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NASA NTRS2004

Passive Measurement of CO2 Column from an Airborne Platform

We are in the third and final year of our IIP funding to develop a sensor for very precise determination of the CO2 Column. Global measurements of this sort from a satellite platform are needed to improve our understanding of the global carbon budget. In previous reports to this meeting we have described the method by which this system operates and presented data taken during ground based tests of the instrument. Work in the final year has concentrated on building the flight hardened version of the instrument that will be used in our field trials on the Dryden DC-8. The flight unit represents an integration of three channels into a single instrument. These three channels are the CO2 channel, the oxygen pressure sensing channel, and the oxygen temperature sensing channel. Integration of the three channels into a single unit significantly decreases the size of the instrument. The flight unit also employs more rugged optical mounts and integrated optical shielding. Light enters the instrument from below first striking the right angled mirror shown extending over the edge of the platform. The light is then focused through a pinhole to define the instrument field of view, chopped and recollimated. Dichroic mirrors are used to separate the CO2 wavelength from the O2 wavelength and that light is further divided by a 50-50 beamsplitter between the 2 oxygen channels - the pressure channel and the temperature channel. The six white boxes contain the detectors for each of the three channels. The detectors on the left in the photo serve the reference channels and the detectors on the right are for the Fabry-Perots. CO2 is measured by the pair of detectors farthest from the viewer. Pressure via O2 is detected by the central pair of detectors. The closest pair is used to determine temperature via O2.

Heaps, William S.↗
NASA NTRS2014

Adaptive Augmenting Control Flight Characterization Experiment on an F/A-18

This paper summarizes the Adaptive Augmenting Control (AAC) flight characterization experiments performed using an F/A-18 (TN 853). AAC was designed and developed specifically for launch vehicles, and is currently part of the baseline autopilot design for NASA's Space Launch System (SLS). The scope covered here includes a brief overview of the algorithm (covered in more detail elsewhere), motivation and benefits of flight testing, top-level SLS flight test objectives, applicability of the F/A-18 as a platform for testing a launch vehicle control design, test cases designed to fully vet the AAC algorithm, flight test results, and conclusions regarding the functionality of AAC. The AAC algorithm developed at Marshall Space Flight Center is a forward loop gain multiplicative adaptive algorithm that modifies the total attitude control system gain in response to sensed model errors or undesirable parasitic mode resonances. The AAC algorithm provides the capability to improve or decrease performance by balancing attitude tracking with the mitigation of parasitic dynamics, such as control-structure interaction or servo-actuator limit cycles. In the case of the latter, if unmodeled or mismodeled parasitic dynamics are present that would otherwise result in a closed-loop instability or near instability, the adaptive controller decreases the total loop gain to reduce the interaction between these dynamics and the controller. This is in contrast to traditional adaptive control logic, which focuses on improving performance by increasing gain. The computationally simple AAC attitude control algorithm has stability properties that are reconcilable in the context of classical frequency-domain criteria (i.e., gain and phase margin). The algorithm assumes that the baseline attitude control design is well-tuned for a nominal trajectory and is designed to adapt only when necessary. Furthermore, the adaptation is attracted to the nominal design and adapts only on an as-needed basis (see Figure 1). The MSFC algorithm design was formulated during the Constellation Program and reached a high maturity level during SLS through simulation-based development and internal and external analytical review. The AAC algorithm design has three summary-level objectives: (1) "Do no harm;" return to baseline control design when not needed, (2) Increase performance; respond to error in ability of vehicle to track command, and (3) Regain stability; respond to undesirable control-structure interaction or other parasitic dynamics. AAC has been successfully implemented as part of the Space Launch System baseline design, including extensive testing in high-fidelity 6-DOF simulations the details of which are described in [1]. The Dryden Flight Research Center's F/A-18 Full-Scale Advanced Systems Testbed (FAST) platform is used to conduct an algorithm flight characterization experiment intended to fully vet the aforementioned design objectives. FAST was specifically designed with this type of test program in mind. The onboard flight control system has full-authority experiment control of ten aerodynamic effectors and two throttles. It has production and research sensor inputs and pilot engage/disengage and real-time configuration of up to eight different experiments on a single flight. It has failure detection and automatic reversion to fail-safe mode. The F/A-18 aircraft has an experiment envelope cleared for full-authority control and maneuvering and exhibits characteristics for robust recovery from unusual attitudes and configurations aided by the presence of a qualified test pilot. The F/A-18 aircraft has relatively high mass and inertia with exceptional performance; the F/A-18 also has a large thrust-to-weight ratio, owing to its military heritage. This enables the simulation of a portion of the ascent trajectory with a high degree of dynamic similarity to a launch vehicle, and the research flight control system can simulate unstable longitudinal dynamics. Parasitic dynamics such as slosh and bending modes, as well as atmospheric disturbances, are being produced by the airframe via modification of bending filters and the use of secondary control surfaces, including leading and trailing edge flaps, symmetric ailerons, and symmetric rudders. The platform also has the ability to inject signals in flight to simulate structural mode resonances or other challenging dynamics. This platform also offers more test maneuvers and longer maneuver times than a single rocket or missile test, which provides ample opportunity to fully and repeatedly exercise all aspects of the algorithm. Prior to testing on an F/A-18, AAC was the only component of the SLS autopilot design that had not been flight tested. The testing described in this paper raises the Technology Readiness Level (TRL) early in the SLS Program and is able to demonstrate its capabilities and robustness in a flight environment.

