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At least 1,639 records · Page 91

Decade-Long Ozone Profile Record from Suomi NPP OMPS Limb Profiler: Assessment of Version 2.6 Data

We evaluate a decadal ozone profile record derived from the Suomi National Polar-orbiting Partnership (SNPP) Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) satellite instrument. In 2023, the OMPS LP data were re-processed with the new version 2.6 retrieval algorithm that combines measurements from the ultraviolet (UV) and visible (VIS) parts of the spectra and employs the second order Tikhonov regularization to retrieve a single vertical ozone profile between 12.5 km (or cloud tops) and 57.5 km with the vertical resolution of about 1.9 - 2.5 km between 20-55 km. The algorithm uses radiances measured at six UV ozone-sensitive wavelengths (295, 302, 306, 312, 317 and 322 nm) paired with 353 nm, and one VIS wavelength at 606 nm combined with 510 nm and 675 nm to form a triplet. Each wavelength pair or triplet is used over a limited range of tangent altitudes where the sensitivity to ozone changes are strongest. A new implemented aerosol correction scheme is based on a gamma-function particle size distribution. Numerous calibration changes that affected ozone retrievals were also applied to measured LP radiances, including updates in altitude registration, radiometric calibration, stray light, and spectral registration. The key version 2.6 improvement is the reduction in relative drifts between LP ozone and correlative measurements, linked previously to a drift in the version 2.5 LP altitude registration. We compare LP ozone profiles with those from Aura Microwave Limb Sensor (MLS) to quantify ozone changes in version 2.6.

Limb scattering↗

A Multilayer Dataset of SSM/I-Derived Global Ocean Surface Turbulent Fluxes

A dataset including daily- and monthly-mean turbulent fluxes (momentum, latent heat, and sensible heat) and some relevant parameters over global oceans, derived from the Special Sensor Microwave/Imager (SSM/I) data, for the period July 1987-December 1994 and the 1988-94 annual and monthly-mean climatologies of the same variables is created. It has a spatial resolution of 2.0deg x 2.5deg latitude-longitude. The retrieved surface air humidity is found to be generally accurate as compared to the collocated radiosonde observations over global oceans. The retrieved wind stress and latent heat flux show useful accuracy as verified against research quality measurements of ship and buoy in the western equatorial Pacific. The 1988-94 seasonal-mean wind stress and latent heat flux show reasonable patterns related to seasonal variations of the atmospheric general circulation. The patterns of 1990-93 annual-mean turbulent fluxes and input variables are generally in good agreement with one of the best global analyzed flux datasets that based on COADS (comprehensive ocean-atmosphere data set) with corrections on wind speeds and covered the same period. The retrieved wind speed is generally within +/-1 m/s of the COADS-based, but is stronger by approx. 1-2 m/s in the northern extratropical oceans. The discrepancy is suggested to be mainly due to higher COADS-modified wind speeds resulting from underestimation of anemometer heights. Compared to the COADS-based, the retrieved latent heat flux and sea-air humidity difference are generally larger with significant differences in the trade wind zones and the ocean south of 40degS (up to approx. 40-60 W/sq m and approx. 1-1.5 g/kg). The discrepancy is believed to be mainly caused by higher COADS-based surface air humidity arising from the overestimation of dew point temperatures and from the extrapolation of observed high humidity southward into data-void regions south of 40degS. The retrieved sensible heat flux is generally within +/-5 W/sq m of UWM/COADS, except for some areas in the extratropical oceans, where the differences in wind speed have large impact on the difference in sensible heat flux. The dataset of SSM/I-derived turbulent fluxes is useful for climate studies, forcing of ocean models, and validation of coupled ocean-atmosphere global models.

Chou, Shu-Hsien↗

Evaluation of high temperature superconductive thermal bridges for space borne cryogenic detectors

Infrared sensor satellites are used to monitor the conditions in the earth's upper atmosphere. In these systems, the electronic links connecting the cryogenically cooled infrared detectors to the significantly warmer amplification electronics act as thermal bridges and, consequently, the mission lifetimes of the satellites are limited due to cryogenic evaporation. High-temperature superconductor (HTS) materials have been proposed by researchers at the National Aeronautics and Space Administration Langley's Research Center (NASA-LaRC) as an alternative to the currently used manganin wires for electrical connection. The potential for using HTS films as thermal bridges has provided the motivation for the design and the analysis of a spaceflight experiment to evaluate the performance of this superconductive technology in the space environment. The initial efforts were focused on the preliminary design of the experimental system which allows for the quantitative comparison of superconductive leads with manganin leads, and on the thermal conduction modeling of the proposed system. Most of the HTS materials were indicated to be potential replacements for the manganin wires. In the continuation of this multi-year research, the objectives of this study were to evaluate the sources of heat transfer on the thermal bridges that have been neglected in the preliminary conductive model and then to develop a methodology for the estimation of the thermal conductivities of the HTS thermal bridges in space. The Joule heating created by the electrical current through the manganin wires was incorporated as a volumetric heat source into the manganin conductive model. The radiative heat source on the HTS thermal bridges was determined by performing a separate radiant interchange analysis within a high-T(sub c) superconductor housing area. Both heat sources indicated no significant contribution on the cryogenic heat load, which validates the results obtained in the preliminary conduction model. A methodology was presented for the estimation of the thermal conductivities of the individual HTS thermal bridge materials and the effective thermal conductivities of the composite HTS thermal bridges as functions of temperature. This methodology included a sensitivity analysis and the demonstration of the estimation procedure using simulated data with added random errors. The thermal conductivities could not be estimated as functions of temperature; thus the effective thermal conductivities of the HTS thermal bridges were analyzed as constants.

