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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Fiber Optic Sensor Components and Systems for Smart Materials and Structures

The general objective of the funded research effort has been the development of discrete and distributed fiber sensors and fiber optic centered opto-electronic networks for the intelligent monitoring of phenomena in various aerospace structures related to NASA Marshall specific applications. In particular, we have proposed and have been developing technologies that we believe to be readily transferrable and which involve new fabrication techniques. The associated sensors developed can be incorporated into the matrix or on the surfaces of structures for the purpose of sensing stress, strain, temperature-both low and high, pressure field variations, phase changes, and the presence of various chemical constituents.

Lyons, R.↗
DOE OSTI2023

A Photovoltaic MPPT Charge Controller Real-Time Testbed for Cybersecurity Applications

The increasing deployment of distributed energy resources (DER) over the last decade is a great ally to combat climate change and strengthen the grid during increasingly common extreme weather events. However, DER systems, combined with the ongoing transition to a digital power grid, also pose substantial cybersecurity threats. One of the most common communication protocols used in DER integration is the Distributed Network Protocol 3 (DNP3), which is known to have many security vulnerabilities. Thus, it is essential to investigate cyberattack behaviors and mitigation on power systems using DNP3. In this paper, we designed and implemented a cybersecurity testbed for a simulated photovoltaic (PV) maximum power point tracking (MPPT) charge controller. Our testbed uses an MPPT charge controller simulated on a Typhoon HIL602+ real-time simulator with a real DNP3 communication connection over TCP/IP, allowing for safe and efficient monitoring and manipulation of data traffic between the simulated hardware and supervisory control and data acquisition (SCADA) systems.

14 SOLAR ENERGY↗
NASA NTRS1995

An investigation of theories of failure for ceramic matrix composites

This final report is comprised of the abstract of a masters thesis research grant. The abstract of the thesis, 'An Investigation of Acoustic Emission Techniques for the Discrimination of Damage Mechanisms in Ceramic Matrix Composites', is as follows: In order to further advance the understanding of the mechanical behavior of ceramic matrix composites (CMS's), acoustic emission (AE) techniques were implemented to monitor and identify damage mechanisms in CMC's under tensile loading. In addition to real-time AE monitoring techniques, a data acquisition system was developed and implemented in order to capture AE waveforms resulting from stress-induced damage. Waveforms were inspected for multiple events, separated in distinct events, and then analyzed to determine waveform characteristics in the time and frequency domains. Waveform characteristics included peak amplitude, event duration, MARSE, energy, and dominant and centroidal frequency. In addition to conventional methods for determining a damage discrimination criteria, a study of the distribution and correlation of the waveform characteristics criteria and a study of the distribution and correlation of the waveform characteristics were performed to aid in the determination of a damage discrimination criteria. The damage discrimination criteria was tested for 'uniqueness', i.e., the effectiveness of the criteria to identify and monitor damage independent of the stress-strain relationship. Insitu radiography was used to substantiate the damage accumulation. A simulation test was also performed over the loading history to study the changes in the waveform characteristics of the system response from a constant excitation. This thesis demonstrates the use of waveform analysis to study the AE activity resulting from stress-induced damage in CMC's in conjunction with other nondestructive evaluation techniques to investigate the mechanical behavior of CMC's.

Hemann, John H.↗
NASA NTRS2021

Chapter 6: Fundamental Satellite Precipitation Data Records

The observation and measurement of precipitation across a range of temporal and spatial scales is of great importance for many user requirements and applications. Precipitation is a key component of the global energy and water cycle moving water, and its’ associated energy, through the Earth system at relatively fine spatial and temporal scales. At the societal level, precipitation provides fresh water and moderates our climate, but can also be destructive through storms, droughts and spreading diseases. Monitoring and measuring the distribution and quantities of precipitation, across the Earth’s surface is therefore crucial to physical and social applications, together with changes in precipitation over time. While conventional surface instruments provide a reasonably long record, these tend to be confined to well populated land surface areas: most ocean regions and sparsely populated regions have few measurements. Satellite-based precipitation products can provide global measurements, although the timespan of such products is limited and the data record is comprised of different instruments that operate over different periods of record. The challenge of any climate record is to provide a consistent product over the full period of record. Many satellite precipitation products incorporate ancillary data, such as surface gauge data or model data, which may limit their utility in the validation or verification of other climate data records. This chapter provides a review of the importance of precipitation to the climate system, the basis of satellite precipitation retrievals, climate data records of satellite data for precipitation retrievals and the development of fundamental precipitation data records for climate applications.