VanZwieten, Tannen S.↗
DOE OSTI2023

Towards Three-Dimensional Neutron Imaging with Light-field Technology

A broad range of applications in nuclear safeguards and security can benefit from compact, fast neutron imagers with large angular acceptance. However, accurate 3D multi-vertex reconstruction in a monolithic detector remains a significant barrier to realization. Current approaches, such as the centroiding approach and the use of shadow masks, have not yet resulted in a successful demonstration in a light-starved environment. This project explored the use of cutting-edge technology—a light field camera—which inherently preserves both the spatial and directional information of incident light. Such technology can, in principle, resolve multi-vertex events and offer accurate position reconstruction in 3D with relatively simple readout electronics. Since the project's inception in May 2023, we have built an experimental setup to calibrate and characterize a commercial light-field camera (Lytro Illum). We assessed its 3D event reconstruction capability in a relatively low-light intensity environment by analyzing the cross-correlation of a series of 2D images of a characterized tunable light source taken at various distances. A sub-cm resolution, lower than typical neutron interaction separations in a compact scintillator volume, was observed with the LED light source, suggesting the promising capability of its nominal optics design to provide the adequate resolution required for a compact monolithic neutron directional detector. However, using a light-field-based readout for a neutron camera requires incorporating an ultra-low-noise light sensor, which is beyond the scope of this project. We also initiated the development of a 3D light-field-based reconstruction algorithm tailored to sparse scenes, as expected from particle interactions in a scintillator medium. Additionally, we demonstrated the capability of the algorithm to replicate the ground truth. Finally, we began the development of a neutron directional detector simulation to determine the performance criteria for light-field-based reconstruction that allows for good neutron directional reconstruction. This Feasibility Study has led to a successful follow-up project under the DNN R&D innovation portfolio starting May 2024.

42 ENGINEERING↗
NASA NTRS2026

PERSIANN-Unet: A Global Deep Learning Framework for Near-Real-Time Precipitation Estimation Using Infrared Data

