Microengineering for Space Exploration: Recent Work at NASA Glenn
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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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A chlorophyll fluorescence measuring system having at least one spectrometer coupled to a data logger. The data logger provides direct control of the spectrometer and includes on-board memory for storage of target and reference spectrum data obtained by the spectrometer. The data logger may be coupled to an external computer that receives and analyzes target and reference spectrum data to determine SIF using a spectral fitting algorithm. The system may include a spectrometer aiming system coupled to and controlled by the data logger. The system may also include one or more environmental sensors configured to measure environment variables. The environmental sensors may be coupled to the data logger for control and data storage. The environmental data may be communicated to the external computer for use in the spectral fitting algorithm. The data logger may be connected to a network for remote monitoring and control.
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Although a nuclear reactor is a hostile environment for sensors and signal transmissions, the reactor core is amenable to acoustic communication. An acoustic measurement infrastructure installed at the Advanced Test Reactor (ATR) nozzle trench area records acoustic signals that can capture reactor operating states. The distinct states produce unique signatures that can be identified and tracked using data processing and data analytics. The infrastructure relies on acoustic transmission through ATR in-pile structural components, piping, and coolant that transmit acoustically modified signals generated by the coolant pumps. This paper will discuss results from using the Recursive Short Time Fast Fourier Transform (RSTFFT) technique used to process acoustic signals and provide signatures that are identified and monitored by analytics. The RSTFFT is applied to ATR data to understand the vibration levels and signatures for different operating regimes as displayed by the spectrogram. The combination of coolant pumps for normal and high-power operation generate unique signatures. These acoustic signatures are used to develop machine learning approaches to automatically classify operating regimes. Two machine-learning models, Support Vector Machines and Linear Discriminant Analysis, were developed to classify two event classes. Class 1 is a normal steady-state operation, and Class 2 is any event that is due to start up, shut down, or other actions. Both types of machine learning models had over a 96% prediction accuracy for the two classes. These results lay the foundation for predictive analytic frameworks that can be leveraged by ATR to optimize operations and maintenance.
This slide deck presents the research results in embedding fiber optic sensors in structural materials. Fiber optic sensors were embedded in stainless steel and nickel via electric field assisted sintering. The embedded sensors were evaluated in terms of fiber integrity, fiber-matrix bonding, fiber functionality, mechanical properties, and machinability.
In extreme environments, even hardened insertion sensors fail quickly. For such environments, we have developed an ultrasonic (US) method for measuring the spatial distribution of temperatures in solid materials and, specifically, across containments of extreme processes. By deploying US sensors in multiple locations, spatial heterogeneity in temperatures inside harsh environments may be characterized. In this note, we update our progress on testing the developed approach in an industrial setting and its performance in describing the temperature distribution inside a 500 MW (electrical) coalfired utility boiler of an electrical power generation plant. We use waveguides (WG) structured to contain echogenic features that produce a train of echoes in response to an excitation pulse. The time of flight between echoes encodes the information on the temperature distribution in the corresponding segment of the WG, which we reconstruct using its parametrization. Five waveguides were welded to the boiler’s heat exchange surface (waterwall) and different locations at the same boiler elevation and produced reliable US waveforms 18 months after the installation. For several weeks during the latest trial, we performed US measurements in five locations spanning half of the boiler’s 14-meter width. The measurements were acquired during regular operation, including load cycling to adjust for demand and intermittent contributions of renewable power sources, and during boiler shutdown for emergency maintenance and the subsequent restart. The interpretation of US waveforms by signal processing resulted in an accurate estimation of temperature distribution along the waveguides. We captured daily cyclical variations in demand-following load. Measurements performed in multiple locations revealed unexpected temperature variations across the boiler. We conclude that an array of developed sensors can provide responsive and spatial temperature measurements while maintaining functionality despite prolonged exposure to an extreme environment.
