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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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Systems and methods for classifying materials utilizing one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials, which may then be sorted into separate groups based on such an identification or classification. The machine learning system may utilize a neural network, and be previously trained to recognize and classify certain types of materials.
A program to develop and demonstrate technology for low gravity propellant gaging on future geostationary satellites is described. Evaluations were performed to select four gaging concepts for ground tests and low gravity tests in the NASA KC-135 aircraft. The selected concepts were: (1) an ultrasonic point sensor system, (2) a nucleonic gaging system, (3) an ultrasonic torsional wave guide, and (4) an ultrasonic flowmeter. As a result of successful ground and KC-135 tests, two concepts (the ultrasonic point sensor and the nucleonic systems) were selected for orbital test in a shuttle Get-Away-Special experiment.
Gravity gradient stabilizing boom and dampers and attitude sensor systems for applications technology satellite
Idaho National Laboratory (INL) is maintaining and gaining knowledge into the nuclear fuel cycle by building a test bed to allow researchers the opportunity to study nuclear fuel processing operations. This includes studying solvent extraction processes that use centrifugal contactors. As part of INL’s mission, the goal of this project is to develop a system that utilizes non-traditional measurement sources such as vibration, acoustics, current, light, flow, and temperature in conjunction with data-based, machine learning techniques that will allow for signal discovery. This multisensory data can support the development of safeguards by design, provide operator process awareness, and discover process anomalies. This poster will highlight some of the data collection and analytics challenges for the multi-sensor system as well as the mitigation strategies to build a robust system. Additionally, some preliminary data from the first testing campaign will be shown to help illustrate the data needs of the system.
Molten mixtures of MgCl2-KCl-NaCl are promising heat transfer fluid (HTF) candidates for the next generation of concentrating solar power systems (Gen3 CSP), because of their low cost, high decomposition temperature, and favorable heat transfer characteristics. However, if the chemistry of the salts is not properly controlled, molten chlorides can cause corrosion of high-temperature metal alloys, such as Inconel (R), in CSP systems. Here we demonstrate a corrosion monitoring system that can be used to monitor the health of the structural alloys over long durations. The monitoring system includes a multielectrode array voltammetry sensor that measures the redox potential of molten MgCl2-KCl-NaCl mixture as well as the presence of corrosion products and impurities. The sensors have been successfully operated in static molten salt environments for long durations, and are capable of detecting corrosion products, such as Cr2+ and Fe2+, quantitatively at low concentrations (i.e., approximately 100 ppm) with less than 4% error.
Three-probe heater sensor system, transient response system, and simulation fluid selection propellant leakage detection system study
The effects of active controls on the suppression of flutter and gust alleviation of two different types of subsonic aircraft (the Arava, twin turboprop STOL transport, and the Westwind twin-jet business transport) are investigated. The active controls are introduced in pairs which include, in any chosen wing strip, a leading-edge (LE) control and a trailing-edge (TE) control. Each control surface is allowed to be driven by a combined linear-rotational sensor system, located on the activated strip. The control law, which translates the sensor signals into control surface rotations, is based on the concept of aerodynamic energy. The results indicate the extreme effectiveness of the active systems in controlling flutter. A single system spanning 10% of the wing semispan made the Arava flutter-free, and a similar active system, for the Westwind aircraft, yielded a reduction of 75% in the maximum bending moment of the wing and a reduction of 90% in the acceleration of the cg of the aircraft. Results for simultaneous activation of several LE - TE systems are presented. Further work needed to bring the investigation to completion is also discussed.
As advanced reactor concepts like small modular reactors (SMRs) progress towards design maturity and commercial deployment, it is important to assess their instrumentation and control (I&C) system sensors and cables to assure their safe, reliable, and efficient operation throughout their service lifetimes. The I&C system of any nuclear power plant (NPP) is the central nervous system of the plant and is made up of field devices such as sensors which are connected via cables to analog and/or digital systems. These systems are responsible for control and/or protection of the plant. The performance of I&C sensors and cables is dependent on several factors, including plant operating conditions. In particular, the plant operation can affect the static (accuracy) and dynamic (response) performance of the sensor, whereas the surrounding ambient environment can impact the remaining useful life of the cables, connectors, and other associated components within I&C sensor circuits.
Ongoing applied research is focused on developing guidance system for robot vehicles. Problems facing the basic research needed to support this development (e.g., scene understanding, real-time vision processing, etc.) are major impediments to progress. Due to the complexity and the unpredictable nature of a vehicle's area of operation, more advanced vehicle control systems must be able to learn about obstacles within the range of its sensor(s). A better understanding of the basic exploration process is needed to provide critical support to developers of both sensor systems and intelligent control systems which can be used in a wide spectrum of autonomous vehicles. Elcee Computek, Inc. has been working under contract to the Flight Dynamics Laboratory, Wright Research and Development Center, Wright-Patterson AFB, Ohio to develop a Knowledge/Geometry-based Mobile Autonomous Robot Simulator (KMARS). KMARS has two parts: a geometry base and a knowledge base. The knowledge base part of the system employs the expert-system shell CLIPS ('C' Language Integrated Production System) and necessary rules that control both the vehicle's use of an obstacle detecting sensor and the overall exploration process. The initial phase project has focused on the simulation of a point robot vehicle operating in a 2D environment.