Scott, Elaine P.↗

Global Precipitation Measurement (GPM) Mission: Overview and Status

The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. NASA and JAXA will deploy a Core Observatory in 2014 to serve as a reference satellite to unify precipitation measurements from the constellation of sensors. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The DPR will be the first dual-frequency radar in space to provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles. The DPR and GMI measurements will together provide a database that relates vertical hydrometeor profiles to multi-frequency microwave radiances over a variety of environmental conditions across the globe. This combined database will be used as a common transfer standard for improving the accuracy and consistency of precipitation retrievals from all constellation radiometers. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NASA or JAXA. Each constellation member may have its unique scientific or operational objectives but contributes microwave observations to GPM for the generation and dissemination of unified global precipitation data products. In addition to the DPR and GMI on the Core Observatory, the baseline GPM constellation consists of the following sensors: (1) Special Sensor Microwave Imager/Sounder (SSMIS) instruments on the U.S. Defense Meteorological Satellite Program (DMSP) satellites, (2) the Advanced Microwave Scanning Radiometer-2 (AMSR-2) on the GCOM-W1 satellite of JAXA, (3) the Multi-Frequency Microwave Scanning Radiometer (MADRAS) and the multi-channel microwave humidity sounder (SAPHIR) on the French-Indian MeghaTropiques satellite, (4) the Microwave Humidity Sounder (MHS) on the National Oceanic and Atmospheric Administration (NOAA)-19, (5) MHS instruments on MetOp satellites launched by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), (6) the Advanced Technology Microwave Sounder (ATMS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), and (7) ATMS instruments on the NOAA-NASA Joint Polar Satellite System (JPSS) satellites. Data from Chinese and Russian microwave radiometers may also become available through international collaboration under the auspices of the Committee on Earth Observation Satellites (CEOS) and Group on Earth Observations (GEO). The current generation of global rainfall products combines observations from a network of uncoordinated satellite missions using a variety of merging techniques. GPM will provide "next-generation" precipitation products characterized by: (1) more accurate instantaneous precipitation estimate (especially for light rain and cold-season solid precipitation), (2) intercalibrated microwave brightness temperatures from constellation radiometers within a consistent framework, and (3) unified precipitation retrievals from constellation radiometers using a common a priori hydrometeor database constrained by combined radar/radiometer measurements provided by the GPM Core Observatory. GPM is a science mission with integrated applications goals. GPM will provide a key measurement to improve understanding of global water cycle variability and freshwater availability in a changing climate. The DPR and GMI measurements will offer insights into 3-dimensional structures of hurricanes and midlatitude storms, microphysical properties of precipitating particles, and latent heat associated with precipitation processes. The GPM mission will also make data available in near realtime (within 3 hours of observations) forocietal applications ranging from position fixes of storm centers, numerical weather prediction, flood forecasting, freshwater management, landslide warning, crop prediction, to tracking of water-borne diseases. An overview of the GPM mission design, retrieval strategy, ground validation activities, and international science collaboration will be presented.

Hou, Arthur Y.↗

Simultaneous Retrieval of Selected Optical Water Quality Indicators From Landsat-8, Sentinel-2, and Sentinel-3

Constructing multi-source satellite-derived water quality (WQ) products in inland and nearshore coastal waters from the past, present, and future missions is a long-standing challenge. Despite inherent differences in sensors’ spectral capability, spatial sampling, and radiometric performance, research efforts focused on formulating, implementing, and validating universal WQ algorithms continue to evolve. This research extends a recently developed machine-learning (ML) model, i.e., Mixture Density Networks (MDNs) (Pahlevan et al., 2020; Smith et al., 2021), to the inverse problem of simultaneously retrieving WQ indicators, including chlorophyll-a (Chla), Total Suspended Solids (TSS), and the absorption by Colored Dissolved Organic Matter at 440 nm (a cdom (440)), across a wide array of aquatic ecosystems. We use a database of in situ measurements to train and optimize MDN models developed for the relevant spectral measurements (400–800 nm) of the Operational Land Imager (OLI), MultiSpectral Instrument (MSI), and Ocean and Land Color Instrument (OLCI) aboard the Landsat-8, Sentinel-2, and Sentinel-3 missions, respectively. Our two performance assessment approaches, namely hold-out and leave-one-out, suggest significant, albeit varying degrees of improvements with respect to second-best algorithms, depending on the sensor and WQ indicator (e.g., 68%, 75%, 117% improvements based on the hold-out method for Chla, TSS, and a cdom (440), respectively from MSI-like spectra). Using these two assessment methods, we provide theoretical upper and lower bounds on model performance when evaluating similar and/or out-of-sample datasets. To evaluate multi-mission product consistency across broad spatial scales, map products are demonstrated for three near-concurrent OLI, MSI, and OLCI acquisitions. Overall, estimated TSS and a cdom (440) from these three missions are consistent within the uncertainty of the model, but Chla maps from MSI and OLCI achieve greater accuracy than those from OLI. By applying two different atmospheric correction processors to OLI and MSI images, we also conduct matchup analyses to quantify the sensitivity of the MDN model and best-practice algorithms to uncertainties in reflectance products. Our model is less or equally sensitive to these uncertainties compared to other algorithms. Recognizing their uncertainties, MDN models can be applied as a global algorithm to enable harmonized retrievals of Chla, TSS, and a cdom (440) in various aquatic ecosystems from multi-source satellite imagery. Local and/or regional ML models tuned with an apt data distribution (e.g., a subset of our dataset) should nevertheless be expected to outperform our global model.

Machine learning↗

Quantification of Plume-Soil Interaction and Excavation Due to the Sky Crane Descent Stage

The quantification of the particulate erosion that occurs as a result of a rocket exhaust plume impinging on soil during extraterrestrial landings is critical for future robotic and human lander mission design. The aerodynamic environment that results from the reflected plumes results in dust lifting, site alteration and saltation, all of which create a potentially erosive and contaminant heavy environment for the lander vehicle and any surrounding structures. The Mars Science Lab (MSL), weighing nearly one metric ton, required higher levels of thrust from its retro propulsive systems and an entirely new descent system to minimize these effects. In this work we seek to quantify plume soil interaction and its resultant soil erosion caused by the MSL's Sky Crane descent stage engines by performing three dimensional digital terrain and elevation mapping of the Curiosity rover's landing site. Analysis of plume soil interaction altitude and time was performed by detailed examination of the Mars Descent Imager (MARDI) still frames and reconstructed inertial measurement unit (IMU) sensor data. Results show initial plume soil interaction from the Sky Crane's eight engines began at ground elevations greater than 60 meters and more than 25 seconds before the rovers' touchdown event. During this time, viscous shear erosion (VSE) was dominant typically resulting in dusting of the surface with flow propagating nearly parallel to the surface. As the vehicle descended and decreased to four powered engines plume-plume and plume soil interaction increased the overall erosion rate at the surface. Visibility was greatly reduced at a height of roughly 20 meters above the surface and fell to zero ground visibility shortly after. The deployment phase of the Sky Crane descent stage hovering at nearly six meters above the surface showed the greatest amount of erosion with several large particles of soil being kicked up, recirculated, and impacting the bottom of the rover chassis. Image data obtained from MSL's navigation camera (NAVCAM) pairs on Sols 002, 003, and 016 were used to virtually recreate local surface topography and features around the rover by means of stereoscopic depth mapping. Images taken simultaneously by the left and right navigation cameras located on the rover's mast assembly spaced 42 centimeters were used to generate a three dimensional depth map from flat, two dimensional images of the same feature at slightly different angles. Image calibration with physical hardware on the rover and known terrain features were used to provide scaling information that accurately sizes features and regions of interest within the images. Digital terrain mapping analysis performed in this work describe the crater geometry (shape, radius, and depth), eroded volume, volumetric erosion rate, and estimated mass erosion rate of the Hepburn, Sleepy Dragon, Burnside, and Goulburn craters. Crater depths ranged from five to ten centimeters deep influencing an area as wide as two meters in some cases. The craters formed were highly asymmetrical and generally oblong primarily due to the underlying bedrock formations underneath the surface. Comparison with ground tests performed at the NASA AMES Planetary Aeolian Laboratory (PAL) by Mehta showed good agreement with volumetric erosion rates and crater sizes of large particle soil simulants, providing validation to Earth based ground tests of Martian regolith.

