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At least 1,135 records · Page 63

Optimizing Facility Configurations and Operating Conditions for Improved Performance in the NASA Ames 24 Inch Shock Tube

The Ames Electric Arc Shock Tube (EAST) is a shock tube wherein the driver gas can be heated by an electric arc discharge. The electrical energy is stored in a 1.2 MJ capacitor bank. Four inch and 24 inch diameter driven tubes are available. The facility is described and the need for testing in the 24 inch tube to better simulate low density NASA mission profiles is discussed. Three test entries, 53, 53B and 59, are discussed. Tests are done with air or Mars gas (95.7% CO2/2.7% N2/1.6% Ar) at pressures of 0.01 to 0.14 Torr. Velocities spanned 6.3-9.2 km/s, with a nominal center of 7 km/s. Many facility configurations are studied in an effort to improve data quality. Various driver and driven tube configurations and the use of a buffer section between the driver and the driven tube are studied. Diagnostics include test times, time histories of the shock light pulses and tilts of the shock wave off the plane normal to the tube axis. The report will detail the results of the various trials, give the best configuration/operating conditions found to date and provide recommendations for further improvements. Finally, diaphragm performance is discussed.

Shock Tube↗

Improving Nocturnal Fire Detection with the VIIRS Day-Night Band

Building on existing techniques for satellite remote sensing of fires, this paper takes advantage of the day-night band (DNB) aboard the Visible Infrared Imaging Radiometer Suite (VIIRS) to develop the Firelight Detection Algorithm (FILDA), which characterizes fire pixels based on both visible-light and infrared (IR) signatures at night. By adjusting fire pixel selection criteria to include visible-light signatures, FILDA allows for significantly improved detection of pixels with smaller and/or cooler subpixel hotspots than the operational Interface Data Processing System (IDPS) algorithm. VIIRS scenes with near-coincident Advanced Spaceborne Thermal Emission and Reflection (ASTER) overpasses are examined after applying the operational VIIRS fire product algorithm and including a modified "candidate fire pixel selection" approach from FILDA that lowers the 4-μm brightness temperature (BT) threshold but includes a minimum DNB radiance. FILDA is shown to be effective in detecting gas flares and characterizing fire lines during large forest fires (such as the Rim Fire in California and High Park fire in Colorado). Compared with the operational VIIRS fire algorithm for the study period, FILDA shows a large increase (up to 90%) in the number of detected fire pixels that can be verified with the finer resolution ASTER data (90 m). Part (30%) of this increase is likely due to a combined use of DNB and lower 4-μm BT thresholds for fire detection in FILDA. Although further studies are needed, quantitative use of the DNB to improve fire detection could lead to reduced response times to wildfires and better estimate of fire characteristics (smoldering and flaming) at night.

Day-night band↗

Utilizing the Vertical Variability of Precipitation to Improve Radar QPE

Characteristics of the melting layer and raindrop size distribution can be exploited to further improve radar quantitative precipitation estimation (QPE). Using dual-polarimetric radar and disdrometers, we found that the characteristic size of raindrops reaching the ground in stratiform precipitation often varies linearly with the depth of the melting layer. As a result, a radar rainfall estimator was formulated using D(sub m) that can be employed by polarimetric as well as dual-frequency radars (e.g., space-based radars such as the GPM DPR), to lower the bias and uncertainty of conventional single radar parameter rainfall estimates by as much as 20%. Polarimetric radar also suffers from issues associated with sampling the vertical distribution of precipitation. Hence, we characterized the vertical profile of polarimetric parameters (VP3)-a radar manifestation of the evolving size and shape of hydrometeors as they fall to the ground-on dual-polarimetric rainfall estimation. The VP3 revealed that the profile of ZDR in stratiform rainfall can bias dual-polarimetric rainfall estimators by as much as 50%, even after correction for the vertical profile of reflectivity (VPR). The VP3 correction technique that we developed can improve operational dual-polarimetric rainfall estimates by 13% beyond that offered by a VPR correction alone.

