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At least 847 records · Page 47

High Ice Water Content at Low Radar Reflectivity near Deep Convection: Part II. Evaluation of Microphysical Pathways in Updraft Parcel Simulations

The aeronautics industry has established that a threat to aircraft is posed by atmospheric conditions of substantial ice water content (IWC) where equivalent radar reflectivity (Ze) does not exceed 20-30 dBZ and supercooled water is not present; these conditions are encountered almost exclusively in the vicinity of deep convection. Part 1 (Fridlind et al., 2015) of this two-part study presents in situ measurements of such conditions sampled by Airbus in three tropical regions, commonly near 11 km and -43 C, and concludes that the measured ice particle size distributions are broadly consistent with past literature with profiling radar measurements of Z(sub e) and mean Doppler velocity obtained within monsoonal deep convection in one of the regions sampled. In all three regions, the Airbus measurements generally indicate variable IWC that often exceeds 2 gm (exp -3) with relatively uniform mass median area-equivalent diameter (MMD(sub eq) of 200-300 micrometers. Here we use a parcel model with size-resolved microphysics to investigate microphysical pathways that could lead to such conditions. Our simulations indicate that homogeneous freezing of water drops produces a much smaller ice MMD(sub eq) than observed, and occurs only in the absence of hydrometeor gravitational collection for the conditions considered. Development of a mass mode of ice aloft that overlaps with the measurements requires a substantial source of small ice particles at temperatures of about -10 C or warmer, which subsequently grow from water vapor. One conceivable source in our simulation framework is Hallett-Mossop ice production; another is abundant concentrations of heterogeneous ice freezing nuclei acting together with copious shattering of water drops upon freezing. Regardless of the production mechanism, the dominant mass modal diameter of vapor-grown ice is reduced as the ice-multiplication source strength increases and as competition for water vapor increases. Both mass and modal diameter are reduced by entrainment and by increasing aerosol concentrations. Weaker updrafts lead to greater mass and larger modal diameters of vapor-grown ice, the opposite of expectations regarding lofting of larger ice particles in stronger updrafts. While stronger updrafts do loft more dense ice particles produced primarily by raindrop freezing, we find that weaker updrafts allow the warm rain process to reduce competition for diffusional growth of the less dense ice expected to persist in convective outflow.

Reflectivity↗

Review and Analysis of Algorithmic Approaches Developed for Prognostics on CMAPSS Dataset

Benchmarking of prognostic algorithms has been challenging due to limited availability of common datasets suitable for prognostics. In an attempt to alleviate this problem several benchmarking datasets have been collected by NASA's prognostic center of excellence and made available to the Prognostics and Health Management (PHM) community to allow evaluation and comparison of prognostics algorithms. Among those datasets are five C-MAPSS datasets that have been extremely popular due to their unique characteristics making them suitable for prognostics. The C-MAPSS datasets pose several challenges that have been tackled by different methods in the PHM literature. In particular, management of high variability due to sensor noise, effects of operating conditions, and presence of multiple simultaneous fault modes are some factors that have great impact on the generalization capabilities of prognostics algorithms. More than 70 publications have used the C-MAPSS datasets for developing data-driven prognostic algorithms. The C-MAPSS datasets are also shown to be well-suited for development of new machine learning and pattern recognition tools for several key preprocessing steps such as feature extraction and selection, failure mode assessment, operating conditions assessment, health status estimation, uncertainty management, and prognostics performance evaluation. This paper summarizes a comprehensive literature review of publications using C-MAPSS datasets and provides guidelines and references to further usage of these datasets in a manner that allows clear and consistent comparison between different approaches.

