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At least 307 records · Page 17

Lateral Cutoff Analysis and Results from NASA's Farfield Investigation of No-Boom Thresholds

In support of the ongoing effort by the National Aeronautics and Space Administration (NASA) to bring supersonic commercial travel to the public, the NASA Armstrong Flight Research Center (AFRC) and the NASA Langley Research Center (LaRC), in partnership with other industry organizations and academia, conducted a flight research experiment to analyze acoustic propagation at the lateral edge of the sonic boom carpet. The name of the effort was the Farfield Investigation of No-boom Thresholds (FaINT). The test helped to build a dataset that will go toward further understanding of the unique acoustic propagation characteristics near the sonic boom carpet extremity. The FaINT was an effort that collected finely-space sonic boom data across the entire lateral cutoff transition region. A major objective of the effort was to investigate the acoustic phenomena that occur at the audible edge of a sonic boom carpet, including the transition and shadow zones. A NASA F-18B aircraft made supersonic passes such that its sonic boom carpet transition zone would intersect a linear 60-microphone, 7500-ft long array. A TG-14 motor glider equipped with a microphone on its wing also attempted to capture the same sonic boom rays that were measured on the ground, at altitudes of 3000 - 6000 ft above ground level. This paper determined an appropriate metric for sonic boom waveforms in the transition and shadow zones called Perceived Sound Exposure Level, and established a value of 65 dB as a limit for the acoustic levels defining the lateral extent of a sonic boom's noise region; analyzed the change in sonic boom levels as a function of distance from flight path both on the ground and 4500 ft above the ground; and compared between sonic boom measurements and numerical predictions.

acoustics↗

Online Visualization and Value Added Services of MERRA-2 Data at GES DISC

NASA climate reanalysis datasets from MERRA-2, distributed at the Goddard Earth Sciences Data and Information Services Center (GES DISC), have been used in broad research areas, such as climate variations, extreme weather, agriculture, renewable energy, and air quality, etc. The datasets contain numerous variables for atmosphere, land, and ocean, grouped into 95 products. The total archived volume is approximately 337 TB ( approximately 562K files) at the end of October 2017. Due to the large number of products and files, and large data volumes, it may be a challenge for a user to find and download the data of interest. The support team at GES DISC, working closely with the MERRA-2 science team, has created and is continuing to work on value added data services to best meet the needs of a broad user community. This presentation, using aerosol over Asia Monsoon as an example, provides an overview of the MERRA-2 data services at GES DISC, including: How to find the data? How many data access methods are provided? What are the best data access methods for me? How do download the subsetted (parameter, spatial, temporal) data and save in preferred spatial resolution and data format? How to visualize and explore the data online? In addition, we introduce a future online analytic tool designed for supporting application research, focusing on long-term hourly time-series data access and analysis.

Shen, Suhung↗

Calibration and Data Analysis of a Frequency Selectable Laser Source for CMB Detector Characterization

Cosmic Microwave Background (CMB) experiments study faint radiation left over from the early universe. The CMB was created when the universe became cool enough for light to travel freely through space, and today it gives scientists one of the earliest images of the universe. One important goal of modern CMB experiments is to measure this radiation with higher precision in order to search for evidence that supports the theory of cosmic inflation. To do this, scientists use extremely sensitive detectors that must be calibrated accurately. The Frequency Selectable Laser Source, or FLS, is a new calibration tool that can send selected frequencies to detectors and help measure their response. During my internship, I worked on the FLS after it returned to Fermilab from Chile, where it had been used to characterize detectors at the Simons Observatory. The system came back in parts, so the first part of my project was helping rebuild the optical and mechanical setup. After the system was rebuilt, we performed alignments to maximize the receiver photocurrent. We then collected calibration measurements over different frequency ranges, including 543 GHz to 568 GHz, 740 GHz to 766 GHz, and 60 GHz to 500 GHz. These measurements were used to check waterline calibration and reflectivity features and compare new data with previous data. Another major part of my project was learning Python so I could understand previous analysis code, modify it for new files, and write my own code to compare the mean response between datasets. The results showed that the new data was close to previous measurements and that waterline features near 556 GHz and 752 GHz were found within less than 1.5 GHz of the expected values. I also completed the reflectivity analysis for five prisms in two polarization orientations. In the original orientation, the results were consistent between the five prisms and close to values measured on a different system at the University of Chicago. I then collected a second set of measurements on my own with the polarization of the laser rotated by 90 degrees and compared them with the original data using the same Python workflow. The measured reflectivity increased for all five prisms in the new orientation, showing that the prism reflectivity depends on polarization. Future work will focus on using the FLS to characterize real CMB detectors.