Access to high-quality, high-resolution, near-real-time precipitation data is essential for hydrological and meteorological research and disaster mitigation. Traditional tools such as rain gauges and radar networks, though effective, have limitations, including sparse coverage in remote areas and high operational costs. Satellite data, with its global coverage and high spatial and temporal resolutions, mitigates limitations in coverage. Satellite precipitation products like Hydro Estimator (HE), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) utilize both geosynchronous thermal infrared (IR) and passive microwave (PMW) data in their operation. PMW sensors offer detailed atmospheric profiles but suffer from higher latency, whereas IR sensors provide lower latency but only capture cloud-top information. Despite this constraint, IR data remains attractive for low-latency precipitation estimation. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have further improved satellite precipitation retrievals. This study introduces PERSIANN-Unet (PUnet or PERSIANN V3), a quasi-global algorithm covering 60°N–60°S that combines IR data, monthly climatology, and the UNet architecture to produce half-hourly precipitation estimates at 0.04° resolution. The product is evaluated against HE, IMERG, and PDIR-Now for 2022–2023. Results show that PUnet closely matches its training target, IMERG V07 Final, at the global scale, and performance is further evaluated against Stage IV as a reference over CONUS. Training PUnet on IMERG (2016–2021) leverages a high-quality, integrated PMW IR-gauge precipitation product while developing an IR-based framework not reliant on PMW availability. By operating on a single global image, PUnet avoids tile partitioning and blending steps, reducing edge discontinuities, and produces more spatially consistent precipitation fields across hemispheres.

Phu Nguyen↗
NASA NTRS2007

EVA Hazards due to TPS Inspection and Repair

Tile inspection and repair activities have implicit hazards associated with them. When an Extra Vehicular Activities (EVA) crewmember and associated hardware are added into the equation, additional hazards are introduced. Potential hazards to the Extravehicular Mobility Unit (EMU), the Orbiter or the crew member themselves are created. In order to accurately assess the risk of performing a TPS inspection or repair, an accurate evaluation of potential hazards and how adequately these hazards are controlled is essential. The EMU could become damaged due to sharp edges, protrusions, thermal extremes, molten metal or impact with the Orbiter. Tools, tethers and the presence of a crew member in the vicinity of the Orbiter Thermal Protection System (TPS) pose hazards to the Orbiter. Hazards such as additional tile or Reinforced Carbon-Carbon (RCC) damage from a loose tool, safety tethers, crewmember or arm impact are introduced. Additionally, there are hazards to the crew which should be addressed. Crew hazards include laser injury, electrical shock, inability to return to the airlock for EMU failures or Orbiter rapid safing scenarios, as well as the potential inadvertent release of a crew member from the arm/boom. The aforementioned hazards are controlled in various ways. Generally, these controls are addressed operationally versus by design, as the majority of the interfaces are to the Orbiter and the Orbiter design did not originally account for tile repair. The Shuttle Remote Manipulator System (SRMS), for instance, was originally designed to deploy experiments, and therefore has insufficient design controls for retention of the Orbiter Boom Sensor System (OBSS). Although multiple methods to repair the Orbiter TPS exist, the majority of the hazards are applicable no matter which specific repair method is being performed. TPS Inspection performed via EVA also presents some of the same hazards. Therefore, the hazards common to all TPS inspection or repair methods will be addressed.

Stewart, Christine E.↗
NASA NTRS2018

Aerodynamic and Structural Evaluation of an SMA Slat-Cove Filler Using Computational and Experimental Tools at Model Scale

Transport class aircraft produce a significant amount of airframe noise during approach and landing due to exposed geometric discontinuities that are hidden during cruise. The leading-edge slat is a primary contributor to this noise. In previous work, use of a slat-cove filler (SCF) has proven to reduce airframe noise by filling the cove aft of the slat, eliminating the circulation region within the cove. The goal of this work is to extend and improve upon past experimental and computational efforts on the evaluation of a scaled high-lift wing with a super elastic shape memory alloy (SMA) SCF. Recent turbulence measurements of the Texas A&M University 3ft-by-4ft wind tunnel allow for more accurate representation of the flow through the test section in computational fluid dynamics (CFD) analysis. The finite volume models used in CFD analysis are coupled to structural finite element models using a framework compatible with an SMA constitutive model and significant deformation, enabling fluid-structure interaction (FSI) analysis of the SCF. Both fully-deployed and retraction/deployment cases are considered. The displacement of the SCF on the experimental model is measured at various stages of retraction/deployment using a laser displacement sensor and digital image correlation system. Due to a lack of structural stiffness in the 3D-printed plastic slat during retraction and SCF stowage, a rigid steel slat is incorporated into the physical model and preliminary wind tunnel tests are conducted at multiple angles of attack in both retracted and deployed configurations.

