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At least 325 records · Page 18

Risk-Based Probabilistic Approach to Aeropropulsion System Assessment

In an era of shrinking development budgets and resources, where there is also an emphasis on reducing the product development cycle, the role of system assessment, performed in the early stages of an engine development program, becomes very critical to the successful development of new aeropropulsion systems. A reliable system assessment not only helps to identify the best propulsion system concept among several candidates, it can also identify which technologies are worth pursuing. This is particularly important for advanced aeropropulsion technology development programs, which require an enormous amount of resources. In the current practice of deterministic, or point-design, approaches, the uncertainties of design variables are either unaccounted for or accounted for by safety factors. This could often result in an assessment with unknown and unquantifiable reliability. Consequently, it would fail to provide additional insight into the risks associated with the new technologies, which are often needed by decision makers to determine the feasibility and return-on-investment of a new aircraft engine. In this work, an alternative approach based on the probabilistic method was described for a comprehensive assessment of an aeropropulsion system. The statistical approach quantifies the design uncertainties inherent in a new aeropropulsion system and their influences on engine performance. Because of this, it enhances the reliability of a system assessment. A technical assessment of a wave-rotor-enhanced gas turbine engine was performed to demonstrate the methodology. The assessment used probability distributions to account for the uncertainties that occur in component efficiencies and flows and in mechanical design variables. The approach taken in this effort was to integrate the thermodynamic cycle analysis embedded in the computer code NEPP (NASA Engine Performance Program) and the engine weight analysis embedded in the computer code WATE (Weight Analysis of Turbine Engines) with the fast probability integration technique (FPI). FPI was developed by Southwest Research Institute under contract with the NASA Glenn Research Center. The results were plotted in the form of cumulative distribution functions and sensitivity analyses and were compared with results from the traditional deterministic approach. The comparison showed that the probabilistic approach provides a more realistic and systematic way to assess an aeropropulsion system. The current work addressed the application of the probabilistic approach to assess specific fuel consumption, engine thrust, and weight. Similarly, the approach can be used to assess other aspects of aeropropulsion system performance, such as cost, acoustic noise, and emissions. Additional information is included in the original extended abstract.

Tong, Michael T.↗

Information Metacatalog for a Grid

SWIM is a Software Information Metacatalog that gathers detailed information about the software components and packages installed on a grid resource. Information is currently gathered for Executable and Linking Format (ELF) executables and shared libraries, Java classes, shell scripts, and Perl and Python modules. SWIM is built on top of the POUR framework, which is described in the preceding article. SWIM consists of a set of Perl modules for extracting software information from a system, an XML schema defining the format of data that can be added by users, and a POUR XML configuration file that describes how these elements are used to generate periodic, on-demand, and user-specified information. Periodic software information is derived mainly from the package managers used on each system. SWIM collects information from native package managers in FreeBSD, Solaris, and IRX as well as the RPM, Perl, and Python package managers on multiple platforms. Because not all software is available, or installed in package form, SWIM also crawls the set of relevant paths from the File System Hierarchy Standard that defines the standard file system structure used by all major UNIX distributions. Using these two techniques, the vast majority of software installed on a system can be located. SWIM computes the same information gathered by the periodic routines for specific files on specific hosts, and locates software on a system given only its name and type.

Kolano, Paul↗

MODIS algorithm development and data visualization using ACTS

The study of the Earth as a system will require the merger of scientific and data resources on a much larger scale than has been done in the past. New methods of scientific research, particularly in the development of geographically dispersed, interdisciplinary teams, are necessary if we are to understand the complexity of the Earth system. Even the planned satellite missions themselves, such as the Earth Observing System, will require much more interaction between researchers and engineers if they are to produce scientifically useful data products. A key component in these activities is the development of flexible, high bandwidth data networks that can be used to move large amounts of data as well as allow researchers to communicate in new ways, such as through video. The capabilities of the Advanced Communications Technology Satellite (ACTS) will allow the development of such networks. The Pathfinder global AVHRR data set and the upcoming SeaWiFS Earthprobe mission would serve as a testbed in which to develop the tools to share data and information among geographically distributed researchers. Our goal is to develop a 'Distributed Research Environment' that can be used as a model for scientific collaboration in the EOS era. The challenge is to unite the advances in telecommunications with the parallel advances in computing and networking.