Uncertainty↗

Analyzing Non Stationary Processes in Radiometers

The lack of well-developed techniques for modeling changing statistical moments in our observations has stymied the application of stochastic process theory for many scientific and engineering applications. Non linear effects of the observation methodology is one of the most perplexing aspects to modeling non stationary processes. This perplexing problem was encountered when modeling the effect of non stationary receiver fluctuations on the performance of radiometer calibration architectures. Existing modeling approaches were found not applicable; particularly problematic is modeling processes across scales over which they begin to exhibit non stationary behavior within the time interval of the calibration algorithm. Alternatively, the radiometer output is modeled as samples from a sequence random variables; the random variables are treated using a conditional probability distribution function conditioned on the use of the variable in the calibration algorithm. This approach of treating a process as a sequence of random variables with non stationary stochastic moments produce sensible predictions of temporal effects of calibration algorithms. To test these model predictions, an experiment using the Millimeter wave Imaging Radiometer (MIR) was conducted. The MIR with its two black body calibration references was configured in a laboratory setting to observe a third ultra-stable reference (CryoTarget). The MIR was programmed to sequentially sample each of the three references in approximately a 1 second cycle. Data were collected over a six-hour interval. The sequence of reference measurements form an ensemble sample set comprised of a series of three reference measurements. Two references are required to estimate the receiver response. A third reference is used to estimate the uncertainty in the estimate. Typically, calibration algorithms are designed to suppress the non stationary effects of receiver fluctuations. By treating the data sequence as an ensemble collection, it is possible to apply temporal algorithms which exacerbate the non stationary effects. By varying the algorithm, information about the properties of the non stationary receiver fluctuations is obtained. Comparisons of analytical calculations and statistical analysis of data demonstrate impressive agreement.

Racette, Paul↗

Thermal Design of the Thermal Infrared Spectrometer (TIRS) Instrument on PREFIRE

The Polar Radiant Energy in the Far-Infrared Experiment (PREFIRE) consists of two 6U CubeSats that each host a Thermal Infrared Spectrometer (TIRS) instrument. The CubeSats are scheduled for launch in March and October of 2023. The purpose of the TIRS instrument is to make spectrally resolved measurements of the Earth’s thermal radiation from the top of the atmosphere. PREFIRE will document, for the first time, variability in spectral fluxes from 4 to 54 microns on hourly to seasonal timescales. The primary mission is 12 months in a polar orbit with inclination of 82 to 98 at altitudes between 450 km and 650 km. The TIRS instrument is an Offner spectrometer that uses a thermopile detector array and a Schwarzchild telescope. In addition, there is a scan mirror which is periodically actuated for calibration. The instrument concept of operation is to collect radiation emitted towards zenith in a nadir sounding orientation with periodic internal and space calibrations. The TIRS thermal control architecture consists of entirely passive elements. The instrument requires all elements be maintained between 0 C and 50 C during operation for the duration of the mission. An overview of the overall thermal control design approach is presented.

Andrade, Andres↗

Soft computing in design and manufacturing of advanced materials

The potential of fuzzy sets and neural networks, often referred to as soft computing, for aiding in all aspects of manufacturing of advanced materials like ceramics is addressed. In design and manufacturing of advanced materials, it is desirable to find which of the many processing variables contribute most to the desired properties of the material. There is also interest in real time quality control of parameters that govern material properties during processing stages. The concepts of fuzzy sets and neural networks are briefly introduced and it is shown how they can be used in the design and manufacturing processes. These two computational methods are alternatives to other methods such as the Taguchi method. The two methods are demonstrated by using data collected at NASA Lewis Research Center. Future research directions are also discussed.

Cios, Krzysztof J.↗

The relationship among sea surface roughness variations, oceanographic analyses, and airborne remote sensing analyses

The synthetic aperture radar (SAR) was studied to determine whether it could image large scale estuaries and oceanic features such as fronts and to explain the electromagnetic interaction between SAR and the individual surface front features. Fronts were observed to occur at the entrance to the Chesapeake Bay. The airborne measurements consisted of data collection by SAR onboard an F-4 aircraft and real aperture side looking radar (SLAR) in Mohawk aircraft. A total of 89 transects were flown. Surface roughness and color as well as temperature and salinity were evaluated. Cross-frontal surveys were made. Frontal shear and convergence flow were obtained. Surface active organic materials, it was indicated, are present at the air-sea interface. In all, 2000 analyses were conducted to characterize the spatial and temporal variabilities associated with water mass boundaries.

