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At least 73 records · Page 4

The Effects of Propellant Slosh Dynamics on the Solar Dynamics Observatory

The Solar Dynamics Observatory (SDO) mission, which is part of the Living With a Star program, was successfully launched and deployed from its Atlas V launch vehicle on February 11, 2010. SDO is an Explorer-class mission now operating in a geosynchronous orbit (GEO). The basic mission is to observe the Sun for a very high percentage of the 5-year mission (10-year goal) with long stretches of uninterrupted observations and with constant, high-data-rate transmission to a dedicated ground station located in White Sands, New Mexico. A significant portion of SDO's launch mass was propellant, contained in two large tanks. To ensure performance with this level of propellant, a slosh analysis was performed. This paper provides an overview of the SDO slosh analysis, the on-orbit experience, and the lessons learned. SDO is a three-axis controlled, single fault tolerant spacecraft. The attitude sensor complement includes sixteen coarse Sun sensors, a digital Sun sensor, three two-axis inertial reference units, two star trackers, and four guide telescopes. Attitude actuation is performed either using four reaction wheels or eight thrusters, depending on the control mode, along with single main engine which nominally provides velocity-change thrust. The attitude control software has five nominal control modes: three wheel-based modes and two thruster-based modes. A wheel-based Safehold running in the Attitude Control Electronics (ACE) box improves the robustness of the system as a whole. All six modes are designed on the same basic proportional-integral-derivative attitude error structure, with more robust modes setting their integral gains to zero. To achieve and maintain a geosynchronous orbit for a 2974-kilogram spacecraft in a cost effective manner, the SDO team designed a high-efficiency propulsive system. This bi-propellant design includes a 100-pound-force main engine and eight 5-pound-force attitude control thrusters. The main engine provides high specific impulse for the maneuvers to attain GEO, while the smaller Attitude Control System (ACS) thrusters manage the disturbance torques of the larger main engine and provide the capability for much smaller orbit adjustment burns. SDO's large solar profile produces a large solar torque disturbance and momentum buildup. This buildup drives the frequency of momentum unloads via ACS thrusters. SDO requires 1409 kilograms (which is approximately half the launch mass) of propellant to achieve and maintain the GEO orbit while performing the momentum unloads for 10 years.

Mason, Paul↗

Safehold Attitude Determination Approach for GPM

Spacecraft sating designs generally have minimal goals with loose pointing requirements. Safe pointing orientations for three-axis stabilized spacecraft are usually chosen to put the spacecraft into a thermally safe and power-positive orientation. In addition, safe mode designs are required to be simple and reliable. This simplicity lends itself to the usage of analog sun sensors, because digital sun sensors will add unwanted complexity to the safe hold mode. The Global Precipitation Measurement (GPM) Mission Core Observatory will launch into lower earth orbit (LEO) at an inclination of 65 degrees. The GPM instrument suite consists of an active radar system and a passive microwave imager to provide the next-generation global observations of rain and snow. The complexity and precision of these instruments along with the operational constraints of the mission result in tight pointing requirements during all phases of the mission. To ensure the instruments are not damaged during spacecraft safing, thermal constraints dictate that the solar pointing orientation must be maintained to better than 6.5 degrees. This requirement is outside the capabilities of a typical analog sun sensor suite, primarily due to the effects of Earth's albedo. To ensure mission success, a new analog sensor, along with the appropriate algorithms, is needed. This paper discusses the design issues involving albedo effects on spacecraft pointing and the development of a simple, low-cost analog sensor and algorithm that will address the needs of the GPM mission. In addition, the algorithms are designed to be easily integrated into the existing attitude determination software by using common interfaces. The sensor design is based on a heritage, commercial off-the-shelf analog sun sensors with a limited field-of-view to reduce the effects of Earth's albedo. High fidelity simulation results are presented that demonstrate the efficacy of the design.