Vizcaino, Jeffrey↗

Spreader-Bar Radiation Detection System Enhancements: A Modeling and Simulation Study

An investigation of radiation detectors on crane-mounted platforms was performed to understand the limitations and optimal capability of these types of systems. Crane-mounted systems are primarily focused on crane-mounted radiation detector systems, where the detectors are mounted on a spreader-bar platform. Spreader bars are attached with cables to a crane at seaports to load and unload containers from cargo ships. The bars can spread from 20 feet to 53 feet using hydraulics, allowing a single bar to move a variety of container lengths. Spreader-bars are also used on straddle carriers, which move containers around the laydown yard in the port. Spreader bar radiation detection (SBRD) systems are commercially available from at least two companies. These systems employ a set of spectroscopic sensors placed on the underside of a gantry crane and held near the top of a cargo container for detection. These systems have been previously tested and some issues and limitations observed. Radiation detectors mounted on spreader-bars are single sided systems (observing cargo only from the top) and it is therefore challenging to obtain the same sensitivity as double-sided systems (for example, portal monitors) especially when considering the possible amounts of intervening cargo that could be present. The approximately exponential attenuation of gamma rays in intervening dense cargo presents an inherent limitation to detection. However, SBRD systems hold detectors closer to the container, have a longer dwell time, and may have lower background (over the ship); all of these aspects help mitigate the single-sided issue. In addition, there are operational considerations that make spreader-bar radiation systems attractive. These include scanning for radiation during other operations (loading, unloading or container movement) which minimizes additional time for scanning, incorporating the radiation detection into existing equipment to minimize initial cost, and in the case of ship unloading, scanning the containers before reaching the laydown yard. This study is focused on researching optimized configurations of SBRD systems, including number of detectors, locations, and best use of detector data, to determine a reasonable limit on the capability of these types of systems. The results will help support decisions on where and how these systems might be effectively deployed, and could be used for future specification development for SBRD acquisition. The next phase of this research and investigation into SBRD systems and quantification of the possible improved capability with an enhanced SBRD is the focus of this report. Supporting this investigation, detailed models of an enhanced SBRD system were created using a 3D radiation transport code, and models were run to simulate the data from sources and background for a realistic cargo-loading port environment. The enhanced SBRD had increased detector material (numbers of detectors) compared to the commercial systems, with a distribution providing more uniform coverage. Measurements using small industrial sources were made with an enhanced SBRD system developed by Sandia National Laboratory to support model validation to establish credibility for the simulations of these threat and background scenarios. A significant simulation effort was undertaken to simulate sources of interest within a 40-foot cargo container. In order to estimate the performance of a generalized SBRD system in scenarios including background and cargo, a highly enriched uranium (HEU) test source (with 3x10 -8 232 U by weight) within a wood cargo model was simulated for a 40-foot cargo container. This source was placed at a variety of locations, and the flux from the source was multiplied as necessary to create estimated minimal detectable quantities (MDQ) figures for various quantities of HEU. Simulated data sets were produced corresponding to a complete container offloading scenario for a large number of statistical realizations. Significant work was performed on both the algorithm development and the container cargo distributions entering the US, and the result of this modeling, validation, and simulation effort was a set of estimates of the performance of a variety of radiation detection algorithms in this cargo-screening environment. In the case of algorithms, a variety of contemporary radiation detection and identification approaches were employed, and the optimal approaches to selecting time and location subsets of detector data were explored. In all cases, algorithm performance was compared, and the best approaches were suggested along with the best expected performance from the enhanced SBRD. In general, template-matching schemes employing a limited set of regression parameters tend to provide best results. The improvements of an enhanced SBRD with increased detector material and improved algorithms result in an effective MDQ of 10 kg of HEU in ~50 percent of the imported cargo in 40-foot containers, assuming a random source location. This is approximately two times the capability of the estimated performance of the commercial systems. For an MDQ of the 10 kg HEU source located in the worst location (bottom of the 40-foot container), the volume of cargo scanned drops to 10% for the enhanced SBRD, again a factor of two or more larger than the commercial systems. Enhancing the SBRD systems by adding more detectors, providing a more uniform coverage, and incorporating more advanced algorithms will result in a significant increase in capability. Although this investigation provided some indication of the performance capabilities of an enhanced SBRD system, additional work is needed to estimate the capability for other container configurations, such as the 20 and 45 foot containers. Since the 20-foot container weight limit is similar to the 40-foot, more dense cargo is typically shipped in 20-foot containers. This will result in a smaller percentage of cargo scanned for the 20-foot containers (for a particular source quantity) compared to the 40-foot containers. In addition to other configuration, other source material needs to be investigated to understand the capabilities for the entire threat space, where only HEU is considered in this work.

crane-mounted↗

Simplified Vicarious Radiometric Calibration

A measurement-based radiance estimation approach for vicarious radiometric calibration of spaceborne multispectral remote sensing systems has been developed. This simplified process eliminates the use of radiative transfer codes and reduces the number of atmospheric assumptions required to perform sensor calibrations. Like prior approaches, the simplified method involves the collection of ground truth data coincident with the overpass of the remote sensing system being calibrated, but this approach differs from the prior techniques in both the nature of the data collected and the manner in which the data are processed. In traditional vicarious radiometric calibration, ground truth data are gathered using ground-viewing spectroradiometers and one or more sun photometer( s), among other instruments, located at a ground target area. The measured data from the ground-based instruments are used in radiative transfer models to estimate the top-of-atmosphere (TOA) target radiances at the time of satellite overpass. These TOA radiances are compared with the satellite sensor readings to radiometrically calibrate the sensor. Traditional vicarious radiometric calibration methods require that an atmospheric model be defined such that the ground-based observations of solar transmission and diffuse-to-global ratios are in close agreement with the radiative transfer code estimation of these parameters. This process is labor-intensive and complex, and can be prone to errors. The errors can be compounded because of approximations in the model and inaccurate assumptions about the radiative coupling between the atmosphere and the terrain. The errors can increase the uncertainty of the TOA radiance estimates used to perform the radiometric calibration. In comparison, the simplified approach does not use atmospheric radiative transfer models and involves fewer assumptions concerning the radiative transfer properties of the atmosphere. This new technique uses two neighboring uniform ground target areas having different reflectance values. The target areas can be natural or artificial and must be large enough to minimize adjacent-pixel contamination effects. The radiative coupling between the atmosphere and the terrain needs to be approximately the same for the two targets. This condition can be met for relatively uniform backgrounds when the distance between the targets is within a few hundred meters. For each target area, the radiance leaving the ground in the direction of the satellite is measured with a radiometrically calibrated spectroradiometer. Using the radiance measurements from the two targets, atmospheric adjacency and atmospheric scattering effects can be subtracted, thereby eliminating many assumptions about the atmosphere and the radiative interaction between the atmosphere and the terrain. In addition, the radiometrically calibrated spectroradiometer can be used with a known reflectance target to estimate atmospheric transmission and diffuse- to-global ratios without the need for ancillary sun photometers. Several comparisons between the simplified method and traditional techniques were found to agree within a few percent. Hence, the simplified method reduces the overall complexity of performing vicarious calibrations and can serve as a method for validating traditional radiative transfer models