Oertel, G. F.↗

The Influence of Soil Moisture, Coastline Curvature, and Land-Breeze Circulations on Sea-Breeze Initiated Precipitation

Idealized numerical simulations are performed with a coupled atmosphere/land-surface model to identify the roles of initial soil moisture, coastline curvature, and land breeze circulations on sea breeze initiated precipitation. Data collected on 27 July 1991 during the Convection and Precipitation Electrification Experiment (CAPE) in central Florida are used. The 3D Goddard Cumulus Ensemble (GCE) cloud resolving model is coupled with the Goddard Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model, thus providing a tool to simulate more realistically land-surface/atmosphere interaction and convective initiation. Eight simulations are conducted with either straight or curved coast-lines, initially homogeneous soil moisture or initially variable soil moisture, and initially homogeneous horizontal winds or initially variable horizontal winds (land breezes). All model simulations capture the diurnal evolution and general distribution of sea-breeze initiated precipitation over central Florida. The distribution of initial soil moisture influences the timing, intensity and location of subsequent precipitation. Soil moisture acts as a moisture source for the atmosphere, increases the connectively available potential energy, and thus preferentially focuses heavy precipitation over existing wet soil. Strong soil moisture-induced mesoscale circulations are not evident in these simulations. Coastline curvature has a major impact on the timing and location of precipitation. Earlier low-level convergence occurs inland of convex coastlines, and subsequent precipitation occurs earlier in simulations with curved coastlines. The presence of initial land breezes alone has little impact on subsequent precipitation. however, simulations with both coastline curvature and initial land breezes produce significantly larger peak rain rates due to nonlinear interactions.

Baker, David R.↗

Geochemical Mapping of 4 Vesta Begins

By December, the NASA Dawn spacecraft will have descended to a low altitude mapping orbit (LAMO), where the Gamma Ray and Neutron Detector (GRaND) will acquire global mapping data for up to four months. Measurements by GRaND will help answer elusive questions about how Vesta differentiated and the nature of processes that shaped Vesta s surface. The data will be analyzed to determine the abundances of Mg, Si, Fe, K, Th, and H at a spatial resolution of roughly 300 km full-width-at-half-maximum from a 465 km radius orbit. Thermal and fast neutron counting data will be analyzed to determine the neutron macroscopic absorption cross section and average atomic mass, providing constraints on additional elements, such as Ca and Al. GRaND will quantify the elemental composition of coarse spatial units identified by Dawn s Framing Camera (FC) and the Visible & Infrared Spectrometer (VIR). In addition, GRaND will map the mixing ratio of compositional end members selected from the howardite, eucrite and diogenite (HED) meteorites, determine the relative proportions of plagioclase and mafic minerals, and search for compositions that are absent or under-represented in the meteorite collection. While it is generally thought that Vesta s crust on a regional scale should be well-represented by linear mixing of HED whole-rock compositions, there are hints that Vesta may be more diverse than implied by this model. For example, the discovery of K-rich impact glasses in howardites suggests that K-rich rocks may be present on a portion of Vesta s surface, and the analysis of diogenites indicates considerable variability in the magmatic processes that formed them. The chemical composition of materials within Vesta s south polar structure may provide further clues to how it formed. An impact might have exposed mantle and lower crustal materials, which should have a distinctive compositional signature. We present the analysis of data acquired by GRaND from cruise through the descent to LAMO, including GRaND s sensitivity to different elements and geochemical processes.