Fitzpatrick, Henry↗

Scene correction (precision techniques) of ERTS sensor data using digital image processing techniques

Techniques have been developed, implemented, and evaluated to process ERTS Return Beam Vidicon (RBV) and Multispectral Scanner (MSS) sensor data using digital image processing techniques. The RBV radiometry has been corrected to remove shading effects, and the MSS geometry and radiometry have been corrected to remove internal and external radiometric and geometric errors. The results achieved show that geometric mapping accuracy of about one picture element RMS and two picture elements (maximum) can be achieved by the use of nine ground control points. Radiometric correction of MSS and RBV sensor data has been performed to eliminate striping and shading effects to about one count accuracy. Image processing times on general purpose computers of the IBM 370/145 to 168 class are in the range of 29 to 3.2 minutes per MSS scene (4 bands). Photographic images of the fully corrected and annotated scenes have been generated from the processed data and have demonstrated excellent quality and information extraction potential.

Bernstein, R.↗

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants: 2nd Annual Report

For economic reasons, the nuclear industry is witnessing premature closure of nuclear power plants, despite excellent safety records. Operations and Maintenance (O&M) activities are some of the largest costs in operating legacy light-water plants. By reducing O&M costs, nuclear energy can become more economically competitive with other energy sources. This can be achieved by leveraging machine-learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose potential faults within the system. Improved accuracy of the models can lead to a reduction in unnecessary maintenance, thus reducing costs associated with parts, labor, and unnecessary planned, forced, or extended outages. To address these challenges, the goal of this project is to perform research and development in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and data science based analytic capabilities, to advance online monitoring and predictive maintenance in nuclear plants and improve plant performance (efficiency gain and economic competitiveness). This report summarizes the fiscal year 2020 research progress encompassing (1) different wireless vibration sensor and data indicators used to assess the health of a plant asset; (2) development of diagnostic models for fault detection; and (3) development of prognostic models for estimating the health of the system up to 7 days ahead.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Digital Architecture for a Trace Gas Sensor Platform

A digital architecture has been implemented for a trace gas sensor platform, as a companion to standard analog control electronics, which accommodates optical absorption whose fractional absorbance equivalent would result in excess error if assumed to be linear. In cases where the absorption (1-transmission) is not equivalent to the fractional absorbance within a few percent error, it is necessary to accommodate the actual measured absorption while reporting the measured concentration of a target analyte with reasonable accuracy. This requires incorporation of programmable intelligence into the sensor platform so that flexible interpretation of the acquired data may be accomplished. Several different digital component architectures were tested and implemented. Commercial off-the-shelf digital electronics including data acquisition cards (DAQs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), and microcontrollers have been used to achieve the desired outcome. The most completely integrated architecture achieved during the project used the CPLD along with a microcontroller. The CPLD provides the initial digital demodulation of the raw sensor signal, and then communicates over a parallel communications interface with a microcontroller. The microcontroller analyzes the digital signal from the CPLD, and applies a non-linear correction obtained through extensive data analysis at the various relevant EVA operating pressures. The microcontroller then presents the quantitatively accurate carbon dioxide partial pressure regardless of optical density. This technique could extend the linear dynamic range of typical absorption spectrometers, particularly those whose low end noise equivalent absorbance is below one-part-in-100,000. In the EVA application, it allows introduction of a path-length-enhancing architecture whose optical interference effects are well understood and quantified without sacrificing the dynamic range that allows quantitative detection at the higher carbon dioxide partial pressures. The digital components are compact and allow reasonably complete integration with separately developed analog control electronics without sacrificing size, mass, or power draw.

Gonzales, Paula↗

Fiber optic, Fabry-Perot high temperature sensor

A digital, fiber optic temperature sensor using a variable Fabry-Perot cavity as the sensor element was analyzed, designed, fabricated, and tested. The fiber transmitted cavity reflection spectra is dispersed then converted from an optical signal to electrical information by a charged coupled device (CCD). A microprocessor-based color demodulation system converts the wavelength information to temperature. This general sensor concept not only utilizes an all-optical means of parameter sensing and transmitting, but also exploits microprocessor technology for automated control, calibration, and enhanced performance. The complete temperature sensor system was evaluated in the laboratory. Results show that the Fabry-Perot temperature sensor has good resolution (0.5% of full seale), high accuracy, and potential high temperature ( 1000 C) applications.

