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At least 1,207 records · Page 67

SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems

Here, we propose new symplectic networks (SympNets) for identifying Hamiltonian systems from data based on a composition of linear, activation and gradient modules. In particular, we define two classes of SympNets: the LA-SympNets composed of linear and activation modules, and the G-SympNets composed of gradient modules. Correspondingly, we prove two new universal approximation theorems that demonstrate that SympNets can approximate arbitrary symplectic maps based on appropriate activation functions. We then perform several experiments including the pendulum, double pendulum and three-body problems to investigate the expressivity and the generalization ability of SympNets. The simulation results show that even very small size SympNets can generalize well, and are able to handle both separable and non-separable Hamiltonian systems with data points resulting from short or long time steps. In all the test cases, SympNets outperform the baseline models, and are much faster in training and prediction. We also develop an extended version of SympNets to learn the dynamics from irregularly sampled data. This extended version of SympNets can be thought of as a universal model representing the solution to an arbitrary Hamiltonian system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Moisture correspondence between lower and upper troposphere over oceans using AIRS observations

The Atmospheric Infrared Sounder (AIRS) mounted on Aqua space craft measures vertical profiles of air temperature and humidity using both microwaves and infrared irradiance. The AIRS' level III data that provide gridded values of 1(sup o) latitude by 1(sup o) longitude for the highest temporal resolution of twice per day became available recently (Granger et al. 2005). This level III data were derived from the level II Version 4.0 AIRS retrieval algorithm. This study uses this level III AIRS moisture profile data to reveal geographical correspondences of atmospheric moisture content between the lower and upper troposphere.

Ye, Hengchun↗

Stirling System Modeling for Space Nuclear Power Systems

A dynamic model of a high-power Stirling convertor has been developed for space nuclear power systems modeling. The model is based on the Component Test Power Convertor (CTPC), a 12.5-kWe free-piston Stirling convertor. The model includes the fluid heat source, the Stirling convertor, output power and heat rejection. The Stirling convertor model includes the Stirling cycle thermodynamics, heat flow, mechanical mass-spring damper systems, and the linear alternator. The model was validated against test data. Both nonlinear and linear versions of the model were developed. The linear version algebraically couples two separate linear dynamic models; one model of the Stirling cycle and one model of the thermal system, through the pressure factors. Future possible uses of the Stirling system dynamic model are discussed. A pair of commercially available 1-kWe Stirling convertors is being purchased by NASA Glenn Research Center. The specifications of those convertors may eventually be incorporated into the dynamic model and analysis compared to the convertor test data. Subsequent potential testing could include integrating the convertors into a pumped liquid metal hot-end interface. This test would provide more data for comparison to the dynamic model analysis.

Lewandowski, Edward J.↗

Stirling System Modeling for Space Nuclear Power Systems

A dynamic model of a high-power Stirling convertor has been developed for space nuclear power systems modeling. The model is based on the Component Test Power Convertor (CTPC), a 12.5-kWe free-piston Stirling convertor. The model includes the fluid heat source, the Stirling convertor, output power, and heat rejection. The Stirling convertor model includes the Stirling cycle thermodynamics, heat flow, mechanical mass-spring damper systems, and the linear alternator. The model was validated against test data. Both nonlinear and linear versions of the model were developed. The linear version algebraically couples two separate linear dynamic models; one model of the Stirling cycle and one model of the thermal system, through the pressure factors. Future possible uses of the Stirling system dynamic model are discussed. A pair of commercially available 1-kWe Stirling convertors is being purchased by NASA Glenn Research Center. The specifications of those convertors may eventually be incorporated into the dynamic model and analysis compared to the convertor test data. Subsequent potential testing could include integrating the convertors into a pumped liquid metal hot-end interface. This test would provide more data for comparison to the dynamic model analysis.