Stanley, Thomas↗

Pressure-Fed LOX/LCH4 Reaction Control System for Spacecraft: Transient Modeling and Thermal Vacuum Hotfire Test Results

An integrated cryogenic liquid oxygen, liquid methane (LOX/LCH4) reaction control system (RCS) was tested at NASA Glenn Research Center's Plum Brook Station in the Spacecraft Propulsion Research Facility (B-2) under vacuum and thermal vacuum conditions. The RCS is a subsystem of the Integrated Cryogenic Propulsion Test Article (ICPTA), a pressure-fed LOX/LCH4 propulsion system composed of a single 2,800 lbf main engine, two 28 lbf RCS engines, and two 7 lbf RCS engines. Propellants are stored in four 48 inch diameter 5083 aluminum tanks that feed both the main engine and RCS engines in parallel. Helium stored cryogenically in a composite overwrapped pressure vessel (COPV) flows through a heat exchanger on the main engine before being used to pressurize the propellant tanks to a design operating pressure of 325 psi. The ICPTA is capable of simultaneous main engine and RCS operation. The RCS engines utilize a coil-on-plug (COP) ignition system designed for operation in a vacuum environment, eliminating corona discharge issues associated with a high voltage lead. There are two RCS pods on the ICPTA, with two engines on each pod. One of these two engines is a heritage flight engine from Project Morpheus. Its sea level nozzle was removed and replaced by an 85:1 nozzle machined using Inconel 718, resulting in a maximum thrust of 28 lbf under altitude conditions. The other engine is a scaled down version of the 28 lbf engine, designed to match the core and overall mixture ratios as well as other injector characteristics. This engine can produce a maximum thrust of 7 lbf with an 85:1 nozzle that was additively manufactured using Inconel 718. Both engines are film-cooled and capable of limited duration gas-gas and gas-liquid operation, as well as steady-state liquid-liquid operation. Each pod contains one of each version, such that two engines of the same thrust level can be fired as a couple on opposite pods. The RCS feed system is composed of symmetrical 3/8 inch lines that tap off of the main propellant manifold to send LOX and LCH4 outboard to the RCS pods. A Thermodynamic Vent System (TVS) is used to condition propellants at each pod by venting through an orifice and then routing the cold expansion products back through tubing that is welded along a large portion of the main RCS feed lines. Prior to final installation on the ICPTA, the RCS engines were tested in a small vacuum chamber at the Johnson Space Center (JSC) Energy Systems Test Area (ESTA) to verify functionality of the new COP ignition system and check out operation of the vacuum nozzles. After engine-level testing, the RCS engines were installed on the vehicle and a series of integrated hot-fire tests were performed at JSC consisting of various pulsing and steady-state firings as well as integrated main engine/RCS operation. The ICPTA was then integrated into the Plum Brook B-2 facility for vacuum and thermal/vacuum testing. Testing in the B-2 facility was composed of multiple thermal and pressure environments. The first set of tests were performed under ambient temperature and altitude pressure conditions. These tests consisted of a range of minimum impulse bit (MIB) pulsing sequences with low duty cycle, analogous to a coast phase in which the RCS is primarily used for station keeping. The primary goal of this sequence is to understand how propellant conditions were effected without an active TVS. In this scenario, consistent gas-gas operation is desirable since it results in a smaller MIB and more efficient propellant consumption. Multiple skin thermocouples are mounted on the feedlines, in addition to a submerged thermocouple on each commodity, in order to gather thermal data on the system. Higher duty cycle pulsing tests were then performed, analogous to an ascent or landing mission phase. The primary goal of this sequence was to examine how well the engines self-conditioned without active TVS when starting from a quiescent state. The TVS was then activated during some tests to demonstrate the capability to quickly condition the engines for higher pulsing demand scenarios. A thermocouple at the TVS outlet allows for the calculation of energy absorbed by the vented propellant. Lastly, tests with longer pulses and multiple engines firing either in sequence or simultaneously were run in order to gather transient system response data on waterhammer. Six total high-speed pressure transducers are installed on the RCS system, one sensor at the end of each propellant manifold line on the pods, and one at the tap-off location for each commodity. This will allow for the accurate characterization of waterhammer in the system under various propellant conditions and firing sequences. Other instrumentation for this test series includes nozzle throat thermocouples, chamber pressure measurement, heat soakback measurement, and tank wall plume impingement temperature measurement. The next set of tests were performed to demonstrate simultaneous main engine and RCS operation. Data from this test will be used to examine if there is any change to nominal operation of the RCS as a result of feed system interaction or other phenomenon. Some of these tests began under high vacuum conditions (target ambient pressure less than 1x10(exp -3) torr) and others began at altitude conditions. The last set of tests were performed with the B-2 cold wall active. Under these tests, many of the same low duty cycle MIB tests were repeated in order to characterize how propellant conditions changed with the lower heat leak. In this scenario the RCS manifold experiences much less heat leak, resulting in a change to how well the engines self-condition. As a result, an increase in maximum waterhammer pressures and a change in natural frequency of the system was expected due to higher density propellants. The lower heat leak should also result in a change to the MIB pulse profile, and data will be examined to understand how MIB repeatability is affected in the different operating environments. Parallel to the test efforts, a set of transient model development efforts were made to predict RCS performance. The primary effort was aimed at producing a SINDA/FLUINT model to predict propellant conditioning up to the engine inlet as a function of different environmental and operating parameters, with the goal of predicting chamber pressure, TVS performance, and propellant consumption over time. Preliminary results for this effort will be presented in comparison with test data. Additional modeling efforts were made using SINDA/FLUINT to predict waterhammer in the system since the software is capable of handling multiphase transient fluid dynamics. These results will be compared with the high-speed pressure transducer test data for validation purposes.