Precipitation↗

AF-M315E Propulsion System Advances and Improvements

Even as for the GR-1 awaits its first on-orbit demonstration on the planned 2017 launch of NASA's Green Propulsion Infusion Mission (GPIM) program, ongoing efforts continue to advance the technical state-of-the-art through improvements in the performance, life capability, and affordability of both Aerojet Rocketdyne's 1-N-class GR-1 and 20-N-class GR-22 green monopropellant thrusters. Hot-fire testing of a design upgrade of the GR-22 thruster successfully demonstrated resolution of a life-limiting thermo-structural issue encountered during prototype testing on the GPIM program, yielding both an approximately 2x increase in demonstrating life capability, as well as fundamental insights relating to how ionic liquid thrusters operate, thruster scaling, and operational factors affecting catalyst bed life. Further, a number of producibility improvements, related to both materials and processes and promising up to 50% unit cost reduction, have been identified through a comprehensive Design for Manufacturing and Assembly (DFMA) assessment activity recently completed at Aerojet Rocketdyne. Focused specifically on the GR-1 but applicable to the common-core architecture of both thrusters, ongoing laboratory (heavyweight) thruster testing being conducted under a Space Act Agreement at NASA Glenn Research Center has already validated a number of these proposed manufacturability upgrades, additionally achieving a greater than 40% increase in thruster life. In parallel with technical advancements relevant to conventional large spacecraft, a joint effort between NASA and Aerojet Rocketdyne is underway to prepare 1-U CubeSat AF-M315E propulsion module for first flight demonstration in 2018.

Liquid propulsion↗

A Diagnosis-Prognosis Feedback Loop for Improved Performance Under Uncertainties

The feed-forward relationship between diagnosis and prognosis is the foundation of both aircraft structural health management and the digital twin concept. Measurements of structural response are obtained either in-situ with mounted sensor networks or offline using more traditional techniques (e.g., nondestructive evaluation). Diagnosis algorithms process this information to detect and quantify damage and then feed this data forward to a prognostic framework. A prognosis of the structure's future operational readiness (e.g., remaining useful life or residual strength) is then made and is used to inform mission- critical decision-making. Years of research have been devoted to improving the elements of this process, but the process itself has not changed significantly. Here, a new approach is proposed in which prognosis information is not only fed forward for decision-making, but it is also fed back to the forthcoming diagnosis. In this way, diagnosis algorithms can take advantage of a priori information about the expected state of health, rather than operating in an uninformed condition. As a feasibility test, a diagnosis-prognosis feedback loop of this manner is demonstrated. The approach is applied to a numerical example in which fatigue crack growth is simulated in a simple aluminum alloy test specimen. A prognosis was derived from a set of diagnoses which provided feedback to a subsequent set of diagnoses. Improvements in accuracy and a reduction in uncertainty in the prognosis- informed diagnoses were observed when compared with an uninformed diagnostic approach.

Leser, Patrick E.↗

Biomechanical Modeling of the Deadlift Exercise to Improve the Efficacy of Resistive Exercise Microgravity Countermeasures