Scholten, William↗
NASA NTRS2016

Assessment of MODIS RSB Detector Uniformity Using Deep Convective Clouds

For satellite sensor, the striping observed in images is typically associated with the relative multiple detector gain difference derived from the calibration. A method using deep convective cloud (DCC) measurements to assess the difference among detectors after calibration is proposed and demonstrated for select reflective solar bands (RSBs) of the Moderate Resolution Imaging Spectroradiometer (MODIS). Each detector of MODIS RSB is calibrated independently using a solar diffuser (SD). Although the SD is expected to accurately characterize detector response, the uncertainties associated with the SD degradation and characterization result in inadequacies in the estimation of each detector's gain. This work takes advantage of the DCC technique to assess detector uniformity and scan mirror side difference for RSB. The detector differences for Terra MODIS Collection 6 are less than 1% for bands 1, 3-5, and 18 and up to 2% for bands 6, 19, and 26. The largest difference is up to 4% for band 7. Most Aqua bands have detector differences less than 0.5% except bands 19 and 26 with up to 1.5%. Normally, large differences occur for edge detectors. The long-term trending shows seasonal oscillations in detector differences for some bands, which are correlated with the instrument temperature. The detector uniformities were evaluated for both unaggregated and aggregated detectors for MODIS band 1 and bands 3-7, and their consistencies are verified. The assessment results were validated by applying a direct correction to reflectance images. These assessments can lead to improvements to the calibration algorithm and therefore a reduction in striping observed in the calibrated imagery.

Clouds↗
DOE OSTI2023

SIF and Vegetation Indices in the US Midwestern Agroecosystems, 2016-2021, Carbon Monitoring System (CMS)

This dataset contains half-hourly ground solar-induced chlorophyll fluorescence (SIF) and vegetation indices including NDVI, EVI, Red edge chlorophyll index, green chlorophyll index, and photochemical reflectance index at seven crop sites in Nebraska and Illinois for the period 2016-2021. Four sites were located at Eddy Covariance (EC) tower sites (sites US-Ne2, US-Ne3, US-UiB, and US-UiC), and three sites were located on private farms (sites Reifsteck, Rund, and Reinhart). The sites were either miscanthus, corn-soybean rotation or corn-corn-soybean rotation. The spectral data for SIF retrieval and hyperspectral reflectance for vegetation index calculation were collected by the FluoSpec2 system, installed near planting, and uninstalled after harvest to collect whole growing-season data. Raw nadir SIF at 760 nm from different algorithms (sFLD, 3FLD, iFLD, SFM) are included. SFM_nonlinear and SFM_linear represent the Spectral fitting method (SFM) with the assumption that fluorescence and reflectance change with wavelength non-linearly and linearly, respectively. Additional data include two SIF correction factors including calibration coefficient adjustment factor (f_cal_corr_QEPRO) and upscaling nadir SIF to eddy covariance footprint factor (ratio_EC footprint, SIF pixel), and measured FPAR from quantum sensors and Rededge NDVI calculated FPAR. The data are provided in comma-separated values (CSV) format.

Ameriflux↗
DOE OSTI2024

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, and robustness. Inspired by the concept of Edge Artificial Intelligence (Edge AI), we propose a robust approach that enables fast FLI with no degradation of accuracy. This approach couples a recurrent neural network (RNN), which is trained to estimate the fluorescence lifetime directly from raw timestamps without building histograms, to SPAD TCSPC systems, thereby drastically reducing transfer data volumes and hardware resource utilization, and enabling real-time FLI acquisition. We train two variants of the RNN on a synthetic dataset and compare the results to those obtained using center-of-mass method (CMM) and least squares fitting (LS fitting). Results demonstrate that two RNN variants, gated recurrent unit (GRU) and long short-term memory (LSTM), are comparable to CMM and LS fitting in terms of accuracy, while outperforming them in the presence of background noise by a large margin. To explore the ultimate limits of the approach, we derive the Cramer-Rao lower bound of the measurement, showing that RNN yields lifetime estimations with near-optimal precision. To demonstrate real-time operation, we build a FLI microscope based on an existing SPAD TCSPC system comprising a 32 x 32 SPAD sensor named Piccolo. Four quantized GRU cores, capable of processing up to 4 million photons per second, are deployed on the Xilinx Kintex-7 FPGA that controls the Piccolo. Powered by the GRU, the FLI setup can retrieve real-time fluorescence lifetime images at up to 10 frames per second. The proposed FLI system is promising and ideally suited for biomedical applications, including biological imaging, biomedical diagnostics, and fluorescence-assisted surgery, etc.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Development of Advanced Instrumentation for Transient Testing

