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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 NTRS2009

NASA Orbital Debris Engineering Model ORDEM2008 (Beta Version)

This is an interim document intended to accompany the beta-release of the ORDEM2008 model. As such it provides the user with a guide for its use, a list of its capabilities, a brief summary of model development, and appendices included to educate the user as to typical runtimes for different orbit configurations. More detailed documentation will be delivered with the final product. ORDEM2008 supersedes NASA's previous model - ORDEM2000. The availability of new sensor and in situ data, the re-analysis of older data, and the development of new analytical techniques, has enabled the construction of this more comprehensive and sophisticated model. Integrated with the software is an upgraded graphical user interface (GUI), which uses project-oriented organization and provides the user with graphical representations of numerous output data products. These range from the conventional average debris size vs. flux magnitude for chosen analysis orbits, to the more complex color-contoured two-dimensional (2-D) directional flux diagrams in terms of local spacecraft pitch and yaw.

Stansbery, Eugene G.↗
NASA NTRSDate not supplied

An Overview of Research in Nondestructive Evaluation at the National Aeronautics and Space Administration’s Langley Research Center

The primary focus of the nondestructive evaluation (NDE) effort at Langley Research Center (LaRC) is to pioneer advances in NDE and structural health monitoring (SHM) through fundamental scientific research, technology development, and transferring these to the scientific and aerospace communities. This research supports a variety of NASA missions in space operations, exploration and aeronautics. The work presented will focus on the development of advanced inspection systems to detect critical flaws in both metallic and non-metallic materials and structures for aerospace applications. The emphasis is on increasing the performance of inspection systems to provide defect detection and quantitative characterization of the material state. LaRC NDE utilizes expertise in computational ultrasonic, thermal and eddy current simulations to reduce measured responses to size and locations of flaws, establish technique limitations and optimize performance. This presentation will highlight research into five strategic areas: (1) The development of novel solutions using state-of-the-art NDE technologies such as eddy current, ultrasound, thermography and x-ray computed tomography; (2) Research in the development of unique NDE technologies such as terahertz, wavefield imaging and nonlinear ultrasound; (3) The application of both computational and analytic models to NDE problems; (4) The development of advanced analytic methods to interpret large complex data sets; and (5) Advanced methods of applying and interrogating sensors for structural health monitoring.

K Elliott Cramer↗
NASA NTRSDate not supplied

An Overview of Research in Nondestructive Evaluation at the National Aeronautics and Space Administration’s Langley Research Center

The primary focus of the nondestructive evaluation (NDE) effort at Langley Research Center (LaRC) is to pioneer advances in NDE and structural health monitoring (SHM) through fundamental scientific research, technology development, and transferring these to the scientific and aerospace communities. This research supports a variety of NASA missions in space operations, exploration and aeronautics. The work presented will focus on the development of advanced inspection systems to detect critical flaws in both metallic and non-metallic materials and structures for aerospace applications. The emphasis is on increasing the performance of inspection systems to provide defect detection and quantitative characterization of the material state. LaRC NDE utilizes expertise in computational ultrasonic, thermal and eddy current simulations to reduce measured responses to size and locations of flaws, establish technique limitations and optimize performance. This presentation will highlight research into five strategic areas: (1) The development of novel solutions using state-of-the-art NDE technologies such as eddy current, ultrasound, thermography and x-ray computed tomography; (2) Research in the development of unique NDE technologies such as terahertz, wavefield imaging and nonlinear ultrasound; (3) The application of both computational and analytic models to NDE problems; (4) The development of advanced analytic methods to interpret large complex data sets; and (5) Advanced methods of applying and interrogating sensors for structural health monitoring.