Pumarino, Rafael [Unlisted]↗

Calibration and Data Analysis of a Frequency Selectable Laser Source for CMB Detector Characterization

Cosmic Microwave Background (CMB) experiments study faint radiation left over from the early universe. The CMB was created when the universe became cool enough for light to travel freely through space, and today it gives scientists one of the earliest images of the universe. One important goal of modern CMB experiments is to measure this radiation with higher precision in order to search for evidence that supports the theory of cosmic inflation. To do this, scientists use extremely sensitive detectors that must be calibrated accurately. The Frequency Selectable Laser Source, or FLS, is a new calibration tool that can send selected frequencies to detectors and help measure their response. During my internship, I worked on the FLS after it returned to Fermilab from Chile, where it had been used to characterize detectors at the Simons Observatory. The system came back in parts, so the first part of my project was helping rebuild the optical and mechanical setup. After the system was rebuilt, we performed alignments to maximize the receiver photocurrent. We then collected calibration measurements over different frequency ranges, including 543 GHz to 568 GHz, 740 GHz to 766 GHz, and 60 GHz to 500 GHz. These measurements were used to check waterline calibration and reflectivity features and compare new data with previous data. Another major part of my project was learning Python so I could understand previous analysis code, modify it for new files, and write my own code to compare the mean response between datasets. The results showed that the new data was close to previous measurements and that waterline features near 556 GHz and 752 GHz were found within less than 1.5 GHz of the expected values. I also completed the reflectivity analysis for five prisms in two polarization orientations. In the original orientation, the results were consistent between the five prisms and close to values measured on a different system at the University of Chicago. I then collected a second set of measurements on my own with the polarization of the laser rotated by 90 degrees and compared them with the original data using the same Python workflow. The measured reflectivity increased for all five prisms in the new orientation, showing that the prism reflectivity depends on polarization. Future work will focus on using the FLS to characterize real CMB detectors.

Pumarino Meza, Rafael [Unlisted, US; Fermilab]↗

Calibration and Data Analysis of a Frequency Selectable Laser Source for CMB Detector Characterization

Cosmic Microwave Background (CMB) experiments study faint radiation left over from the early universe. The CMB was created when the universe became cool enough for light to travel freely through space, and today it gives scientists one of the earliest images of the universe. One important goal of modern CMB experiments is to measure this radiation with higher precision in order to search for evidence that supports the theory of cosmic inflation. To do this, scientists use extremely sensitive detectors that must be calibrated accurately. The Frequency Selectable Laser Source, or FLS, is a new calibration tool that can send selected frequencies to detectors and help measure their response. During my internship, I worked on the FLS after it returned to Fermilab from Chile, where it had been used to characterize detectors at the Simons Observatory. The system came back in parts, so the first part of my project was helping rebuild the optical and mechanical setup. After the system was rebuilt, we performed alignments to maximize the receiver photocurrent. We then collected calibration measurements over different frequency ranges, including 543 GHz to 568 GHz, 740 GHz to 766 GHz, and 60 GHz to 500 GHz. These measurements were used to check waterline calibration and reflectivity features and compare new data with previous data. Another major part of my project was learning Python so I could understand previous analysis code, modify it for new files, and write my own code to compare the mean response between datasets. The results showed that the new data was close to previous measurements and that waterline features near 556 GHz and 752 GHz were found within less than 1.5 GHz of the expected values. I also completed the reflectivity analysis for five prisms in two polarization orientations. In the original orientation, the results were consistent between the five prisms and close to values measured on a different system at the University of Chicago. I then collected a second set of measurements on my own with the polarization of the laser rotated by 90 degrees and compared them with the original data using the same Python workflow. The measured reflectivity increased for all five prisms in the new orientation, showing that the prism reflectivity depends on polarization. Future work will focus on using the FLS to characterize real CMB detectors.

