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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Incorporating Edge Information into Best Merge Region-Growing Segmentation

We have previously developed a best merge region-growing approach that integrates nonadjacent region object aggregation with the neighboring region merge process usually employed in region growing segmentation approaches. This approach has been named HSeg, because it provides a hierarchical set of image segmentation results. Up to this point, HSeg considered only global region feature information in the region growing decision process. We present here three new versions of HSeg that include local edge information into the region growing decision process at different levels of rigor. We then compare the effectiveness and processing times of these new versions HSeg with each other and with the original version of HSeg.

Image segmentation↗
NASA NTRS2015

The Reusable Handheld Electrolyte and Lab Technology for Humans (rHEALTH) Sensor

The DNA Medicine Institute has produced a reusable microfluidic device that performs rapid, low-cost cell counts and measurements of electrolytes, proteins, and other biomarkers. The rHEALTH sensor is compact and portable, and it employs cutting-edge fluorescence detection optics, innovative microfluidics, and nanostrip reagents to perform a suite of hematology, chemistry, and biomarker assays from a single drop of blood. A handful of current portable POC devices provide generalized blood analysis, but they perform only a few tests at a time. These devices also rely on disposable components and depend on diverse detection technologies to complete routine tests-all ill-suited for space travelers on extended missions. In contrast, the rHEALTH sensor integrates sample introduction, processing, and detection with a compact, resource-conscious, and efficient design. Developed to monitor astronaut health on the International Space Station and during long-term space flight, this microscale lab analysis tool also has terrestrial applications that include POC diagnostics conducted at a patient's bedside, in a doctor's office, and in a hospital.

Chan, Eugene↗
NASA NTRS2022

Surface Corrected Lunar MTF Measurements in MODIS and VIIRS Using the SP Model

Lunar observations have been used for sensor performance assessments for a number of Earth-observing instruments, including the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) on board Suomi-NPP (SNPP) and NOAA-20 (N20). While the primary purpose of lunar observations in MODIS and VIIRS is radiometric calibration, these observations have been leveraged for other sensor performance assessments such as spatial registration and deriving the modulation transfer function (MTF). In this work, we will derive the lunar MTF using a knife edge approach similar to previous work. However, to further isolate the edge of the lunar disk when deriving the edge spread function (ESF), we will apply a lunar surface variation correction using a model based on data obtained by the Spectral Profiler (SP) on board the SELENE spacecraft. This model was provided to us by AIST in Japan. To align the measured and modeled data, we developed techniques for projecting the measured lunar surface pixels onto the radiance maps produced by the SP model. We correct the lunar surface variation while preserving the signal of the lunar disk edge in the ESF, and then calculate the MTF results using standard techniques. These results are in good agreement with previously published results from both Moon-based observations in MODIS and VIIRS and from the spectroradiometric calibration assembly (SRCA) on MODIS. With the exception of MODIS bands 1 and 2, the MTF is stable on orbit for the reflective bands in both instruments.

MODIS↗
NASA NTRS2024

BLAYER User Guide

Estimation of boundary layer edge or thickness is an essential aspect of utilizing high fidelity aerothermodynamic flow solutions. For viscous flow over a flat plate, the boundary layer thickness is usually defined as the distance from the wall at which the flow velocity (zero at the wall) has increased through some profile to 99% or 99.5% of the free stream velocity. In real gas flows over aerospace vehicles, a total enthalpy profile is employed for edge calculations. The importance of knowing boundary layer thickness and its relation to possible transition from laminar to turbulent flow is illustrated by Space Shuttle mission STS-114, when the appearance of tile gap filler protrusions on the nose was deemed serious enough that a crew member was called upon to exit the vehicle and remove the potential threat prior to its descent from orbit. The BLAYER utility used as part of post-processing Orion/MPCV flow solutions is a generalization of the earlier BLAYER_RESULTS utility developed following the STS-107 Columbia accident. BLAYER handles a variable number of gas species (not just 5), allows for more than one temperature and for optional extra flow quantities, and omits optional handling of Orbiter tile datasets.