Climate data record↗
DOE OSTI2021

Aerosol Chemical Speciation Monitor (ACSM) Composition-Dependent Collection Efficiency (CDCE) Value-Added Product Report

Aerosol particles influence the Earth’s radiation balance directly by absorbing and scattering light and indirectly by influencing cloud formation, properties, and lifetimes. Measurements of aerosol particle optical properties, mass loading, size distributions, microphysical properties, cloud formation properties, and chemical composition are important for understanding the aerosol life cycle and for validating earth system models that predict these quantities. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Aerosol Observing System (AOS) is a highly instrumented platform that measures many of these aerosol properties in situ. The Aerodyne aerosol chemical speciation monitor (ACSM) is a baseline instrument deployed in the AOS. The ACSM provides a quantitative measurement of aerosol particle chemical composition for non-refractory (operationally defined as components that evaporate on the 600ºC vaporizer) aerosol components in real time. Standard output is the mass concentration of particulate organics, nitrate, sulfate, chloride, and ammonium. One well-known limitation to the accuracy of the ACSM data is in evaluating the fraction of the ambient aerosol particles that are detected by the instrument. This quantity is referred to as the collection efficiency (CE) and is often less than unity. This is attributed to particles rebounding after impaction onto the heated vaporizer rather than being trapped, volatilized rapidly, and detected. Other factors, such as divergence of the aerosol particle beam, may also impact CE, but the particle rebound effect is the dominant factor. Scientists will sometimes assume CE = 0.5 (i.e., one half of sampled particles are detected) for ambient particles collected during field missions. However, parameterizations have been developed that express CE as a function of the measured chemical composition, referred to as the composition-dependent collection efficiency (CDCE). The physical explanation for a CDCE, supported by laboratory studies, is that rebound from the vaporizer is a function of the particle phase, with liquid-like particles “sticking” to the vaporizer and solid-like or crystalline particles “bouncing” from the vaporizer. Thus, particles with compositions are liquids-like under the measurement conditions (e.g., certain organics, acidic particles, particles enriched in nitrate) have CE close to unity while crystalline or solid particles (e.g., deliquesced ammonium sulfate) have lower CE. This value-added product (VAP) implements the procedure described by Middlebrook et al. (2012) to correct the ACSM data for the composition-dependent collection efficiency. Applying this parameterization improves the accuracy of the ACSM data and brings them into better agreement with other co-located aerosol measurements.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Three-Axis Distributed Fiber Optic Strain Measurement in 3D Woven Composite Structures

Recent advancements in composite materials technologies have broken further from traditional designs and require advanced instrumentation and analysis capabilities. Success or failure is highly dependent on design analysis and manufacturing processes. By monitoring smart structures throughout manufacturing and service life, residual and operational stresses can be assessed and structural integrity maintained. Composite smart structures can be manufactured by integrating fiber optic sensors into existing composite materials processes such as ply layup, filament winding and three-dimensional weaving. In this work optical fiber was integrated into 3D woven composite parts at a commercial woven products manufacturing facility. The fiber was then used to monitor the structures during a VARTM manufacturing process, and subsequent static and dynamic testing. Low cost telecommunications-grade optical fiber acts as the sensor using a high resolution commercial Optical Frequency Domain Reflectometer (OFDR) system providing distributed strain measurement at spatial resolutions as low as 2mm. Strain measurements using the optical fiber sensors are correlated to resistive strain gage measurements during static structural loading. Keywords: fiber optic, distributed strain sensing, Rayleigh scatter, optical frequency domain reflectometry

Castellucci, Matt↗
NASA NTRSDate not supplied

Snow Depth from AMSR-2 Using Multispectral Satellite Data in an Artificial Neural Network

