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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Optical Flow for Intermediate Frame Interpolation of Multispectral Geostationary Satellite Data

Applications in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on spatial and temporal resolutions of satellite observations. However, there are typically trade-offs between spatial and temporal resolutions in dataset selection. For instance, geostationary weather tracking satellites are designed to take snapshots many times throughout the day but sensor hardware limits data collection. In this work we tackle this limitation, developing a method for temporal upsampling of multi-spectral satellite imagery using optical flow video interpolation deep convolutional neural networks. The presented model, extends Super SloMo (SSM) from single optical flow estimates to multichannel where flows are computed per band. We apply this technique on 8 multi-spectral bands of NOAA/NASA's GOES-16 mesoscale dataset to temporally enhance full disk hemispheric snapshots from 15 minutes to 1 minute. Through extensive experimentation, we show SSM vastly outperforms the linear interpolation baseline and that multichannel optical flows improves performance on GOES-16. A visual analysis of optical flow vectors clearly identifies hurricanes and large-scale atmospheric dynamics. Furthermore, we discuss challenges and open questions related to optical flow and temporal interpolation of multispectral geostationary satellite imagery.

Optical Flow↗
DOE OSTI2018

Real-time Erosion-Corrosion Detection in Waste Transfer Pipelines using Guided Wave Ultrasonic Sensors - 18368

A Fitness-for-Service (FFS) program for the Waste Transfer System has been implemented by the United States Department of Energy Hanford Site Tank Farm to examine structural parameters of the waste transfer systems in order to develop erosion/corrosion rates for relevant system components. The FFS information is acquired from opportunistic evaluations of pipelines that have been removed from service. The objective is to deliver more realistic estimates to the remaining useful life of the components and incorporate those estimates into future design/testing plans across the DOE complex. To aid to this objective, previous efforts at Hanford included the installation of sensors on some of the POR 104 components, to provide real time pipe wall thickness measurements. Due to certain limitations, alternative approaches for remote permanently mounted pipe wall ultrasonic thickness measurement systems have been investigated by FIU. Present research work is a supportive effort by FIU-ARC for DOE and WRPS, which investigates the option for remote-permanently mount guided wave ultrasonic transducer (UT) systems for HLW pipe wall thickness measurements. Specific applications include straight sections, elbows and other fittings used in jumper pits, evaporators, and valve boxes. The proposed method will provide information that will assist engineers with understanding the failure potential of HLW transfer components due to corrosion and erosion. This information can assist in determining if and when lines need to be removed, saving time and resources on the unneeded excavation of transfer lines. This information will also assist engineers with designing new transfer systems by establishing more detailed/accurate guidelines governing the life expectancy of the transfer system and its components. In the previous work, FIU has investigated the use of various ultrasonic systems that are either commercially available or used previously at Hanford and selected the most promising systems for further evaluation. The down-selected system is the guided wave UT sensor system from Permasense which is a UK based manufacturer. It is an integrated wireless sensor network system which used a patented technology for the acoustic wave propagation and has proven applications in the oil and gas industries. Scope of the present research includes the initial verification and validation of the Permasense Guided Wave sensor system as a potential erosion/corrosion detection system for carbon steel pipelines under static conditions. In future, the real-time erosion/corrosion detection will be investigated by measuring the thinning of the pipe sections by circulating simulants and continuous monitoring. This is achieved by passing abrasive and caustic solutions through an in-house designed pipe loop system. Results obtained provide realistic wear rates on 2 inch and 3 inch carbon steel pipes with straight sections and elbows using the Permasense UT sensor system. Thus, the present research delivers solutions for sensor evaluations, conducts bench scale testing followed by data acquisition and analysis for corrosion and erosion assessment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Quantitative decoding of the response a ceramic mixed potential sensor array for engine emissions control and diagnostics

