous sulfuric acid, and agreement with correlative measurements in the stratosphere is generally excellent. However, comparisons of sets of coincident HALOE and ozonesonde profiles indicate occasional large differences at the lowest levels of the stratosphere. Most of those instances occur at altitudes just below a well-defined minimum in the 5.26 microns channel aerosol extinction profile, whose wavelength dependence is not represented by a sulfuric acid aerosol model. Further, when the aerosol extinction exceeds about 10(exp 3)/ km, the aerosol correction to the ozone channel transmittances is both large and uncertain. After screening out the HALOE ozone profile segments whose corresponding aerosol/cirrus corrections are likely uncertain and after averaging lie ozonesonde profiles into 2.5 km thick layers, we find that the HALOE ozone areas, on average, to within 10% of their coincident ozonesonde measurements down to 100 hPa at tropical/subtropical latitudes and to 200 hPa at extratropical latitudes. A tightening of the coincidence criteria for the comparisons does not improve the mean differences for the sets nearly as much. Part of the variance of the paired differences was also accounted for when the ozonesonde profile values were integrated into those 2.5 km layers, prior to taking differences. This improvement is due mainly to the vertical averaging of the local, higher-resolution ozonesonde data, matching the lower resolution for HALOE ozone in the lower stratosphere. It is concluded that HALOE is providing accurate ozone profiles throughout the lower stratosphere, when its correction for interfering aerosols has been well characterized and when cirrus layers are not indicated.

Bhatt, Praful P.↗
NASA NTRS2010

NASA Tech Briefs, November 2010

Topics covered include: Portable Handheld Optical Window Inspection Device; Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction; Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems ; Predicting Long-Range Traversability from Short-Range Stereo-Derived Geometry; Browser-Based Application for Telemetry Monitoring of Robotic Assets; Miniature Low-Noise G-Band I-Q Receiver; Methods of Using a Magnetic Field Response Sensor Within Closed, Electrically Conductive Containers; Differential Resonant Ring YIG Tuned Oscillator; Microfabricated Segmented-Involute-Foil Regenerator for Stirling Engines; Reducing Seal Adhesion in Low Impact Docking Systems; Optimal Flow Control Design; Corrosion-Resistant Container for Molten-Material Processing; Reusable Hot-Wire Cable Cutter; Deployment of a Curved Truss; High-Volume Airborne Fluids Handling Technologies to Fight Wildfires; Modeling of Alkane Oxidation Using Constituents and Species; Fabrication of Lanthanum Telluride 14-1-11 Zintl High-Temperature Thermoelectric Couple; A Computer Model for Analyzing Volatile Removal Assembly; Analysis of Nozzle Jet Plume Effects on Sonic Boom Signature; Optical Sidebands Multiplier; Single Spatial-Mode Room-Temperature-Operated 3.0 to 3.4 micrometer Diode Lasers; Self-Nulling Beam Combiner Using No External Phase Inverter; Portable Dew Point Mass Spectrometry System for Real-Time Gas and Moisture Analysis; Maximum Likelihood Time-of-Arrival Estimation of Optical Pulses via Photon-Counting Photodetectors; Handheld White Light Interferometer for Measuring Defect Depth in Windows; Decomposition Algorithm for Global Reachability on a Time-Varying Graph; Autonomous GN and C for Spacecraft Exploration of Comets and Asteroids; Efficient Web Services Policy Combination; Using CTX Image Features to Predict HiRISE-Equivalent Rock Density; Isolation of the Paenibacillus phoenicis, a Spore-Forming Bacterium; Monolithically Integrated, Mechanically Resilient Carbon-Based Probes for Scanning Probe Microscopy; Cell Radiation Experiment System; Process to Produce Iron Nanoparticle Lunar Dust Simulant Composite; Inversion Method for Early Detection of ARES-1 Case Breach Failure; Use of ILTV Control Laws for LaNCETS Flight Research;and Evaluating Descent and Ascent Trajectories Near Non-Spherical Bodies.

Source record↗
DOE OSTI2020

Video Summarization Using Deep Action Recognition Features and Robust Principal Components Analysis

In an instance where desired pre-defined actions, behaviors, or other categories are known a priori, various video classification and recognition models can be trained to discover those classifications and their location within the video. Absent that information, one might still be tasked with identifying interesting portions within a video, a process which—if done manually—is onerous and time-consuming as it requires manual inspection of the video itself. Recognizing high-level interesting segments within a whole video has been a general area of interest due to the ubiquity of video data. However the size of the data makes storage, retrieval, and inspection of large collections of videos cumbersome. This problem motivates the task of generating shortened clips highlighting the primary content of a video, relieving the burden of having to watch the entire video. This paper presents an unsupervised method of creating shortened clips of videos, enabling the rapid review of the most interesting content within a video. Our method uses features extracted from pre-trained action recognition models as input to online moving window robust principal component analysis to generate summaries. The procedure is tested on a publicly available video summarization dataset and demonstrates comparable performance to state-of-the-art in an un-augmented setting while requiring no training.

Claborne, Daniel M.↗
NASA NTRS2008

International Space Station United States Orbital Segment Oxygen Generation System On-Orbit Operational Experience

The International Space Station (ISS) United States Orbital Segment (USOS) Oxygen Generation System (OGS) was originally intended to be installed in ISS Node 3. The OGS rack delivery was accelerated, and it was launched to ISS in July of 2006 and installed in the US Laboratory Module. Various modification kits were installed to provide its interfaces, and the OGS was first activated in July of 2007 for 15 hours, In October of 2007 it was again activated for 76 hours with varied production rates and day/night cycling. Operational time in each instance was limited by the quantity of feedwater in a Payload Water Reservoir (PWR) bag. Feedwater will be provided by PWR bag until the USOS Water Recovery System (WRS) is delivered to SS in fall of 2008. This paper will discuss operating experience and characteristics of the OGS, as well as operational issues and their resolution.