A fuel safety research program centered on in-pile transient testing experiments is being developed to support assessment and qualification of advanced nuclear fuel systems using the recently restarted Transient Reactor Test (TREAT) facility at the Idaho National Laboratory (INL). While resumption of transient testing at TREAT is crucial to enable these programs, full recovery and cutting-edge transient testing capability also requires a well-coordinated and innovative instrumentation development and qualification program to support near-term and future objectives. This paper summarizes the experimental approach of transient testing to focus on measuring the response of nuclear fuel to off-normal (or power-cooling mismatch) conditions for modern and advanced reactor environments requiring capabilities extending over wide measurement and environment conditions. It also highlights unique attributes of transient testing of importance to in-pile instruments including relatively low total neutron fluence, high gamma heating, and the need for well-defined and possibly short time response. Historical approaches to instrumentation for transient testing are also reviewed to provide context to the modern instrument strategy. The instrumentation needs of a modern transient testing are detailed while summarizing several ongoing R&D activities are supporting the development of state-of-the-art and ‘advanced’ measurement technologies that will provide baseline capability for Light Water Reactor (LWR) and Sodium-Cooled Fast Reactor (SFR) experiment objectives, while extending to other advanced reactor needs and advanced sensing technology opportunities. Examples of specific sensors planned for near-term deployment with ongoing development includes prompt-response self-powered neutron detectors (SPND), miniature fission chambers, optical-fiber-coupled infrared pyrometer, cladding surface thermocouples, electrical-impedance based boiling detector, and Linear Variable Differential Transformer (LVDT) based sensors for fuel elongation and pressure measurement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Final Report: Sampling-Based Algorithms for Estimating Structure in Big Data.

The purpose of this project was to develop sampling-based algorithms to discover hidden struc- ture in massive data sets. Inferring structure in large data sets is an increasingly common task in many critical national security applications. These data sets come from myriad sources, such as network traffic, sensor data, and data generated by large-scale simulations. They are often so large that traditional data mining techniques are time consuming or even infeasible. To address this problem, we focus on a class of algorithms that do not compute an exact answer, but instead use sampling to compute an approximate answer using fewer resources. The particular class of algorithms that we focus on are streaming algorithms , so called because they are designed to handle high-throughput streams of data. Streaming algorithms have only a small amount of working storage - much less than the size of the full data stream - so they must necessarily use sampling to approximate the correct answer. We present two results: * A streaming algorithm called HyperHeadTail , that estimates the degree distribution of a graph (i.e., the distribution of the number of connections for each node in a network). The degree distribution is a fundamental graph property, but prior work on estimating the degree distribution in a streaming setting was impractical for many real-world application. We improve upon prior work by developing an algorithm that can handle streams with repeated edges, and graph structures that evolve over time. * An algorithm for the task of maintaining a weighted subsample of items in a stream, when the items must be sampled according to their weight, and the weights are dynamically changing. To our knowledge, this is the first such algorithm designed for dynamically evolving weights. We expect it may be useful as a building block for other streaming algorithms on dynamic data sets.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2000

Optical Measurements of Axial and Tangential Steady-State Blade Deflections Obtained Simultaneously

