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At least 451 records · Page 25

NASA Tech Briefs, March 2007

Topics include: Advanced Systems for Monitoring Underwater Sounds; Wireless Data-Acquisition System for Testing Rocket Engines; Processing Raw HST Data With Up-to-Date Calibration Data; Mobile Collection and Automated Interpretation of EEG Data; System for Secure Integration of Aviation Data; Servomotor and Controller Having Large Dynamic Range; Digital Multicasting of Multiple Audio Streams; Translator for Optimizing Fluid-Handling Components; AIRSAR Web-Based Data Processing; Pattern Matcher for Trees Constructed From Lists; Reducing a Knowledge-Base Search Space When Data Are Missing; Ground-Based Correction of Remote-Sensing Spectral Imagery; State-Chart Autocoder; Pointing History Engine for the Spitzer Space Telescope; Low-Friction, High-Stiffness Joint for Uniaxial Load Cell; Magnet-Based System for Docking of Miniature Spacecraft; Electromechanically Actuated Valve for Controlling Flow Rate; Plumbing Fixture for a Microfluidic Cartridge; Camera Mount for a Head-Up Display; Core-Cutoff Tool; Recirculation of Laser Power in an Atomic Fountain; Simplified Generation of High-Angular-Momentum Light Beams; Imaging Spectrometer on a Chip; Interferometric Quantum-Nondemolition Single-Photon Detectors; Ring-Down Spectroscopy for Characterizing a CW Raman Laser; Complex Type-II Interband Cascade MQW Photodetectors; Single-Point Access to Data Distributed on Many Processors; Estimating Dust and Water Ice Content of the Martian Atmosphere From THEMIS Data; Computing a Stability Spectrum by Use of the HHT; Theoretical Studies of Routes to Synthesis of Tetrahedral N4; Estimation Filter for Alignment of the Spitzer Space Telescope; Antenna for Measuring Electric Fields Within the Inner Heliosphere; Improved High-Voltage Gas Isolator for Ion Thruster; and Hybrid Mobile Communication Networks for Planetary Exploration.

Source record↗

Controlling Herds of Cooperative Robots

A document poses, and suggests a program of research for answering, questions of how to achieve autonomous operation of herds of cooperative robots to be used in exploration and/or colonization of remote planets. In a typical scenario, a flock of mobile sensory robots would be deployed in a previously unexplored region, one of the robots would be designated the leader, and the leader would issue commands to move the robots to different locations or aim sensors at different targets to maximize scientific return. It would be necessary to provide for this hierarchical, cooperative behavior even in the face of such unpredictable factors as terrain obstacles. A potential-fields approach is proposed as a theoretical basis for developing methods of autonomous command and guidance of a herd. A survival-of-the-fittest approach is suggested as a theoretical basis for selection, mutation, and adaptation of a description of (1) the body, joints, sensors, actuators, and control computer of each robot, and (2) the connectivity of each robot with the rest of the herd, such that the herd could be regarded as consisting of a set of artificial creatures that evolve to adapt to a previously unknown environment. A distributed simulation environment has been developed to test the proposed approaches in the Titan environment. One blimp guides three surface sondes via a potential field approach. The results of the simulation demonstrate that the method used for control is feasible, even if significant uncertainty exists in the dynamics and environmental models, and that the control architecture provides the autonomy needed to enable surface science data collection.

Quadrelli, Marco B.↗

A Data Filter for Identifying Steady-State Operating Points in Engine Flight Data for Condition Monitoring Applications

This paper presents an algorithm that automatically identifies and extracts steady-state engine operating points from engine flight data. It calculates the mean and standard deviation of select parameters contained in the incoming flight data stream. If the standard deviation of the data falls below defined constraints, the engine is assumed to be at a steady-state operating point, and the mean measurement data at that point are archived for subsequent condition monitoring purposes. The fundamental design of the steady-state data filter is completely generic and applicable for any dynamic system. Additional domain-specific logic constraints are applied to reduce data outliers and variance within the collected steady-state data. The filter is designed for on-line real-time processing of streaming data as opposed to post-processing of the data in batch mode. Results of applying the steady-state data filter to recorded helicopter engine flight data are shown, demonstrating its utility for engine condition monitoring applications.