Prettyman, Thomas H.↗

Advanced Clothing Studies

All human space missions require significant logistical mass and volume that add an unprecedented burden on longduration missions beyond low-Earth orbit. For these missions with limited cleaning resources, a new wardrobe must be developed to reduce this logistical burden by reducing clothing mass and extending clothing wear. The present studies have been undertaken, for the first time, to measure length of wear and to assess the acceptance of such extended wear. Garments in these studies are commercially available exercise T-shirts and shorts, routine-wear T-shirts, and longsleeved pullover shirts. Fabric composition (cotton, polyester, light-weight, superfine Merino wool, modacrylic, cotton/rayon, polyester/Cocona, modacrylic/Xstatic, modacrylic/rayon, modacrylic/lyocell/aramid), construction (open knit, tight knit, open weave, tight weave), and finishing treatment (none, quaternary ammonium salt) are the independent variables. Eleven studies are reported here: five studies of exercise T-shirts, three of exercise shorts, two of routine wear Tshirts, and one of shirts used as sleep-wear. All studies are conducted in a climate-controlled environment, similar to a space vehicle's. For exercise clothing, study participants wear the garments during aerobic exercise. For routine wear clothing, study participants wear the T-shirts daily in an office or laboratory. Daily questionnaires collected data on ordinal preferences of nine sensory elements and on reason for retiring a used garment. Study 1 compares knitted cotton, polyester, and Merino exercise T-shirts (61 participants), study 2, knitted polyester, modacrylic, and polyester/Cocona exercise T-shirts (40 participants), study 3, cotton and polyester exercise shorts, knitted and woven (70 participants), all three using factorial experimental designs with and without a finishing treatment, conducted at the Johnson Space Center, sharing study participants. Study 4 compares knitted polyester and ZQ Merino exercise T-shirts, study 5, knitted ZQ Merino and modacrylic routine-wear T-shirts, with study 6 using only knitted polyester exercise shorts. No finishing treatment is used. Studies 4 and 5 use cross-over experimental designs, and all three studies were conducted aboard the ISS with six crew. Studies 4 and 6 were repeated on the ground with the same participants to learn if perception was affected microgravity. Study 7 is a longer-term, single-blind panel study of knitted routine-wear undershirts with at least 12 participants to assess tolerance to Merino by comparing it with a cotton/rayon blends, using a cross-over design, eliminating carryover effects with wash-out periods between shirts.

Orndoff, Evelyne↗

TPSAS-NF1676L-13204-DND

Invasive perennial pepperweed (Lepidium latifolium) has spread rapidly throughout the western United States in the past fifteen years. Pepperweed outcompetes many native species for water and nutrients, disturbing sensitive ecosystems. The purpose of this study is to map the contemporary distribution of pepperweed throughout the wetland ecosystem of the restored South San Francisco Bay Salt Ponds and create a habitat suitability model to predict future spread. Pepperweed reflectance data were collected in-situ with the GER 1500 spectroradiometer along with presence and absence pepperweed GPS data points. A Spectral Angle Mapper (SAM) classification algorithm (Method A) was used to distinguish pepperweed spectra and map its distribution on an EO-1 Hyperion image of the study area. Similarly, a supervised classification was run on an ASTER image of the study area. A GIS multivariate habitat suitability model was created to predict areas most susceptible to pepperweed colonization. Variables incorporated into the model were tidal extent, propensity for disturbance, pond salinity, proximity to levees and channels, and terrain curvature. A Generalized Additive Model (GAM) was also used to generate a suitability map (Method B) and investigate the statistical probability that each variable contributed to predict pepperweed spread. Results from the GAM revealed distance to channels, distance to disturbance factors, extreme pond salinity and curvature as statistically significant in determining the locations of suitable pepperweed habitats

Andrew Nguyen↗

Multiversion software reliability through fault-avoidance and fault-tolerance

In this project we have proposed to investigate a number of experimental and theoretical issues associated with the practical use of multi-version software in providing dependable software through fault-avoidance and fault-elimination, as well as run-time tolerance of software faults. In the period reported here we have working on the following: We have continued collection of data on the relationships between software faults and reliability, and the coverage provided by the testing process as measured by different metrics (including data flow metrics). We continued work on software reliability estimation methods based on non-random sampling, and the relationship between software reliability and code coverage provided through testing. We have continued studying back-to-back testing as an efficient mechanism for removal of uncorrelated faults, and common-cause faults of variable span. We have also been studying back-to-back testing as a tool for improvement of the software change process, including regression testing. We continued investigating existing, and worked on formulation of new fault-tolerance models. In particular, we have partly finished evaluation of Consensus Voting in the presence of correlated failures, and are in the process of finishing evaluation of Consensus Recovery Block (CRB) under failure correlation. We find both approaches far superior to commonly employed fixed agreement number voting (usually majority voting). We have also finished a cost analysis of the CRB approach.