In order to test and monitor the operational stability and conditions of various energy, and manufacturing systems and their components, development of accurate sensors capable of operating at temperatures in excess of 1000 °C in various environments for long durations is required. In addition, many of these harsh-environment systems do not permit sensors to be directly inserted, so these sensors need to be embedded into thermal protective materials. In this work were developed high-temperature embedded thermocouples composed of various doped lanthanum chromites-refractory based composites synthesized by a mixed-oxide route and directly embedded into a Al2O3 based refractory. The electrical properties were specifically manipulated by altering the level of percolation of the conductive phase within the refractory constituent. Chemical stability of sensors was determined by phase development analysis by X-ray diffraction and X-ray photoelectron spectroscopy; Seebeck coefficients were determined by thermoelectric voltages measurements at temperature up to 1400 oC.
For aircraft engine control, one key parameter to detect on an airplane is the exhaust gas temperature (EGT). Presently, thermocouples are used to perform this measurement. These electrical sensors perform adequately; however, fully utilizing the benefits of optical sensors requires replacing electrical architectures with optical architectures. Part of this requires replacing electrical sensors with optical sensors, such as the EGT sensor chosen for these tests. The objective of the development and testing of this prototype sensor system was to determine the feasibility of operating an optical sensor in a hostile aircraft environment. The fiber optic sensor system was developed to measure temperatures from 20C to 600C in an aircraft environment and was utilized to monitor the EGT of an OV-10D aircraft engine. The sensor has successfully flown over 50 hours and proven to be immune to surface deterioration of the optical element (located inside the sensor head) and able to withstand and operate in normal and sustained severe flight conditions where forces on the airplane exceeded 4 g's. Potential commercial uses for this sensor include monitoring temperature for aeropropulsion system control, military vehicle and naval engine control, conventional and nuclear power plant monitoring and industrial plan monitoring where EMI issues are critical.
In this project, robust heat-flux measurement systems were developed. The heat-flux sensors utilize thermoelectric effects to directly transduce the heat-flux inputs to analog electrical voltage signals. They were constructed from dedicated materials that can withstand temperatures of at least 1000°C and maintain adequate performance at these conditions for prolonged periods of time. The proposed approaches took into account numerous considerations, including system cost, sensor head resilience, sensor footprint, data accuracy, response time, and maintenance requirements. Through modern thermoelectric materials design, methodical materials selection and rigorous testing in materials characterization labs and medium-scale fire research facilities, we have demonstrated functioning laboratory prototypes, upon which one could base industrial heat-flux sensing platforms capable of operating in the challenging high-temperature, corrosive environments of the boilers of coal-fired power plants. A distributed sensor array for heat-flux measurements throughout the furnace water-wall, the superheater area and the economizer coils can provide critical data for the power plant control systems to increase efficiency, improve safety and reduce down times. For example, the combined heat-flux sensor/control systems can contribute to the optimization of burner and boiler operations under flexible loads, the optimization of heat-exchange conditions and overall reduction of heat rate and emissions, the prediction of imminent overheating conditions, and the optimization of the soot-blowing protocols.
Over the past five decades, NASA Glenn Research Center had been advancing the development of single crystal silicon carbide growth, sensors and electronics device technologies, culminating in the recent demonstration of Micro-Electro-Mechanical Systems scale batch fabricated pressure sensors operating at 800 °C and integrated circuit electronics with demonstrated durability of over 1000 hours at 500 °C. As a result of the progress made in demonstrating the high temperature capability of the technology, insertion into actual operational environments, such as in jet engines and planet Venus, are in progress. The high temperature, near inert surface chemistry, and radiation hardness attributes of SiC, coupled with the relative maturation of the device batch microfabrication, contact metallization, and packaging technologies, make the material a prime candidate for use as part of future advanced nuclear reactor instrumentation and control strategy. Hence the current research efforts at NASA Glenn are aimed toward harnessing these attributes in developing SiC sensors and electronics for nuclear reactor applications, potentially for future Lunar/Martian nuclear power and the emerging terrestrial micro nuclear power plants.