Abbott, Mark R.↗

An Intelligent Archive Testbed Incorporating Data Mining

Many significant advances have occurred during the last two decades in remote sensing instrumentation, computation, storage, and communication technology. A series of Earth observing satellites have been launched by U.S. and international agencies and have been operating and collecting global data on a regular basis. These advances have created a data rich environment for scientific research and applications. NASA s Earth Observing System (EOS) Data and Information System (EOSDIS) has been operational since August 1994 with support for pre-EOS data. Currently, EOSDIS supports all the EOS missions including Terra (1999), Aqua (2002), ICESat (2002) and Aura (2004). EOSDIS has been effectively capturing, processing and archiving several terabytes of standard data products each day. It has also been distributing these data products at a rate of several terabytes per day to a diverse and globally distributed user community (Ramapriyan et al. 2009). There are other NASA-sponsored data system activities including measurement-based systems such as the Ocean Data Processing System and the Precipitation Processing system, and several projects under the Research, Education and Applications Solutions Network (REASoN), Making Earth Science Data Records for Use in Research Environments (MEaSUREs), and the Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) programs. Together, these activities provide a rich set of resources constituting a value chain for users to obtain data at various levels ranging from raw radiances to interdisciplinary model outputs. The result has been a significant leap in our understanding of the Earth systems that all humans depend on for their enjoyment, livelihood, and survival. The trend in the community today is towards many distributed sets of providers of data and services. Despite this, visions for the future include users being able to locate, fuse and utilize data with location transparency and high degree of interoperability, and being able to convert data to information and usable knowledge in an efficient, convenient manner, aided significantly by automation (Ramapriyan et al. 2004; NASA 2005). We can look upon the distributed provider environment with capabilities to convert data to information and to knowledge as an Intelligent Archive in the Context of a Knowledge Building system (IA-KBS). Some of the key capabilities of an IA-KBS are: Virtual Product Generation, Significant Event Detection, Automated Data Quality Assessment, Large-Scale Data Mining, Dynamic Feedback Loop, and Data Discovery and Efficient Requesting (Ramapriyan et al. 2004).

Ramapriyan, H.↗

Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme

As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.

Molthan, Andrew L.↗

"Green Planet Architecture"-A Methodology for Self-Sustainable Distributed Renewable Energy Ecosystems

This planet has been endowed with a host of natural mechanisms to keep the environment and climate in balance. Humans are now facing the need to restore this balance that has been upset in the past years because of a growing population and resource demands. To steer dependency away from freshwater crops and decrease environmental damage from humanity s fuel and energy demands, it is necessary to take advantage of the natural adaptive biomass resources that are already in place. Using methods of "Green Planet Architecture," based on compilations of current research and procedures, could lead to new forms of energy and fueling as well as new sources for food and feed. Green Planet Architecture involves climatic adaptive biomass; geospatial intelligence; agri- and aqua-culture life cycles; and soil, wetland, and shoreline restoration. Plants such as Salicornia, seashore mallow, castor, mangroves, and perhaps Moringa can be modified (naturally, model-assisted, or genetically) to thrive in salt water and brackish water or otherwise not arable conditions, making them potentially new crops that will not displace traditional farming. These fueling sources also have potential to be used in other rapid-growth industries, such as the aviation industry, that have incentive to move towards more sustainable fuel supplies. This report highlights an example of how synergistic development of biomass resources and geospatial intelligence high-performance computing capabilities can be focused to resolve potential drought-famine problems. These techniques provide a basis for future e-science-based discovery (and access) through technology that can be expanded to support global societal applications.