Pumarino Meza, Rafael [Unlisted, US; Fermilab]↗

Interference-Fit Life Factors for Ball Bearings

The effect of hoop stresses on the rolling-element fatigue life of angular-contact and deep-groove ball bearings was determined for common inner-ring interference fits at the ABEC-5 tolerance level. The analysis was applied to over 1150 bearing configurations and load cases. Hoop stresses were superimposed on the Hertzian principal stresses created by the applied bearing load to calculate the inner-race maximum shearing stress. The resulting fatigue life of the bearing was recalculated through a series of equations. The reduction in the fatigue life is presented as life factors that are applied to the unfactored bearing life. The life factors found in this study ranged from 1.00 (no life reduction)--where there was no net interface pressure--to a worst case of 0.38 (a 62-percent life reduction). For a given interference fit, the reduction in life is different for angular-contact and deep-groove ball bearings. Interference fits also affect the maximum Hertz stress-life relation. Experimental data of Czyzewski, showing the effect of interference fit on rolling-element fatigue life, were reanalyzed to determine the shear stress-life exponent. The Czyzewski data shear stress-life exponent c equals 8.77, compared with the assumed value of 9. Results are presented as tables and charts of life factors for angular-contact and deep-groove ball bearings with light, normal, and heavy loads and interference fits ranging from extremely light to extremely heavy.

Oswald, Fred B.↗

The Use of Water Vapor for Detecting Environments that Lead to Convectively Produced Heavy Precipitation and Flash Floods

This Tech Report summarizes years of study and experiences on using GOES Water vapor (6.7 micron and precipitable water) and Special Sensor Microwave Imager (SSM/1) from the Defense Meteorological Satellite Program (DMSP) derived Precipitable Water (PNAI) for detecting environments favorable for convectively produced flash floods. An emphasis is on the moisture. upper air flow, and equivalent potential temperature (Theta(sub e)) patterns that lead to devastating flood events. The 15 minute 6.7 micron water vapor imagery is essential for tracking middle to upper tropospheric disturbances that produce upward vertical motion and initiate flash flood producing systems. Water vapor imagery at 6.7 micron is also used to detect surges of upper level moisture (called tropical water vapor plumes) that have been associated with extremely heavy rainfall. Since the water vapor readily depicts lifting mechanisms and upper level moisture, water vapor imagery is often an excellent source of data for recognizing patterns of heavy precipitation and flash floods. In order to analyze the depth of the moisture, the PW aspects of the troposphere must be measured. The collocation (or nearby location) of high values ofP\V and instability are antecedent conditions prior to the flash flood or heavy rainfall events. Knowledge of PW magnitudes have been used as thresholds for impending flash flood events, PW trends are essential in flash flood prediction. Conceptual models and water vapor products are used to study some of the characteristics of convective systems that occurred over the United States of America (USA) during the summer of 1997 and the 1997-1998 El Nino. P\V plumes were associated with most of the \vest coast heavy precipitation events examined during the winter season of 1997 - 1998, In another study, conducted during the summer season of 1997. results showed that the collocation of water vapor (6.7 micron) and P\N' plumes possessed higher correlations with predicted rainfall amounts than when PW plumes occurred by themselves (i.e.. without the presence of 6.7 micron water vapor plumes). Satellite Analysis Branch (SAB) meteorologists use the 6.7 micron water and P\V products for their QPE's (interactive Flash Flood Analyzer (IFFA) and Auto-Estimator precipitation estimates), Outlooks, and heavy precipitation briefings with the Hydrometeorological Prediction Center/National Center for Environmental Prediction.

Scofield, Rod↗

SiC Receiver/Reactor by Additive Manufacturing for Concentrated Solar Thermocatalysis with Thermal Energy Storage (Final Technical Report - Public)