During long-duration spaceflight missions, astronauts exposure to microgravity without adequate countermeasures can result in losses of muscular strength and endurance, as well as loss of bone mass. As a countermeasure to this challenge, astronauts engage in resistive exercise during spaceflight to maintain their musculoskeletal function. The Hybrid Ultimate Lifting Kit (HULK) has been designed as a prototype exercise device for an exploration-class vehicle; the HULK features a much smaller footprint than previous devices such as the Advanced Resistive Exercise Device (ARED) on the International Space Station (ISS), which makes the HULK suitable for extended spaceflight missions in vehicles with limited volume. As current ISS exercise countermeasure equipment represents an improvement over previous generations of such devices, the ARED is being employed as a benchmark of functional performance. This project involves the development of a biomechanical model of the deadlift exercise, and is novel in that it is the first exercise analyzed in this context to include the upper limbs in the loading path, in contrast to the squat, single-leg squat, and heel raise exercises also being modeled by our team. OpenSim software is employed to develop these biomechanical models of humans performing resistive exercises to assess and improve the new exercise device designs. Analyses include determining differences in joint and muscle forces when using different loading strategies with the device, comparing and contrasting with the ARED benchmark, and determining whether the loading is sufficient to maintain musculoskeletal health. During data collection, the number of repetitions, load, cadence, stance, and grip width are controlled in order to facilitate comparisons between loading configurations. To date, data have been collected for two human subjects performing the deadlift exercise on the HULK device using two different loading conditions. Recorded data include motion capture, electromyography (EMG), ground reaction forces, device load cell data, photos and videos, and anthropometric data. Work is ongoing to perform biomechanical analyses including inverse kinematics and inverse dynamics to compare different versions of the deadlift model in order to determine which provides an appropriate level of detail to study this exercise. This work is supported by the National Space Biomedical Research Institute through NCC 9-58.

physical exercise↗

Improved Absolute Radiometric Calibration of a UHF Airborne Radar

The AirMOSS airborne SAR operates at UHF and produces fully polarimetric imagery. The AirMOSS radar data are used to produce Root Zone Soil Moisture (RZSM) depth profiles. The absolute radiometric accuracy of the imagery, ideally of better than 0.5 dB, is key to retrieving RZSM, especially in wet soils where the backscatter as a function of soil moisture function tends to flatten out. In this paper we assess the absolute radiometric uncertainty in previously delivered data, describe a method to utilize Built In Test (BIT) data to improve the radiometric calibration, and evaluate the improvement from applying the method.

radar calibration↗

The Uncertainty of Crop Yield Projections Is Reduced by Improved Temperature Response Functions

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for is greater than 50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 C to 33 C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

Wang, Enli↗

Improving Photometric Calibration of Meteor Video Camera Systems

We present the results of new calibration tests performed by the NASA Meteoroid Environment Office (MEO) designed to help quantify and minimize systematic uncertainties in meteor photometry from video camera observations. These systematic uncertainties can be categorized by two main sources: an imperfect understanding of the linearity correction for the MEO's Watec 902H2 Ultimate video cameras and uncertainties in meteor magnitudes arising from transformations between the Watec camera's Sony EX-View HAD bandpass and the bandpasses used to determine reference star magnitudes. To address the first point, we have measured the linearity response of the MEO's standard meteor video cameras using two independent laboratory tests on eight cameras. Our empirically determined linearity correction is critical for performing accurate photometry at low camera intensity levels. With regards to the second point, we have calculated synthetic magnitudes in the EX bandpass for reference stars. These synthetic magnitudes enable direct calculations of the meteor's photometric flux within the camera bandpass without requiring any assumptions of its spectral energy distribution. Systematic uncertainties in the synthetic magnitudes of individual reference stars are estimated at approx. 0.20 mag, and are limited by the available spectral information in the reference catalogs. These two improvements allow for zero-points accurate to 0.05 - 0.10 mag in both filtered and unfiltered camera observations with no evidence for lingering systematics. These improvements are essential to accurately measuring photometric masses of individual meteors and source mass indexes.

Steven Ehlert↗

Improved Intraseasonal Variability in the NASA GEOS AGCM with 2-moment Microphysics and a Shallow Cumulus Parameterization

Weather and climate models have long struggled to realistically simulate the Madden-Julian Oscillation (MJO). Here we present a significant improvement in MJO simulation in NASA's GEOS atmospheric model with the implementation of 2-moment microphysics and the UW shallow cumulus parameterization. Comparing ten-year runs (2007-2016) with the old (1mom) and updated (2mom+shlw) model physics, the updated model has increased intra-seasonal variance with increased coherence. Surface fluxes and OLR are found to vary more realistically with precipitation, and a moisture budget suggests that changes in rain reevaporation and the cloud longwave feedback help support heavy precipitation. Preliminary results also show improved MJO hindcast skill.