Continuous monitoring of areas nearby the electric grid is critical for preventing and early detection of devastating wildfires. Existing wildfire monitoring systems are intermittent and oblivious to local ambient risk factors, resulting in poor wildfire awareness. Ambient sensor suites deployed near the gridlines can increase the monitoring granularity and detection accuracy. However, these sensors must address two challenging and competing objectives at the same time. First, they must remain powered for years without manual maintenance due to their remote locations. Second, they must provide and transmit reliable information if and when a wildfire starts. The first objective requires aggressive energy savings and ambient energy harvesting, while the second requires continuous operation of a range of sensors. To the best of our knowledge, this paper presents the first self-sustained cyber-physical system that dynamically co-optimizes the wildfire detection accuracy and active time of sensors. The proposed approach employs reinforcement learning to train a policy that controls the sensor operations as a function of the environment (i.e., current sensor readings), harvested energy, and battery level. Here, the proposed cyber-physical system is evaluated extensively using real-life temperature, wind, and solar energy harvesting datasets and an open-source wildfire simulator. In long-term (5 years) evaluations, the proposed framework achieves 89% uptime, which is 46% higher than a carefully tuned heuristic approach. At the same time, it averages a 2-minute initial response time, which is at least 2.5× faster than the same heuristic approach. Furthermore, the policy network consumes 0.6 mJ per day on the TI CC2652R microcontroller using TensorFlow Lite for Micro, which is negligible compared to the daily sensor suite energy consumption.
Ambient infrasound noise in quiet, rural environments has been extensively studied and well-characterized through noise models for several decades. More recently, creating noise models for high-noise rural environments has also become an area of active research. However, far less work has been done to create generalized low-frequency noise models for urban areas. The high ambient noise levels expected in cities and other highly populated areas means that these environments are regarded as poor locations for acoustic sensors, and historically, sensor deployment in urban areas were avoided for this reason. However, there are several advantages to placing sensors in urban environments, including convenience of deployment and maintenance, and increasingly, necessity, as more previously rural areas become populated. This study seeks to characterize trends in low-frequency urban noise by creating a background noise model for Las Vegas, NV, using the Las Vegas Infrasound Array (LVIA): a network of eleven infrasound sensors deployed throughout the city. Data included in this study spans from 2019 to 2021 and provides a largely uninterrupted record of noise levels in the city from 0.1–500 Hz, with only minor discontinuities on individual stations. We organize raw data from the LVIA sensors into hourly power spectral density (PSD) averages for each station and select from these PSDs to create frequency distributions for time periods of interest . These frequency distributions are converted into probability density functions (PDFs), which are then used to evaluate variations in frequency and amplitude over daily to seasonal timescale s. In addition to PDFs, the median, 5 th percentile, and 95 th percentile amplitude values are calculated across the entire frequency range. This methodology follows a well-established process for noise model creation.
NASA ARC has conducted flight tests of a new type of aerodynamic pressure sensor based on a luminescent surface coating. Flights were conducted at the NASA ARC-Dryden Flight Research Facility. The luminescent pressure sensor is based on a surface coating which, when illuminated with ultraviolet light, emits visible light with an intensity dependent on the local air pressure on the surface. This technique makes it possible to obtain pressure data over the entire surface of an aircraft, as opposed to conventional instrumentation, which can only make measurements at pre-selected points. The objective of the flight tests was to evaluate the effectiveness and practicality of a luminescent pressure sensor in the actual flight environment. A luminescent pressure sensor was installed on a fin, the Flight Test Fixture (FTF), that is attached to the underside of an F-104 aircraft. The response of one particular surface coating was evaluated at low supersonic Mach numbers (M = 1.0-1.6) in order to provide an initial estimate of the sensor's capabilities. This memo describes the test approach, the techniques used, and the pressure sensor's behavior under flight conditions. A direct comparison between data provided by the luminescent pressure sensor and that produced by conventional pressure instrumentation shows that the luminescent sensor can provide quantitative data under flight conditions. However, the test results also show that the sensor has a number of limitations which must be addressed if this technique is to prove useful in the flight environment.