Vouk, Mladen A.↗

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

Modern computational and experimental tools for aerodynamics and propulsion applications have matured to a stage where they can provide substantial insight into engineering processes involving fluid flows, and can be fruitfully utilized to help improve the design of practical devices. In particular, rapid and continuous development in aerospace engineering demands that new design concepts be regularly proposed to meet goals for increased performance, robustness and safety while concurrently decreasing cost. To date, the majority of the effort in design optimization of fluid dynamics has relied on gradient-based search algorithms. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space, can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables, and methods for predicting the model performance. In this article, we review recent progress made in establishing suitable global optimization techniques employing neural network and polynomial-based response surface methodologies. Issues addressed include techniques for construction of the response surface, design of experiment techniques for supplying information in an economical manner, optimization procedures and multi-level techniques, and assessment of relative performance between polynomials and neural networks. Examples drawn from wing aerodynamics, turbulent diffuser flows, gas-gas injectors, and supersonic turbines are employed to help demonstrate the issues involved in an engineering design context. Both the usefulness of the existing knowledge to aid current design practices and the need for future research are identified.

Shyy, Wei↗

Challenges and Accomplishments of Viscous Incompressible Flow Computations in Aerospace and Beyond

Recent progress in incompressible Navier-Stokes solution methods will be presented. Discussions are focused on the methods designed for complex geometry applications in three dimensions, and thus are limited to primitive variable formulation. Both steady- and unsteady-solution algorithms and their salient features are discussed. A summary of our recent progress in flow solver development is given followed by numerical studies of a few example problems of our current interest. Solvers discussed here are based on structured-grid approach using finite-difference or finite-volume frame work. This short course will be delivered in three one-our lectures. The material in the course are collected from the work performed by the Incompressible Navier-Stokes group at NASA Ames Research Center over the past several years, and can be found in our publications widely disseminated in the US and abroad. This short course is sponsored by AGARD Consultant and Exchange Program under Support Project P-110.

Kwak, Dochan↗

In-Situ Measurements of HCN and CH3CN In the Pacific Troposphere: Sources, Sinks, and Comparisons with Satellite Observations

A new capillary gas chromatographic method using a Reduction Gas Detector was developed to measure HCN and CH3CN in the remote troposphere. This instrumental configuration was deployed for the very first time in the Trace-P field mission performed during the spring of 2001. The NASA DC-8 aircraft afforded an opportunity to measure HCN and CH3CN in polluted and pristine environments over the Pacific to a maximum altitude of 12 km. These are some of the first in situ measurements of the distribution of HCN and CH3CN over the Pacific. Large background concentrations of both nitriles were found to be present and significant variability was observed. The abundance of HCN and CH3CN was strongly impacted by outflow of pollution from Asia. In general there appeared to be a direct but nonlinear relationship between the mixing ratios of HCN and CH3CN. The vertical structure of these chemicals shows direct evidence of the presence of a significant oceanic sink. These observations will be compared with the column content HCN data from satellites and other available measurements. A large body of data have been collected and are being analyzed, both statistically and with the help of models, to better understand the sources and sinks of these nitriles. These results will be presented.