NDE↗
DOE OSTI2022

Energy Efficient Material Processing through Automated Process Monitoring and Controls

Smart manufacturing is bound to play a crucial role in reducing global energy consumption while accelerating economic development. This phenomenon is evident in advanced sensing technology developments, data analytics and machine learning/AI, automated controls, cloud computing, etc. The immediate opportunity for smart manufacturing is to improve the energy efficiency of manufacturing operations through innovations in processes and controls. The manufacturing industry still consumes about 30% of total global energy production, which is significant. This program focused on the recommendation of heterogeneous sensors to monitor the Chemical Vapor Infiltration (CVI) process parameters, states, and key performance indices and utilize cloud computing to sort and analyze the real-time data. Learning through data analytics helps guide the control parameters affecting energy usage. The target process in the program is the CVI process at the Honeywell South Bend facility, which is one of the most energy-intensive manufacturing industries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2019

Sensitivity of Inherent Optical Properties from Ocean Reflectance Inversion Models to Satellite Instrument Wavelength Suites

The Earth science community seeks to develop climate data records (CDRs) from satellite measurements of ocean color, a continuous data record that now exceeds 20 years. Space agencies will launch additional instruments in the coming decade that will continue this data record, including the NASA PACE spectrometer. Inherent optical properties (IOPs) quantitatively describe the absorbing and scattering constituents of seawater and can be estimated from satellite-observed spectroradiometric data using semi-analytical algorithms (SAAs). SAAs exploit the contrasting optical signatures of constituent matter at spectral bands observed by satellite sensors. SAA performance, therefore, depends on the spectral resolution of the satellite spectroradiometer. A CDR spanning SeaWiFS, MODIS, OLCI, and PACE, for example, would include IOPs derived using varied wavelength suites if all available wavelengths were considered. Here, we explored differences in derived IOPs that stem simply from the use of (eight) different wavelength suites of input radiometric measurements. Using synthesized data and SeaWiFS Level-3 mission-long composites, we demonstrated equivalent SAA performance for all wavelength suites, but that IOP retrievals vary by several percent across wavelength suites and as a function of water type. The differences equate to roughly ≤ 6, 12, and 7% for a(sub dg)(443), a(sub ph)(443), and b(sub bp)(443), respectively, for waters with C(sub a) ≤ 1 mg -cu m. These values shrink for sensors with similar wavelength suites (e.g., SeaWiFS, MODIS, and MERIS) and rise to substantially larger values for higher C(sub a) waters. Our results also indicate that including 400 nm (in the case of OLCI) influences the derived IOPs, using longer wavelengths (>600 nm) influences the derived IOPs when there is a red signal, and, including additional spectral information shows potential for improved IOP estimation, but not without revisiting SAA parameterizations and execution. While modest in scope, we believe this study contributes to the knowledge base for CDR development. The implication of ignoring such an analysis as CDRs continue to be developed is a prolonged inability to distinguish between algorithmic and environmental contributions to trends and anomalies in the IOP time-series.

ocean color satellites↗
NASA NTRS1992

Elemental analyses of hypervelocity micro-particle impact sites on interplanetary dust experiment sensor surfaces

The Interplanetary Dust Experiment (IDE) had over 450 electrically active ultra-high purity metal-oxide-silicon impact detectors located on the six primary sides of the Long Duration Exposure Facility (LDEF). Hypervelocity micro-particles that struck the active sensors with enough energy to breakdown the 0.4 to 1.0 micron thick SiO2 insulator layer separating the silicon base (the negative electrode), and the 1000 A thick surface layer of aluminum (the positive electrode) caused electrical discharges that were recorded for the first year of orbit. These discharge features, which include 50 micron diameter areas where the aluminum top layer has been vaporized, facilitate the location of the impacts. The high purity Al-SiO2-Si substrates allow detection of trace (ppm) amounts of hypervelocity impactor residues. After sputtering through a layer of surface contamination, secondary ion mass spectrometry (SIMS) is used to create two-dimensional elemental ion intensity maps of micro-particle impact sites on the IDE sensors. The element intensities in the central craters of the impacts are corrected for relative ion yields and instrumental conditions and then normalized to silicon. The results are used to classify the particles' origins as 'manmade', 'natural' or 'indeterminate'. The last classification results from the presence of too little impactor residue (a frequent occurrence on leading edge impacts), analytical interference from high background contamination, the lack of information on silicon residue, the limited usefulness of data on aluminum in the central craters, or a combination of these circumstances. Several analytical 'blank' discharges were induced on flight sensors by pressing down on the sensor surface with a pure silicon shard. Analyses of these blank discharges showed that the discharge energy blasts away the layer of surface contamination. Only Si and Al were detected inside the discharge zones, including the central craters, of these features. A total of 35 impacts on leading edge sensors and 22 impacts on trailing edge sensors were analyzed.