Simon, Donald L.↗

Signal-to-Noise Ratio Prediction and Validation for Space Shuttle GPS Flight Experiment

A deterministic method for Space Station Global Positioning System (GPS) Signal-To- Noise Ratio (SNR) predictions is proposed. The complex electromagnetic interactions between GPS antennas and surrounding Space Station structures are taken into account by computational electromagnetic technique. This computer simulator is capable of taking into account multipath effects from dynamically changed solar panels and thermal radiators. A comparison with recent collected Space Station GPS system flight experiment data is presented. The simulation results are in close agreement with flight data.

Hwu, Shian U.↗

Data-driven landslide nowcasting at the global scale

Landslides affect nearly every country in the world each year. To better understand this global hazard, the Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed previously. LHASA version 1 combines satellite precipitation estimates with a global landslide susceptibility map to produce a gridded map of potentially hazardous areas from 60° North-South every 3 h. LHASA version 1 categorizes the world’s land surface into three ratings: high, moderate, and low hazard with a single decision tree that first determines if the last seven days of rainfall were intense, then evaluates landslide susceptibility. LHASA version 2 has been developed with a data-driven approach. The global susceptibility map was replaced with a collection of explanatory variables, and two new dynamically varying quantities were added: snow and soil moisture. Along with antecedent rainfall, these variables modulated the response to current daily rainfall. In addition, the Global Landslide Catalog (GLC) was supplemented with several inventories of rainfall-triggered landslide events. These factors were incorporated into the machine-learning framework XGBoost, which was trained to predict the presence or absence of landslides over the period 2015–2018, with the years 2019–2020 reserved for model evaluation. As a result of these improvements, the new global landslide nowcast was twice as likely to predict the occurrence of historical landslides as LHASA version 1, given the same global false positive rate. Furthermore, the shift to probabilistic outputs allows users to directly manage the trade-off between false negatives and false positives, which should make the nowcast useful for a greater variety of geographic settings and applications. In a retrospective analysis, the trained model ran over a global domain for 5 years, and results for LHASA version 1 and version 2 were compared. Due to the importance of rainfall and faults in LHASA version 2, nowcasts would be issued more frequently in some tropical countries, such as Colombia and Papua New Guinea; at the same time, the new version placed less emphasis on arid regions and areas far from the Pacific Rim. LHASA version 2 provides a nearly real-time view of global landslide hazard for a variety of stakeholders.

XGBoos↗

Evaluation of Retrieving Chlorophyll a Concentration and Colored Dissolved Organic Matter Absorption from Satellite Ocean Color Remote Sensing in the Coastal Waters of Hokkaido, Japan

Coastal ecosystems are important in biogeochemical cycles, because they provide many pathways for chemical elements and compounds to flow between the physical environment and living organisms. The spatial and temporal scales of the biotic and abiotic interactions establish the inherent dynamics of the coastal zone and the requirement for high-resolution investigations. Using match-up data collected in Hokkaido coastal waters, the study herein evaluated the performance of deriving chlorophyll (Chl) a concentration and colored dissolved organic matter (CDOM) absorption (a(sub CDOM)) as a function of wavelength (λ) from satellite observations. The Japanese Aerospace Exploration Agency (JAXA) Second generation GLobal Imager (SGLI), which has 250 m spatial resolution, was compared with other satellite ocean color (OC) sensors. Our results show that the standard SGLI OC4 algorithm with the 530 nm band provided the best performance for Chl a retrievals, and the end-member analysis (EMA) technique improved the estimation of a(sub CDOM)(λ) . Overall differences between in situ radiometric data and satellite retrievals suggest that additional challenges remain, especially in the ultraviolet and blue spectral domains which are useful for studying CDOM and harmful algae blooms in coastal waters. To fulfill applications wherein high-quality remote sensing data are required, the improvement of the atmospheric correction is a likely research area where additional accomplishment will be beneficial for satellite observations of optically complex coastal waters.