momentum thicknes↗
DOE OSTI2025

Edge ML for CAN bus intrusion detection in AVs

Autonomous Vehicles (AVs) are revolutionizing transportation, but their reliance on interconnected cyber-physical systems exposes them to unprecedented cybersecurity risks. This study addresses the critical challenge of detecting real-time cyber intrusions in self-driving vehicles by leveraging a dataset from the Udacity self-driving car project. We simulate four high-impact attack vectors, Denial of Service (DoS), spoofing, replay, and fuzzy attacks, by injecting noise into spatial features (e.g., bounding box coordinates) to replicate adversarial scenarios. We develop and evaluate two lightweight neural network architectures (NN-1 and NN-2) alongside a logistic regression baseline (LG-1) for intrusion detection. The models achieve exceptional performance, with NN-2 attaining an AUC score of 93.15% and 93.15% accuracy, demonstrating their suitability for edge deployment in AV environments. Through explainable AI techniques, we uncover unique forensic fingerprints of each attack type, such as spatial corruption in fuzzy attacks and temporal anomalies in replay attacks, offering actionable insights for feature engineering and proactive defense. Visual analytics, including confusion matrices, ROC curves, and feature importance plots, validate the models' robustness and interpretability. This research sets a new benchmark for AV cybersecurity, delivering a scalable, field-ready toolkit for Original Equipment Manufacturers (OEMs) and policymakers. By aligning intrusion fingerprints with SAE J3061 automotive security standards, we provide a pathway for integrating machine learning into safety-critical AV systems. Our findings underscore the urgent need for security-by-design AI, ensuring that AVs not only drive autonomously but also defend autonomously. This work bridges the gap between theoretical cybersecurity and life-preserving engineering, offering a leap toward safer, more secure autonomous transportation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Data Security Defense: Modeling and Detection of Synchrophasor Data Spoofing Attack for Grid Edge

Data security and cyberattack have become critical issues in the distributed power system where adversaries can swap the source information of sensors or even spoof and alter measurements. However, the cyber security of the power system is challenged by the unpredictability and stealth of the spoofing attacks. Here, to protect the data security at the grid edge, this paper developed a synchrophasor data spoofing attack detection framework based on the time-frequency feature extraction techniques including the short-time Fourier transform (STFT) and object detection network for real-time synchrophasor data categorization and spoofing attack localization. The proposed approach outperforms earlier work in terms of spoofing attack detection and offers a vital localization function employing distributed synchrophasor sensors.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1974

Detection of radon emission at the edges of lunar maria with the Apollo alpha-particle spectrometer

The distribution of radioactive polonium-210, a decay product of radon-222, shows enhanced concentrations at the edges of lunar maria. Enhancements are seen at the edges of Mare Fecunditatis, Mare Crisium, Mare Smythii, Mare Tranquillitatis, Mare Nubium, Mare Cognitum, and Oceanus Procellarum. The observation is indicative of the transient emission of radon gas from the perimeters of lunar maria.

Gorenstein, P.↗
NASA NTRS1991

Infrared lidar windshear detection for commercial aircraft and the edge technique, a new method for atmospheric wind measurement

The edge technique, a new method for measuring small frequency shifts, is described. The technique allows high-accuracy measurement of atmospheric winds (0.2-1 m/s) with a high vertical resolution (10 m) using currently available technology. With the edge technique, a lidar system can be used to obtain range resolved measurements of the wind in the atmosphere from the ground, aircraft, or spaceborne platforms. The edge technique can be used with different lasers over a broad range of wavelengths.

Targ, Russell↗
DOE OSTI2025

Edge AI-Enhanced Traffic Monitoring and Anomaly Detection Using Multimodal Large Language Models

This paper addresses the challenge of traffic monitoring and incident detection in remote areas, utilizing multimodal large language models (LLMs) deployed on edge AI devices. The key novelty of the LLM is to convert real-time video streams into descriptive texts, enabling low-bandwidth transmissions and reliable detection of anomalies and incidents in environments of intermittent connectivity. The model is developed based on fine-tuning open-source LLMs and extending it with multi-modal capabilities to analyze video frames. Our work also involves deploying this model on edge devices such as Nvidia IGX Orin and is planned to be tested in realistic environments in future work. The methodology includes data set curation, iterative model fine-tuning and compression, and hardware-based optimization. This approach aims to enhance traffic safety and response speed in remote areas, marking a significant advancement in the application of AI for traffic monitoring and safety management.