Madden-Julian Oscillatio↗

Improvement of Automated POST Case Success Rate Using Support Vector Machines

During early conceptual design of complex systems, concept down selection can have a large impact upon program life-cycle cost. Therefore, any concepts selected during early design will inherently commit program costs and affect the overall probability of program success. For this reason it is important to consider as large a design space as possible in order to better inform the down selection process. For conceptual design of launch vehicles, trajectory analysis and optimization often presents the largest obstacle to evaluating large trade spaces. This is due to the sensitivity of the trajectory discipline to changes in all other aspects of the vehicle design. Small deltas in the performance of other subsystems can result in relatively large fluctuations in the ascent trajectory because the solution space is non-linear and multi-modal [1]. In order to help capture large design spaces for new launch vehicles, the authors have performed previous work seeking to automate the execution of the industry standard tool, Program to Optimize Simulated Trajectories (POST). This work initially focused on implementation of analyst heuristics to enable closure of cases in an automated fashion, with the goal of applying the concepts of design of experiments (DOE) and surrogate modeling to enable near instantaneous throughput of vehicle cases [2]. Additional work was then completed to improve the DOE process by utilizing a graph theory based approach to connect similar design points [3]. The conclusion of the previous work illustrated the utility of the graph theory approach for completing a DOE through POST. However, this approach was still dependent upon the use of random repetitions to generate seed points for the graph. As noted in [3], only 8% of these random repetitions resulted in converged trajectories. This ultimately affects the ability of the random reps method to confidently approach the global optima for a given vehicle case in a reasonable amount of time. With only an 8% pass rate, tens or hundreds of thousands of reps may be needed to be confident that the best repetition is at least close to the global optima. However, typical design study time constraints require that fewer repetitions be attempted, sometimes resulting in seed points that have only a handful of successful completions. If a small number of successful repetitions are used to generate a seed point, the graph method may inherit some inaccuracies as it chains DOE cases from the non-global-optimal seed points. This creates inherent noise in the graph data, which can limit the accuracy of the resulting surrogate models. For this reason, the goal of this work is to improve the seed point generation method and ultimately the accuracy of the resulting POST surrogate model. The work focuses on increasing the case pass rate for seed point generation.

Zwack, Matthew R.↗

Continuous Calibration Improvement in Solar Reflective Bands: Landsat 5 Through Landsat 8

Launched in February 2013, the Operational Land Imager (OLI) on-board Landsat 8 continues to perform exceedingly well and provides high science quality data globally. Several design enhancements have been made in the OLI instrument relative to prior Landsat instruments: pushbroom imaging which provides substantially improved Signal-to-Noise Ratio (SNR), spectral bandpasses refinement to avoid atmospheric absorption features, 12 bit data resolution to provide a larger dynamic range that limits the saturation level, a set of well-designed onboard calibrators to monitor the stability of the sensor. Some of these changes such as refinements in spectral bandpasses compared to earlier Landsats and well-designed on-board calibrator have a direct impact on the improved radiometric calibration performance of the instrument from both the stability of the response and the ability to track the changes. The on-board calibrator lamps and diffusers indicate that the instrument drift is generally less than 0.1% per year across the bands. The refined bandpasses of the OLI indicate that temporal uncertainty of better than 0.5% is possible when the instrument is trended over vicarious targets such as Pseudo Invariant Calibration Sites (PICS), a level of precision that was never achieved with the earlier Landsat instruments. The stability measurements indicated by on-board calibrators and PICS agree much better compared to the earlier Landsats, which is very encouraging and bodes well for the future Landsat missions too.