SGLI/GCOM-C↗

Modeling and Simulation for Exercise Vibration Isolation and Stabilization System Design

The microgravity environment that crew members experience on orbit presents a well-known health challenge, particularly when it comes to loss of muscle and bone mass. To counteract these negative effects, exercise countermeasures play a critical role in the daily routine of the crew on the International Space Station (ISS). To help inform requirements for upcoming exploration missions such as the Gateway Program, a new device, called the European Enhanced Exploration Exercise Device (E4D), is being built by the European Space Agency through their contractor, the Danish Aerospace Company. The E4D is being demonstrated on the ISS and is unique from other current exercise devices in that it provides four separate modalities in a single device: resistive, cycle ergometry, seated aerobic rowing, and rope pulling. To support the integration of E4D on ISS, a passive Vibration Isolation and Stabilization (VIS) system was required by NASA, and this responsibility was given to the Johnson Space Center. This paper describes the end-to-end process of modeling, simulation, and analysis used to inform the mechanical design of the VIS system. The process begins with the collection of representative exerciser motion capture (MoCap) through ground-based testing with the developmental E4D in both the Prototype Immersive Technology (PIT) Laboratory and the Active Response Gravity Offload System (ARGOS) facility at the Johnson Space Center. These collected MoCap data are processed through human biomechanics modeling to create forcing functions as input to a multibody dynamics simulation of the combined E4D/VIS system, with numerous resulting outputs. These outputs include microgravity accelerations, overall system displacements, internal and transmitted loads, as well as collisions. Microgravity accelerations are compared for compliance against ISS requirements while displacements are used for sway space determinations on the design and volumetric constraints within the targeted module. Internal loads are supplied to the supporting stress analysis teams and external loads for structural loads and dynamics teams, both at NASA and ESA. Finally, contact and clearance analysis is performed using the simulation to eliminate potential design issues. To ensure that the elements of the multibody simulation were verified and validated, correlation against multiple VIS related ground hardware testbeds was performed and characterized. In addition to the isolation part of the VIS problem, stabilization is also key to the integrated performance and evaluation. Due to the difficulty in defining ISS requirements in this area, the stability of the exerciser was inspected via analysis. Loss of balance was defined analytically as occurring when the resultant force vector acting on the exerciser lies outside the base of support of the feet. Both the VIS and E4D teams have recently gone through their Critical Design Reviews (CDRs) and the iterative model-based approach has been integral to inform mechanical design, particularly in the case of the VIS. This same end-to-end approach is now being applied for the Gateway Program, where an Exploration Exercise Device (EED) derived from the E4D and notional VIS for the device are under concept development.

Countermeasures↗

Effects of Replacing Treadmill Running with Alternative Exercise Countermeasures During Long-Duration Spaceflight