The direct use of solar thermal energy provides opportunities for low-cost heating sources for a variety of applications. Ultra-high temperatures around 1000°C are high value and highly useful for energy-demanding industries. Many materials cannot withstand these conditions. In the area of Sustainable Chemicals, further limitations on material stability exist. Combining state-of-the-art materials with new designs provides a promising pathway for harvesting solar thermal energy and performing high temperature chemical processes. However, conventional manufacturing limits the potential for design flexibility. In this project, Additive Manufacturing was combined with advanced materials and new chemical reactor designs. In addition, 24/7 energy is necessary for chemical processing, and designs for ultra-high temperature thermal storage were devised. Specifically, preliminary design of a novel solar thermal receiver was developed in this project and designed to work with thermocatalytic reactors for producing sustainable chemicals and fuels. An ultra-high temperature particle storage system and heat exchangers were proposed to transport ultra-hot air as thermal fluid for the system. On a broader scale, this system could be used to tap solar thermal energy for a centralized facility with capability of transferring that heat to various segments at a full range of temperatures to 1000°C. The project pushed the temperature boundaries past those in current use, and Additive Manufacturing was envisaged for fabricating the receiver to meet requirements of extreme environments. An extensive analysis of silicon carbide additive manufacturing was performed to compare the thermal and mechanical properties of complex geometries compared to conventional material and those manufactured via other methods. The Additive Manufacturing via Binder-Jet printing was optimized and characterized to provide high quality and reproducible components capable of withstanding the proposed extreme environments. The designs for the concentrating solar thermal cavity with ultra-hot air thermal fluid showed high performance in simulations, attributable to the complex optimized geometries of the 3D printed systems. The bright future of Additive Manufacturing with advanced materials developments should provide more options and even higher quality as the technology further develops. Current costs for Additive Manufacturing of advanced ceramics is relatively low, however post-processing of the materials for extreme environments is currently high. There is little industrial-scale infrastructure for these, but it is growing as niche applications become more mainstream. The results of the project can be translated into similar extreme environments for concentrating solar thermal energy as well as its integration with ultra-hot air thermal fluids. A number of industries that require ultra-high temperatures need to electrify or otherwise decarbonize for climate goals, and this project showed that theoretically there is a pathway to do so with direct concentrated solar thermal power.

10 SYNTHETIC FUELS↗

Optimizing enzymes for plastic upcycling using machine learning design and high throughput experiments

Plastic use is ubiquitous in the modern world, and polyethylene terephthalate (PET) is one of the most abundantly produced plastics (and the most highly produced polyester), with ~65 million metric tons manufactured annually. To the consumer, PET is likely most recognizable as the plastic used to make beverage bottles. Like many plastics, traditional mechanical or chemical means of PET deconstruction and upcycling are costly and inefficient. Because of these challenges, recycled plastic is generally of lower quality and is more expensive to produce than virgin plastic derived from petroleum. Ultimately, this results in most plastic ending up as waste. We view plastic waste as an underutilized resource which, with the development of more efficient and high-quality recycling processes, could (1) generate significant economic value while (2) decreasing petroleum usage and greenhouse gas emissions, as well as (3) minimizing its negative environmental and health impacts. Biocatalytic recycling, or biomanufacturing the basic building blocks of new plastic from plastic waste, is a promising approach to plastic reuse that complements existing recycling technologies. Recently, biological enzymes capable of breaking down PET have garnered significant attention as an attractive means of dealing with the plastic problem. These enzymes are currently undergoing pilot studies for implementation in industrial-scale enzyme-based recycling. However, there are significant limitations to current enzymes, including the need to perform costly pre-processing of the plastic waste before the enzymes are able to work. Further optimization of these enzymes is necessary to make these technologies competitive, and ultimately incentivise industry-wide adoption of this biology-based green recycling technology. n this work we demonstrate a means to design and generate performant biological enzymes, capable of efficiently deconstructing plastic waste. Specifically, we applied recent advances in artificial intelligence, machine learning, and statistical analysis to design new versions and discover natural enzymes capable of breaking down PET. We focused on optimizing key properties that are important for industrial-scale enzymatic recycling such as pH and thermotolerance. Normal testing of enzymatic plastic-deconstruction is extremely labor intensive and so through this work we also developed a robotic-assisted experimental pipeline capable of characterizing thousands of candidate enzymes. The results of this iterative, AI-guided, multi-discipline approach have led to increases in enzymatic breakdown of over 150X over starting enzymes. This work supports the rapidly developing and transformative field of biocatalytic solutions to environmental problems beyond the discovery and predictive understanding of enzymes for polymer recycling, and has wide implications for tackling numerous energy problems such as carbon capture and fixation (e.g., engineering carbon monoxide dehydrogenase and the rubisco-pathway), biomining (e.g., design of lanthanide-binding proteins) and biomanufacturing (e.g., lignin-deconstruction enzymes).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Estimation of Surface Temperature and Heat Flux by Inverse Heat Transfer Methods Using Internal Temperatures Measured While Radiantly Heating a Carbon/Carbon Specimen up to 1920 F