Saxena, Nikita T.↗

Green Planet Architecture - A Methodology for Self-Sustainable Distributed Renewable Energy Ecosystems

Our planet has been endowed with a host of natural mechanisms to keep the environment and climate in balance. Humans are now facing the need to restore this balance that has been upset in the past years because of a growing population and resource demands. To steer dependency away from freshwater crops and decrease environmental damage from humanity s fuel and energy demands, it is necessary to take advantage of the natural adaptive biomass resources that are already in place. Using methods of Green Planet Architecture, based on compilations of current research and procedures, could lead to new forms of energy and fueling as well as new sources for food and feed. Green Planet Architecture involves climatic adaptive biomass; geospatial intelligence; agri- and aqua-culture life cycles; and soil, wetland, and shoreline restoration. Plants such as Salicornia, seashore mallow, castor, mangroves, and perhaps Moringa can be modified (natural, model-assisted, or genetically modified) to thrive in salt-water and brackish water or otherwise not arable conditions, making them potentially new crops that will not displace traditional farming. These fueling sources also have potential to be used in other rapid-growth industries, such as the aviation industry, that have incentive to move towards more sustainable fuel supplies. This paper highlights an example of how synergistic development of biomass resources and geospatial intelligence high-performance computing capabilities can be focused to resolve potential drought-famine problems. These techniques, provide a basis for future e-science-based discovery (and access) through technology that can be expanded to support global societal applications.

Saxena, Nikita T.↗

Preserving the Finger Lakes for the Future: A Prototype Decision Support System for Water Resource Management, Open Space, and Agricultural Protection

This report summarizes the activity conducted under NASA Grant NAG13-02059 entitled "Preserving the Finger Lakes for the Future" A Prototype Decision Support System for Water Resources Management, Open Space and Agricultural Protection, for the period of September 26, 2003 to September 25, 2004. The RACNE continues to utilize the services of its affiliate, the Institute for the Application of Geospatial Technology at Cayuga Community College, Inc. (IAGT), for the purposes of this project under its permanent operating agreement with IAGT. IAGT is a 501(c)(3) not-for-profit Corporation created by the RACNE for the purpose of carrying out its programmatic and administrative mission. The "Preserving the Finger Lakes for the Future" project has progressed and evolved as planned, with the continuation or initiation of a number of program facets at programmatic, technical, and inter-agency levels. The project has grown, starting with the well received core concept of the Virtual Management Operations Center (VMOC), to the functional Watershed Virtual Management Operations Center (W-VMOC) prototype, to the more advanced Finger Lakes Decision Support System (FLDSS) prototype, deployed for evaluation and assessment to a wide variety of agencies and organizations in the Finger Lakes region and beyond. This suite of tools offers the advanced, compelling functionality of interactive 3D visualization interfaced with 2D mapping, all accessed via Internet or virtually any kind of distributed computer network.

Brower, Robert↗

The Invasive Species Forecasting System

The Invasive Species Forecasting System (ISFS) provides computational support for the generic work processes found in many regional-scale ecosystem modeling applications. Decision support tools built using ISFS allow a user to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of management concern, such as a national park, monument, forest, or refuge. This type of decision product helps resource managers plan invasive species protection, monitoring, and control strategies for the lands they manage. Until now, scientists and resource managers have lacked the data-assembly and computing capabilities to produce these maps quickly and cost efficiently. ISFS focuses on regional-scale habitat suitability modeling for invasive terrestrial plants. ISFS s component architecture emphasizes simplicity and adaptability. Its core services can be easily adapted to produce model-based decision support tools tailored to particular parks, monuments, forests, refuges, and related management units. ISFS can be used to build standalone run-time tools that require no connection to the Internet, as well as fully Internet-based decision support applications. ISFS provides the core data structures, operating system interfaces, network interfaces, and inter-component constraints comprising the canonical workflow for habitat suitability modeling. The predictors, analysis methods, and geographic extents involved in any particular model run are elements of the user space and arbitrarily configurable by the user. ISFS provides small, lightweight, readily hardened core components of general utility. These components can be adapted to unanticipated uses, are tailorable, and require at most a loosely coupled, nonproprietary connection to the Web. Users can invoke capabilities from a command line; programmers can integrate ISFS's core components into more complex systems and services. Taken together, these features enable a degree of decentralization and distributed ownership that have helped other types of scientific information services succeed in recent years.