Introduction: Current exercise countermeasures on the International Space Station (ISS), including treadmill running, cycle ergometry, and resistive exercise, are used to protect crewmember health and performance during long-duration spaceflight. However, exploration vehicles for Artemis and beyond will have volume and power restrictions, requiring exercise hardware to have a smaller footprint and use fewer resources. Thus, recent efforts have focused on developing exercise devices (such as the European Enhanced Exploration Exercise Device [E4D]) that provide both aerobic and resistive training on one platform without including a treadmill. It is critical to validate the efficacy of exploration-focused exercise modalities to preserve muscle strength, aerobic fitness, bone density, and sensorimotor performance. Thus, the aim of this study is to determine the physiological effects of spaceflight that occur with nominal ISS exercise prescriptions compared to exploration-forward exercise modalities to determine if a treadmill is required to maintain current levels of protection during long-duration missions. Methods: Crewmembers will be assigned to one of three groups: 1) Control Group (n ≥ 40), who will partake in nominal exercise on the ISS, including running on the Treadmill with Vibration Isolation and Stabilization 2 (T2), ergometry on the Cycle Ergometer with Vibration Isolation and Stabilization (CEVIS) device, and strength training on the Advanced Resistive Exercise Device (ARED); 2) Active Group 1, who will partake in CEVIS and ARED exercise only (n = 8); and 3) Active Group 2, who will partake in aerobic and resistive exercise on the E4D only (n = 8). For Active Group 1, nominal aerobic exercise on T2 will be replaced with corresponding exercise on CEVIS. For Active Group 2, a dedicated exercise prescription will be designed to maximize the capabilities of the E4D to include resistive exercise, cycle ergometry, rowing, and rope pulling. Crewmembers in both active groups will not be permitted to perform treadmill exercise. Health and performance markers including bone mineral density (dual-energy x-ray absorptiometry [DXA]), body composition (DXA), cardiovascular fitness (cycle VO2peak), muscle strength and endurance (isometric/isokinetic testing, power endurance testing), sensorimotor performance (sit-to-stand, obstacle course), postural control (computerized dynamic posturography), Results: Eight subjects (2 Active [CEVIS + ARED], 6 Control) have been recruited for this study. Data collection is currently in progress. Conclusions: This study will assess the efficacy of exploration exercise modalities, including the effects of removing the treadmill exercise capability or of exclusively using the E4D, compared to nominal ISS exercise across an entire mission on bone, muscle, aerobic, and sensorimotor health and performance. Findings from this study will help provide a recommendation on whether these exploration exercise modalities can sufficiently protect against physiological deconditioning during spaceflight or whether a treadmill may be required to maintain current levels of protection during future exploration class spaceflight missions.

A.N. Varanoske↗

Response of Subsurface Nitrogen-Cycling Microbial Communities to Environmental Fluctuations (Final Technical Report)

Riparian floodplains are dynamic ecosystems linking terrestrial and riverine systems. These floodplains experience hydrological shifts such as changes in water table height, flooding, and drought and can be ‘hotspots’ of biogeochemical cycling due to shifting sediment moisture (and saturation) and subsurface exchanges of water, nutrients, and other compounds across different sediment layers. Subsurface microbial communities are the primary drivers of biogeochemical processes in floodplains, and thus their structure and function can directly influence both surface and groundwater quality. The microbial nitrogen (N) cycle is particularly important in floodplains as it affects nutrient availability and removal. Two functional guilds of chemoautotrophic (i.e. CO2-fixing) microorganisms are responsible for the first oxidative step of the N cycle, nitrification: ammonia-oxidizing archaea (AOA) and bacteria (AOB) catalyze the oxidation of ammonia to nitrite, while nitrite-oxidizing bacteria (NOB) oxidize nitrite to nitrate. Despite the critical role nitrification plays in N-cycling in both terrestrial and aquatic ecosystems, our understanding of the diversity, ecophysiology, and activity of nitrifying organisms in subsurface floodplain soils/sediments is extremely limited. To help address this critical knowledge gap, the overarching goal of this project was to determine how shifts in key environmental parameters and gradients impact microbial N-cycling communities/processes, with particular emphasis on nitrification, within hydrologically-variable floodplain sediments in the Wind River Basin near Riverton, Wyoming. The three specific objectives of this project were to: (1) to associate in situ environmental drivers of N cycling with distinct functional guilds; (2) determine the guild response to variation in key ecosystem drivers; and (3) develop a dynamic ecosystem model of the microbial N cycle with the Riverton subsurface using community genomic and biogeochemical data collected in the first two objectives. Over the course of this project, we employed both 16S rRNA gene amplicon sequencing and genome-resolved metagenomics to examine the phylogenetic diversity and metabolic potential of subsurface nitrifier communities within 68 samples collected across multiple sites, depths, and time points within the Riverton floodplain, allowing for both spatial and temporal investigations at different scales. This project benefitted tremendously from recent advances in high-throughput sequencing technologies coupled with dramatic improvements in the computational tools and algorithms available for analyzing such large, complex genomic datasets. By pairing these cutting-edge genomic approaches with depth-resolved sampling and detailed geochemical analyses of the Riverton floodplain, we have gained novel insights into the structure and function of subsurface nitrifier communities in relation to both hydrology and biogeochemistry. This project resulted in the most detailed and comprehensive characterization of N-cycling floodplain microbial communities to date and will hopefully inspire and pave the way for future studies using similar approaches in other floodplains. Indeed, such information is critical for understanding subsurface biogeochemical cycling and how elemental stores are altered from perturbations initiated by the water cycle within floodplains. Finally, because of the terrestrial-aquatic nature of the Riverton floodplain, results from this project are also of relevance to disciplines such as soil science, estuarine science, limnology & oceanography, biogeochemistry, geobiology, environmental engineering, as well as genomics and data science.

