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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

A real time dashboard was developed in order to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users across a number of roles benefit from a real time system that enables common situational awareness. In addition to shared situational awareness the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial set of metrics computed on operational data. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017; Charlotte-Douglas International Airport. Analysis and metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of metrics across delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

integrated arrival departure surface operations↗
NASA NTRS2014

WetLab-2: Tools for Conducting On-Orbit Quantitative Real-Time Gene Expression Analysis on ISS

The objective of NASA Ames Research Centers WetLab-2 Project is to place on the ISS a research platform capable of conducting gene expression analysis via quantitative real-time PCR (qRT-PCR) of biological specimens sampled or cultured on orbit. The project has selected a Commercial-Off-The-Shelf (COTS) qRT-PCR system, the Cepheid SmartCycler and will fly it in its COTS configuration. The SmartCycler has a number of advantages including modular design (16 independent PCR modules), low power consumption, rapid ramp times and the ability to detect up to four separate fluorescent channels at one time enabling multiplex assays that can be used for normalization and to study multiple genes of interest in each module. The team is currently working with Cepheid to enable the downlink of data from the ISS to the ground and provide uplink capabilities for programming, commanding, monitoring, and instrument maintenance. The project has adapted commercial technology to design a module that can lyse cells and extract RNA of sufficient quality and quantity for use in qRT-PCR reactions while using a housekeeping gene to normalize RNA concentration and integrity. The WetLab-2 system is capable of processing multiple sample types ranging from microbial cultures to animal tissues dissected on-orbit. The ability to conduct qRT-PCR on-orbit eliminates the confounding effects on gene expression of reentry stresses and shock acting on live cells and organisms or the concern of RNA degradation of fixed samples. The system can be used to validate terrestrial analyses of samples returned from ISS by providing on-orbit gene expression benchmarking prior to sample return. The ability to get on orbit data will provide investigators with the opportunity to adjust experiment parameters for subsequent trials based on the real-time data analysis without need for sample return and re-flight. Researchers will also be able to sample multigenerational changes in organisms. Finally, the system can be used for analysis of air, surface, water, and clinical samples to monitor environmental contaminants and crew health. The verification flight of the instrument is scheduled to launch on SpaceX-7 in June 2015.

quantitative PCR↗
DOE OSTI2024

Real-time breath analysis towards a healthy human breath profile

Abstract The direct analysis of molecules contained within human breath has had significant implications for clinical and diagnostic applications in recent decades. However, attempts to compare one study to another or to reproduce previous work are hampered by: variability between sampling methodologies, human phenotypic variability, complex interactions between compounds within breath, and confounding signals from comorbidities. Towards this end, we have endeavored to create an averaged healthy human ‘profile’ against which follow-on studies might be compared. Through the use of direct secondary electrospray ionization combined with a high-resolution mass spectrometry and in-house bioinformatics pipeline, we seek to curate an average healthy human profile for breath and use this model to distinguish differences inter- and intra-day for human volunteers. Breath samples were significantly different in PERMANOVA analysis and ANOSIM analysis based on Time of Day, Participant ID, Date of Sample, Sex of Participant, and Age of Participant ( p < 0.001). Optimal binning analysis identify strong associations between specific features and variables. These include 227 breath features identified as unique identifiers for 28 of the 31 participants. Four signals were identified to be strongly associated with female participants and one with male participants. A total of 37 signals were identified to be strongly associated with the time-of-day samples were taken. Threshold indicator taxa analysis indicated a shift in significant breath features across the age gradient of participants with peak disruption of breath metabolites occurring at around age 32. Forty-eight features were identified after filtering from which a healthy human breath profile for all participants was created.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Toward an AI-Powered Software Pipeline for Real-Time Tracking and Analysis of Wildfire and Smoke