James, K.↗

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants (4th Annual Report)

Nuclear plant sites collect and store large volumes of data collected from various equipment and systems. These datasets typically include plant process parameters, maintenance records, technical logs, online monitoring data, and equipment failure data. The collection of such data affords an opportunity to leverage data-driven machine learning and artificial intelligence technologies to provide diagnostic and prognostic capabilities within the nuclear power industry to reduce operating and maintenance costs. In this way, nuclear energy can become more economically competitive with other energy sources, and premature closures can be avoided. From a maintenance standpoint, savings can be achieved by leveraging machine learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose and predict potential faults within the system. Improved model accuracy can lead to reductions in unnecessary maintenance and more efficient planning of future maintenance, thus lowering the costs associated with parts, labor, and unnecessary planned, forced, or extended outages. From an operations perspective, cost savings can be generated by shifting from route-based monitoring to wireless technologies for online monitoring, and by transitioning from onsite- to cloud-based computing and storage services. Wireless monitoring would reduce the operator manhours required for taking routine measurements, while cloud computing services would generate cost savings by reducing the amount of hardware needing to be purchased and maintained—all while scaling to both computational and storage demands. This report summarizes this project’s effort to shift from costly, labor-intensive preventative maintenance to cheaper predictive maintenance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Experimental data for damage mechanics simulation challenge

While there are many computational approaches for simulating damage in rock and other materials, few have been ground truth tested with either known experimental data or with blind data sets. Here, in this work, we present a bench-mark laboratory data set for a damage mechanics challenge to compare computational approaches on damage evolution in brittle-ductile materials. The samples were fabricated through additive manufacturing to produce repeatable specimens designed to fail in controlled ways. The failure was induced in the samples using a 3-point bending test to produce different Modes such as Mode I and mixed Modes including I-II, I-III and I-II-III Modes to generate a calibration data set and a blind challenge data set. Data collected included spatial and temporal measurements from traditional digital load–displacement sensors, 2D digital image correlation measurement to map surface deformations, 3D X-ray microscopy to ground-truth the crack-failure geometry, and laser profilometry to capture surface roughness. The data sets are available, on a data repository, to the community to advance computational models to improve our ability to predict damage in brittle-ductile materials.

3-point bending↗

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants (3 rd Annual Report)

Nuclear power plants collect and store large volumes of heterogeneous data from various components and systems. With recent advances in machine learning (ML) techniques, these data can be leveraged to develop diagnostic and short-term forecasting models to better predict future equipment condition. Maintenance operations can then be planned in advance whenever degraded performance is predicted, thus resulting in fewer unplanned outages and the optimization of maintenance activities. This enables lower maintenance costs and improves the overall economics of nuclear power. This report primarily focuses on developing a short-term forecasting process that leverages a feature selection process to distill large volumes of heterogeneous data and predict specific equipment parameters. A variety of feature selection methods, including Shapley Additive Explanations (SHAP) and variance inflation factor (VIF), were used to select the optimal features as inputs for three ML methods: long short-term memory (LSTM) networks, support vector regression (SVR), and random forest (RF). Each combination of model and input features was used to predict a pump bearing temperature both 1 and 24 hours in advance, based on actual plant system data. The optimal inputs for the LSTM and SVR were selected using the SHAP values, while the optimal input for the RF consisted solely of the response variable itself. Each model produced similar 1-hour-ahead predictions, with root mean square errors (RMSEs) of roughly 0.006. For the 24-hour-ahead predictions, differences could be seen between LSTM, SVR, and RF, as reflected by model performances of 0.036 ± 0.014, 0.0026 ± 0, and 0.063 ± 0.004 RMSE, respectively. As big data and continuous online monitoring become more widely available, the proposed feature selection process can be used for many applications beyond the prediction of process parameters within nuclear infrastructure. This report summarizes the Fiscal Year 2021 research progress encompassing the (1) data cleaning and feature selection necessary for ML applications; (2) development of short-term forecasting models to predict future plant process parameters for both single and multiple time steps ahead; and (3) validation of the feature selection methods and short-term forecasting models given new data from different systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of a Robust star identification technique for use in attitude determination of the ACE spacecraft