By using diffusion theory and Monte Carlo lidar radiative transfer simulations, Hu et al. (2022b) has derived snow depth from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. Lu et al. (2022) calculated the snow depth by applying the methods to the satellite ICESat-2 lidar measurements over the Arctic sea ice, as well as land surfaces of Northern Hemisphere. In this paper, an artificial neural network (ANN) algorithm, employing several channels from Advanced Microwave Scanning Radiometer 2 (AMSR-2) and the humidity vertical profiles from Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System for Instrument Teams (GEOS-IT) product, is trained to determine snow depth identified by time and geolocation matched 2019 ICESat-2 snow-depth data during winter months over the Arctic sea ice. The trained ANN snow-depth was applied to 2018 AMSR-2 clear pixel data, although the algorithms perform reasonably well in thinner clouds. The validation data (different from the training set) of ANN snow depth from AMSR-2 showed a good agreement with time matched and co-located snow-depth values from ICESat-2. The bias was near zero, with mean absolute error (MAE) 0.05 cm and a root-mean-square-error (RMSE) 0.08 cm. Prior applying the trained ANN snow depth to AMSR-2 data, a cloud screening algorithm was developed with a similar approach. A separate ANN cloud mask was trained to determine an AMSR-2 pixel is clear or cloudy with time and geolocation matched 2015 CALIOP Vertical Feature Mask (VFM) over Arctic sea ice. The ANN cloud mask from AMSR-2 under-estimated cloud fraction by 3-6% compared to CALIOP . The additional research is needed to conclusively evaluate the ANN cloud mask accuracy. Finally, this paper will lay the foundation for a sustained long-term snowfall and snow-storm monitoring system. The future Cloud Aerosol LIdar for Global scale Observations of the ocean-Land Atmosphere system (CALIGOLA) mission will provide a means to calculate snow depth from the lidar backscattering pathlength distribution, benefiting from the UV, visible and infrared pulses. With the calculated snow depth as the truth one could develop a machine learning algorithm, as it was done in this paper, using a passive microwave instrument available at that time to generate a wide range of snow depth data, covering extensive spatial areas in the cross-orbit direction.

Neural Network↗
DOE OSTI2023

Data-driven quantum approximate optimization algorithm for power systems

Abstract Quantum technology provides a ground-breaking methodology to tackle challenging computational issues in power systems. It is especially promising for Distributed Energy Resources (DERs) dominant systems that have been widely developed to promote energy sustainability. In those systems, knowing the maximum sections of power and data delivery is essential for monitoring, operation, and control. However, high computational effort is required. By leveraging quantum resources, Quantum Approximate Optimization Algorithm (QAOA) provides a means to search for these sections efficiently. However, QAOA performance relies heavily on critical parameters, especially for weighted graphs. Here we present a data-driven QAOA, which transfers quasi-optimal parameters between weighted graphs based on the normalized graph density. We verify the strategy with 39,774 expectation value calculations. Without parameter optimization, our data-driven QAOA is comparable with the Goemans-Williamson algorithm. This work advances QAOA and pilots its practical application to power systems in noisy intermediate-scale quantum devices.

Jing, Hang (ORCID:0000000256343489)↗
NASA NTRS1974

Natural resource inventories and management applications in the Great Basin

ERTS-1 resolution capabilities and repetitive coverage have allowed the acquisition of several statewide inventories of natural resource features not previously completed or that could not be completed in any other way. Familiarity with landform, tone, pattern and other converging factors, along with multidate imagery, has been required. Nevada's vegetation has been mapped from ERTS-1. Dynamic characteristics of the landscape have been studied. Sequential ERTS-1 imagery has proved its usefulness for mapping vegetation, following vegetation phenology changes, monitoring changes in lakes and reservoirs (including water quality), determining changes in surface mining use, making fire fuel estimates and determining potential hazard, mapping the distribution of rain and snow events, making range readiness determinations, monitoring marshland management practices and other uses. Feasibility has been determined, but details of incorporating the data in management systems awaits further research and development. The need is to accurately define the steps necessary to extract required or usable information from ERTS imagery and fit it into on-going management programs.

Tueller, P. T.↗
NASA NTRS1990

NASA ground terminal communication equipment automated fault isolation expert systems