The ability to solve the heat conduction equation is needed when designing materials to be used on vehicles exposed to extremely high temperatures; e.g. vehicles used for atmospheric entry or hypersonic flight. When using test and flight data, computational methods such as finite difference schemes may be used to solve for both the direct heat conduction problem, i.e., solving between internal temperature measurements, and the inverse heat conduction problem, i.e., using the direct solution to march forward in space to the surface of the material to estimate both surface temperature and heat flux. The completed research first discusses the methods used in developing a computational code to solve both the direct and inverse heat transfer problems using one dimensional, centered, implicit finite volume schemes and one dimensional, centered, explicit space marching techniques. The developed code assumed the boundary conditions to be specified time varying temperatures and also considered temperature dependent thermal properties. The completed research then discusses the results of analyzing temperature data measured while radiantly heating a carbon/carbon specimen up to 1920 F. The temperature was measured using thermocouple (TC) plugs (small carbon/carbon material specimens) with four embedded TC plugs inserted into the larger carbon/carbon specimen. The purpose of analyzing the test data was to estimate the surface heat flux and temperature values from the internal temperature measurements using direct and inverse heat transfer methods, thus aiding in the thermal and structural design and analysis of high temperature vehicles.

Pizzo, Michelle↗

Improved Subseasonal Forecasting of Extreme Polar Vortices Using Machine Learning

Our research was focused on forecasting the position and shape of the winter stratospheric polar vortex at a subseasonal timescale of 15 days in advance. To achieve this, we employed both statistical and neural network machine learning techniques. The analysis was performed on 42 winter seasons of reanalysis data provided by NASA giving us a total of 6,342 days of data. The state of the polar vortex for determined by using geometric moments to calculate the centroid latitude and the aspect ratio of an ellipse fit onto the vortex. Timeseries for thirty additional precursors were calculated to help improve the predictive capabilities of the algorithm. Feature importance of these precursors was performed using random forest to measure the predictive importance and the ideal number of precursors. Then, using the precursors identified as important, various statistical methods were tested for predictive accuracy with random forest and nearest neighbor performing the best. An echo state network, a type of recurrent neural network that features sparsely connected hidden layer and a reduced number of trainable parameters that allows for rapid training and testing, was also implemented for the forecasting problem. Hyperparameter tuning was performed for each methods using a subset of the training data. The algorithms were trained and tuned on the first 41 years of data, then tested for accuracy on the final year. In general, the centroid latitude of the polar vortex proved easier to predict than the aspect ratio across all algorithms. Random forest outperformed other statistical forecasting algorithms overall but struggled to predict extreme values. Forecasting from echo state network suggested a strong predictive capability past 15 days, but further work is required to fully realize the potential of recurrent neural network approaches.

54 ENVIRONMENTAL SCIENCES↗

Differences in Femoral Geometry and Structure Due to Immobilization

Reduction in bone mass of the lower extremity is well documented in individuals with paralysis resulting from spinal cord injury (SCI). The consequent osteopenia leads to elevated fracture risk with fractures occurring more commonly in the femoral shaft and supracondylar regions than the hip. A model has recently been described to estimate geometry and structure of the femoral midshaft from whole body scans by dual X-ray absorptiometry (DXA). Increases in femoral geometric and structural properties during growth were primarily related to mechanical loading as reflected by body mass. In this study, we investigate the relationship between body mass and femoral geometry and structure in adults with normal habitual mechanical loading patterns and those with severely reduced loading. The subjects were 78 ambulatory men (aged 20-72 yrs) and 113 men with complete paralysis from SCI of more than 4 years duration (aged 21 73 yrs). Subregional analysis was performed on DXA whole body scans to obtain bone mineral content (BMC, g), cortical thickness (cm), crosssectional moment of inertia (CSMI, cm4), and section modulus (cm3) of the femoral midshaft. All measured bone variables were significantly lower in SCI compared with ambulatory subjects: -29% (BMC), -33% (cortical thickness), -23% (CSMI), and -22% (section modulus) while body mass was not significantly different. However, the associations between body mass and bone properties were notably different; r2 values were higher for ambulatory than SCI subjects in regressions of body mass on BMC (0.48 vs 0.20), CSMI (0.59 vs 0.32), and section modulus (0.59 vs 0.31). No association was seen between body mass and cortical thickness for either group. The greatest difference between groups is in the femoral cortex, consistent with reduced bone mass via endosteal expansion. The relatively lesser difference in geometric and structural properties implies that there is less effect on mechanical integrity than would be expected from bone mass results alone. The reduced association in SCI subjects between body mass and bone properties is not unexpected. Although mean body mass differs little between ambulatory and SCI individuals, the association between body mass and in vivo skeletal loading is no longer present, as mechanical influences are removed except for transfer activities. The residual association is probably attributable to the strength of this influence during growth. These results highlight the importance of examining geometry and structure in conjunction with bone mass.