The development of on-board sensors for emissions monitoring is necessary for continuous monitoring of the performance of catalytic systems in automobiles. We have fabricated mixed potential electrochemical gas sensing devices with Pt, La 0.8 Sr 0.2 CrO 3 (LSCO), and Au/Pd alloy electrodes and a porous yttria-stabilized zirconia electrolyte. The three-electrode design takes advantage of the preferential selectivity of the Pt + Au/Pd and Pt + LSCO pairs towards different species of gases and has additional tunable selectivity achieved by applying a current bias to the latter pair. Voltages were recorded in single, binary, and ternary gas streams of NO, NO 2 , C 3 H 8 , and CO. We have also trained artificial neural networks to examine the voltage output from sensors in biased and unbiased modes to both identify which single test gas or binary mixture of two test gases is present in a gas stream as well as extract concentration values. We were then able to identify single and binary mixtures of these gases with accuracy of at least 98%. For determining concentration, the peak in the error distribution for binary mixtures was 5% and 80% of test data fell under <12% error. The sensor stability was also evaluated over the course of over 100 days and the ability to retrain ANNs with a small dataset was demonstrated.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2005

Requirements to Design to Code: Towards a Fully Formal Approach to Automatic Code Generation

A general-purpose method to mechanically transform system requirements into a provably equivalent model has yet to appear. Such a method represents a necessary step toward high-dependability system engineering for numerous possible application domains, including distributed software systems, sensor networks, robot operation, complex scripts for spacecraft integration and testing, and autonomous systems. Currently available tools and methods that start with a formal model of a system and mechanically produce a provably equivalent implementation are valuable but not sufficient. The gap that current tools and methods leave unfilled is that their formal models cannot be proven to be equivalent to the system requirements as originated by the customer. For the classes of systems whose behavior can be described as a finite (but significant) set of scenarios, we offer a method for mechanically transforming requirements (expressed in restricted natural language, or in other appropriate graphical notations) into a provably equivalent formal model that can be used as the basis for code generation and other transformations.

Hinchey, Michael G.↗
NASA NTRS2005

Requirements to Design to Code: Towards a Fully Formal Approach to Automatic Code Generation

A general-purpose method to mechanically transform system requirements into a provably equivalent model has yet to appear. Such a method represents a necessary step toward high-dependability system engineering for numerous possible application domains, including distributed software systems, sensor networks, robot operation, complex scripts for spacecraft integration and testing, and autonomous systems. Currently available tools and methods that start with a formal model of a: system and mechanically produce a provably equivalent implementation are valuable but not sufficient. The "gap" that current tools and methods leave unfilled is that their formal models cannot be proven to be equivalent to the system requirements as originated by the customer. For the ciasses of systems whose behavior can be described as a finite (but significant) set of scenarios, we offer a method for mechanically transforming requirements (expressed in restricted natural language, or in other appropriate graphical notations) into a provably equivalent formal model that can be used as the basis for code generation and other transformations.

Hinchey, Michael G.↗
DOE OSTI2021

Molecular Engineering of 2D Nanomaterial Field-Effect Transistor Sensors: Fundamentals and Translation across Innovation Spectrum

We report over the last decade, 2D layered nanomaterials have attracted significant attention across the scientific community due to their rich and exotic properties. Various nanoelectronic devices based on these 2D nanomaterials have been explored and demonstrated, including those for environmental applications. Here, the fundamental attributes of 2D layered nanomaterials for field-effect transistor (FET) sensors and tunneling FET (TFET) sensors, which provide versatile detection of water contaminants such as heavy-metal ions, bacteria, nutrients, and organic pollutants, are discussed. The major challenges and opportunities are also outlined for designing and fabricating 2D nanomaterial FET/TFET sensors with superior performance. Translation of these FET/TFET sensors from fundamental research to applied technology is illustrated through a case study on graphene-based real-time FET water sensors. A second case study centers on large-scale sensor networks for water-quality monitoring to enable intelligent drinking water and river-water systems. Overall, 2D nanomaterial FET sensors have significant potential for enabling a human-centered intelligent water system that can likely be applied to other precarious water supplies around the globe.