Lewandowski, Edward J.↗

Long-Term Ozone Variability and Trends from Reanalyses

Stratospheric ozone has a profound impact on radiation and chemistry over various spatial and temporal scales. The evolution of stratospheric ozone over the 21st century, however, is not well understood, especially in the lower stratosphere. Highly vertically resolved ozone data from satellite-borne limb sounders have proved to be invaluable for studying ozone in the middle and upper stratosphere but it was not until recently that these measurements were successfully incorporated in atmospheric reanalyses. Validation and comparison studies have demonstrated that the addition of observations from the Microwave Limb Sounder (MLS) on EOS (Earth Observing System) Aura greatly improved the quality of ozone fields in MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) making these assimilated data sets more useful for scientific research. In this presentation we demonstrate that multidecadal lower-stratospheric ozone variability and trends can be derived from NASA's MERRA-2 reanalysis ozone. In particular, the reanalysis ozone bias-corrected using a chemistry model simulation as a transfer function agrees very well with recently reprocessed long ozonesonde records. Ozone trends in the lower stratosphere will be discussed in the context of recent findings (Ball et al., 2018) and interpreted in connection with long-term circulation changes in the lower stratosphere. Next, we show that the use of ozone data retrieved from the next generation OMPS (Ozone Mapping Profiler Suite) instruments, including the OMPS Limb Profiler, can successfully extend the reanalyses into the future allowing comprehensive monitoring of global ozone and interpretation of its evolution during the critical period of expected ozone recovery and climate change from increasing concentration of greenhouse gases.

ozone↗

Building Performance Database API (BPD API) v2.1

The Building Performance Database (BPD) is the largest publicly-available source of measured energy performance data for buildings in the United States. It contains information about the building's energy use, location, and physical and operational characteristics. The BPD can be used by building owners, operators, architects and engineers to compare a building's energy efficiency against customized peer groups, identify energy efficiency opportunities, and set energy efficiency targets. It can also be used by energy efficiency program implementers and policymakers to analyze energy efficiency features and trends in the building stock. The BPD compiles data from various data sources, converts it into a standard format, cleanses and quality checks the data, and provides users with access to the data in a way that maintains anonymity for data providers. This software is the database and the Application Programming Interface (API). Users can utilize the BPD's data to develop their own applications using the API. Version 2.1 included a major update for multiple years of data and refactoring of code for faster queries.

Mathew, Paul↗

Application of MCM image construction to IRAS comet observations

There is a wealth of IRAS comet data, obtained in both the survey and pointed observations modes. However, these measurements have remained largely untouched due to difficulties in removing instrumental effects from the data. We have developed a version of the Maximum Correlation Method for Image Construction algorithm (MCM) which operates in the moving coordinate system of the comet and properly treats both real cometary motion and apparent motion due to spacecraft parallax. This algorithm has been implemented on a 486/33 PC in FORTRAN and IDL codes. Preprocessing of the IRAS CRDD includes baseline removal, deglitching, and removal of long tails due to dielectric time constants of the detectors. The resulting images are virtually free from instrumental effects and have the highest possible spatial resolution consistent with the data sampling. We present examples of high resolution IRAS images constructed from survey observations of Comets P/Tempel 1 and P/Tempel 2, and pointed observations of IRAS-Araki-Alcock.

Schlapfer, Martin F.↗

Validation of Aura Microwave Limb Sounder O3 and CO Observations in the Upper Troposphere and Lower Stratosphere

Global satellite observations of ozone and carbon monoxide from the Microwave Limb Sounder (MLS) on the EOS Aura spacecraft are discussed with emphasis on those observations in the 2 15 - 100 hPa region (the upper troposphere and lower stratosphere). The precision, resolution and accuracy of the data produced by the MLS "version 2.2" processing algorithms are discussed and quantified. O3 accuracy is estimated at approx.40 ppbv +5% (approx.20 ppbv +20% at 215 hPa) while the CO accuracy is estimated at approx.30 ppbv +30% for pressures of 147 hPa and less. Comparisons with expectations and other observations show good agreements for the O3 product, generally consistent with the systematic errors quoted above. In the case of COY a persistent factor of approx.2 high bias is seen at 215 hPa. However, the morphology is shown to be realistic, consistent with raw MLS radiance data, and useful for scientific study. The MLS CO data at higher altitudes are shown to be consistent with other observations.

Livesey, N. J.↗

Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

Barlow, Jonathan Spencer↗

A consistent dataset for the net income distribution for 190 countries and aggregated to 32 geographical regions from 1958 to 2015

Abstract. Data on income distributions within and across countries are becoming increasingly important for informing analysis of income inequality and understanding the distributional consequences of climate change. While datasets on income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same concept of inequality (or income concept) and therefore make comparisons across countries, over time and across datasets difficult. Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. For the imputation, we use a recently developed nonparametric principal-component-based approach that shows an excellent fit to data on income distributions compared to other approaches. We also present another version of this dataset aggregated from the country level to 32 geographical regions. Our dataset is developed for the purpose of calibrating models such as integrated human–Earth system models with detailed data on income distributions. This dataset will enable more robust analysis of income distribution at multiple scales. The latest version of our data are available on Zenodo: https://doi.org/10.5281/zenodo.7093997 (Narayan et al., 2022b).