Schnase, John↗

COSMIC: Software catalog 1991 edition diskette format

The PC edition of the annual COSMIC Software contains descriptions of the over 1,200 computer programs available for use within the United States as of January 1, 1991. By using the PC version of the catalog, it is possible to conduct extensive searches of the software inventory for programs that meet specific criteria. Elements such as program keywords, hardware specifications, source code languages, and title acronyms can be used for the basis of such searches. After isolating those programs that might be of best interest to the user, it is then possible to either view at the monitor, or generate a hardcopy listing of all information on those packages. In addition to the program elements that the user can search on, information such as total program size, distribution media, and program price, as well as extensive abstracts on the program, are also available to the user at this time. Another useful feature of the catalog allows for the retention of programs that meet certain search criteria between individual sessions of using the catalog. This allows users to save the information on those programs that are of interest to them in different areas of application. They can then recall a specific collection of programs for information retrieval or further search reduction if desired. In addition, this version of the catalog is adaptable to a network/shared resource environment, allowing multiple users access to a single copy of the catalog database simultaneously.

Source record↗

Cold Season QPF: Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

As operational numerical weather prediction is performed at increasingly finer spatial resolution, precipitation traditionally represented by sub-grid scale parameterization schemes is now being calculated explicitly through the use of single- or multi-moment, bulk water microphysics schemes. As computational resources grow, the real-time application of these schemes is becoming available to a broader audience, ranging from national meteorological centers to their component forecast offices. A need for improved quantitative precipitation forecasts has been highlighted by the United States Weather Research Program, which advised that gains in forecasting skill will draw upon improved simulations of clouds and cloud microphysical processes. Investments in space-borne remote sensing have produced the NASA A-Train of polar orbiting satellites, specially equipped to observe and catalog cloud properties. The NASA CloudSat instrument, a recent addition to the A-Train and the first 94 GHz radar system operated in space, provides a unique opportunity to compare observed cloud profiles to their modeled counterparts. Comparisons are available through the use of a radiative transfer model (QuickBeam), which simulates 94 GHz radar returns based on the microphysics of cloudy model profiles and the prescribed characteristics of their constituent hydrometeor classes. CloudSat observations of snowfall are presented for a case in the central United States, with comparisons made to precipitating clouds as simulated by the Weather Research and Forecasting Model and the Goddard single-moment microphysics scheme. An additional forecast cycle is performed with a temperature-based parameterization of the snow distribution slope parameter, with comparisons to CloudSat observations provided through the QuickBeam simulator.

Molthan, A. L.↗

Numerical Study of Magnetic Damping During Unidirectional Solidification

A fully 3-D numerical model is developed to represent magnetic damping of complex fluid flow, heat transfer and electromagnetic field distributions in a melt cavity. The model is developed based on our in-house finite element code for the fluid flow, heat transfer and electromagnetic field calculations. The computer code has been tested against benchmark test problems that are solved by other commercial codes as well as analytical solutions whenever available. The numerical model is tested against numerical and experimental results for water reported in literature. With the model so tested, various numerical simulations are carried out for the Sn-35.5% Pb melt convection and temperature distribution in a cylindrical cavity with and without the presence of a transverse magnetic field. Numerical results show that magnetic damping can be effectively applied to reduce turbulence and flow levels in the melt undergoing solidification and over a certain threshold value a higher magnetic field resulted in a higher velocity reduction. It is found also that for a fully 3-D representation of the magnetic damping effects, the electric field induced in the melt by the applied DC magnetic field does not vanish, as some researchers suggested, and must be included even for molten metal and semiconductors. Also, for the study of the melt flow instability, a long enough time has to be applied to ensure the final fluid flow recirculation pattern. Moreover, our numerical results suggested that there seems to exist a threshold value of applied magnetic field, above which magnetic damping becomes possible and below which the convection in the melt is actually enhanced. Because of the limited financial resource allocated for the project, we are unable to carry out extensive study on this effect, which should warrant further theoretical and experimental study. In that endeavor, the developed numerical model should be very useful; and the model should serve as a useful tool for exploring necessary design parameters for planning magnetic damping experiments and interpreting the experimental results.