Atwell, Matthew J.↗

State-of-the-Art: Small Spacecraft Technology

When the first edition of NASA’s Small Spacecraft Technology State-of-the-art report was published in 2013, 247 CubeSats and 105 other non-CubeSat small spacecraft under 50 kilograms (kg) had been launched worldwide, representing less than 2% of launched mass into orbit over multiple years. In 2013 alone, around 60% of the total spacecraft launched had a mass under 600 kg, and of those under 600 kg, 83% were under 200 kg and 37% were nanosatellites (1). Of the total 1,849 spacecraft launched in 2021, 94% were small spacecraft with an overall mass under 600 kg, and of those under 600 kg, 40% were under 200 kg, and 11% were nanosatellites (1). Since 2013, the fight heritage for small spacecraft has increased by over 30% and has become the primary source to space access for commercial, government, private, and academic institutions. The total number of spacecraft launched in the past 10 years is 5,681 and 45% of those had a mass. As with all previous editions of this report, the 2022 edition captures and distills a wealth of new information available on small spacecraft systems from NASA and other publicly available sources. This report is limited to publicly available information and cannot reflect major advances in development that are not publicly disclosed. We encourage any opportunity to publish mission outcomes and technology development milestones (e.g., via conference papers, press releases, company website) so they can be reflected in this report. Overall, this report is a survey of small spacecraft technologies sourced from open literature; it does not endeavor to be an original source, and only considers literature in the public domain to identify and classify devices. Commonly used sources for data include manufacturer datasheets, press releases, conference papers, journal papers, public filings with government agencies, news articles, presentations, the compendium of databases accessed via NASA’s Small Spacecraft Systems Virtual Institute (S3VI) Information Search, and engagement with companies. Data not appropriate for public dissemination, such as proprietary, export controlled, or otherwise restricted data, are not considered. As a result, this report includes many dedicated hours of desk research performed by subject matter experts reviewing resources noted above. Content in this 2022 edition is based on data available by October 2022. This report should not be considered as a comprehensive overview of all the technologies but a great reference for the current state-of-the-art SmallSat technologies. The organizational approach for each chapter is relatively consistent with previous editions and includes an introduction of the technology, current development status of the technology’s procurable systems, and summary tables of technologies surveyed. The content in each chapter is uniquely organized to present a mini-stand-alone report on spacecraft subsystems. As in previous years, chapters include information from previous editions but are updated with new and maturating technologies and reference missions. Tables in each section provide a convenient summary of the technologies discussed, with explanations and references in the body text. The authors have attempted to isolate trends in the small spacecraft industry to point out which technologies have been adopted after successful demonstration missions. Lastly, the authors tried to use the terms “SmallSat,” “microsatellite,” “nanosatellite,” and “CubeSat” in a consistent manner, even as these terms are often used interchangeably in the space industry. Every subsystem chapter contains updated information to reflect the growth in the small spacecraft market. Significant changes are included in several chapters. The “Complete Spacecraft Platforms” chapter now includes information on the two main market options, hosted payload services and dedicated buses. The “Power” chapter provides information on the development of solid-state batteries with significantly higher energy than the current state-of-theart lithium-ion batteries. A large effort was made to update the “Communications” chapter to appropriately capture the recent technology maturation of optical communications for SmallSats. The “Ground Data Systems and Mission Operations” chapter was updated to reflect the recent establishment of the Near Space Network and influx of SmallSat Optical Ground Stations. The “Guidance, Navigation and Control” chapter was updated to include Lidar sensor technology. The “Deorbit Systems” chapter includes a discussion of recently proposed changes by the Federal Communications Commission (FCC) to limit a spacecraft’s lifetime to no longer than 5 years after end-of-mission. The “Identification and Tracking” Chapter includes updated information on the progress of SmallSat tracking. Finally, this report now encompasses technology funded by NASA’s Small Spacecraft Technology (SST) program’s SmallSat Technology Partnerships (STP) initiative which is described further in this Introduction. The reader can find the included SST technology in the “On the Horizon” section of the “Thermal Systems”, “Communications”, and “Guidance, Navigation, and Control” chapters. A central element of this report is to list state-of-the-art technologies by NASA standard Technology Readiness Level (TRL) as defined by the 2020 NASA Engineering Handbook, found in NASA NPR 7123.1C NASA Systems Engineering Processes and Requirements. The authors have endeavored to independently verify the TRL value of each technology by reviewing and citing published test results or publicly available data to the best of their ability. Where test results and data disagree with vendors’ own advertised TRL, the authors have attempted to engage the vendors to discuss the discrepancy. Readers are strongly encouraged to follow the references cited in the literature describing the full performance range and capabilities of each technology. Readers of this report should reach out to individual companies to further clarify information. It is important to note that this report takes a broad system-level view. To attain a high TRL, the subsystem must be in a flight-ready configuration with all supporting infrastructure—such as mounting points, power conversion, and control algorithms—in an integrated unit. An accurate TRL assessment requires a high degree of technical knowledge on a subject device, and an in-depth understanding of the mission (including interfaces and environment) on which the device was flown. There is variability in TRL values depending on design factors for a specific technology. For example, differences in TRL assessment based on the operating environment may result from the thermal environment, mechanical loads, mission duration, or radiation exposure. If a technology has flown on a mission without success, or without providing valid confirmation to the operator, such claimed “flight heritage” was discounted. The authors believe TRLs are most accurately determined when assessed within the context of a program’s unique requirements. While the overall capability of small spacecraft has matured since the 2021 edition of this report, technologies are still being developed to make deep space SmallSat missions more routine and more cost effective. Future editions of this report may include content dedicated to the rapidly growing fields of assembly, integration, and testing services, and mission modeling and simulation–all of which are now extensively represented at small spacecraft conferences. Many of these subsystems and services are still in their infancy, but as they evolve and reliable conventions and standards emerge, the next iteration of this report may also evolve to include additional chapters.

Bruce Yost↗

All-digital Sensor System for Distributed Downhole Pressure Monitoring in Unconventional Fields

This project developed and validated (through field tests) a new low-cost all-digital pressure sensing technology for in situ distributed downhole pressure monitoring in unconventional oil and gas (UOG) fields. The all-digital sensing technology uses a built-in non-electric analog-to-digital converter (ADC) to transform the pressure information into a combination of binary (ON/OFF) states. As such, the system does not need downhole electronics for signal conditioning and telemetry. The all-digital sensors can be remotely logged over a long distance, and many sensors can be multiplexed for distributed sensing. Based on a review of unconventional wells in the Lower 48 states, the specification of the sensor is to measure pressure up to 69 MPa (10,000 psi) and temperature up to 250°C. A sensor with a helical bourdon sensing element and a digital signal decoder of 50 mm diameter and 109 mm length was constructed. The helical bourdon sensing element was made of 304L stainless steel and filled with motor oil. The digital converter was made up of 8 digital reading pads constructed of high-temperature epoxy with conductive inserts made of stainless steel. The sensor had a linear response to pressure with an accuracy of 0.14 MPa (20 psi). To withstand the high pressure, the sensor was enclosed in a stainless-steel pressure housing with a wall thickness of 5.5 mm, a diameter of 73 mm, and a length of 724 mm. In the laboratory tests, the sensor exhibited no temperature-related effects on the results. The sensor did not show drift over a 14-day test period at elevated pressure. A field test was conducted where the sensor was deployed in a test wellbore at the Quest drilling test facility to a depth of 0 feet over three weeks. The sensor was attached to the production rods, along with a downhole reference sensor of PPS27 type, which is a permanent downhole monitoring system. During the testing phase, the test well annular blow-out preventer was closed, and the well was pressurized at the surface to 11 MPa (1600 psi). The sensor read the elevated bottom hole pressure of 1500 psi. A multiplexing unit was created for the sensor to deploy multiple sensors on one data transmission line in a distributed approach. The multiplexing unit was tested in a simulated environment of 3048 m (10,000 ft) with five sensors distributed. The sensors were pressurized at different intervals. The multiplexed sensors recorded the correct pressure, and the multiplexing did not interfere with the readings. The proposed concept of an all-digital pressure sensor for harsh downhole environments was designed, manufactured, and tested in the laboratory and tested at the field to a up to 69 MPa and 250°C. This technology has high-temperature tolerance and has potential in downhole areas outside oil and gas, such as carbon capture and storage (CCS) and geothermal wells. The sensor concept has been proven in this project, but to create a commercially viable product, manufacturing a sensor with a smaller diameter needs to be performed.