Nischal Mishra↗

Applications of Satellite Data to Support Improvements in Irrigation and Groundwater Management in California

In agricultural regions around the world, threats to water supplies from drought and groundwater depletion are driving increased demand for tools to advance agricultural water use efficiency and support sustainable groundwater management. Satellite mapping of evapotranspiration (ET) from irrigated agricultural lands can provide agricultural producers and water resource managers with information that can be used to both optimize ag water use and improve estimates of groundwater withdrawals for irrigation. We describe the development of two remote sensing-based tools for ET mapping in California, including important lessons in terms of system design, partnership development, and transition to operations. For irrigation management, the integration of satellite data and surface sensor networks to provide timely delivery of information on crop water requirements can make irrigation scheduling more practical, convenient, and accurate.Developed through a partnership between NASA and the CA Department of Water Resources, the Satellite Irrigation Management Support (SIMS) framework integrates satellite data with information from agricultural weather networks to map crop canopy development and crop water requirements at the scale of individual fields. Information is distributed to agricultural producers and water managers via a web-based interface and web data services. SIMS also provides an API that facilitates integration with other irrigation decision support tools, such as CropManage and IrriQuest. Field trials using these integrated tools have shown that they can be used to sustain yields while improving water use efficiency and nutrient management. For sustainable groundwater management, the combination of satellite-derived estimates of ET and data on surface water deliveries for irrigation can increase the accuracy of estimates of groundwater pumping. We are developing an OpenET platform to facilitate access to ET data from multiple models and accelerate operational use of ET data in support of a range of water management applications, including implementation of the Sustainable Groundwater Management Act in CA. By providing a shared basis for decision making, we anticipate that the OpenET platform will accelerate implementation of solutions for sustainable groundwater management.

Satellite↗

Improving Aquatic Plant Management in the California Sacramento-San Joaquin Delta

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass), direct operations, and assess management impacts on plant communities. Archived satellite records going are used to review results from previous climate and management events and aide in developing long-term strategies. Modeling at local and watershed scales provides insight into land-use effects on water quality. Plant growth models informed by remote sensing are being applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments, phenology, environmental regulations, and economics in selection of management practices. Initial utilization of remote sensing tools developed for mapping of aquatic invasive weeds improved operational efficiency by focusing limited chemical use to strategic areas with high plant-control impact and incorporating mechanical harvesting when chemical use is restricted. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plants communities in the California Delta, both spatial and temporal, informed by ecological understanding with the objective of improving management and assessment effectiveness.

Aquatic↗

Improvements to Integrated Tradespace Analysis of Communications Architectures (ITACA) Network Loading Analysis Tool

NASA's SCENIC project aims to simplify and reduce the cost of space mission planning by replicating the analysis capabilities of commercially licensed software which are integrated with relevant analysis parameters specific to SCaN assets and SCaN supported user missions. SCENIC differs from current tools that perform similar analyses in that it 1) does not require any licensing fees, 2) will provide an all-in-one package for various analysis capabilities that normally requires add-ons or multiple tools to complete. As part of SCENIC's capabilities, the ITACA network loading analysis tool will be responsible for assessing the loading on a given network architecture and generating a network service schedule. ITACA will allow users to evaluate the quality of service of a given network architecture and determine whether or not the architecture will satisfy the mission's requirements. ITACA is currently under development, and the following improvements were made during the fall of 2017: optimization of runtime, augmentation of network asset pre-service configuration time, augmentation of Brent's method of root finding, augmentation of network asset FOV restrictions, augmentation of mission lifetimes, and the integration of a SCaN link budget calculation tool. The improvements resulted in (a) 25% reduction in runtime, (b) more accurate contact window predictions when compared to STK(Registered Trademark) contact window predictions, and (c) increased fidelity through the use of specific SCaN asset parameters.

analysis↗

Advanced Environmental Barrier Coating and SA Tyrannohex SiC Composites Integration for Improved Thermomechanical and Environmental Durability