Kiratli, Beatrice Jenny↗

Percentage Contributions from Atmospheric and Surface Features to Computed Brightness Temperatures

Over the past few years, there has become an increasing interest in the use of millimeter-wave (mm-wave) and sub-millimeter-wave (submm-wave) radiometer observations to investigate the properties of ice particles in clouds. Passive radiometric channels respond to both the integrated particle mass throughout the volume and field of view, and to the amount, location, and size distribution of the frozen (and liquid) particles with the sensitivity varying for different frequencies and hydrometeor types. One methodology used since the 1960's to discern the relationship between the physical state observed and the brightness temperature (TB) is through the temperature weighting function profile. In this research, the temperature weighting function concept is exploited to analyze the sensitivity of various characteristics of the cloud profile, such as relative humidity, ice water path, liquid water path, and surface emissivity. In our numerical analysis, we compute the contribution (in Kelvin) from each of these cloud and surface characteristics, so that the sum of these various parts equals the computed TB. Furthermore, the percentage contribution from each of these characteristics is assessed. There is some intermingling/contamination of the contributions from various components due to the integrated nature of passive observations and the absorption and scattering between the vertical layers, but all in all the knowledge gained is useful. This investigation probes the sensitivity over several cloud classifications, such as cirrus, blizzards, light snow, anvil clouds, and heavy rain. The focus is on mm-wave and submm-wave frequencies, however discussions of the effects of cloud variations to frequencies as low as 10 GHz and up to 874 GHz will also be presented. The results show that nearly 60% of the TB value at 89 GHz comes from the earth's surface for even the heaviest blizzard snow rates. On the other hand, a significant percentage of the TB value comes from the snow in the cloud for 166, and 183 plus or minus 7 GHz for the heavy and medium snow rates. For submm-wave channels, there is no contribution from the surface because these channels cannot probe through clouds, nor normal water vapor amounts in clear air regions. This work is extremely valuable in physically-based retrieval algorithm development research.

Gail Skofronick-Jackson↗

Consideration of Alternate Working Fluid Properties in Gas Lubricated Foil Journal Bearings

The Oil-Free Turbomachinery Program at the NASA Glenn Research center is committed to, revolutionary improvements in performance, efficiency and reliability of turbomachinery propulsion systems. One of the key breakthroughs by which this goal is being achieved is the maturation of air lubricated foil bearing technology. Through experimental testing, foil bearings have demonstrated a variety of exceptional qualities that show them to have an important role in the future of rotordynamic lubrication. Most of the work done with foil bearings thus far has considered ambient air at atmospheric pressure as the working fluid or lubricating fluid in the bearing. However, special applications of oil-free technology require the use of air at non- standard ambient conditions or completely different working fluids altogether. The NASA Jupiter Icy Moon Orbiter program presents power generation needs far beyond that of any previous space exploration effort. The proposed spacecraft will require significant power generation to provide the propulsion necessary to reach the moons of Jupiter and navigate between them. Once there, extensive scientific research will be conducted that will also present significant power requirements. Such extreme needs require exploring a new method for power generation in space. A proposed solution involves a Brayton cycle nuclear fission reactor. The nature of this application requires reliable performance of all reactor components for many years of operation under demanding conditions. This includes the bearings which will be operating with an alternative working fluid that is a combination of Helium and Xenon gases commonly known as HeXe. This fluid has transport and thermal properties that vary significantly from that of air and the effect of these property differences on bearing performance must be considered. One of the most promising applications of oil-free technology is in aircraft turbine engines. Eliminating the oil supply systems from aircraft engines will lead to significant weight and maintenance reduction. In such applications, the lubricating fluid will be high altitude air. This air will be at much lower pressure than that at sea level. Again this property change will result in a change in bearing performance, and analysis is required to quantify this effect. The study of these alternate working fluid properties will be conducted in two ways: analytically and experimentally. Analytical research will include the use of a mathematical code that can predict film thickness profiles for various ambient conditions. Estimations of load capacity can be made based upon the film thickness trends. These values will then be compared to those obtained from classical rigid bearing analysis. Experimental Research will include testing a foil bearing at a variety of ambient air pressures. The analytical and experimental data will be compared to draw conclusions on bearing performance under alternate working fluid properties.