Simon, Charles G.↗
DOE OSTI2014

Semantic Interaction for Visual Analytics: Toward Coupling Cognition and Computation

The dissertation discussed in this article [1] was written in the midst of an era of digitization. The world is becoming increasingly instrumented with sensors, monitoring, and other methods for generating data describing social, physical, and natural phenomena. Thus, data exist with the potential of being analyzed to uncover, or discover, the phenomena from which it was created. However, as the analytic models leveraged to analyze these data continue to increase in complexity and computational capability, how can visualizations and user interaction methodologies adapt and evolve to continue to foster discovery and sensemaking?

semantic interaction↗
NASA NTRS1987

Heat flux calibration facility capable of SSME conditions

There is a need to more thoroughly characterize the hostile space shuttle main engine (SSME) turbopump environment. It has been estimated that component surface heat flux in the hot-gas environment is about 10 MW/square meter, and this is about 50 times that encountered in aircraft engines. Also, material temperature transients can be as high as 1000 K in about 1 second. These transients can cause durability problems such as material cracking. Heat flux sensors placed in the turbopump components can partially characterize this environment by measuring surface heat flux. These heat flux data can be used to verify analytical-stress, boundary-layer, and heat-transfer design models. Preliminary plans were discussed at the first SSME durablity conference for designing and fabricating a new facility for the calibration and durability testing of prototype heat flux sensors for the SSME. This facility, which is necessary for assessment of new heat flux gauge concepts needed in the hostile SSME turbopump environment, is described.

Liebert, Curt H.↗
DOE OSTI2013

On-Ramp Wireless: Program Final Report

The objective of the project was to develop and demonstrate a centrally managed, wide area wireless distribution grid sensor and faulted circuit indicator system capable of monitoring underground and other hard-to-reach distribution circuits while delivering the reliability, ease of installation, security, battery life and low cost structure required to be a commercially viable product for the electric utility industry. This integrated wireless grid monitoring system enables utilities across the United States to enhance the reliability of their distribution grids, improve performance metrics (i.e., SAIFI, CAIDI, SAIDI), support dynamic load management and predictive maintenance, and enable future remote monitoring applications necessary to achieve the goals of the Smart Grid. This project scope included: conceptual design; trade studies focused on maximizing ease of installation, sensing capabilities, power budget analysis to reduce maintenance costs and time to replace; sensor product development; and field technology demonstration. The trade studies included Radio Frequency (RF) propagation. The RF Trade Study was completed for the 2.4 GHz ISM-band and not extended to 1 GHz band due to availability of suitable radio solutions and associated impacts to overall commercial value of the solution. The technology demonstrations/field trials were performed in partnership with Southern California Edison and San Diego Gas and Electric. The sensing systems included fault indicator and wireless analog sensor devices from Schweitzer Engineering Labs (SEL) and smart transformer monitoring devices from Gridsense. Both SEL and Gridsense worked with ORW during this project to During the demonstration phase, sensors were deployed in multiple locations. Resulting data was analyzed for the following: RF performance, communication systems reliability, sensor system capabilities, and system level analytics relative to the commercial value to the smart grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Large-Scale Trajectory Analysis via Feature Vectors

The explosion of both sensors and GPS-enabled devices has resulted in position/time data being the next big frontier for data analytics. However, many of the problems associated with large numbers of trajectories do not necessarily have an analog with many of the historic big-data applications such as text and image analysis. Modern trajectory analytics exploits much of the cutting-edge research in machine-learning, statistics, computational geometry and other disciplines. We will show that for doing trajectory analytics at scale, it is necessary to fundamentally change the way the information is represented through a feature-vector approach. We then demonstrate the ability to solve large trajectory analytics problems using this representation.