97 MATHEMATICS AND COMPUTING↗

The NASA Merra-2 Reanalysis Products: Data and Tools Used for Aerosol and Air Quality Studies

The NASA Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) is atmospheric reanalysis data spanning 1980 to present. It has been produced by the NASA Global Modeling and Assimilation Office (GMAO) and is distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 data includes 100 collections of Earth system variables, mainly from the atmospheric model, such as aerosol fields and meteorological fields, radiation fields, and aerosol fields, guided by the assimilation of as many as six million observations every six hours. MERRA-2 has been one of the most popular datasets from NASA and is widely used in interdisciplinary research and applications, with increasing numbers of new users. For example, at least 7000 users accessed MERRA-2 data at GES DISC in the year 2021, ~1000 more users than in the year 2020. In this presentation, we will introduce the MERRA-2 datasets associated with aerosol and air quality studies and use a wildfire case study to demonstrate the data tools developed at GES DISC to analyze and visualize MERRA-2 data, such as Giovanni and the level 3 and level 4 subsetter, and Jupyter Python notebook. We will also update the status of cloud migration of the MERRA-2 data to Amazon Web Services (AWS).

Xiaohua Pan↗

SpaceCube Mini

This version of the SpaceCube will be a full-fledged, onboard space processing system capable of 2500+ MIPS, and featuring a number of plug-andplay gigabit and standard interfaces, all in a condensed 3x3x3 form factor [less than 10 watts and less than 3 lb (approximately equal to 1.4 kg)]. The main processing engine is the Xilinx SIRF radiation- hardened-by-design Virtex-5 FX-130T field-programmable gate array (FPGA). Even as the SpaceCube 2.0 version (currently under test) is being targeted as the platform of choice for a number of the upcoming Earth Science Decadal Survey missions, GSFC has been contacted by customers who wish to see a system that incorporates key features of the version 2.0 architecture in an even smaller form factor. In order to fulfill that need, the SpaceCube Mini is being designed, and will be a very compact and low-power system. A similar flight system with this combination of small size, low power, low cost, adaptability, and extremely high processing power does not otherwise exist, and the SpaceCube Mini will be of tremendous benefit to GSFC and its partners. The SpaceCube Mini will utilize space-grade components. The primary processing engine of the Mini is the Xilinx Virtex-5 SIRF FX-130T radiation-hardened-by-design FPGA for critical flight applications in high-radiation environments. The Mini can also be equipped with a commercial Xilinx Virtex-5 FPGA with integrated PowerPCs for a low-cost, high-power computing platform for use in the relatively radiation- benign LEOs (low-Earth orbits). In either case, this version of the Space-Cube will weigh less than 3 pounds (.1.4 kg), conform to the CubeSat form-factor (10x10x10 cm), and will be low power (less than 10 watts for typical applications). The SpaceCube Mini will have a radiation-hardened Aeroflex FPGA for configuring and scrubbing the Xilinx FPGA by utilizing the onboard FLASH memory to store the configuration files. The FLASH memory will also be used for storing algorithm and application code for the PowerPCs and the Xilinx FPGA. In addition, it will feature highspeed DDR SDRAM (double data rate synchronous dynamic random-access memory) to store the instructions and data of active applications. This version will also feature SATA-II and Gigabit Ethernet interfaces. Furthermore, there will also be general-purpose, multi-gigabit interfaces. In addition, the system will have dozens of transceivers that can support LVDS (low-voltage differential signaling), RS-422, or SpaceWire. The SpaceCube Mini includes an I/O card that can be customized to meet the needs of each mission. This version of the SpaceCube will be designed so that multiple Minis can be networked together using SpaceWire, Ethernet, or even a custom protocol. Scalability can be provided by networking multiple SpaceCube Minis together. Rigid-Flex technology is being targeted for the construction of the SpaceCube Mini, which will make the extremely compact and low-weight design feasible. The SpaceCube Mini is designed to fit in the compact CubeSat form factor, thus allowing deployment in a new class of missions that the previous SpaceCube versions were not suited for. At the time of this reporting, engineering units should be available in the summer 2012.