The development of 2700 degF capable environmental barrier coating (EBC) systems, particularly, the Rare Earth "Hafnium" Silicon bond coat systems, have significantly improved the temperature capability and environmental stability of SiC/SiC Ceramic Matrix Composite Systems. We have specifically developed the advanced 2700 degF EBC systems, integrating the EBC to the high temperature SA Tyrannohex SiC fiber composites, for comprehensive performance and durability evaluations for potential turbine engine airfoil component applications. The fundamental mechanical properties, environmental stability and thermal gradient cyclic durability performance of the EBC - SA Tyrannohex composites were investigated. The paper will particularly emphasize the high pressure combustion rig recession, cyclic thermal stress resistance and thermomechanical low cycle fatigue testing of uncoated and environmental barrier coated Tyrannohex SiC SA composites in these simulated turbine engine combustion water vapor, thermal gradients, and mechanical loading conditions. We have also investigated high heat flux and flexural fatigue degradation mechanisms, determined the upper limits of operating temperature conditions for the coated SA composite material systems in thermomechanical fatigue conditions. Recent progress has also been made by using the self-healing rare earth-silicon based EBCs, thus enhancing the SA composite hexagonal fiber columns bonding for improved thermomechanical and environmental durability in turbine engine operation environments. More advanced EBC- composite systems based on the new EBC-Fiber Interphases will also be discussed.

Tyrannohex SiC Ceramics↗

Biocybernetic Adaptation Strategies: Machine Awareness of Human Engagement for Improved Operational Performance

Human operators interacting with machines or computers continually adapt to the needs of the system ideally resulting in optimal performance. In some cases, however, deteriorated performance is an outcome. Adaptation to the situation is a strength expected of the human operator which is often accomplished by the human through self-regulation of mental state. Adaptation is at the core of the human operator's activity, and research has demonstrated that the implementation of a feedback loop can enhance this natural skill to improve training and human/machine interaction. Biocybernetic adaptation involves a “loop upon a loop,” which may be visualized as a superimposed loop which senses a physiological signal and influences the operator’s task at some point. Biocybernetic adaptation in, for example, physiologically adaptive automation employs the “steering” sense of “cybernetic,” and serves a transitory adaptive purpose – to better serve the human operator by more fully representing their responses to the sys- tem. The adaptation process usually makes use of an assessment of transient cog- nitive state to steer a functional aspect of a system that is external to the operator’s physiology from which the state assessment is derived. Therefore, the objective of this paper is to detail the structure of biocybernetic systems regarding the level of engagement of interest for adaptive systems, their processing pipeline, and the adaptation strategies employed for training purposes, in an effort to pave the way towards machine awareness of human state for self-regulation and improved operational performance.

Stephens, Chad↗

Blunt-Body Paradox and Improved Application of Transient-Growth Framework

The “Reshotko-Tumin transition criterion" based on optimal transient growth successfully correlates laboratory measurements of roughness induced transition over blunt body configurations. Even though transient growth has not been conclusively linked to the measured onset of transition, the above correlation denotes the only available physics-based model for subcritical transition in blunt body flows, since the latter do not support any modal instabilities at typical experimental conditions. Unlike other established models based on empirical curve fits that are valid for a specific subclass of datasets, the optimal-growth-based transition criterion appears to provide a reasonable correlation with measurements in various wind tunnel and ballistic range facilities and for a broad range of surface temperature ratios. This paper is focused on optimal growth calculations that improve upon significant shortcomings of the computations underlying the Reshotko-Tumin correlation. The improved framework is applied to leeward transition over a spherical section forebody that was tested in the Mach 6 Adjustable Contour Expansion wind tunnel at Texas A&M University. The computed results highlight the significance of nonparallel basic state evolution, curvature terms, and an optimization procedure that varies both inflow and outflow locations of the transient growth interval. More important, the results indicate that the modified correlation is very close to its original form, and hence, that the accuracy of the transient-growth-based transition criterion is not compromised by using a more thorough theoretical framework. Yet the results also show that the optimal energy gain up to the predicted transition onset location can be rather small, highlighting the need to further investigate the optimal growth criterion for additional experimental configurations and to also uncover the in-depth physics underlying blunt body transition.

Freestream conditions↗