02 PETROLEUM↗

Development of an Inertial Sensor-based Methodology for Spacesuited Geology Task Assessments during Simulated Lunar Extravehicular Activities

Lunar surface exploration during Artemis missions will require the specific skill set of geology sampling. Apollo astronauts had extensive training and used specialized tools to collect lunar rocks, core samples, pebbles, sand, and dust. The inflexibility of the pressurized Apollo spacesuits forced sampling to be taken at a standstill posture. However, new exploration spacesuits are expected to incorporate advanced materials and joint bearings, allowing for greater mobility and a wider range of functional postures. Thus, science and exploration during Artemis missions will likely involve a variety of standing, squatting, and kneeling postures. In preparation for future lunar exploration missions, NASA provides geologic training to astronauts and other mission personnel. This professional training with a spacesuit in simulated lunar environments will enhance performance and reduce risk of injury to astronauts on the lunar surface. However, anecdotally, untrained or newly trained people wearing prototype planetary spacesuits have been observed to performing motions differently than a trained geologist would when conducting the same geology sampling tasks. Therefore, a tool for evaluating geology postures at extravehicular activity (EVA) training facilities becomes required. In this paper, we introduce a novel inertial measurement unit (IMU)-based method of geology task assessments in spacesuited conditions during simulated lunar EVAs. As a case study, two subjects (one geologist and one non-geologist) participated and donned the Mark III prototype planetary spacesuit during offloading with the spreader bar gimbal in NASA’s Active Response Gravity Offload System (ARGOS). For automated geology task assessments, the spacesuit was instrumented with three wireless IMUs (APDM Opal, OR, USA): one on the chest and one each on the left and right ankle bearings. Then subjects performed geology tasks using various tools (rake, trench, hammer chisel, scoop, and drive tube) for 45 minutes each. The chest IMU measured the torso tilt angle in the sagittal plane. We used an ensemble learning method with the ankle IMUs to discriminate between standing and kneeling activities. IMU data were processed using custom MATLAB (Mathworks, MA, USA) software. In our case study, the developed method was able to discriminate differences in standing and kneeling activity levels between subjects who were all highly experienced with spacesuited testing. Our preliminary data showed one subject maintained the constant and lower range of the upper body tilt angle while both standing and kneeling, while the other subject showed more variation of the upper body tilt angle and preferred bending the upper body rather than changing from standing to kneeling posture and vice versa. While geology experience may be a factor, these results need further investigation as suit sizing and ARGOS offloading configurations have been proven to have a significant influence on suited ARGOS tasks. Also, more subjects will be needed to complete these tasks for validation. IMU-based geology task assessments can provide useful information for geology training programs. Additionally, our IMU-based posture analysis can provide new insights into how to evaluate spacesuited geology task characteristics of astronauts during simulated lunar EVAs.

Kyoung Jae Kim↗

The Suomi National Polar-Orbiting Partnership (SNPP): Continuing NASA Research and Applications

The Suomi National Polar-orbiting Partnership (SNPP) satellite was successfully launched into a polar orbit on October 28, 2011 carrying 5 remote sensing instruments designed to provide data to improve weather forecasts and to increase understanding of long-term climate change. SNPP provides operational continuity of satellite-based observations for NOAA's Polar-orbiting Operational Environmental Satellites (POES) and continues the long-term record of climate quality observations established by NASA's Earth Observing System (EOS) satellites. In the 2003 to 2011 pre-launch timeframe, NASA's SNPP Science Team assessed the adequacy of the operational Raw Data Records (RDRs), Sensor Data Records (SDRs), and Environmental Data Records (EDRs) from the SNPP instruments for use in NASA Earth Science research, examined the operational algorithms used to produce those data records, and proposed a path forward for the production of climate quality products from SNPP. In order to perform these tasks, a distributed data system, the NASA Science Data Segment (SDS), ingested RDRs, SDRs, and EDRs from the NOAA Archive and Distribution and Interface Data Processing Segments, ADS and IDPS, respectively. The SDS also obtained operational algorithms for evaluation purposes from the NOAA Government Resource for Algorithm Verification, Independent Testing and Evaluation (GRAVITE). Within the NASA SDS, five Product Evaluation and Test Elements (PEATEs) received, ingested, and stored data and performed NASA's data processing, evaluation, and analysis activities. The distributed nature of this data distribution system was established by physically housing each PEATE within one of five Climate Analysis Research Systems (CARS) located at either at a NASA or a university institution. The CARS were organized around 5 key EDRs directly in support of the following NASA Earth Science focus areas: atmospheric sounding, ocean, land, ozone, and atmospheric composition products. The PEATES provided the system level interface with members of the NASA SNPP Science Team and other science investigators within each CARS. A sixth Earth Radiation Budget CARS was established at NASA Langley Research Center (NASA LaRC) to support instrument performance, data evaluation, and analysis for the SNPP Clouds and the Earth's Radiant Budget Energy System (CERES) instrument. Following the 2011 launch of SNPP, spacecraft commissioning, and instrument activation, the NASA SNPP Science Team evaluated the operational RDRs, SDRs, and EDRs produced by the NOAA ADS and IDPS. A key part in that evaluation was the NASA Science Team's independent processing of operational RDRs and SDRs to EDRs using the latest NASA science algorithms. The NASA science evaluation was completed in the December 2012 to April 2014 timeframe with the release of a series of NASA Science Team Discipline Reports. In summary, these reports indicated that the RDRs produced by the SNPP instruments were of sufficiently high quality to be used to create data products suitable for NASA Earth System science and applications. However, the quality of the SDRs and EDRs were found to vary greatly when considering suitability for NASA science. The need for improvements in operational algorithms, adoption of different algorithmic approaches, greater monitoring of on-orbit instrument calibration, greater attention to data product validation, and data reprocessing were prominent findings in the reports. In response to these findings, NASA, in late 2013, directed the NASA SNPP Science Team to use SNPP instrument data to develop data products of sufficiently high quality to enable the continuation of EOS time series data records and to develop innovative, practical applications of SNPP data. This direction necessitated a transition of the SDS data system from its pre-launch assessment mode to one of full data processing and production. To do this, the PEATES, which served as NASA's data product testing environment during the prelaunch and early on-orbit periods, were transitioned to Science Investigator-led Processing Systems (SIPS). The distributed data architecture was maintained in this new system by locating the SIPS at the same institutions at which the CARS and PEATES were located. The SIPS acquire raw SNPP instrument Level 0 (i.e. RDR) data over the full SNPP mission from the NOAA ADS and IDPS through the NASA SDS Data Distribution and Depository Element (SD3E). The SIPS process those data into NASA Level 1, Level 2, and global, gridded Level 3 standard products using peer-reviewed algorithms provided by members of the NASA Science Team. The SIPS work with the NASA SNPP Science Team in obtaining enhanced, refined, or alternate real-time algorithms to support the capabilities of the Direct Readout Laboratory (DRL). All data products, algorithm source codes, coefficients, and auxiliary data used in product generation are archived in an assigned NASA Distributed Active Archive Center (DAAC).