Case-mounted fiber-optic sensors have been used by aircraft engine manufacturers mainly to monitor blade vibration in fans and compressors. The simplest probe arrangement is a spot probe where, typically, a center fiber transmits laser light, and the outer fibers collect the reflected light from the blade tips and transmit it to a photodetector. Because the spot of incident light is fixed in space, whereas the blade deflects dynamically, the reflected light will originate from slightly different portions of the blade tip under different operating conditions. Unless corrections are developed to compensate for this effect, some error in vibratory tangential amplitude will occur. For monitoring vibrations, this error is usually not critical. However, when steady-state blade deflections are being measured, it is very important to fix the spot on the blade tip at a particular location because the operating speed blade deflections are evaluated against a low-speed reference run. The change in speed usually implies a significant change in the blade orientation and possibly its shape brought about by the aerodynamic and centrifugal loading. It is most convenient to select the blade s leading and trailing edges as the fixed points for which deflections will be evaluated. To capture the blade edges at various speeds, the light probe must be movable. This was achieved by mounting the probe in an eccentric hole in a bushing that fit the fan case in the region that overlapped the path of the blade edge. The probe was actuated to search for a blade edge while all the blades were viewed on an oscilloscope. The blade edge was considered to be captured when a pulse associated with a particular blade was significantly reduced in magnitude but was clearly distinguishable from the background noise level. By tracing the axial position of either blade edge, one could extend the deflection measurement to two dimensions: axial and tangential. These blade deflection measurements were obtained during a wind tunnel test of a fan prototype.

Kurkov, Anatole P.↗
DOE OSTI2018

Modeling the one-dimensional imager of neutrons (ODIN) for neutron response functions at the Sandia Z facility

The one-dimensional imager of neutrons (ODIN) at the Sandia Z facility consists of a 10-cm block of tungsten with rolled edges, creating a slit imager with slit widths of either 250, 500, or 750 μm. Designed with a 1-m neutron imaging line of sight, we achieve about 4:1 magnification and 500-μm axial spatial resolution. The baseline inertial confinement fusion concept at Sandia is magnetized liner inertial fusion, which nominally creates a 1-cm line source of neutrons. ODIN was designed to determine the size, shape, and location of the neutron producing region, furthering the understanding of compression quality along the cylindrical axis of magnetized liner implosions. Challenges include discriminating neutrons from hard x-rays and gammas with adequate signal-to-noise in the 2 × 10 12 deuterium-deuterium (DD) neutron yield range, as well as understanding the point spread function of the imager to various imaging detectors (namely, CR-39). Modeling efforts were conducted with MCNP6.1 to determine neutron response functions for varying configurations in a clean DD neutron environment (without x-rays or gammas). Configuration alterations that will be shown include rolled-edge slit orientation and slit width, affecting the resolution and response function. The experiment to determine CR-39 neutron sensitivity, with and without a high density polyethylene (n, p) converter, an edge spread function, and resolution will be discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1990

Comparison of satellite based cloud retrieval methods for cirrus and stratocumulus

One difficulty in using satellite remote sensing data is the spatial variability of cloud properties on scales smaller than most meteorological satellite fields of view (approx. 4 to 8 km). The variation is examined of satellite derived cloud cover as a function of the satellite sensor spatial resolution for seven cloud cover retrieval methods: (1) Reflectance threshold; (2) Temperature threshold; (3) ISCCP; (4) HBTM (Hybrid Bispectral Threshold Method); (5) NCLE; (6) Spatial coherence; and (7) Functional Box Counting. The first two methods are simple single spectral thresholds which specify a satellite pixel as cloud filled if the measured reflectance is greater than the threshold, or if the measured equivalent blackbody temperature is less than the threshold. The next three methods are bispectral, using one visible wavelength window channel and one thermal infrared wavelength window. The final two algorithms rely on the spatial variability within the cloud field to determine cloud cover. Spatial coherence assumes only that the cloud field occurs in a single layer and that the clouds are optically thick in the infrared window. LANDSAT Thematic Mapper (TM) data is used to test the spatial resolution dependence of the cloud algorithms. The ISCCP bispectral threshold applied to the full resolution data is used as the reference or truth cloud cover, after which the retrieval methods are applied to the spatial resolutions. Studies of the fraction of pixels in the scene at cloud edge, and of the profile of reflectance and temperature near cloud edges indicate an uncertainty in the reference cloud fraction of 1 to 5 percent.