Singh, Hanwant B.↗

Miniature Variable Pressure Scanning Electron Microscope for In-Situ Imaging and Chemical Analysis

NASA Marshall Space Flight Center (MSFC) is leading an effort to develop a Miniaturized Variable Pressure Scanning Electron Microscope (MVP-SEM) for in-situ imaging and chemical analysis of uncoated samples. This instrument development will be geared towards operation on Mars and builds on a previous MSFC design of a mini-SEM for the moon (funded through the NASA Planetary Instrument Definition and Development Program). Because Mars has a dramatically different environment than the moon, modifications to the MSFC lunar mini-SEM are necessary. Mainly, the higher atmospheric pressure calls for the use of an electron gun that can operate at High Vacuum, rather than Ultra-High Vacuum. The presence of a CO2-rich atmosphere also allows for the incorporation of a variable pressure system that enables the in-situ analysis of nonconductive geological specimens. Preliminary testing of Mars meteorites in a commercial Environmental SEM(Tradmark) (FEI) confirms the usefulness of lowcurrent/low-accelerating voltage imaging and highlights the advantages of using the Mars atmosphere for environmental imaging. The unique capabilities of the MVP-SEM make it an ideal tool for pursuing key scientific goals of NASA's Flagship Mission Max-C; to perform in-situ science and collect and cache samples in preparation for sample return from Mars.

Gaskin, Jessica A.↗

The GEOS-5 Neural Network Retrieval (NNR) for AOD

One of the difficulties in data assimilation is the need for multi-sensor data merging that can account for temporal and spatial biases between satellite sensors. In the Goddard Earth Observing System Model Version 5 (GEOS-5) aerosol data assimilation system, a neural network retrieval (NNR) is used as a mapping between satellite observed top of the atmosphere (TOA) reflectance and AOD, which is the target variable that is assimilated in the model. By training observations of TOA reflectance from multiple sensors to map to a common AOD dataset (in this case AOD observed by the ground based Aerosol Robotic Network, AERONET), we are able to create a global, homogenous, satellite data record of AOD from MODIS observations on board the Terra and Aqua satellites. In this talk, I will present the implementation of and recent updates to the GEOS-5 NNR for MODIS collection 6 data.

Castellanos, Patricia↗

Changes in Exercise Data Management

The suite of exercise hardware aboard the International Space Station (ISS) generates an immense amount of data. The data collected, treadmill, cycle ergometer, and resistance strength training hardware, are basic exercise parameters (time, heart rate, speed, load, etc.). The raw data are processed in the laboratory and more detailed parameters are calculated from each exercise data file. Updates recently have been made to how these valuable data are stored, adding an additional level of security, increasing accessibility, and resulting in overall increased efficiency of medical report delivery. Questions regarding exercise performance or how exercise may influence other variables of crew health frequently arise within the crew health care community. Inquiries regarding the health of the exercise hardware often need quick analysis and response to ensure the exercise system is operable on a continuous basis. Consolidating all of the exercise system data in a single repository enables a quick response to both the medical and engineering communities. A SQL server database is currently in use, and provides a secure location for all of the exercise data starting at ISS Expedition 1 to current date. The database has been structured to update derived metrics automatically, making analysis and reporting available within minutes of dropping the in-flight data into the database. Commercial tools were evaluated to help aggregate and visualize data from the SQL database. The Tableau software provides manageable interface, which has improved the laboratory’s output time of crew reports by 67%. Expansion of the SQL database, to be inclusive of additional medical requirement metrics, addition of ‘app-like’ tools for mobile visualization, and collaborative use (e.g., operational support teams, research groups, and International Partners) of the data system, is currently being explored.

Buxton, R. E.↗

Application of remote sensing in the determination of water quality in Nebraska reservoirs

In June, July, and August, 1975, ground truth was collected from Lake McConaughy, a 35,000 acre reservoir in western Nebraska, coincident with the overflights of LANDSAT. Water samples were collected on six different dates and analyzed for turbidity, suspended solids, and chlorophyll, parameters which had correlated well with CCT reflectances. The correlations and regressions reported were derived from data obtained on only three of the six sampling dates. The radiance values from each of the four spectral bands were printed out in the form of a map of Lake McConaughy. Reflectances in the various bands were then obtained from the map at the appropriate sampling sites. The dependent variables chlorophyll, suspended solids, and turbidity were compared to the independent variables - reflectances in the four bands - by regression analysis. Both multiple and univariate regressions were examined. It is concluded that CCT's from LANDSAT can be used to detect and quantify the water quality parameters suspended solids, turbidity, and chlorophyll.

Hergenrader, G. L.↗