54 ENVIRONMENTAL SCIENCES↗

Foundational Dataset for Developing Large-Sample Stream Temperature Models in the Conterminous United States

This dataset provides inputs, evaluation results, and trained weights from a large-sample Long Short-Term Memory (LSTM) model designed to predict daily stream temperatures across unregulated river reaches in the conterminous United States (CONUS). It includes dynamic meteorological and hydrologic forcings, static physiographic attributes, and model outputs from cross-validation experiments spanning 300 basins. It supports reproducible modeling, direct application for new basins, and provides data suitable for integration with reservoir and river simulations under current and future climates. It contains two .zip files described below · RQ-AI_runs.zip: Model outputs from 10-fold cross-validation experiments, including observed and predicted daily stream temperatures, along with test performance metrics for water years 2017–2019. Two versions are included: 1. Model trained and validated using subbasin-area weighted dynamic features. 2. Model trained and validated using whole-basin area weighted dynamic features. · RQ-AI_inputs.zip: Collection of all formatted dynamic and static predictor datasets (meteorological, hydrologic, and physiographic features) used in model training and analysis. Detailed instructions and data structure is held at the following GitLab repository: https://code.ornl.gov/tempwise/training.

Gomez-Velez, Jesus [Oak Ridge National Laboratory ↗

Changuinola peat soil characteristics and gas emission raw data October 2019

This dataset comprises radiocarbon and geochemical measurements from peat and porewater samples collected across various depths at a site in Bocas del Toro, Panama. The study focuses on carbon cycling dynamics in tropical peatlands by examining carbon isotopic signatures (¹⁴C and ¹³C) and elemental compositions of bulk peat, dissolved organic carbon (DOC), carbon dioxide (CO₂), and methane (CH₄). Key parameters include radiocarbon ages and isotopic ratios (δ¹³C) of bulk peat, concentrations of carbon (%C) and nitrogen (%N), and radiocarbon content of porewater gases and dissolved organic carbon (DOC). The data provide insights into the vertical and spatial distribution of carbon sources and possible preservation and decomposition processes within tropical peat profiles, offering critical information for understanding carbon storage and greenhouse gas emissions in these ecosystems.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) carbon isotopic signatures (¹⁴C and ¹³C); (5) concentrations of carbon (%C) and nitrogen (%N); (6) radiocarbon content of porewater carbon dioxide (CO₂), and methane (CH₄) ; (7) porewater DOC; (8) bulk peat sampling protocol; (9) porewater sampling protocol; (10) porewater gas collection methods; and (11) gas extraction methods. All files are in .csv format and can be opened with any software that supports this file types.

54 ENVIRONMENTAL SCIENCES↗

Twist Model Development and Results From the Active Aeroelastic Wing F/A-18 Aircraft

Understanding the wing twist of the active aeroelastic wing F/A-18 aircraft is a fundamental research objective for the program and offers numerous benefits. In order to clearly understand the wing flexibility characteristics, a model was created to predict real-time wing twist. A reliable twist model allows the prediction of twist for flight simulation, provides insight into aircraft performance uncertainties, and assists with computational fluid dynamic and aeroelastic issues. The left wing of the aircraft was heavily instrumented during the first phase of the active aeroelastic wing program allowing deflection data collection. Traditional data processing steps were taken to reduce flight data, and twist predictions were made using linear regression techniques. The model predictions determined a consistent linear relationship between the measured twist and aircraft parameters, such as surface positions and aircraft state variables. Error in the original model was reduced in some cases by using a dynamic pressure-based assumption and by using neural networks. These techniques produced excellent predictions for flight between the standard test points and accounted for nonlinearities in the data. This report discusses data processing techniques and twist prediction validation, and provides illustrative and quantitative results.