remote sensing↗

The Collection 6 'dark-target' MODIS Aerosol Products

Aerosol retrieval algorithms are applied to Moderate resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua, creating two streams of decade-plus aerosol information. Products of aerosol optical depth (AOD) and aerosol size are used for many applications, but the primary concern is that these global products are comprehensive and consistent enough for use in climate studies. One of our major customers is the international modeling comparison study known as AEROCOM, which relies on the MODIS data as a benchmark. In order to keep up with the needs of AEROCOM and other MODIS data users, while utilizing new science and tools, we have improved the algorithms and products. The code, and the associated products, will be known as Collection 6 (C6). While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. In its entirety, the C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties over different surfaces: These include the dark-target DT algorithms to retrieve over (1) ocean and (2) vegetated-dark-soiled land, plus the (3) Deep Blue (DB) algorithm, originally developed to retrieve over desert-arid land. Focusing on the two DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to 84) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such as topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time as we have introduced algorithm changes, we have also accounted for upstream changes including: new instrument calibration, revised land-sea masking, and changed cloud masking. Upstream changes also impact the coverage and global statistics of the retrieved AOD. Although our responsibility is to the DT code and products, we have also added a product that merges DT and DB product over semi-arid land surfaces to provide a more gap-free dataset, primarily for visualization purposes. Preliminary validation shows that compared to surface-based sunphotometer data, the C6, Level 2 (along swath) DT-products compare at least as well as those from C5. C6 will include new diagnostic information about clouds in the aerosol field, including an aerosol cloud mask at 500 m resolution, and calculations of the distance to the nearest cloud from clear pixels. Finally, we have revised the strategy for aggregating and averaging the Level 2 (swath) data to become Level 3 (gridded) data. All together, the changes to the DT algorithms will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. Changes in calibration will have more impact to Terras time series, especially over land. This will result in a significant reduction in artificial differences in the Terra and Aqua datasets, and will stabilize the MODIS data as a target for AEROCOM studie

Aerosol retrieval algorithms↗

Satellite-Assisted Particulate Matter (SAPM) for the Models, In situ, and Remote Sensing of Aerosols (MIRA) Working Group

Models, In situ, and Remote sensing of Aerosols (MIRA) is an international working group that provides a forum for collaborations amongst these three atmospheric aerosol communities. MIRA consists of a collection of interdisciplinary and independently funded Topic/Project groups with clear goals and generally characterized by requests for additional scientific data. The Satellite-Assisted Particulate Matter (SAPM) Topic group focuses on the study of fine particulate matter (PM2.5), as it is a major contributor to air pollution and negatively impacts human health. Our group aims to provide intercomparisons of various methods and techniques for estimating surface PM2.5 assisted by satellite remote sensors (passive and active), global aerosol models, and in situ aerosol measurements. The overall motivation of our work is to enhance PM2.5 coverage beyond in situ ground stations, which can be limited. In this presentation, we provide an overview of various PM2.5 estimation approaches by current SAPM team members, as each approach has its own strengths and limitations. One approach uses near-surface aerosol extinction retrievals from the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and an assumed value of mass extinction efficiency to derive PM2.5 concentrations (Toth et al 2019). A study using this method found a promising agreement (R=0.60; slope=0.89) with U.S. Environmental Protection Agency (EPA) in situ PM2.5 measurements over the contiguous United States (CONUS) for a 12-year (2007-2018) period (Toth et al 2022). In a different approach combining spaceborne lidar and a model, the Cloud Aerosol Transport System (CATS) lidar and Goddard Earth Observing System (GEOS) model are blended in an ensemble variational assimilation scheme to retrieve aerosol extinction and convert speciated mass concentrations to total PM2.5. A recent study (Matus et al in prep.) found agreement within 2 μg/m3 over the CONUS on the 2016 annual mean when compared to EPA ground-based measurements. Another study explored trends in city aerosol optical depth (AOD) from a spaceborne passive remote sensor, Moderate Resolution Imaging Spectroradiometer (MODIS), and found that these trends agree well with trends in city surface PM2.5, which provides confidence in the use of city AOD for city PM2.5 trend studies (Vohra et al 2021). In a follow-on study, steep and significant trends (~2.5 to 7.8% a-1) in AOD are found for several South Asian cities (e.g., Bangalore and Hyderabad), suggesting rapid growth in PM2.5 (Vohra et al 2022). Also in this presentation, we report results on our current collective SAPM study of India, a country that exhibits high levels of PM2.5 pollution. We show the temporal (i.e., seasonal) and spatial variability of PM2.5 over India using the CALIOP and CATS+model approaches, comparisons between the estimated PM2.5 from the retrieval schemes, and validation with in situ PM2.5 ground-based observations from the Central Pollution Control Board in India. This region provides us with an excellent case study to test our PM2.5 retrievals in heavily polluted scenes and over a complex and varying topography. The SAPM Topic group actively seeks international participants/collaborators in our group, including those working with in situ aerosol measurements (e.g., ACTRIS). We are interested in aerosol datasets in order to either improve our PM2.5 estimates from various approaches (e.g., using in situ mass scattering/absorption coefficient and aerosol hygroscopic properties for various aerosol species) and/or validate the PM2.5 estimates (e.g., using in situ ground-based PM2.5 concentrations).