2D nanomaterials↗
DOE OSTI2018

Nucleation and Crystal Growth in the Formation of Hierarchical Three-Dimensional Nanoarchitecture

This project is to obtain fundamental understandings of the operation of the Ostwald-Lussac (OL) Law and the oriented attachment (OA) mechanism in nucleation and growth of TiO2 nanorods (NR) via surface-reaction-limited pulsed chemical vapor deposition (SPCVD) process. Three-dimensional (3D) NW networks are a unique type of mesoporous architecture that offers extraordinary surface area density and superior transport properties of electrons, photons, and phonons. It is exceptionally promising for advancing the design and application of functional materials for photovoltaic devices, catalysts beds, hydrogen storage systems, sensors, and battery electrodes. Our group has developed the SPCVD technique by mimicking the mechanism of atomic layer deposition (ALD), which effectively decoupled the crystal growth from precursor concentration while retaining anisotropic 1D growth. For the first time, this technique realized a 3D NW architecture with ultrahigh density and achieved ~4-5 times enhancement on photo-conversion efficiency. Through the support of our current DOE award, we revealed the governing role of the OL Law in the nucleation stage of SPCVD. The formation of NR morphology in SPCVD was identified following the OA mechanism. We also discovered a unique vapor-phase Kirkendall effect in the evolution of tubular or core-shell NR structures. These understandings opened many new opportunities in designing 3D NW architectures with improved properties or new functionalities. Specifically, our accomplishments from this project include five aspects: (1) Observation of the Ostwald-Lussac Law in high-temperature ALD. (2) Observation of vapor-solid Kirkendall effect in ZnO-to-TiO2 nanostructure conversion. (3) Development of highly-efficient capillary photoelectrochemical (PEC) solar-fuel generation. (4) Development of efficient and stable electrochemical protections for black silicon PEC electrodes. (5) Development of doped polymers with tunable electrical properties. This project brings a new level of transformative knowledge on nucleation and crystal growth in the SPCVD NR growth processes. Specifically, quantification of the activation energy landscape guided by the OL law will allow us to establish a critical knowledge base of nucleation kinetics for SPCVD synthesis of NR branches on different material surfaces. Studying the OA kinetics will establish a transformative knowledge base to support this new crystal growth mechanism that can be applied to many functional material systems. This research will pave the road toward a capable and versatile synthesis technology for creating 3D hierarchical mesoscale structures.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Distributed Sensing and Computer Vision Methods for Advanced Air Mobility Approach and Landing

Advanced Air Mobility (AAM) aircraft require precision approach and landing systems (PALS) in several types of environments such as urban, suburban, and rural. It is difficult to implement current state-of-the-art methods approved for automated approach and landing for AAM operations. However, existing technology and systems that use vision, IR, radar, and GPS methods provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL and computer vision feature correspondence methods to demonstrate a baseline navigation system while adhering to the Federal Aviation Administration requirements and regulations. The coplanar algorithm determines pose estimation, which feeds into an Extended Kalman filter that combines IMU with vision to create a sensor fusion navigation solution for GPS-denied environments. The state estimate leads to glideslope and localizer error computations, which will be pertinent for designing and deriving guidance laws and control laws for AAM PALS. The IMU and vision navigation solution provides promising simulation results for AAM PALS. This paper builds on previous work by incorporating high fidelity simulations with computer graphics rendering to demonstrate a distributed sensor network to track an AAM aircraft during approach and landing to compare with the aircraft's onboard navigation solution.