The topics covered include: 1) Replaceable Sensor System for Bioreactor Monitoring; 2) Unitary Shaft-Angle and Shaft-Speed Sensor Assemblies; 3) Arrays of Nano Tunnel Junctions as Infrared Image Sensors; 4) Catalytic-Metal/PdO(sub x)/SiC Schottky-Diode Gas Sensors; 5) Compact, Precise Inertial Rotation Sensors for Spacecraft; 6) Universal Controller for Spacecraft Mechanisms; 7) The Flostation - an Immersive Cyberspace System; 8) Algorithm for Aligning an Array of Receiving Radio Antennas; 9) Single-Chip T/R Module for 1.2 GHz; 10) Quantum Entanglement Molecular Absorption Spectrum Simulator; 11) FuzzObserver; 12) Internet Distribution of Spacecraft Telemetry Data; 13) Semi-Automated Identification of Rocks in Images; 14) Pattern-Recognition Algorithm for Locking Laser Frequency; 15) Designing Cure Cycles for Matrix/Fiber Composite Parts; 16) Controlling Herds of Cooperative Robots; 17) Modification of a Limbed Robot to Favor Climbing; 18) Vacuum-Assisted, Constant-Force Exercise Device; 19) Production of Tuber-Inducing Factor; 20) Quantum-Dot Laser for Wavelengths of 1.8 to 2.3 micron; 21) Tunable Filter Made From Three Coupled WGM Resonators; and 22) Dynamic Pupil Masking for Phasing Telescope Mirror Segments.
A nuclear power plant is typically instrumented with a variety of sensors to continually monitor its variables, and their sensor’s measurements may be used to assess the plant state and initiate safety actions, if needed. Errors in sensor measurements, due to factors such as calibration drifts, critically affect such state assessments. Here, we address a problem of estimating sensor errors using physics-informed machine learning methods that use measurements collected under known plant conditions. For a given sensor, we propose an information fusion method that uses measurements from other sensors to estimate its output assuming it is error-free and provides its difference from an actual measurement as an error estimate. We present the ensemble of trees and support vector machine fusers, and evaluate their performance using measurements collected over an emulated test loop of a pressurized water reactor. The plant variables are related to each other through the underlying physical laws under inertial constraints that place bounds on their derivatives, which analytically justify the applicability of machine learning methods for computing these fusers. Under twenty scenarios, we assess their sensor error estimates for pressure sensors of the heat exchanger of a reactor’s primary coolant system. Multiple types of errors are captured by both fusers under externally induced calibration drifts, blockages, minor leaks and air gaps in sensing lines, and electromagnetic interference; the root mean square error of the estimation of error is under 2.2% percent of the maximum measurement. We present generalization equations, in the framework of statistical learning theory, for these methods that characterize the confidence probability that the estimation error is bounded by a specified parameter in future test scenarios.
Triboluminescence exploited in fiber-optic sensor system for measuring changes in pressures, strains, vibrations, and acoustic emissions, in structural members. Sensors embedded in members for in situ monitoring of condition of structure. System passive in sense no source of radiation required to interrogate optical fiber. Technique has potential for wide range of applications in which detection and measurement of structural stress required.
The benefits to be obtained from cost-effective global observation of the earth, its environment, and its natural and man-made features are examined using typical spacecraft and missions which could enhance the benefits of space operations. The technology needs and areas of interest include: (1) a ten-fold increase in the dimensions of deployable and erectable structures to provide booms, antennas, and platforms for global sensor systems; (2) control and stabilization systems capable of pointing accuracies of 1 arc second or less to locate targets of interest and maintain platform or sensor orientation during operations; (3) a factor of five improvements in spacecraft power capacity to support payloads and supporting electronics; (4) auxiliary propulsion systems capable of 5 to 10 years on orbit operation; (5) multipurpose sensors; and (6) end-to-end data management and an information system configured to accept new components or concepts as they develop.
Systems analysis and integration, boom subsystem, combination passive damper, and attitude sensor system for Applications Technology Satellite gravity gradient stabilization system
The author has identified the following significant results. Study emphasis was on developing a unified concept for the required ground system, capable of handling data from all viable acquisition platforms and sensor groupings envisaged as supporting operational earth survey programs. The platforms considered include both manned and unmanned spacecraft in near earth orbit, and continued use of low and high altitude aircraft. The sensor systems include both imaging and nonimaging devices, operated both passively and actively, from the ultraviolet to the microwave regions of the electromagnetic spectrum.
This redundant strapdown INS preliminary design study demonstrates the practicality of a skewed sensor system configuration by means of: (1) devising a practical system mechanization utilizing proven strapdown instruments, (2) thoroughly analyzing the skewed sensor redundancy management concept to determine optimum geometry, data processing requirements, and realistic reliability estimates, and (3) implementing the redundant computers into a low-cost, maintainable configuration.
The geolocational accuracy of products from the IKONOS, QuickBird, and OrbView-3 sensors was evaluated using two test sites: one developed in and around Brookings, SD, and one near Stennis Space Center, MS. Both of these relatively flat sites host over 100 ground control points surveyed to an accuracy of approximately 5 cm. They provide robust locations to test the basic geolocational accuracy of a variety of spaceborne and aircraft sensor systems. Imagery of both test sites was acquired by these three sensors in 2004 and in 2005; several products from each sensor, ranging from basic datasets through orthorectified imagery, were analyzed at Stennis Space Center and at South Dakota State University. While direct comparisons between sensors and products are difficult because of differing processing schemes, results indicate that these products tend to display stated levels of accuracy.
Many embodiments provide a hybrid data processing system (HySDS) of an end-to-end geodetic imaging data system enabling near-real-time science, assessment, response, and rapid recovery. The HySDS may be an operation data processing system that integrates data from many different geodetic data sources and/or sensors, including interferometric synthetic aperture radar (InSAR), GPS, pixel tracking, seismology, and/or modeling, and processes the data to generate actionable high quality science data products. The HySDS may provide for an automated imaging and analysis capabilities that is able to handle the imminent increases in raw data from new and existing geodetic monitoring sensor systems.