58 GEOSCIENCES↗
DOE OSTI2023

Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing

Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station’s capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station’s use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station’s open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Investigation of new radar-data-reduction techniques used to determine drag characteristics of a free-flight vehicle

An investigation was conducted of new techniques used to determine the complete transonic drag characteristics of a series of free-flight drop-test models using principally radar tracking data. The full capabilities of the radar tracking and meteorological measurement systems were utilized. In addition, preflight trajectory design, exact kinematic equations, and visual-analytical filtering procedures were employed. The results of this study were compared with the results obtained from analysis of the onboard, accelerometer and pressure sensor data of the only drop-test model that was instrumented. The accelerometer-pressure drag curve was approximated by the radar-data drag curve. However, a small amplitude oscillation on the latter curve precluded a precise definition of its drag rise.

Woodbury, G. E.↗
NASA NTRS1975

Arizona land use experiment

Utilization of new sources of statewide remote sensing data, taken from high-altitude aircraft and from spacecraft is discussed along with incorporation of information extracted from these sources into on-going land and resources management programs in Arizona. Statewide cartographic applications of remote sensor data taken by NASA high-altitude aircraft include the development of a statewide semi-analytic control network, the production of nearly 1900 orthophotoquads (image maps) that are coincident in scale and area with the U.S. Geological Survey (USGS) 7. 5 minute topographic quadrangle map series, and satellite image maps of Arizona produced from LANDSAt multispectral scanner imagery. These cartographic products are utilized for a wide variety of experimental and operational earth resources applications. Applications of the imagery, image maps, and derived information discussed include: soils and geologic mapping projects, water resources investigations, land use inventories, environmental impact studies, highway route locations and mapping, vegetation cover mapping, wildlife habitat studies, power plant siting studies, statewide delineation of irrigation cropland, position determination of drilling sites, pictorial geographic bases for thematic mapping, and court exhibits.

Winikka, C. C.↗
NASA NTRS2015

Thermal Testing and Model Correlation of the Magnetospheric Multiscale (MMS) Observatories

International Conference on Envronmental Systems (ICES), Seattle WA NCTS 20964-15. The Magnetospheric Multiscale (MMS) mission is a Solar Terrestrial Probes mission comprising four identically instrumented spacecraft that will use Earths magnetosphere as a laboratory tostudy the microphysics of three fundamental plasma processes: magnetic reconnection, energetic particle acceleration, and turbulence. This paper presents the complete thermal balance (TB) test performed on the first of four observatories to go through thermal vacuum (TV) and the minibalance testing that was performed on the subsequent observatories to provide a comparison of all four. The TV and TB tests were conducted in a thermal vacuum chamber at the Naval Research Laboratory (NRL) in Washington, D.C. with the vacuum level higher than 1.3 x 10-4 Pa (10-6 torr)and the surrounding temperature achieving -180 C. Three TB test cases were performed that included hot operational science, cold operational science and a cold survival case. In addition to the three balance cases a two hour eclipse and a four hour eclipse simulation was performed during the TV test to provide additional transient data points that represent the orbit in eclipse (or Earth's shadow) The goal was to perform testing such that the flight orbital environments could be simulated as closely as possible. A thermal model correlation between the thermal analysis and the test results was completed. Over 400 1-Wire temperature sensors, 200 thermocouples and 125 flight thermistor temperature sensors recorded data during TV and TB testing. These temperatureversus time profiles and their agreements with the analytical results obtained using Thermal Desktop and SINDAFLUINT are discussed. The model correlation for the thermal mathematical model (TMM) is conducted based on the numerical analysis results and the test data. The philosophy of model correlation was to correlate the model to within 3 C of the test data using the standard deviation and mean deviation error calculation. Individual temperature error goal is to be within 5 C and the heater power goal is to be within 5 of test data. The results of the model correlation are discussed and the effect of some material and interface parameters on the temperature profiles are presented.