Lizotte, Andrew↗

Twist Model Development and Results from the Active Aeroelastic Wing F/A-18 Aircraft

Understanding the wing twist of the active aeroelastic wing (AAW) F/A-18 aircraft is a fundamental research objective for the program and offers numerous benefits. In order to clearly understand the wing flexibility characteristics, a model was created to predict real-time wing twist. A reliable twist model allows the prediction of twist for flight simulation, provides insight into aircraft performance uncertainties, and assists with computational fluid dynamic and aeroelastic issues. The left wing of the aircraft was heavily instrumented during the first phase of the active aeroelastic wing program allowing deflection data collection. Traditional data processing steps were taken to reduce flight data, and twist predictions were made using linear regression techniques. The model predictions determined a consistent linear relationship between the measured twist and aircraft parameters, such as surface positions and aircraft state variables. Error in the original model was reduced in some cases by using a dynamic pressure-based assumption. This technique produced excellent predictions for flight between the standard test points and accounted for nonlinearities in the data. This report discusses data processing techniques and twist prediction validation, and provides illustrative and quantitative results.

Lizotte, Andrew M.↗

Comparison of Dynamic Stability Testing Techniques with Magnetic Suspension Wind Tunnel

Dynamic stability testing techniques currently utilized at NASA Langley Research Center (LaRC) are conducted in multiple facilities and consists of free flight, forced oscillation, and free-to-oscillate tests. The MIT/NASA/ODU Magnetic Suspension and Balance System (MSBS) has been recommissioned to explore its utility as an additional facility to expand the dynamic stability test capabilities currently available at NASA LaRC. Simulations were created to replicate each current test facility and method as closely as possible. Data collected from the simulated environments was corrupted with replicated noise sources of the different testing environments and then compared to real data collected during tests when such data was available. The corrupted data was then passed through data reduction and System Identification (SID) to estimate the accuracy of the results with the known aerodynamic model that was utilized within the simulation to generate the original data. Magnitudes of noise were varied utilizing Monte Carlo analysis to perform sensitivity analysis of each noise source on the extracted dynamic stability coefficients. Some preliminary results will be presented.

Otoniel Ramirez↗

Comparison of Dynamic Stability Testing Techniques with Magnetic Suspension Wind Tunnel

Dynamic stability testing techniques currently utilized at NASA Langley Research Center (LaRC) are conducted in multiple facilities and consists of free flight, forced oscillation, and free-to-oscillate tests. The MIT/NASA/ODU Magnetic Suspension and Balance System (MSBS) has been recommissioned to explore its utility as an additional facility to expand the dynamic stability test capabilities currently available at NASA LaRC. Simulations were created to replicate each current test facility and method as closely as possible. Data collected from the simulated environments was corrupted with replicated noise sources of the different testing environments and then compared to real data collected during tests when such data was available. The corrupted data was then passed through data reduction and System Identification (SID) to estimate the accuracy of the results with the known aerodynamic model that was utilized within the simulation to generate the original data. Magnitudes of noise were varied utilizing Monte Carlo analysis to perform sensitivity analysis of each noise source on the extracted dynamic stability coefficients. Some preliminary results will be presented.