Travis D Toth↗

Lithium-Ion Battery Diagnostics Using Electrochemical Impedance via Machine-Learning

Diagnosing battery states such as health, state-of-charge, or temperature is crucial for ensuring the safety and reliability of electrochemical energy storage systems. While some states, such as temperature, may be measured using cheap sensors, accurate diagnosis of battery health metrics usually requires time-consuming performance measurements, making them infeasible for use in real-world operation. These health metrics can be measured during lab-testing and then estimated on-line using predictive life models or via state observer algorithms such as Kalman filters, but these predictive methods should be supplemented by actual measurement of battery health whenever possible to ensure reliability. Rapid measurement of battery health may be done by various types of fast diagnostic techniques such as electrochemical impedance spectroscopy (EIS), which can be performed in only a few minutes and require only a fraction of the energy and power needed for a full charge and discharge measurement. But there is a substantial challenge for estimating battery health using EIS data, as EIS is sensitive to cell temperature, state-of-charge, current, and resting time in addition to health. Thus, utilizing EIS data to predict battery capacity requires correcting for all these additional variables, a task that is extremely difficult to handle analytically. This talk utilizes machine-learning methods to estimate the effectiveness of battery capacity prediction from EIS data, leveraging a data set of hundreds of EIS measurements recorded at varying temperature and state-of-charge throughout a 500-day aging study of 32 commercial, large-format NMC-Graphite lithium-ion batteries. Using EIS as input to machine-learning models is complicated by the nonlinear response of impedance to battery health, temperature, and state-of-charge, as well as the collinearity between the impedance response at neighboring frequencies, which can easily lead to overfit models. To train robust models, features from EIS data need to be extracted from the data or some subset of critical frequencies selected. Many approaches for extracting and selecting features from EIS data from electrochemical analysis and machine-learning fields were identified for analysis: using the entire raw spectra; selection of one, two, or many frequencies from the entire spectra; selecting interesting points from the EIS measurement using domain knowledge; fitting EIS with an equivalent-circuit model; calculating statistics on the raw impedance values; and reducing the dimensionality of the data using unsupervised linear (principal component analysis) and non-linear (uniform manifold approximation and projection) methods. These approaches were rigorously compared using a machine-learning pipeline approach, training linear, Gaussian process, and random forest regression models and quantifying performance using cross-validation as well as a held-out test set. An artificial neural network model trained on the raw spectra was also tested. Promising pipelines were fine-tuned via Bayesian hyperparameter optimization using cross-validation loss and training with class-specific weights to counter data set imbalance. The most reliable method for utilizing impedance in this work was the selection of two optimal frequencies through an exhaustive search, resulting in about 2% mean absolute error on test data for both Gaussian process and random forest model architectures. Interrogation of a variety of models reveals critical frequencies of 100 Hz and 103 Hz for this data set, though the optimal set of frequencies is not necessarily intuitive, i.e., the best performing models are not simply those that use impedance at frequencies that have the highest correlation to the relative discharge capacity. The best performing model is an ensemble model, which is able to predict battery capacity with 1.9% mean absolute error for unseen cells using impedance recorded at a variety of temperatures and states-of-charge.

battery↗

The ePIC dual-radiator RICH detector

The dual radiator Ring Imaging Cherenkov (dRICH) detector is required to provide continuous hadron identification from ≈3 GeV/c up to ≈50 GeV/c, and to supplement electron and positron identification from a few hundred MeV/c up to about 15 GeV/c, in the forward (ion-side) end-cap of the ePIC experiment. Such an extended momentum range imposes the use of two radiators, gas and aerogel. The common imaging system, that ensures compactness and cost-effectiveness, is based on SiPM sensors to work in a high non-uniform magnetic field. During the R&D phase, the dual radiator principle and the single component performance have been validated. A status overview of the project is presented. The design and technological choices are discussed together with the results obtained from laboratory characterization of the component demonstrators and beam tests of the evolving prototypes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Test and Validate Distributed Coaxial Cable Sensors for in situ Condition Monitoring of Coal-Fired Boiler Tubes

This project aims to test, validate, and advance the technology readiness level (from TRL5 to TRL7) of a novel low-cost distributed stainless-steel/ceramic coaxial cable sensing (SSC-CCS) technology for in situ monitoring of the boiler tube temperature in existing coal-fired power plants. The novel SSC-CCS sensing technology and associated condition-based monitoring (CBM) software to be demonstrated in this project will lead to an improved understanding of the boiler tube failure mechanisms and a prognostic system to improve the overall performance, reliability, and flexibility of the nation’s coal-fired power plant fleet. A boiler tube monitoring system with distributed coaxial cable temperature sensors and a sensor acquisition system was constructed. The high-temperature coaxial cable sensor with a length of 1.3m was made by using a quartz tube (1mm inner diameter (ID) and 6mm outer diameter (OD)) to concentrically separate a 304 stainless-steel (SS) rod (1mm OD) and SS tube (7.94mm OD and 6.16mm ID). The sensor acquisition system includes a vector network analyzer (VNA), a radio frequency (RF) power amplifier, multiple switches and a USB hub. The distributed stainless-steel quartz coaxial cable sensor (SSQ-CCS) had a linear response to temperature with a resolution uncertainty of σ = 0.77℃. To withstand the harsh conditions of 3,300 steam pressures and 800℃ high temperatures, the sensor was shielded by a protective tube made of the same material as the boiler tube. The protection tube had an OD of 1.5 inches and a thickness of 0.25 inches. In the laboratory tests, the sensor showed good sensitivity and fast response. The drift was bounded between +0.33% and -0.67% during a test at 600℃ for 350 hours, indicating good stability of the sensor. A field test was conducted where four sensors were welded on four superheat tubes (SH-Ts) at a coal-fired power station over 400 days. Conventional thermocouples were welded to the superheater tubes alongside the coaxial cable sensors for the purpose of comparison. Two sensors were capable of distributed sensing, with three multiplexed sensing sections. The other two sensors were single section. During the 400-day test period, the power plant experienced startups and shutdowns. At the steady state operations, the temperature of the boiler tube is about 600℃ (1112°F). The sensors recorded the entire coal-firing processes (start-up, steady state, and shut-down) and the glitch event. A GSM modem and a Watchdog were added to the system to ensure reliable data recording. The GSM modem sent daily messages to plant managers and Clemson team to inform the status of the sensor system. If the system was not normally working, the Watchdog would reboot the system automatically. The new coaxial cable based distributed sensing technology has been proven to be successful in both laboratory and field tests. A comprehensive four-stage multi-physics computational framework has been developed to assist the design, optimization, installation, and operation of SSQ-CCS. With the consideration of various operation conditions, we predict the distributions of flue gas temperatures within coal-fired boilers, the temperature correlation between the boiler tube and SSQ-CCS, and the safety of SSQ-CCS. A conditional-based monitoring system is implemented as well. The computational framework developed in this work can guide the future operation of coal-fired plants and other power plants for the safety prediction of boiler operations.

01 COAL, LIGNITE, AND PEAT↗