Two different Earth-pointing missions dealing with attitude control and dynamics changes illustrate concerns with correlated error sources and coupled effects that can occur. On the OrbView-2 (OV-2) spacecraft, the assumption of a nearly-inertially-fixed momentum axis was called into question when a residual dipole bias apparently changed magnitude. The possibility that alignment adjustments and/or sensor calibration errors may compensate for actual motions of the spacecraft is discussed, and uncertainties in the dynamics are considered. Particular consideration is given to basic orbit frequency and twice orbit frequency effects and their high correlation over the short science observation data span. On the Tropical Rainfall Measuring Mission (TRMM) spacecraft, the switch to a contingency Kalman filter control mode created changes in the pointing error patterns. Results from independent checks on the TRMM attitude using science instrument data are reported, and bias shifts and error correlations are discussed. Various orbit frequency effects are common with the flight geometry for Earth pointing instruments. In both dual-spin momentum stabilized spacecraft (like OV-2) and three axis stabilized spacecraft with gyros (like TRMM under Kalman filter control), changes in the initial attitude state propagate into orbit frequency variations in attitude and some sensor measurements. At the same time, orbit frequency measurement effects can arise from dynamics assumptions, environment variations, attitude sensor calibrations, or ephemeris errors. Also, constant environment torques for dual spin spacecraft have similar effects to gyro biases on three axis stabilized spacecraft, effectively shifting the one-revolution-per-orbit (1-RPO) body rotation axis. Highly correlated effects can create a risk for estimation errors particularly when a mission switches an operating mode or changes its normal flight environment. Some error effects will not be obvious from attitude sensor measurement residuals, so some independent checks using imaging sensors are essential and derived science instrument attitude measurements can prove quite valuable in assessing the attitude accuracy.
The harsh environment inherent in propulsion systems is especially challenging for Smart Sensor Systems; this paper addresses technology development for such applications. A basic sensing system for high temperature wireless pressure monitoring composed of a sensor, electronics, and wireless communication with scavenged power developed for health monitoring of aircraft engines and other high temperature applications has been demonstrated at 475 C. Other efforts will be discussed including a brief overview of the status of high temperature electronics and sensors, as well as their use and applications.
From the first Saturn V rocket booster (S-II-T) testing in 1966 and the routine Space Shuttle Main Engine (SSME) testing beginning in 1975, to more recent test programs such as the X-33 Aerospike Engine, the Integrated Powerhead Development (IPD) program, and the Hybrid Sounding Rocket (HYSR), Stennis Space Center (SSC) continues to be a premier location for conducting large-scale propulsion testing. Central to each test program is the capability for sensor systems to deliver reliable measurements and high quality data, while also providing a means to monitor the test stand area to the highest degree of safety and sustainability. As part of an on-going effort to enhance the testing capabilities of Stennis Space Center, the Test Technology and Development group is developing and applying a number of wireless and intelligent sensor technologies in ways that are new to the test existing test environment.
In an effort to develop harsh environment electronic and sensor technologies for aircraft engine safety and monitoring, we have used capacitive-based pressure sensors to shift the frequency of a SiC-electronics-based oscillator to produce a pressure-indicating signal that can be readily transmitted, e.g. wirelessly, to a receiver located in a more benign environment. Our efforts target 500 C, a temperature well above normal operating conditions of commercial circuits but within areas of interest in aerospace engines, deep mining applications and for future missions to the Venus atmosphere. This paper reports for the first time a ring oscillator circuit integrated with a capacitive pressure sensor, both operating at 500 C. This demonstration represents a significant step towards a wireless pressure sensor that can operate at 500 C and confirms the viability of 500 C electronic sensor systems.