The Advanced Composition Explorer (ACE) spacecraft is designed to fly in a spin-stabilized attitude. The spacecraft will carry two attitude sensors - a digital fine Sun sensor and a charge coupled device (CCD) star tracker - to allow ground-based determination of the spacecraft attitude and spin rate. Part of the processing that must be performed on the CCD star tracker data is the star identification. Star data received from the spacecraft must be matched with star information in the SKYMAP catalog to determine exactly which stars the sensor is tracking. This information, along with the Sun vector measured by the Sun sensor, is used to determine the spacecraft attitude. Several existing star identification (star ID) systems were examined to determine whether they could be modified for use on the ACE mission. Star ID systems which exist for three-axis stabilized spacecraft tend to be complex in nature and many require fairly good knowledge of the spacecraft attitude, making their use for ACE excessive. Star ID systems used for spinners carrying traditional slit star sensors would have to be modified to model the CCD star tracker. The ACE star ID algorithm must also be robust, in that it will be able to correctly identify stars even though the attitude is not known to a high degree of accuracy, and must be very efficient to allow real-time star identification. The paper presents the star ID algorithm that was developed for ACE. Results from prototype testing are also presented to demonstrate the efficiency, accuracy, and robustness of the algorithm.

Woodard, Mark↗

TRMM On Orbit Attitude Control System Performance

This paper presents an overview of the Tropical Rainfall Measuring Mission (TRMM) Attitude Control System (ACS) along with detailed in-flight performance results for each operational mode. The TRMM spacecraft is an Earth-pointed, zero momentum bias satellite launched on November 27, 1997 from Tanegashima Space Center, Japan. TRMM is a joint mission between NASA and the National Space Development Agency (NASDA) of Japan designed to monitor and study tropical rainfall and the associated release of energy. Launched to provide a validation for poorly known rainfall data sets generated by global climate models, TRMM has demonstrated its utility by reducing uncertainties in global rainfall measurements by a factor of two. The ACS is comprised of Attitude Control Electronics (ACE), an Earth Sensor Assembly (ESA), Digital Sun Sensors (DSS), Inertial Reference Units (IRU), Three Axis Magnetometers (TAM), Coarse Sun Sensors (CSS), Magnetic Torquer Bars (MTB), Reaction Wheel Assemblies (RWA), Engine Valve Drivers (EVD) and thrusters. While in Mission Mode, the ESA provides roll and pitch axis attitude error measurements and the DSS provide yaw updates twice per orbit. In addition, the TAM in combination with the IRU and DSS can be used to provide pointing in a contingency attitude determination mode which does not rely on the ESA. Although the ACS performance to date has been highly successful, lessons were learned during checkout and initial on-orbit operation. This paper describes the design, on-orbit checkout, performance and lessons learned for the TRMM ACS.