Li, Ben Q.↗

Grid Enabled Geospatial Catalogue Web Service

Geospatial Catalogue Web Service is a vital service for sharing and interoperating volumes of distributed heterogeneous geospatial resources, such as data, services, applications, and their replicas over the web. Based on the Grid technology and the Open Geospatial Consortium (0GC) s Catalogue Service - Web Information Model, this paper proposes a new information model for Geospatial Catalogue Web Service, named as GCWS which can securely provides Grid-based publishing, managing and querying geospatial data and services, and the transparent access to the replica data and related services under the Grid environment. This information model integrates the information model of the Grid Replica Location Service (RLS)/Monitoring & Discovery Service (MDS) with the information model of OGC Catalogue Service (CSW), and refers to the geospatial data metadata standards from IS0 19115, FGDC and NASA EOS Core System and service metadata standards from IS0 191 19 to extend itself for expressing geospatial resources. Using GCWS, any valid geospatial user, who belongs to an authorized Virtual Organization (VO), can securely publish and manage geospatial resources, especially query on-demand data in the virtual community and get back it through the data-related services which provide functions such as subsetting, reformatting, reprojection etc. This work facilitates the geospatial resources sharing and interoperating under the Grid environment, and implements geospatial resources Grid enabled and Grid technologies geospatial enabled. It 2!so makes researcher to focus on science, 2nd not cn issues with computing ability, data locztic~, processir,g and management. GCWS also is a key component for workflow-based virtual geospatial data producing.

Chen, Ai-Jun↗

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

Current data processing practice limits the volume and variety of relevant geoscience data that can practically be applied to important problems. File archives in centralized data centers are the principal means by which Earth Science data are accessed. This approach, however, requires laborious search, retrieval, and eventual customization/adaptation for the data to be used. Such fractionation makes it even more difficult to share outcomes, i.e. research artifacts and data products, hampering reusability and repeatability, since end users generally have their own research agenda and preferences as well as scarce resources. Thus, while finding and downloading data files from central data centers are already costly for end users working in their own field, using data products from other disciplines rapidly becomes prohibitive. This curtails scientific productivity, limits avenues of study, and endangers quality and reproducibility. The Spatio-Temporal Adaptive Resolution Encoding (STARE) is a unifying scheme that facilitates the indexing, access, and fusion of diverse Earth Science data. STARE implements an innovative encoding of geo-spatiotemporal information, originally developed for aligning datasets with diverse spatiotemporal characteristics in an array database. The spatial component of STARE recursively quadfurcates a root polyhedron, producing a hierarchical scheme for addressing geographic locations and regions. The temporal component of STARE uses conventional date-time units as an indexing hierarchy. The additional encoding of spatial and temporal resolution information in STARE enables comparisons and conditional selections across diverse datasets. Moreover, spatiotemporal set-operations, e.g. union and intersection, are mapped to efficient integer operations with STARE. Applied to existing data models (point, grid, spacecraft swath) and corresponding granules, STARE indexes provide a streamlined description usable as geo-spatiotemporal metadata. When coupled with large scale, distributed hardware and software, STARE-based data access reduces pre-analysis data preparation costs by offering a convenient means to align different datasets spatiotemporally without specialized effort in parallel computing or distributed data management.