Erickson, Robert J.↗
DOE OSTI2024

Beyond Binary: Automated PLC Memory Forensics through RGB Image Analysis and Deep Learning

The introduction of Industry 4.0 and the evolution of industrial control systems (ICS) to adopt Internet-based technologies enhanced productivity, but have inadvertently increased their vulnerability to cyber-based malicious attacks. When an ICS system is compromised, security analysts need to identify the root cause quickly to start the recovery process and develop mitigation strategies to safeguard against future instances. Memory forensics is critical in the analysis process to ascertain what occurred. To date, approaches to analyze the persistent memory in ICS devices are limited, and almost nonexistent for volatile memory. This paper proposes an automated methodology, COMA, for PLC memory dump analysis using computer vision and deep learning techniques. Specifically, COMA converts the sequences of bytes in a PLC memory dump to RGB pixels and creates a deep learning model that learns the underlying patterns and features of pre-labeled forensic artifacts in images and segments them into distinct regions. COMA then uses the trained model to automatically segment new memory images and extract forensic artifacts. We evaluate COMA on a Schneider Electric Modicon M221 PLC involving two cyber-based attack scenarios: (i) code injection and (ii) code modification. The empirical results show that COMA can successfully detect attack artifacts in memory dumps in both scenarios.

Asmar Awad, Rima↗
NASA NTRS2010

International Space Station Common Cabin Air Assembly Condensing Heat Exchanger Hydrophilic Coating Failures and Lessons Learned

The ability to control the temperature and humidity of an environment or habitat is critical for human survival. These factors are important to maintaining human health and comfort, as well as maintaining mechanical and electrical equipment in good working order to support the human and to accomplish mission objectives. The temperature and humidity of the International Space Station (ISS) United States On-orbit Segment (USOS) cabin air is controlled by the Common Cabin Air Assembly (CCAA). The CCAA consists of a fan, a condensing heat exchanger (CHX), an air/water separator, temperature and liquid sensors, and electrical controlling hardware and software. The CHX is the primary component responsible for control of temperature and humidity. The CCAA CHX contains a chemical coating that was developed to be hydrophilic and thus attract water from the humid influent air. This attraction forms the basis for water removal and therefore cabin humidity control. However, there have been several instances of CHX coatings becoming hydrophobic and repelling water. When this behavior is observed in an operational CHX, the unit s ability to remove moisture from the air is compromised and the result is liquid water carryover into downstream ducting and systems. This water carryover can have detrimental effects on the cabin atmosphere quality and on the health of downstream hardware. If the water carryover is severe and widespread, this behavior can result in an inability to maintain humidity levels in the USOS. This paper will describe the operation of the five CCAAs within in the USOS, the potential causes of the hydrophobic condition, and the impacts of the resulting water carryover to downstream systems. It will describe the history of this behavior and the actual observed impacts to the ISS USOS. Information on mitigation steps to protect the health of future CHX hydrophilic coatings and potential remediation techniques will also be discussed.

Balistreri, Steven F.↗
DOE OSTI2024

Hyperspectral Detection of the Fluorescence Shift between Chirality-Sorted Empty and Water-Filled Single-Wall Carbon Nanotube Enantiomers

Single-wall carbon nanotubes (SWCNTs) have extraordinary electronic and optical properties that depend strongly on their exact chiral structure and their interaction with their inner and outer environment. The fluorescence (PL) of semiconducting SWCNTs, for instance, will shift depending on the molecules with which the SWCNT’s hollow core is filled. These interaction-induced shifts are challenging to resolve on the ensemble level in samples containing a mixture of different filling contents due to the relatively large inhomogeneous line width of the ensemble SWCNT PL compared to the size of these shifts. To circumvent this inhomogeneous broadening, single-tube spectroscopy and hyperspectral imaging are often applied, which until now required time-consuming statistical studies. Here, we present hyperspectral PL microscopy combined with automated SWCNT segmenting based on either principal component analysis or a convolutional neural network, capable of both spatially and spectrally resolving the PL along the length of many individual SWCNTs at the same time and automatically fitting peak positions and line widths of individual SWCNTs. The methodology is demonstrated by accurately determining the emission shifts and line widths of thousands of left- and right-handed empty and water-filled SWCNTs coated with a chiral surfactant, resulting in four statistical distributions which cannot be resolved in ensemble spectroscopy of unsorted samples. The results demonstrate a robust method to quickly probe ensemble properties with single-enantiomer spectral resolution. Moreover, it promises to be an absolute quantitative method to characterize the relative abundances of SWCNTs with different handedness or filling content in macroscopic samples, simply by counting individual species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Permeability Hysteresis From Microchannels Opening During Dissolution/Reprecipitation Cycle

Abstract Permeability is a critical parameter for geological resources characterization. Its evolution with respect to porosity is particularly interesting and many research initiatives focus on deriving such relationships, to understand some hydraulic impacts of microstructure alteration. Permeability evolution from chemical reactions, for instance, can become complex as flow channels may open during rock dissolution. In this contribution, we show that this phenomenon can lead to irregular porosity‐permeability curves and permeability hysteresis after reprecipitation. Current approaches describing permeability as a simple function of porosity can therefore not capture this behavior, and we advocate instead the use of dynamic modeling for such scenarios. We demonstrate our approach by modeling a dissolution/precipitation cycle for a unit cell pore channel and quantify the process at larger scale on three different rock samples, whose microstructures are reconstructed from segmented micro‐Computerised Tomography scans.

Lesueur, Martin↗