Robertson, Brent↗

Solar Dynamics Observatory Guidance, Navigation, and Control System Overview

The Solar Dynamics Observatory (SDO) was designed and built at the Goddard Space Flight Center, launched from Cape Canaveral on February 11, 2010, and reached its final geosynchronous science orbit on March 16, 2010. The purpose of SDO is to observe the Sun and continuously relay data to a dedicated ground station. SDO remains Sun-pointing throughout most of its mission for the instruments to take measurements of the Sun. The SDO attitude control system (ACS) is a single-fault tolerant design. Its fully redundant attitude sensor complement includes sixteen coarse Sun sensors (CSSs), a digital Sun sensor (DSS), three two-axis inertial reference units (IRUs), and two star trackers (STs). The ACS also makes use of the four guide telescopes included as a part of one of the science instruments. Attitude actuation is performed using four reaction wheels assemblies (RWAs) and eight thrusters, with a single main engine used to provide velocity-change thrust for orbit raising. The attitude control software has five nominal control modes, three wheel-based modes and two thruster-based modes. A wheel-based Safehold running in the attitude control electronics box improves the robustness of the system as a whole. All six modes are designed on the same basic proportional-integral-derivative attitude error structure, with more robust modes setting their integral gains to zero. This paper details the final overall design of the SDO guidance, navigation, and control (GN&C) system and how it was used in practice during SDO launch, commissioning, and nominal operations. This overview will include the ACS control modes, attitude determination and sensor calibration, the high gain antenna (HGA) calibration, and jitter mitigation operation. The Solar Dynamics Observatory mission is part of the NASA Living With a Star program, which seeks to understand the changing Sun and its effects on the Solar System, life, and society. To this end, the SDO spacecraft carries three Sun-observing instruments: Helioseismic and Magnetic Imager (HMI), led by Stanford University; Atmospheric Imaging Assembly (AIA), led by Lockheed Martin Space and Astrophysics Laboratory; and Extreme Ultraviolet Variability Experiment (EVE), led by the University of Colorado. The basic mission is to observe the Sun for a very high percentage of the 5-year mission (10-year goal) with long stretches of uninterrupted observations and with constant, high-data-rate transmission to a dedicated ground station to be located in White Sands, New Mexico. These goals guided the design of the spacecraft bus that will carry and service the three-instrument payload. Overarching design goals for the bus are geosynchronous orbit, near-constant Sun observations with the ability to fly through eclipses, and constant HGA contact with the dedicated ground station. A three-axis stabilized ACS is needed both to point at the Sun accurately and to keep the roll about the Sun vector correctly positioned with respect to the solar north pole. This roll control is especially important for the magnetic field imaging of HM I. The mission requirements have several general impacts on the ACS design. Both the AIA and HMI instruments are very sensitive to the blurring caused by jitter. Each has an image stabilization system (ISS) with some ability to filter out high frequency motion, but below the bandwidth of the ISS the control system must compensate for disturbances within the ACS bandwidth or avoid exciting jitter at higher frequencies. Within the ACS bandwidth, the control requirement imposed by AIA is to place the center of the solar disk no more than 2 arc sec, 3 , from a body-defined target based on one of the GTs that accompany the instrument. This body-defined target, called the science reference boresight (SRB), was determined from the postlaunch orientation of the GTs by averaging the bounding telescope boresights for pitch to get a pitch SRB coordinate, and by averaging the bounding boresights for yaw toet the yaw SRB coordinate. The location of this SRB in the 0.5-deg field-of-view for each GT then becomes the central target for each telescope; one GT is selected for use as the ACS controlling guide telescope (CGT) at any given time. Fine Sun-pointing is effected based on this SRB for all three instruments when the Sun is within the linear range of the CGT. In addition to limiting jitter, HMI science requires averaging several observations, making the instrument sensitive to low frequency motion that induces differential motion between each observation. This requires the spacecraft attitude to be stable about the roll axis to approximately 10 arcsec over a ten-minute period. Instrument calibrations require that the spacecraft point the SRB up to 2.5 degrees in pitch and yaw away from the center of the Sun, placing the Sun outside the field-of-view of the guide telescopes. In such instances, when the GTs cannot provide the definitive target for the ACS, on-board attitude determination combined with ephemeris prediction of the Sun direction must provide the definitive target. EVE is capable of observing the Sun with less dependence on attitude control. However, the ground data processing needs for calibrations result in the most strict attitude knowledge requirements for the mission: [35,70,70] arcsec, 3 , of knowledge with respect to the center of the solar disk. In addition to driving the ACS sensor selection, the knowledge requirements, which have their effect primarily during Inertial mode calibrations, drive the accuracy requirements for the solar ephemeris. The need to achieve and maintain geosynchronous orbit (GEO) drove the need for high-efficiency propulsive systems and appropriate attitude control. The main engine provided high specific impulse for the maneuvers to attain GEO, while the smaller ACS thrusters managed the disturbance torques of the larger engine and provided the capability for much smaller adjustment burns on orbit. SDO s large solar profile means that solar radiation pressure is a large torque disturbance, and the momentum buildup from this disturbance and the GEO altitude drives the ACS to use thrusters to manage vehicle momentum. The demanding data capture budget for the mission, however, requires SDO to avoid frequent thruster maneuvers, while concerns about on-orbit jitter restrict the maximum desired wheel speeds desired from the RWAs. The plan for on-orbit wheel speed and momentum management will be discussed as well as what is now being done in operation after the jitter environment was characterized. The SDO ACS hardware complement is single-fault tolerant. Two main processors carry virtually identical copies of the command and data handling and ACS software, and two identical attitude control electronics (ACE) boxes carry Coldfire processors with contingency ACS software and other hardware interface cards; the ACE structure allows reaction wheels to be commanded by the Sun-pointing Safehold independent of the Mil Std 1553 data bus. The sixteen Adcole CSSs are grouped into primary and backup sets of eight sensors, each set providing the ability to calculate a sun vector. Each set of eight eyes provides full 4 -steradian coverage. The Adcole DSS comprises an optics head and a separate electronics box providing a 1553 data interface. The electronics box is mounted inside the Faraday cage created by the spacecraft bus module. The DSS head with its 32- deg square FOV is mounted on the instrument module with its boresight along the spacecraft X axis, nearly aligned with the Sun during observations. Adcole has designed the DSS calibration parameters so that the accuracy is 0.24 arcminutes within 10 deg of the boresight, and diminishes to 3 arcminutes as the Sun moves towards the edges of its FOV . This DSS calibration scheme provides higher accuracy attitude determination over the range of the instrument calibration maneuvers.