Evan Kawamura↗
NASA NTRS2003

Mobile Sensor Technologies Being Developed

The NASA Glenn Research Center is developing small mobile platforms for sensor placement, as well as methods for communicating between roving platforms and a central command location. The first part of this project is to use commercially available equipment to miniaturize an existing sensor platform. We developed a five-circuit-board suite, with an average board size of 1.5 by 3 cm. Shown in the preceding photograph, this suite provides all motor control, direction finding, and communications capabilities for a 27- by 21- by 40-mm prototype mobile platform. The second part of the project is to provide communications between mobile platforms, and also between multiple platforms and a central command location. This is accomplished with a low-power network labeled "SPAN," Sensor Platform Area Network, a local area network made up of proximity elements. In practice, these proximity elements are composed of fixed- and mobile-sensor-laden science packages that communicate to each other via radiofrequency links. Data in the network will be shared by a central command location that will pass information into and out of the network through its access to a backbone element. The result will be a protocol portable to general purpose microcontrollers satisfying a host of sensor networking tasks. This network will enter the gap somewhere between television remotes and Bluetooth but, unlike 802.15.4, will not specify a physical layer, thus allowing for many data rates over optical, acoustical, radiofrequency, hardwire, or other media. Since the protocol will exist as portable C-code, developers may be able to embed it in a host of microcontrollers from commercial to space grade and, of course, to design it into ASICs. Unlike in 802.15.4, the nodes will relate to each other as peers. A demonstration of this protocol using the two test bed platforms was recently held. Two NASA modified, commercially available, mobile platforms communicated and shared data with each other and a central command location. Web-based control and interrogation of similar mobile sensor platforms have also been demonstrated. Expected applications of this technology include robotic planetary exploration, astronaut-to-equipment communication, and remote aerospace engine inspections.

FROM↗
NASA NTRS2016

Self-Aware Vehicles: Mission and Performance Adaptation to System Health

Advances in sensing (miniaturization, distributed sensor networks) combined with improvements in computational power leading to significant gains in perception, real-time decision making/reasoning and dynamic planning under uncertainty as well as big data predictive analysis have set the stage for realization of autonomous system capability. These advances open the design and operating space for self-aware vehicles that are able to assess their own capabilities and adjust their behavior to either complete the assigned mission or to modify the mission to reflect their current capabilities. This paper discusses the self-aware vehicle concept and associated technologies necessary for full exploitation of the concept. A self-aware aircraft, spacecraft or system is one that is aware of its internal state, has situational awareness of its environment, can assess its capabilities currently and project them into the future, understands its mission objectives, and can make decisions under uncertainty regarding its ability to achieve its mission objectives.

Gregory, Irene M.↗
NASA NTRS2016

Reducing Multisensor Satellite Monthly Mean Aerosol Optical Depth Uncertainty: 1. Objective Assessment of Current AERONET Locations

Various space-based sensors have been designed and corresponding algorithms developed to retrieve aerosol optical depth (AOD), the very basic aerosol optical property, yet considerable disagreement still exists across these different satellite data sets. Surface-based observations aim to provide ground truth for validating satellite data; hence, their deployment locations should preferably contain as much spatial information as possible, i.e., high spatial representativeness. Using a novel Ensemble Kalman Filter (EnKF)- based approach, we objectively evaluate the spatial representativeness of current Aerosol Robotic Network (AERONET) sites. Multisensor monthly mean AOD data sets from Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, Sea-viewing Wide Field-of-view Sensor, Ozone Monitoring Instrument, and Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar are combined into a 605-member ensemble, and AERONET data are considered as the observations to be assimilated into this ensemble using the EnKF. The assessment is made by comparing the analysis error variance (that has been constrained by ground-based measurements), with the background error variance (based on satellite data alone). Results show that the total uncertainty is reduced by approximately 27% on average and could reach above 50% over certain places. The uncertainty reduction pattern also has distinct seasonal patterns, corresponding to the spatial distribution of seasonally varying aerosol types, such as dust in the spring for Northern Hemisphere and biomass burning in the fall for Southern Hemisphere. Dust and biomass burning sites have the highest spatial representativeness, rural and oceanic sites can also represent moderate spatial information, whereas the representativeness of urban sites is relatively localized. A spatial score ranging from 1 to 3 is assigned to each AERONET site based on the uncertainty reduction, indicating its representativeness level.

aerosol optical depth↗
DOE OSTI2020

One-Step Ahead Prediction of Thermal Mixing Tee Sensors with Long Short Term Memory (LSTM) Neural Networks