Peruski, Ryan [University of Tennessee, Knoxville ↗
NASA NTRS1974

Techniques for the processing of remotely sensed imagery

The following techniques are considered for classifying low resolution satellite imagery: (1) Gradient operations; (2) histogram methods; (3) gray level detection; (4) frequency domain operations; (5) Hadamard transform in digital image matching; and (6) edge and line detection schemes.

Deutsch, E. S.↗
NASA NTRS1993

Parallel algorithm for dominant points correspondences in robot binocular stereo vision

This paper presents an algorithm to find the correspondences of points representing dominant feature in robot stereo vision. The algorithm consists of two main steps: dominant point extraction and dominant point matching. In the feature extraction phase, the algorithm utilizes the widely used Moravec Interest Operator and two other operators: the Prewitt Operator and a new operator called Gradient Angle Variance Operator. The Interest Operator in the Moravec algorithm was used to exclude featureless areas and simple edges which are oriented in the vertical, horizontal, and two diagonals. It was incorrectly detecting points on edges which are not on the four main directions (vertical, horizontal, and two diagonals). The new algorithm uses the Prewitt operator to exclude featureless areas, so that the Interest Operator is applied only on the edges to exclude simple edges and to leave interesting points. This modification speeds-up the extraction process by approximately 5 times. The Gradient Angle Variance (GAV), an operator which calculates the variance of the gradient angle in a window around the point under concern, is then applied on the interesting points to exclude the redundant ones and leave the actual dominant ones. The matching phase is performed after the extraction of the dominant points in both stereo images. The matching starts with dominant points in the left image and does a local search, looking for corresponding dominant points in the right image. The search is geometrically constrained the epipolar line of the parallel-axes stereo geometry and the maximum disparity of the application environment. If one dominant point in the right image lies in the search areas, then it is the corresponding point of the reference dominant point in the left image. A parameter provided by the GAV is thresholded and used as a rough similarity measure to select the corresponding dominant point if there is more than one point the search area. The correlation is used as a final decision tool when there is still more than one point in the search area. If there is no dominant point in the search area of if the points in the search area are below a correlation threshold, then the dominant point in the reference image is occluded and can not be corresponded. The algorithm has been modeled, implemented and shown to be fast, robust and parallel. The parallelism is created from three main features: locality of the operators; a memory optimization scheme; and the ability to fully parallelize the extraction phase which is the most computational intensive task in the algorithm. The last feature is achieved by performing the extraction phase on the two images simultaneously.

Al-Tammami, A.↗
DOE OSTI2024

Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements

Abstract A real-time detection of the plasma confinement regime can enable new advanced plasma control capabilities for both the access to and sustainment of enhanced confinement regimes in fusion devices. For example, a real-time indication of the confinement regime can facilitate transition to the high-performing wide-pedestal (WP) quiescent H-mode, or avoid unwanted transitions to lower confinement regimes that may induce plasma termination. To demonstrate real-time confinement regime detection, we use the 2D beam emission spectroscopy (BES) diagnostic system to capture localized density fluctuations of long wavelength turbulent modes in the edge region at a 1 MHz sampling rate. BES data from 330 discharges in either L-mode, H-mode, quiescent H (QH)-mode, or WP QH-mode were collected from the DIII-D tokamak and curated to develop a high-quality database to train a deep-learning classification model for real-time confinement detection. We utilize the 6×8 spatial configuration with a time window of 1024 µ s and recast the input to obtain spectral-like features via fast Fourier transform preprocessing. We employ a shallow 3D convolutional neural network for the multivariate time-series classification task and utilize a softmax in the final dense layer to retrieve a probability distribution over the different confinement regimes. Our model classifies the global confinement state on 44 unseen test discharges with an average F 1 score of 0.94, using only ∼1 ms snippets of BES data at a time. This activity demonstrates the feasibility for real-time data analysis of fluctuation diagnostics in future devices such as ITER, where the need for reliable and advanced plasma control is urgent.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1989

The Lyman edge test of the quasar emission mechanism

The Lyman edge region in the spectra of 11 high-redshift quasars is studied using data designed to detect broadened Lyman edge absorption predicted by thermal models of the 'big blue bump' continuum component, especially thin accretion disks. Three objects have broadened, partial edges near the systemic redshifts, as expected for thermal models. In two cases, however, narrow Lyamn lines with the edge absorption, ruling out the disk interpretation. Thus, the data are negative for thermal models, at least for opaque thin accretion disks.