The prototype expert systems are described that diagnose the Distribution and Switching System I and II (DSS1 and DSS2), Statistical Multiplexers (SM), and Multiplexer and Demultiplexer systems (MDM) at the NASA Ground Terminal (NGT). A system level fault isolation expert system monitors the activities of a selected data stream, verifies that the fault exists in the NGT and identifies the faulty equipment. Equipment level fault isolation expert systems are invoked to isolate the fault to a Line Replaceable Unit (LRU) level. Input and sometimes output data stream activities for the equipment are available. The system level fault isolation expert system compares the equipment input and output status for a data stream and performs loopback tests (if necessary) to isolate the faulty equipment. The equipment level fault isolation system utilizes the process of elimination and/or the maintenance personnel's fault isolation experience stored in its knowledge base. The DSS1, DSS2 and SM fault isolation systems, using the knowledge of the current equipment configuration and the equipment circuitry issues a set of test connections according to the predefined rules. The faulty component or board can be identified by the expert system by analyzing the test results. The MDM fault isolation system correlates the failure symptoms with the faulty component based on maintenance personnel experience. The faulty component can be determined by knowing the failure symptoms. The DSS1, DSS2, SM, and MDM equipment simulators are implemented in PASCAL. The DSS1 fault isolation expert system was converted to C language from VP-Expert and integrated into the NGT automation software for offline switch diagnoses. Potentially, the NGT fault isolation algorithms can be used for the DSS1, SM, amd MDM located at Goddard Space Flight Center (GSFC).

Tang, Y. K.↗
NASA NTRS1990

River and lake ice conditions as determined from AIRSAR imagery

Synthetic aperture radar (SAR) imagery data can provide information on types and distribution of river and lake ice needed for studying river ice processes and dynamics, monitoring ice during winter navigation, and formulating ice control strategies. Visible and IR remote sensing systems cannot provide such data and present field methods are inadequate for characterizing ice conditions over long river reaches. Our ongoing analysis of JPL's AIRSAR imagery data and concurrent ground truth of ice conditions on the Tanana River and surrounding lakes near Fairbanks, Alaska, in March 1988, has resulted in several findings: hummocked ice covers and zones of variable ice surface roughness within them can be differentiated; C- and L-band data are more sensitive than P-band to the range of surface roughnesses encountered; smooth, level ice that is clear or contains small bubbles produces little backscatter; snow-covered river ice, whether rough or smooth, is distinguishable from snow-covered river sediments on exposed river beds and unvegetated bars; and open water leads are readily distinguished.

Melloh, Rae A.↗
NASA NTRS1999

Control of Mixing and Reactive Flow Processes

The interdisciplinary field of reactive flow control is one that holds a great deal of promise for the optimization of complex phenomena occurring in many practical systems, ranging from automobile and gas turbine engines to environmental thermal destruction systems. The fundamental underpinnings of combustion control, however, require a detailed level of understanding of complex reactive flow phenomena, and, in the case of closed-loop active control, require the ability to sense (monitor) and actuate (manipulate) flow processes in a spatially distributed manner in "near real time". Hence the ultimate growth and success of the field of reactive flow control is intimately linked: 1) to advances in the understanding, simulation, and model reduction for complex reactive flows, 2) to the development of experimental diagnostic techniques, in particular, to the development of physically robust sensors, and 3) to the development of a framework or frameworks for generation of closed loop control algorithms suitable for unsteady, nonlinear reactive flow systems. The present paper seeks to outline the potential benefits and technical challenges that exist for mixing and combustion control in fundamental as well as practical systems and to identify promising research directions that could help meet these challenges.

Karagozian, A. R.↗
NASA NTRS2000

The Evolution of Tropical Precipitation Patterns During ENSO Events Using 21+ Years of GPCP Merged Data

The ENSO phenomenon is characterized by fluctuations in the climate system of the tropical Pacific. Quantifying changes in the precipitation component of this system is important in understanding the distribution of heating in the atmosphere which drives the large-scale circulation and affects the weather patterns in the mid-latitudes. Monitoring precipitation anomalies in the Pacific is also an important component for tracking the evolution of ENSO. The most timely and complete observations of the earth come from satellite instruments. In this study, the state of the art satellite-gauge merged monthly precipitation data set from the Global Precipitation Climatology Project (GPCP) is used to depict tropical rainfall patterns during ENSO events over the past two decades and quantify these patterns using indices. This analysis will be complemented by daily precipitation data which can resolve the Madden-Julian Oscillation and westerly wind burst events. The 1997-98 El Nino and 1998-2000 La Nina were the best observed ENSO cycle in the historic record. Prior to the El Nino (in terms of anomalous warming of the east Pacific) dry anomalies over the Maritime Continent were observed in February 1997 as a westerly wind burst advected convection to the east. The largest SST anomalies occurred around November-December 1997, which were followed by the largest precipitation anomalies in the beginning of 1998. The largest precipitation departures from normal were not colocated with the SST anomalies, but were further west, In the spring of 1998 negative precipitation anomalies to the north of the equator intensified, signaling the mature phase of the El Nino. A rapid increase in the precipitation-based La Nina index from December-January 1998 to March-April 1998 signaled the coming La Nina. The 1982-1983 El Nino was comparable in strength (according to several indices) and the precipitation patterns evolved in a similar fashion. For the 1998-2000 La Nina, the coldest anomalies, were confined to the central equatorial Pacific, while the driest anomalies were found in the west Pacific,