Real-time tracking of wildfires and smoke is crucial for effective response, minimizing damage, protecting lives, and efficiently managing resources during fire emergencies. We develop a web-based AI-powered pipeline that detects wildfires in aerial video and estimates deployment-relevant behavior metrics, including cumulative burned area, burned-area growth rate, fire spread direction, and smoke dispersion. The system combines a YOLO-based detector with YCbCr-based fire segmentation, HSV-based smoke segmentation, Farneback optical flow, and centroid-based spatiotemporal tracking. Using ground sampling distance (GSD), pixel-level fire masks are converted to physical burned-area measurements by correlating fire pixel counts with camera altitude and tilt angle. We benchmark YOLO variants and non-YOLO baselines (GoogLeNet, CNN, DBN, Autoencoder, U-Net, and AlexNet) on the IEEE FLAME dataset and a newly created aerial frame dataset, Wildfire-DB. Cross-dataset evaluation uses a strict threshold-transfer protocol: decision thresholds are selected on FLAME validation and transferred unchanged to Wildfire-DB to quantify generalization under domain shift. YOLOv6 achieves the strongest cross-dataset frame-level fire detection on Wildfire-DB (ROC-AUC 0.8200, PR-AUC 0.8044, and transferred-threshold F1 0.7596). For tracking-oriented deployment requiring oriented localization, YOLO11-OBB provides the most reliable cross-dataset behavior among OBB-capable models while remaining computationally feasible. To analyze the feasibility of UAV deployment, we further measure inference efficiency using synchronized GPU and CPU power logs on a fixed workload of 1569 frames. YOLO-family models process the video in 5.73–12.47 seconds with net energy of 1247.28–1775.39 J, substantially lower latency and energy than heavier classification and reconstruction baselines. Overall, model optimality depends on operational objectives: YOLOv6 is best for cross-dataset detection robustness, whereas YOL...

Color segmentation↗
DOE OSTI2020

Real-Time Acoustic Analysis of Batteries

The project explored development and commercialization of an acoustical approach to battery diagnostics. The technology has significant potential impacts for battery manufacturing and quality assurance, battery management during operation, and could be an enabler for the second-life battery market. Research was focused on inspecting and analyzing the physical condition of batteries using ultrasound. This consisted of designing and building hardware for gathering high-quality acoustic data, as well as using battery charge-discharge cyclers and temperature chambers to operate and age the batteries. Over the course of the 2-year program, we were able to build our first prototypes that are robust enough to be used by industry partners to evaluate our technology. Using the same prototypes, we also showed preliminary evidence that our acoustic inspection method may have distinct advantages over standard electrical methods in terms of detecting differences in the physical quality of battery cells. The project also expanded the participant’s core capabilities beyond time-of-flight acoustic measurements.

25 ENERGY STORAGE↗
NASA NTRS1991

Error analysis of real time and post processed or bit determination of GFO using GPS tracking

The goal of the Navy's GEOSAT Follow-On (GFO) mission is to map the topography of the world's oceans in both real time (operational) and post processed modes. Currently, the best candidate for supplying the required orbit accuracy is the Global Positioning System (GPS). The purpose of this fellowship was to determine the expected orbit accuracy for GFO in both the real time and post-processed modes when using GPS tracking. This report presents the work completed through the ending date of the fellowship.

Schreiner, William S.↗
NASA NTRS1989

Laser ranging data analysis

Results of the near real-time analysis of Lageos laser ranging data are reported. The data was analyzed in terms of range bias, time bias, and internal precision; and estimates for the Earth orientation parameters X sub p, Y sub p, and UT1 are obtained. The results of these analyses are reported in a variety of formats. Sample copies of the weekly summaries from the second half of 1988 are included along with an annotated distribution list of the weekly summaries. Annual summaries for 1987 and 1988 are also included.

Source record↗
NASA NTRS1990

Flight-measured streamwise disturbance instabilities in laminar flow

NASA is presently conducting laminar-flow flight research to explore the limits of practical applications of laminar-flow drag reduction technology. An important aspect of this research involves studies of the dominant instability or instabilities responsible for initiating the transition process from laminar to turbulent flow. Recent subsonic flight experiments using an instrumented wing glove on a Lear 28/29 airplane measured the growth of the two-dimensional, viscous Tollmien-Schlichting (T-S) instability. The gloved wing section incorporated closely-spaced, flush-mounted, streamwise-located instrumentation for measuring the instability frequencies, surface temperatures, and pressure distributions. Flight conditions of the experiment includeed Mach numbers from 0.70 to 0.79 and chord Reynolds numbers from 10 to 20 million. An onboard engineer's station allowed for real-time analysis of the instability frequency data. In addition to a sample of results on the streamwise growth of instabilities, details of the glove and sensor installation and the onboard real-time data analysis system are given.

Lee, Cynthia C.↗