Morgenstern, Wendy M.↗

Digital image processing of earth observation sensor data

This paper describes digital image processing techniques that were developed to precisely correct Landsat multispectral earth observation data and gives illustrations of the results achieved, e.g., geometric corrections with an error of less than one picture element, a relative error of one-fourth picture element, and no radiometric error effect. Techniques for enhancing the sensor data, digitally mosaicking multiple scenes, and extracting information are also illustrated.

Bernstein, R.↗

Application of a Near Infrared Imaging System for Thermographic Imaging of the Space Shuttle during Hypersonic Re-Entry

High resolution calibrated near infrared (NIR) imagery was obtained of the Space Shuttle s reentry during STS-119, STS-125, and STS-128 missions. The infrared imagery was collected using a US Navy NP-3D Orion aircraft using a long-range infrared optical package referred to as Cast Glance. The slant ranges between the Space Shuttle and Cast Glance were approximately 26-41 nautical miles at point of closest approach. The Hypersonic Thermodynamic Infrared Measurements (HYTHIRM) project was a NASA Langley led endeavor sponsored by the NASA Engineering Safety Center, the Space Shuttle Program Office and the NASA Aeronautics Research Mission Directorate to demonstrate a quantitative thermal imaging capability. HYTHIRM required several mission tools to acquire the imagery. These tools include pre-mission acquisition simulations of the Shuttle trajectory in relationship to the Cast Glance aircraft flight path, radiance modeling to predict the infrared response of the Shuttle, and post mission analysis tools to process the infrared imagery to quantitative temperature maps. The spatially resolved global thermal measurements made during the Shuttle s hypersonic reentry provides valuable flight data for reducing the uncertainty associated with present day ground-to-flight extrapolation techniques and current state-of-the-art empirical boundary-layer transition or turbulent heating prediction methods. Laminar and turbulent flight data is considered critical for the development of turbulence models supporting NASA s next-generation spacecraft. This paper will provide the motivation and details behind the use of an upgraded NIR imaging system used onboard a Navy Cast Glance aircraft and describe the characterizations and procedures performed to obtain quantitative temperature maps. A brief description and assessment will be provided of the previously used analog NIR camera along with image examples from Shuttle missions STS-121, STS-115, and solar tower test. These thermal observations confirmed the challenge of a long-range acquisition during re-entry. These challenges are due to unknown atmospheric conditions, image saturation, vibration etc. This provides the motivation for the use of a digital NIR sensor. The characterizations performed on the digital NIR sensor included radiometric, spatial, and spectral measurements using blackbody radiation sources and known targets. An assessment of the collected data for three Space Shuttle atmospheric re-entries, STS-119, STS-125, and STS-128, are provided along with a description of various events of interest captured using the digital NIR imaging system such as RCS firings and boundary layer transitions. Lastly the process used to convert the raw image counts to quantitative temperatures is presented along with comparisons to the Space Shuttle's onboard thermocouples.

Zalameda, Joseph N.↗