Curtis, Scott↗
DOE OSTI2021

(Poster) TRIPWIRE: Multi-modal Distributed Sensing For Repository Verification

Poster submission. This project is developing and demonstrating a multi-modal sensor system, TRIPWIRE, for containment verification in inaccessible radiological and nuclear waste repositories. The TRIPWIRE system will continuously monitor ionizing radiation, electromagnetic fields and vibration in the vicinity of emplaced nuclear materials buried in a repository, reporting on disturbances with a real-time alarm control station.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2022

Distributed Frequency Divider for Power System Bus Frequency Online Estimation Considering Virtual Inertia From DFIGs

In this work, a distributed frequency divider is proposed to estimate power system bus frequency with a limited number of PMUs while considering the inertial contributions from double-fed induction generators (DFIGs). The key idea is to reformulate the original frequency divider by modeling the contributions of DFIGs with inertia emulation and external regional power system through Thevenin equivalents. The distributed frequency divider is general and able to estimate local bus frequencies in a distributed manner. Besides, only the knowledge of the rotor speeds of synchronous generator, boundary bus frequencies and terminal bus frequencies of DFIGs as well as the admittance matrix are required to estimate the frequencies at all buses. This is drastically different from existing approaches that require system observability by PMUs to monitor all bus frequencies. Numerical results carried out on the IEEE 39-bus and modified 118-bus power systems with DFIGs demonstrate and effectiveness and robustness of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Time-Sensitive Quantum Key Distribution (TSQKD)

This is the final report for the Time-Sensitive Quantum Key Distribution (TSQKD) project and summarizes the demonstration and longer-term field testing at an electric utility, EPB of Chattanooga, in Chattanooga, TN. The demonstration was held virtually (due to the COVID pandemic) and successfully executed the tests outlined in a prior report, “Task 10: Develop a QKD Time-Sensitive Networking Test Suite” submitted 9/30/2020. The portable test equipment explained in Task 10 and earlier task reports was tested at GE Research remotely connected with Qubitekk’s QKD equipment in San Diego, CA. Then the equipment was shipped to Qubitekk for physical integration with Qubitekk’s Quantum DataLoc™ Key Server 1570nm (http://qubitekk.com/products/qkd-for-industrial-control-systems-ics/). The portable test equipment was shipped from Qubitekk to EPB for demonstration and extended field testing. A summary of the demonstration and test results are described in this report. The demo and extended field test results are enabled by the NETCONF/YANG IEEE P1913 data management model developed as part of this project (Task 5). The NETCONF/YANG IEEE P1913 data management model demonstrated significant practical utility in providing a common means of monitoring and configuring the QKD system. All data in this report comes from the IEEE P1913 data management model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Distributed Energy Resource Cybersecurity Framework and Cyber Range Integration

Distributed energy resource (DER) systems feature complex, data-driven communications networks that require careful system coordination and constant vigilance to ensure that grid assets are secure. Because DERs are an important component of the decarbonization strategy, agencies need to secure energy data that could implicate issues of national security if compromised. To help federal energy managers assess, monitor, and manage cybersecurity while achieving decarbonization, the National Renewable Energy Laboratory's (NREL's) Distributed Energy Resource Cybersecurity Framework (DER-CF) offers a comprehensive, web-based assessment tool focusing on cyber governance or policies, technical management, and physical security. The DER-CF currently presents users with a series of pertinent cybersecurity questions that are used to generate a site-specific report and recommendations. This paper outlines a plan to integrate the DER-CF with another key asset-NREL's cyber range-to visualize cybersecurity resilience and compliance and to enhance the usability and accessibility of the DER-CF for federal facility energy managers and planners. This integration will result in a visualization environment to interpret and interact with compliance data. Its development will include regular conversations with stakeholders to assess the effectiveness of these efforts, refine the visualization capability, and ensure its value to our partners.

24 POWER TRANSMISSION AND DISTRIBUTION↗