High-temperature advanced reactors under development, such as sodium fast reactors (SFR) and molten salt cooled reactors (MSCR), are expected to offer lower levelized cost of energy (LCOE) compared to existing light water reactor (LWR’s). In the existing light water reactors (LWR’s), operation and maintenance (O&M) expenses constitute the largest fraction of the total operating cost. Some of the O&M costs are related maintenance of sensors which can fail due to exposure to harsh environment in a reactor. The O&M costs of Advanced Reactor (AR)’s are expected to constitute a significant fraction of the total cost as well, because of high temperature and radiation level in AR are likely to cause material fatigue and premature failure of sensors and components. The O&M costs in AR’s could be reduced through integration of advanced informatics of performance-related sensors into a digital twin designed for reactor monitoring. For example, machine learning (ML) could be employed for real-time validation and correction of performance-related sensors, and reducing the number of performance-related physical sensor units through virtual sensing. As part of the effort, we investigate real-time validation of thermal hydraulic sensors through one-step ahead forecasting of sensor values using long short-term memory (LSTM) recurrent neural networks (RNN). The sensors are installed in a flow loop containing a thermal mixing tee, which is a common experimental model to study thermal fatigue in a thermal hydraulic loop. In addition, nonlinear transients generated in a thermal mixing tee constitute a good challenge data set for training and validation of ML algorithms. Sensors in this study include thermocouples, flow meters, and optical fibers for distributed temperature sensing. In one experiment, measurement data sets were obtained for a loop was filled with water, and in another experiment, measurements were performed on a loop filled with liquid metal Galinstan. We have also conducted preliminary investigation of one-step ahead prediction of fiber optics-based distributed temperature sensing with LSTM networks. In predicting fiber-based temperature measurements, we treated each gauge pitch of the fiber as an independent sensor. Accuracy of one-step ahead forecasting was estimated by calculating root mean square error (RMSE) for the test segment of time series of each sensor. RMSE’s for temperature sensors in water loop were, for the most part, lower than for the same sensors in Galinstan loop. The RMSE’s for flow meters were similar for both loops. The RMSE’s for distributed temperature measured with the fiber optic sensor were similar to those of the point sensors. Results of this study demonstrated the capability of LSTM one-step ahead forecasting with RMSE comparable to uncertainty in sensor measurements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2005

Tumbleweed Rovers

Tumbleweed rovers, now undergoing development, are lightweight, inflatable, approximately spherical exploratory robotic vehicles designed to roll across terrain, using only wind for propulsion. Tumbleweed rovers share many features with beach-ball rovers, which were discussed in several prior NASA Tech Briefs articles. Conceived for use in exploring remote planets, tumbleweed rovers could also be used for exploring relatively inaccessible terrain on Earth. A fully developed tumbleweed rover would consist of an instrumentation package suspended in an inflated twolayer (nylon/polypropylene) ball. The total mass of the rover would be of the order of 10 kg, the diameter of the ball when inflated would be 2 meters, and the minimum wind speed needed for propulsion would be about 5 m/s. The instrumentation package would contain a battery power supply, sensors, a Global Positioning System (GPS) receiver, and a radio transmitter that would send the sensor readings and the GPS position and time readings to a monitoring station via a satellite communication system. Depending on the specific exploratory mission, the sensors could include a thermometer, a barometer, a magnetometer (for studying the terrestrial magnetic field and/or detecting buried meteorites), a subsurface radar system (for measuring ice thickness and/or detecting buried meteorites), and/or one or two diametrally opposed cameras that would take the part of sending two side-looking images out. In the planned Antarctic field test, a prototype tumbleweed rover was released at a location near the South Pole. Using the global Iridium satellite network to send information about its position, the rover transmitted temperature, pressure, humidity, and light intensity data to NASA s Jet Propulsion Laboratory. The rover reached speeds of 30 km per hour over the Antarctic ice cap, and traveled at an average speed of about 6 km per hour. The test was designed to confirm the rover s long-term durability in an extremely cold environment, with the goal being eventual use of the device to explore the Martian polar caps and other planets in the solar system. On future Antarctic exploratory missions, tumbleweed rovers might be used to acquire sensor data for studies of global warming, ozone depletion, and impacts of meteorites.