Thermal↗
DOE OSTI2014

PMU Data Integrity Evaluation through Analytics on a Virtual Test-Bed

Power systems are rapidly becoming populated by phasor measurement units (PMUs) in ever increasing numbers. PMUs are critical components of today s energy management systems, designed to enable near real-time wide area monitoring and control of the electric power system. They are able to measure highly accurate bus voltage phasors as well as branch current phasors incident to the buses at which PMUs are equipped. Synchrophasor data is used for applications varying from state estimation, islanding control, identifying outages, voltage stability detection and correction, disturbance recording, and others. However, PMU-measured readings may suffer from errors due to meter biases or drifts, incorrect configurations, or even cyber-attacks. Furthermore, the testing of early PMUs showed a large disparity between the reported values from PMUs provided by different manufacturers, particularly when frequency was off-nominal, during dynamic events, and when harmonic/inter-harmonic content was present. Detection and identification of PMU gross measurement errors are thus crucial in maintaining highly accurate phasor readings throughout the system. In this paper, we present our work in conducting analytics to determine the trustworthiness and worth of the PMU readings collected across an electric network system. By implementing the IEEE 118 bus test case on a virtual test bed (VTB) , we are able to emulate PMU readings (bus voltage and branch current phasors in addition to bus frequencies) under normal and abnormal conditions using (virtual) PMU sensors deployed across major substations in the network. We emulate a variety of failures such as bus, line, transformer, generator, and/or load failures. Data analytics on the voltage phase angles and frequencies collected from the PMUs show that specious (or compromised) PMU device(s) can be identified through abnormal behaviour by comparing the trend of its frequency and phase angle reading with the ensemble of all other PMU readings in the network. If the reading trend of a particular PMU deviates from the weighted average of the reading trends of other PMUs at nearby substations, then it is likely that the PMU is malfunctioning. We assign a weight to each PMU denoting how electric-topology-wise close it is from where the PMU under consideration is located. The closer a PMU is, the higher the weight it has. To compute the closeness between two nodes in the power network, we employ a form of the resistance distance metric. It computes the electrical distance by taking into consideration the underlying topology as well as the physical laws that govern the electrical connections or flows between the network components. The detection accuracy of erroneous PMUs should be improved by employing this metric. We present results to validate the proposed approach. We also discuss the effectiveness of using an end-to-end VTB approach that allows us to investigate different types of failures and their responses as seen by the ensemble of PMUs. The collected data on certain types of events may be amenable to certain types of analysis (e.g., alerting for sudden changes can be done on a small window of data) and hence determine the data analytics architectures is required to evaluate the streaming PMU data.

and data analytics architecture.↗
NASA NTRS1974

Analytical and experimental study of mean flow and turbulence characteristics inside the passages of an axial flow inducer

The effort conducted to gather additional understanding of the complex inviscid and viscid effects existing within the passages of a three-bladed axial flow inducer operating at a flow coefficient of 0.065 is summarized. The experimental investigations included determination of the blade static pressure and blade limiting streamline angle distributions, and measurement of the three components of mean velocity, turbulence intensities and turbulence stresses at locations inside the inducer blade passage utilizing a rotating three-sensor hotwire probe. Applicable equations were derived for the hotwire data reduction analysis and solved numerically to obtain the appropriate flow parameters. Analytical investigations were conducted to predict the three-dimensional inviscid flow in the inducer by numerically solving the exact equations of motion, and to approximately predict the three-dimensional viscid flow by incorporating the dominant viscous terms into the exact equations. The analytical results are compared with the experimental measurements and design values where appropriate.

Gorton, C. A.↗
NASA NTRS2005

Prospecting for In Situ Resources on the Moon and Mars Using Wheel-Based Sensors

The Apollo and Russian missions during 1970's were reviewed to rediscover the type and distribution of minerals on the Moon. This study revealed that the Moon is a relatively barren place in mineral content when compared with the Earth. Results from the Lunar minerals brought back to Earth, indicate that the Moon lacks water, hydroxyl ions, and carbon based minerals. Our approach to prospecting utilizes a vehicle with sensors embedded in a wheel that allow measurements while the vehicle is in motion. Once a change in soil composition is detected, decision making software stops the vehicle and analytical instruments perform a more definitive analysis of the soil. The focus of this paper is to describe the instrumentation and data from the wheel-based sensors.

moon↗