Parker, Lindsay↗
NASA NTRS2018

Sea Surface Salinity Distribution in the Southern Ocean as Observed from Space

Large scale spatial and temporal variabilities of sea surface salinity (SSS) in the Southern Ocean from 2011 to 2017 were studied using products derived from microwave sensors on board Aquarius/SAC-D, Soil Moisture and Ocean Salinity (SMOS), and Soil Moisture Active and Passive (SMAP) satellites. Four products, three from Aquarius and one from SMOS, were evaluated and shown to be generally consistent within 0.3 to 0.6 psu and agree favorably with in situ measurements. However, although the Aquarius products show consistent seasonality of SSS with high values of 34.45 in October and low values of 33.40 in May, the SMOS and SMAP products lack such seasonal variations. This may be caused by larger uncertainties in the SMOS and SMAP data due in part to the lack of concurrent scatterometer measurements that is used to correct for roughness effects. The four products provide similar spatial distributions of SSS with root-mean-square-errors from 0.25 to 0.58 psu. Differences among Aquarius products are mainly due to varying salinity retrieval algorithms, smoothing, and masking of sea ice, while the SMOS product showed the highest SSS deviation that is likely due to the bias-adjustment done on the dataset. Our analyses show that SSS in the Southern Ocean region has significant meridional variations with the lowest SSS near the ice edge and highest at lower latitudes. The SSS is also lowest in summer indicating the predominant influence of sea ice and glacial melt, but it stays low near ice edges even during the growth season.

SSS↗
NASA NTRS2019

Sea Surface Salinity Distribution in the Southern Ocean as Observed from Space

Large-scale spatial and temporal variabilities of sea surface salinity (SSS) in the Southern Ocean from 2011 to 2017 were studied using products derived from microwave sensors on board Aquarius, Soil Moisture and Ocean Salinity (SMOS), and Soil Moisture Active and Passive (SMAP) satellites. Four products, three from Aquarius and one from SMOS, were evaluated and shown to be generally consistent within 0.3 to 0.6 psu and agree favorably with in situ measurements. However, although the Aquarius products show consistent seasonality of SSS with high values of 34.45 psu in October and low values of 33.40 psu in May, theSMOS and SMAP products lack such seasonal variations. This may be caused by larger uncertainties in the SMOS and SMAP data due in part to the lack of concurrent scatterometer measurements that is used to correct for roughness effects. The four products provide similar spatial distributions of SSS with root mean square difference from 0.25 to 0.58 psu. Differences among Aquarius products are mainly due to varying salinity retrieval algorithms, smoothing, and masking of sea ice, while the SMOS product showed the highest SSS deviation that is likely due to the bias adjustment done on the data set. Our analyses show that SSS in the Southern Ocean region has significant meridional variations with the lowest SSS near the ice edge and highest at lower latitudes. The SSS is also lowest in summer indicating the predominant influence of sea ice and glacial melt, but it stays low near ice edges even during the growth season. Salinity together with temperature is the key parameters that control the state and circulation of the World's oceans. The large‐scale distribution of the sea surface salinity of the Southern Ocean is quantified for the first time using Aquarius, Soil Moisture and Ocean Salinity, and Soil Moisture Active and Passive satellite microwave data. Seasonal and interannual changes in the distribution as affected by the sea ice cover, surface temperature, and precipitation are evaluated. Comparative studies were done, using four different products that are publicly available, in conjunction with in situ observations to gain insights into the true nature of the distribution and how consistently the sea surface salinity is depicted by the different products. There are general consistencies in the products, and discrepancies are attributed to different algorithms, smoothing techniques, and sea ice masking. Aquarius data are shown to have higher accuracy than Soil Moisture and Ocean Salinity and Soil Moisture Active and Passive products in part because of having concurrent scatterometer that provides accurate correction to roughness effects.