Behar, Alberto↗
DOE OSTI2020

Characterization of an architecture for front-end pixel binning in an integrating pixel array detector

Optimization of an area detector involves compromises between various parameters like frame rate, read noise, dynamic range and pixel size. We have implemented and tested a novel front-end binning design in a photon-integrating hybrid pixel array detector using the MM-PAD- 2.0 pixel architecture. In this architecture, the pixels can be optionally binned in a 2 x 2 pixel configuration using a network of switches to selectively direct the output of 4 sensor pixels to a single amplifier input. Doing this allows a trade-off between frame rate and spatial resolution. Tests show that the binned pixels perform well, but with some degradation on performance as compared to an un-binned pixel. The increased parasitic input capacitance does reduce the signal collected per x-ray as well as increases the noise of the pixel. Here, the increase in noise is, however, less than the factor of 2 increase one would observe for binning in post-processing. Spatial scans across the binned pixels show that no measured signal intensity is lost at the inner binning unit boundaries. In the high flux regime, at a 2 x 2 pixel wide beam spot (FWHM) size, binned mode responds linearly up to a photon flux of 10 7 x-rays/s, and performs comparably with un-binned mode up to a photon flux of 10 8 x-rays/s. While this study demonstrates a proof of concept for front-end binning in integrating detectors, we also identify changes to this early-stage prototype which can further improve the performance of binning pixel structures.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Point defects in semiconductors: Friends and foes for quantum technologies

Point defects in semiconductors are both a curse and a blessing in microelectronics: they enable the control of electrical conductivity through doping, yet can also act as trapping and recombination centers that degrade device performance. In quantum information science, defects play a similarly dual role. They can be harnessed as spin–photon interfaces enabling the coupling of electronic and nuclear spins to light and the creation of distributed entanglement for quantum networks or used as atomistic scale sensors for quantum sensing. At the same time, defects are a major source of decoherence for superconducting qubits, one of the leading quantum computing platforms. This article discusses how a deeper materials-level understanding of defects can guide the design of improved quantum devices for communication, sensing, and computation.

Zhu, Yizhi [Rice University, Houston, TX (United S↗
DOE OSTI2020

5G Enabled Energy Innovation: Advanced Wireless Networks for Science

Digital wireless communication has become a foundational technology for the nation. The U.S. Department of Energy’s Office of Science (DOE-SC) is the Nation’s largest supporter of basic research in the physical sciences discovering new materials, designing advanced microelectronics, and understanding the physics of radio frequency signaling. The expanding national rollout of a new fifth-generation (5G) mobile network, coupled with the torrent of scientific data generated by next-generation devices such as battery-powered Internet of Things (IoT) sensors, has created an urgent need to enhance cutting-edge wireless technology. Breakthroughs in the deployment, integration, security, and operational range of wireless networking can provide new scientific capabilities for the next decade - from autonomous mobile instruments for scientific user facilities to intelligent sensors networks distributed over thousands of kilometers to study environmental processes. To realize this promise, however, we must continue to drive innovations in computing, artificial intelligence (AI), advanced materials, high-speed networking, and microelectronics. In March 2020, the DOE-SC convened a workshop to identify the potential opportunities and explore the scientific challenges of advanced wireless technologies.

42 ENGINEERING↗
NASA NTRS1981

RAMP - A fault tolerant distributed microcomputer structure for aircraft navigation and control

Design methodologies for realizing future high authority autoflight control systems are being investigated, taking into account also the study of distributed microcomputer architectures. Attention is given to the redundant asynchronous microprocessor (RAMP) structure. RAMP comprises a connected network of microcomputers which has as input command and sensor information, and which generates servo information to drive actuators, and thrust linkages. Tolerance to hardware failures is achieved by static redundancy. Results of a failed microcomputer are simply rejected. This is done in lieu of dynamic redundancy wherein the distributed computer system performs real time fault detection and reconfiguration of the system. Attention is given to the RAMP network structure and operation, flight control with parallel asynchronous computers, and intermittent fault tolerance.

Dunn, W. R.↗