Otoniel Ramirez↗

Precise mean sea level measurements using the Global Positioning System

This paper describes the results of a sea level measurement test conducted off La Jolla, California, in November of 1991. The purpose of this test was to determine accurate sea level measurements using a Global Positioning System (GPS) equipped buoy. These measurements were intended to be used as the sea level component for calibration of the ERS 1 satellite altimeter. Measurements were collected on November 25 and 28 when the ERS 1 satellite overflew the calibration area. Two different types of buoys were used. A waverider design was used on November 25 and a spar design on November 28. This provided the opportunity to examine how dynamic effects of the measurement platform might affect the sea level accuracy. The two buoys were deployed at locations approximately 1.2 km apart and about 15 km west of a reference GPS receiver located on the rooftop of the Institute of Geophysics and Planetary Physics at the Scripps Institute of Oceanography. GPS solutions were computed for 45 minutes on each day and used to produce two sea level time series. An estimate of the mean sea level at both locations was computed by subtracting tide gage data collected at the Scripps Pier from the GPS-determined sea level measurements and then filtering out the high-frequency components due to waves and buoy dynamics. In both cases the GPS estimate differed from Rapp's mean altimetric surface by 0.06 m. Thus, the gradient in the GPS measurements matched the gradient in Rapp's surface. These results suggest that accurate sea level can be determined using GPS on widely differing platforms as long as care is taken to determine the height of the GPS antenna phase center above water level. Application areas include measurement of absolute sea level, of temporal variations in sea level, and of sea level gradients (dominantly the geoid). Specific applications would include ocean altimeter calibration, monitoring of sea level in remote regions, and regional experiments requiring spatial and temporal resolution higher than that available from altimeter data.

Kelecy, Thomas M.↗

Geometrical-Based Generative Adversarial Network to Enhance Digital Rock Image Quality

X-ray microcomputed tomography (micro-CT) is a common tool for the study of porous media structures and properties. High-quality micro-CT data are required to accurately capture pore structures. Acquiring high-quality micro-CT data, however, is not always possible, owing to application limitations and experimental constraints. Therefore, we propose a geometrical-based generative adversarial network (GAN) to rapidly restore noisy micro-CT images to their clean counterparts. The training data and related ground-truth (GT) data are scanned for 7 min and 9.5 h, respectively. To evaluate the performance of the geometrical-based GAN, a 6003 voxel image that has never been used for training is reconstructed and compared with the corresponding GT image. Histogram matching and linear normalization are implemented to adjust the histogram of the reconstructed image to that of the GT image. A watershed-based segmentation method is then applied to delineate pore and solid phases. Lastly, we measure the Minkowski functionals and petrophysical properties, including absolute permeability, pore size distribution, drainage capillary pressure-saturation curve, and imbibition relative permeability, to estimate the physical accuracy of the denoised image. The results show that the proposed geometrical-based GAN can accurately restore noisy micro-CT data. By reducing the scanning time from 9.5 h to 7 min, the expenditure of collecting micro-CT can be decreased significantly. This is particularly important for applications where time-lapse images of a dynamic process are required, high-throughput imaging is necessary for real-time data analysis, or where the quantification of large sample volumes is required.

58 GEOSCIENCES↗

Airborne Subscale Transport Aircraft Research Testbed: Aircraft Model Development

The Airborne Subscale Transport Aircraft Research (AirSTAR) testbed being developed at NASA Langley Research Center is an experimental flight test capability for research experiments pertaining to dynamics modeling and control beyond the normal flight envelope. An integral part of that testbed is a 5.5% dynamically scaled, generic transport aircraft. This remotely piloted vehicle (RPV) is powered by twin turbine engines and includes a collection of sensors, actuators, navigation, and telemetry systems. The downlink for the plane includes over 70 data channels, plus video, at rates up to 250 Hz. Uplink commands for aircraft control include over 30 data channels. The dynamic scaling requirement, which includes dimensional, weight, inertial, actuator, and data rate scaling, presents distinctive challenges in both the mechanical and electrical design of the aircraft. Discussion of these requirements and their implications on the development of the aircraft along with risk mitigation strategies and training exercises are included here. Also described are the first training (non-research) flights of the airframe. Additional papers address the development of a mobile operations station and an emulation and integration laboratory.

Jordan, Thomas L.↗