Garcia-Eidell, Cynthia↗
DOE OSTI2021

On the Bandwidth and Beam Profile Characteristics of a Simple Low-Frequency Collimated Ultrasound Beam Source

We numerically investigate the bandwidth and collimation characteristics of ultrasound beams generated by a simple collimated ultrasound beam source that consists of a piezoelectric disk operated near its radial mode resonances. We simulate the ultrasound beam generated in a fluid medium as a function of the excitation frequency for two cases: (1) free piezoelectric disk that corresponds to zero-traction along the lateral edge and (2) fixed piezoelectric disk that corresponds to zero-displacement along the lateral edge. We present and discuss the physical mechanism underpinning the frequency-dependent collimation and bandwidth properties of the ultrasound beams. We observe that the collimated beam generated by the free disk repeatedly lengthens/shortens and also extends/retracts sidelobes with increasing frequency. Alternatively, fixing the piezoelectric disk results in a consistent beam profile shape across a broad range of frequencies. This facilitates generating broadband signals such as a Gaussian pulse or chirp, which are common in ultrasound imaging. Thus, the fixed piezoelectric disk finds application as a collimated ultrasound beam source in a wide range of applications including medical ultrasound imaging, scanning acoustic microscopy, sonar detection, and other nondestructive ultrasound inspection techniques.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Bio-inspired Surface Structures to Mitigate Interfacial Particle Adhesion and Erosion - A Review

Lunar dust known as regolith is a huge challenge for lunar exploration missions. Formed over millennia by a complex process involving impacts of meteoroids and micrometeoroids on the lunar surface, lunar dust is porous, highly abrasive with sharp jagged edges, chemically reactive, electrostatically charged and sometimes magnetic. The chemical composition and thickness of the dust layer also varies in different regions of the lunar surface. From samples obtained by previous lunar missions, the average particle size is below 100 microns. This dust has the tendency to strongly adhere to any exposed surfaces, and often degrades the material functionality to eventually cause failure. Any material on the lunar surface is also subject to harsh temperature cycles ranging from -178 ̊C to + 123 ̊C and extreme ultraviolet radiation. While on the lunar surface, different classes of materials would be required for different applications. Advanced materials have been and will be used throughout the lunar lander, habitat, and mission equipment. Examples include: polymeric materials for astronaut protective clothing; metals and ceramics for the lunar lander legs and habitats, and excavating equipment; and semiconductors for solar panels and on-board electronics. In all these applications, the surfaces of the materials are expected or understood to be exposed to the extreme lunar environment condition that includes the regolith dust. During the Apollo missions, the dust clung to and abraded the astronaut’s suits, degraded seals, optics, clogged sensors and reduced performance of thermal radiators. The lunar dust adheres to the surface by various mechanisms, which include electrostatic and Coulombic interactions, Van-der-Waals forces, magnetic forces, mechanical interlocking, chemical bonding and donor-acceptor interactions. There are three primary strategies for developing technologies to minimize the lunar dust adhesion: active, passive and a combination of active and passive. In the active approach, an external energy is needed to prevent or remove particles from collecting on the surface. Mechanically powered brushes and electrodynamic dust screens are two examples. In the passive approach, no external power is needed, and the material surface properties are able to mitigate dust adhesion. A well-known example of this strategy is the low work function coatings for non-stick surfaces. In most cases a combination of active and passive methods might be needed to optimally manage the lunar regolith. The passive method is significantly more attractive as it does not require any external power or an additional control subsystem. These approaches optimize the mission payload and reduce risk. Surface modification to minimize the dust adhesion is thus very important to lunar missions. Here, naturally evolved surface structures might provide guidance for solutions. There are several factors that have to be considered for minimizing particle adhesion to a surface. These include the substrate material properties, surface topography, chemistry, and the characteristics of the adhering particles. When engineering a surface, the substrate material chosen would be dependent on the needs of the application. Tailoring the surface microstructure or chemistry opens up more possibilities for its optimal utilization

Lunar Dust↗