Antonucci, R. R. J.↗
NASA NTRS1992

Forward rotor vortex effects on counter rotating propeller noise

Three configurations of a model counter rotating propeller manipulate the blade tip flow by: placing the CRP at angle of attack, installing shrouds, and turning the upstream blades to provide forward sweep. Flow visualization and flow measurements with thermal anemometry show no evidence of a tip vortex; however, a leading edge vortex was detected on aft swept blades. The modifications served to alter the strength and/or path of the leading edge vortex. The vortical flow is eliminated by forward sweep on the upstream propeller blades. Far field acoustic data from each test indicate only small influences on the level and directivity of the BPFs. The interaction tone at the sum of the two BPF's was significantly altered in a consistent manner. As the vortex system varied, the interaction tone was affected: far field noise levels in the forward quandrant increased and the characteristic noise minimum near the plane of rotation became less pronounced and in some cases were eliminated. If the forward propeller leading edge vortex system does not impact the rear propeller in the standard manner, a net increase in the primary interaction tone occurs for the model tested. If the leading edge vortex is removed, the interaction tone increases.

Laur, Michele↗
DOE OSTI2022

Security Enhancement of Network Constraint Grid-Edge Energy Management System

Network constrained grid edge energy management system (EMS) provides economic solution for active and reactive power dispatch of distributed energy resources (DERs) at the grid edge level. Grid edge EMS ensures secure interconnection of a circuit segment to the distribution system by maintaining grid code requirements (e.g. IEEE 1547–2018). Grid edge EMS is dependent on communication to receive load measurement, which brings a risk of unobservable false data injection attacks (FDIAs). To mitigate the risk, this paper proposes a framework to enhance resilient operation of grid edge EMS by detecting the unobservable FDIAs on loads and replacing them with forecasted values. In this work, a two-step detection algorithm is proposed. In first step, conventional residual based algorithm is deployed. Autoencoder (AE) based data driven mechanism is included in second step to detect the presence of unobservable FDIAs. After ensuring the presence of FDIA, its specific location is detected by checking the maximum residue values till the predefined threshold value is reached. Detected false data injected loads are then replaced with forecasted load values following long-short term memory (LSTM) based forecast to ensure resilient performance of grid edge EMS in the presence of attacks. This proposed security enhancement framework for grid edge EMS is evaluated in IEEE 13 bus system with three integrated DERs. Numerical simulation shows the validation of the proposed framework by reducing voltage violation in real operation of grid edge EMS.

cyber attack detection↗
NASA NTRS2002

Broadband Direct Detection Submillimeter Spectrometer with Multiplexed Superconducting Transition Edge Thermometer Bolometers

We present performance results based on the first astronomical use of multiplexed superconducting bolometers as direct detectors (i.e., with cold electrons) for spectroscopy. The Fabry-Perot Interferometer Bolometer Research Experiment (FIBRE) is a broadband submillimeter spectrometer for the Caltech Submillimeter Observatory (CSO). FIBRE's detectors are superconducting transition edge sensor (TES) bolometers read out by a SQUID multiplexer. The Fabry-Perot uses a low resolution grating to order sort the incoming light. A linear bolometer array consisting of 16 elements detects this dispersed light, capturing 5 orders simultaneously from one position on the sky. With tuning of the Fabry-Perot over one free spectral range, a spectrum covering Delta lambda/lambda = 1/7 at a resolution of delta lambda/lambda = 1/1200 can be acquired. This spectral resolution is sufficient to resolve Doppler-broadened line emission from external galaxies. FIBRE has been operated in the 350 Am (850 GHz) band. These bands cover line emission from the important star formation tracers neutral carbon [CI] and carbon monoxide (CO).

Benford, D. J.↗