Kuo, Kwo-Sen↗

BioWires: Conductive DNA Nanowires in a Computationally-Optimized, Synthetic Biological Platform for Nanoelectronic Fabrication

DNA is an ideal template for a biological nanowire-it has a linear structure several atoms thick; it possesses addressable nucleobase geometry that can be precisely defined; and it is massively scalable into branched networks. Until now, the drawback of DNA as a conducting nanowire been, simply put, its low conductance. To address this deficiency, we extensively characterize a chemical variant of canonical DNA that exploits the affinity of natural cytosine bases for silver ions. We successfully construct chains of single silver ions inside double-stranded DNA, confirm the basic dC-Ag+-dC bond geometry and kinetics, and show length-tunability dependent on mismatch distribution, ion availability and enzyme activity. An analysis of the absorbance spectra of natural DNA and silver-binding, poly-cytosine DNA demonstrates the heightened thermostability of the ion chain and its resistance to aqueous stresses such as precipitation, dialysis and forced reduction. These chemically critical traits lend themselves to an increase in electrical conductivity of over an order of magnitude for 11-base silver-paired duplexes over natural strands when assayed by STM break junction. We further construct and implement a genetic pathway in the E. coli bacterium for the biosynthesis of highly ionizable DNA sequences. Toward future circuits, we construct a model of transcription network architectures to determine the most efficient and robust connectivity for cell-based fabrication, and we perform sequence optimization with a genetic algorithm to identify oligonucleotides robust to changes in the base-pairing energy landscape. We propose that this system will serve as a synthetic biological fabrication platform for more complex DNA nanotechnology and nanoelectronics with applications to deep space and low resource environments.

DNA↗

Earth Science Technology Office (ESTO) New Observing Strategies (NOS) and NOS-Testbed (NOS-T)

With the advancement of space hardware technologies such as smaller spacecraft, component and instrument miniaturization and high performance space processors, and with the advancement of software technologies in artificial intelligence, big data analysis and autonomous decision making, Earth Science is looking at novel ways to observe phenomena that previously could not have been studied or would have been too expensive to study with traditional missions. In particular, the New Observing Strategies (NOS) component of the NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program aims at leveraging these novel technologies as well as low cost and easy access to space to acquire multi-temporal or simultaneous multi-angular, multi-locations, multi-resolution and multi-spectral observations that will provide better multi-source measurements and will build a more dynamic and comprehensive picture of Earth Science phenomena that need to be studied and analyzed. For applications such as water resources management, air quality monitoring, biodiversity studies or disaster management, NOS will integrate the use of small instruments, small spacecraft, constellations of spacecraft and networks of sensors to design new missions that will provide the necessary measurements to improve future forecast and science modeling systems.Measurement acquisition will therefore be approached as a system of systems rather than on a mission basis, and a system of this complexity should not be expected to work without full integration and experimental characterization. Although most of the individual technologies enabling to link and coordinate multi-source observations are more or less mature, a few technologies need to be developed and all of them need to be integrated and tested as a system. In order for this validation to occur, the AIST Program is developing the NOS Testbed that includes 3 main goals:1.Validate novel NOS technologies, independently and as a system2.Demonstrate novel distributed operations concepts3.Socialize new Distributed Spacecraft Mission (DSM) and SensorWeb (SW) technologies and concepts to the science community by significantly retiring the risk of integrating these new technologies.The NOS Testbed will consist of multiple sensing nodes, simulated or actual, representing space, air and/or ground measurements, that are interconnected by a communications fabric (infrastructure that permits nodes to transmit and receive data between one another and interact with each other). Each node will be supported by hardware capabilities required to perform nodes monitoring and command & control, as well as intelligent "onboard" computing. The nodes will work together in a collaborative manner to demonstrate optimal science capabilities. The testbed will enable to validate technologies such as inter-node communication models, techniques and protocols; inter-node coordination; real-time data fusion and understanding; planning; sensor re-targeting; etc. Additionally, the testbed will have the capability to interact with various mission design tools, OSSEs and one or several forecast models. More details about the NOS Testbed will be presented at the confererence.