Smith, Matthew J.↗

Disk-resolved Photometric Properties of Pluto and the Coloring Materials across its Surface

A multiwavelength regionally dependent photometric analysis of Pluto's anti-Charon-facing hemisphere using images collected by New Horizons' Multispectral Visible Imaging Camera (MVIC) reveals large variations in the absolute value and spectral slope of the single-scattering albedo. Four regions of interest are analyzed: the dark equatorial belt, Pluto's north pole, nitrogen-rich regions, and the mid-latitude terrains. Regions dominated by volatile ices such as Lowell Regio and Sputnik Planitia present single-scattering albedos of ~0.98 at 492 nm, almost neutral across MVIC's visible wavelength range (400–910 nm), indicating limited contributions from tholin materials. Pluto's dark equatorial regions, informally named Cthulhu and Krun Maculae, have single-scattering albedos of ~0.16 at 492 nm and are the reddest regions. Applying the Hapke radiative transfer model to combined MVIC and Linear Etalon Imaging Spectral Array (LEISA) spectra (400–2500 nm) of Cthulhu Macula and Lowell Regio successfully reproduces the spectral properties of these two regions of dramatically disparate coloration, composition, and morphology. Since this model uses only a single coloring agent, very similar to the Titan-like tholin of Khare et al., to account for all of Pluto's colors, this result supports the Grundy et al. conclusion that Pluto's coloration is the result of photochemical products mostly produced in the atmosphere. Although cosmic rays and extreme ultraviolet photons reach Pluto's surface where they can drive chemical processing, observations of diverse surface colors do not require different chemical products produced in different environments. We report a correction scaling factor in the LEISA radiometric calibration of 0.74 ± 0.05.

Silvia Protopapa↗

Prediction of Acoustic Environments from Horizontal Rocket Firings

In recent years, advances in research and engineering have led to more powerful launch vehicles which can reach areas of space not yet explored. These more powerful vehicles yield acoustic environments potentially destructive to the vehicle or surrounding structures. Therefore, it has become increasingly important to be able to predict the acoustic environments created by these vehicles in order to avoid structural and/or competent failure. The current industry standard technique for predicting launch-induced acoustic environments was developed by Eldred in the early 1970's and is published in NASA SP-80721. Recent work2 has shown Eldred's technique to be inaccurate for current state-of-the-art launch vehicles. Due to the high cost of full-scale and even sub-scale rocket experiments, very little rocket noise data is available. Furthermore, much of the work thought to be applicable to rocket noise has been done with heated jets. Tam3,4 has done an extensive amount of research on jets of different nozzle exit shape, diameter, velocity, and temperature. Though the values of these parameters, especially exit velocity and temperature, are often very low compared to these values in rockets, a lot can be learned about rocket noise from jet noise literature. The turbulent nature of jet and rocket exhausts is quite similar. Both exhausts contain turbulent structures of varying scale-termed the fine and large scale turbulence by Tam. The finescale turbulence is due to small eddies from the jet plume interacting with the ambient atmosphere. According to Tam et al., the noise radiated by this envelope of small-scale turbulence is statistically isotropic. Hence, one would expect the noise from the small scale turbulence of the jet to be nearly omni-directional. The coherent nature of the large-scale turbulence results in interference of the noise radiated from different spatial locations within the jet. This interference-whether it is constructive or destructive-results in highly directional noise radiation. Tam3 has proposed a model to predict the acoustic environment due to jets and while it works extremely well for jets, it was found to be inappropriate for rockets8. A model to predict the acoustic environment due to a launch vehicle in the far-field which incorporates concepts from both Eldred and Tam was created. This was done using five sets of horizontally fired rocket data, obtained between 2008 and 2012. Three of these rockets use solid propellant and two use liquid propellant. Through scaling analysis, it is shown that liquid and solid rocket motors exhibit similar spectra at similar amplitudes. This model is accurate for these five data sets within 5 dB of the measured data for receiver angles of 30deg to 160deg (with respect to the downstream exhaust centerline). The model uses the following vehicle parameters: nozzle exit diameter and velocity, radial distance from source to receiver, receiver angle, mass flow rate, and acoustic efficiency.