Earth Science missions; Advanced information Syste↗

Towards Probablistic Assessment of Hypobaric Decompression Sickness Treatment

INTRODUCTION: Pressure, oxygen (O2), and time are the pillars to effective treatment of decompression sickness (DCS). The NASA DCS Treatment Model links a decrease in computed bubble volume to the resolution of a symptom. The decrease in volume is realized in two stages: a) during the Boyle's Law compression and b) during subsequent dissolution of the gas phase by the O2 window. METHODS: The cumulative distribution of 154 symptoms that resolved during repressurization was described with a log-logistic density function of pressure difference (deltaP as psid) associated with symptom resolution and two other explanatory variables. The 154 symptoms originated from 119 cases of DCS during 969 exposures in 47 different altitude tests. RESULTS: The probability of symptom resolution [P(symptom resolution)] = 1 / (1+exp(- (ln(deltaP) - 1.682 + 1.089×AMB - 0.00395×SYMPTOM TIME) / 0.633)), where AMB is 1 when the subject ambulated as part of the altitude exposure or else 0 and SYMPTOM TIME is the elapsed time in min from start of the altitude exposure to recognition of a DCS symptom. The P(symptom resolution) was estimated from computed deltaP from the Tissue Bubble Dynamics Model based on the "effective" Boyle's Law change: P2 - P1 (deltaP, psid) = P1×V1/V2 - P1, where V1 is the computed volume of a spherical bubble in a unit volume of tissue at low pressure P1 and V2 is computed volume after a change to a higher pressure P2. V2 continues to decrease through time at P2, at a faster rate if 100% ground level O2 was breathed. The computed deltaP is the effective treatment pressure at any point in time as if the entire deltaP was just from Boyle's Law compression. DISCUSSION: Given the low probability of DCS during extravehicular activity and the prompt treatment of a symptom with options through the model it is likely that the symptom and gas phase will resolve with minimum resources and minimal impact on astronaut health, safety, and productivity.

Conkin, J.↗

NASA’s Prototype Spectral Water Inversion Processor and Emulator (SWIPE): Towards Global Coastal and Inland Water Quality and Algal Biodiversity Monitoring

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will provide updates on NASA’s prototype open-source aquatic modeling platform, Spectral Water Inversion Processor and Emulator (SWIPE), which is a comprehensive, multi-faceted modeling platform for both forward and inverse modeling of diverse aquatic ecosystems from the benthos to top-of-atmosphere (TOA). SWIPE provides a cohesive application which leverages recent advancements in particle modeling, Big Data analytics, and machine learning to develop a high-fidelity synthetic training ground for sensitivity studies and algorithm development for multispectral or upcoming hyperspectral missions. Some of the prominent features of SWIPE to be discussed include: 1. Advanced hyperspectral modeling of globally diverse algal and non-algal particles using a novel two-layer coated sphere scattering model and radiative transfer modeling, 2. Massive, highly detailed synthetic spectral libraries of Analysis-Ready-Data (ARD) which include spectral libraries of particle microphysics, water biogeophysical and optical properties, as well as surface and TOA reflectances at 1 nm resolution, 3. An ensemble of pre-built analytic, machine learning, and deep learning inversion algorithms for various water quality and biodiversity related retrieval parameters and uncertainty quantification, 4. Sensor-agnostic water quality inversion at wide ranging spatial and spectral resolutions including a codebase for seamless application in the Google Earth Engine and NASA Earth Exchange (NEX) for planetary scale analysis. SWIPE will be a fully open-source platform based in python with comprehensive documentation, tutorials, and options for distributed computing on high performance computing clusters or on single, local machines. Further, we will discuss how we envision SWIPE contributing towards a global analysis of coastal and inland water quality dynamics.

top-of-atmosphere (TOA)↗