Giacomoni, Clothilde↗

Selection of Next Priority IMPACT Medical Conditions Based on Available Terrestrial and Spaceflight Data

BACKGROUND: As the era of exploration class missions begins, identification of medical conditions that may occur and require management becomes essential for the modeling of medical risk. To this end, NASA has developed IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces), a suite of tools to assist in assessment of medical risk analysis. It has incorporated an initial list of the 120 conditions of highest concern, labeled the IMPACT condition list 1.0 (ICL 1.0). This abstract describes a method for prioritizing the 92 conditions included on the Proposed Future Conditions List (PFCL) for inclusion in future iterations of the ICL. OVERVIEW: To construct the Prioritized Proposed Future Conditions List (P-PFCL), each condition on the PFCL was scored as “low,” “medium,” or “high” on each of four variables: incidence, likelihood of significant task impairment, diagnostic and treatment complexity, and treatment futility. Qualitative assessment using clinical judgement was utilized to score complexity, futility, and likelihood of impairment. Incidence was assessed quantitatively using spaceflight data and/or analog populations where available then assigned a score using established cutoffs. Logarithmic numerical values were assigned to each category label. A Prioritization Score was generated for each condition by taking the product of incidence and likelihood of task impairment (risk) divided by the product of complexity and futility (difficulty of care), with higher values corresponding to higher priority for future inclusion in the ICL. DISCUSSION: The described methods allow for the generation of a ranked P-PFCL to act as a decision support tool for selection of the next generation of modeled medical conditions. Some of the conditions ranked highly on the P-PFCL include EVA-related upper and lower extremity sprain/strain, iron deficiency, delirium, and hypertension, among others. While this effort does not attempt to quantify the absolute risk associated with each condition, it does attempt to semi-quantitatively estimate the risk of each condition relative to the other possible conditions. This tool in concert with subject matter expert opinion could optimize the future use of limited resources thereby producing a more accurate medical risk model, which will be essential to the upcoming exploration class missions.

Michael Pohlen↗

Investigation of Critical Heat Flux in Reduced Gravity Using Photomicrographic Techniques

Experiments were performed to examine the effects of body force on flow boiling critical heat flux (CHF). FC-72 was boiled along one wall of a transparent rectangular flow channel that permitted photographic study of the vapor-liquid interface just prior to CHF. High-speed video imaging techniques were used to identify dominant CHF mechanisms corresponding to different flow orientations and liquid velocities. Six different CHF regimes were identified: Wavy Vapor Layer, Pool Boiling, Stratification, Vapor Counterflow, Vapor Stagnation, and Separated Concurrent Vapor Flow. CHF showed significant sensitivity to orientation for flow velocities below 0.2 m/s, where extremely low CHF values where measured, especially with downward-facing heated wall and downflow orientations. High flow velocities dampened the effects of orientation considerably. The CHF data were used to assess the suitability of previous CHF models and correlations. It is shown the Interfacial Lift-off Model is very effective at predicting CHF for high velocities at all orientations. The flooding limit, on the other hand, is useful at estimating CHF at low velocities and for downflow orientations. A new method consisting of three dimensionless criteria is developed for determining the minimum flow velocity required to overcome body force effects on near-saturated flow boiling CHF. Vertical upflow boiling experiments were performed in pursuit of identifying the trigger mechanism for subcooled flow boiling CHF. While virtually all prior studies on flow boiling CHF concern the prediction or measurement of conditions that lead to CHF, this study was focused on events that take place during the CHF transient. High-speed video imaging and photomicrographic techniques were used to record the transient behavior of interfacial features from the last steady-state power level before CHF until the moment of power cut-off following CHF. The video records show the development of a wavy vapor layer which propagates along the heated wall, permitting cooling prior to CHF only in wetting fronts corresponding to the wave troughs. Image analysis software was developed to estimate void fraction from the individual video images. The void fraction records for subcooled flow boiling show the CHF transient is accompanied by gradual lift-off of wetting fronts culminating in some maximum vapor layer mean thickness, following which the vapor layer begins to thin down as the transition to film boiling ensues. This study proves the Interfacial Lift-off Model, which has been validated for near-saturated flow boiling CHF, is equally valid for subcooled conditions.

Mudawar, Issam↗