Michael Lin↗

PCAfold 2.0—Novel tools and algorithms for low-dimensional manifold assessment and optimization

We describe an update to our open-source Python package, PCAfold, designed to help researchers generate, analyze and improve low-dimensional data manifolds. In the current version, PCAfold 2.0, we introduce novel tools and algorithms for assessing and optimizing low-dimensional manifolds. This includes a method that generates a “map” of local feature sizes that can help pinpoint researchers to problematic regions on a manifold. We introduce a novel cost function that characterizes the quality of a manifold topology with a single number. We develop two algorithms for feature selection based on principal component analysis (PCA) that use the cost function as an objective function to minimize. We introduce a quantity of interest (QoI)-aware dimensionality reduction strategy where data projections are computed using an artificial neural network and are directly optimized towards representing various projection-independent and projection-dependent QoIs. We also introduce an implementation of partition of unity networks (POUnets) for efficient reconstruction of QoIs from low-dimensional manifolds based on combining neural network classification with localized polynomial regression. Our software can be broadly applicable in all domains of science and engineering that aim to reduce data dimensionality, as well as in the fundamental research on representation learning.

97 MATHEMATICS AND COMPUTING↗

Technical report series on global modeling and data assimilation. Volume 1: Documentation of the Goddard Earth Observing System (GEOS) General Circulation Model, version 1

This technical report documents Version 1 of the Goddard Earth Observing System (GEOS) General Circulation Model (GCM). The GEOS-1 GCM is being used by NASA's Data Assimilation Office (DAO) to produce multiyear data sets for climate research. This report provides a documentation of the model components used in the GEOS-1 GCM, a complete description of model diagnostics available, and a User's Guide to facilitate GEOS-1 GCM experiments.

Suarez, Max J.↗

Use of Quality Controlled AIRS Temperature Soundings to Improve Forecast Skill

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. Also included are the clear column radiances used to derive these products which are representative of the radiances AIRS would have seen if there were no clouds in the field of view. All products also have error estimates. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20 percent, in cases with up to 90 percent effective cloud cover. The products are designed for data assimilation purposes for the improvement of numerical weather prediction, as well as for the study of climate and meteorological processes. With regard to data assimilation, one can use either the products themselves or the clear column radiances from which the products were derived. The AIRS Version 5 retrieval algorithm is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates for retrieved quantities and clear column radiances, and the use of these error estimates for Quality Control. The temperature profile error estimates are used to determine a case-by-case characteristic pressure pbest, down to which the profile is considered acceptable for data assimilation purposes. The characteristic pressure p(sub best) is determined by comparing the case dependent error estimate (delta)T(p) to the threshold values (Delta)T(p). The AIRS Version 5 data set provides error estimates of T(p) at all levels, and also profile dependent values of pbest based on use of a Standard profile dependent threshold (Delta)T(p). These Standard thresholds were designed as a compromise between optimal use for data assimilation purposes, which requires highest accuracy (tighter Quality Control), and climate purposes, which requires more spatial coverage (looser Quality Control). Subsequent research using Version 5 sounding and error estimates showed that tighter Quality Control performs better for data assimilation proposes, while looser Quality Control better spatial coverage) performs better for climate purposes. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 degree latitude x 0.67 degree longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates (delta)T(p) were used as the uncertainty for each measurement in the data assimilation process.

Susskind, Joel↗

Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)

The scientific community is faced with a need for greatly improved data sharing, analysis, visualization and advanced collaboration based firmly on open science principles. Recent and upcoming launches of new satellite missions with more complex and voluminous data, as well as the ever more urgent need to better understand the global carbon budget and related ecological processes, provided the immediate rational for the ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP). This highly collaborative joint project of ESA and NASA established a framework between ESA and NASA to share data, science algorithms and compute resources in order to foster and accelerate scientific research conducted by ESA and NASA EO data users. Presented to the public in October 2021, the current version of MAAP provides a common cloud-based platform with computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of global above-ground biomass. Data from the Global Ecosystem Dynamics Investigation (GEDI) mission on the International Space Station and the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) have been instrumental in the first products of MAAP including the first comprehensive map of Boreal above-ground Biomass and a current Global Biomass Harmonization Activity, but the platform is also being specifically designed to support the forthcoming ESA Biomass mission and incorporate data from the upcoming NASA-ISRO SAR (NISAR) mission. While these missions and the corresponding research which includes airborne, field, and calibration/validation data collection and analyses, provide a wealth of data and information relating to global biomass estimation, they also present data storing, processing and sharing challenges. The NISAR mission alone will produce about 80TB/day. These large data volumes present a challenge that would otherwise place accessibility limits on the scientific community and impact scientific progress. Other challenges being addressed by MAAP include: 1) Enabling researchers to easily discover, process, visualize and analyze large volumes of data from both agencies; 2) Providing a wide variety of data in the same coordinate reference frame to enable comparison, analysis, data evaluation, and data generation; 3) Providing a version-controlled science algorithm development environment that supports tools, co-located data and processing resources; and 4) Addressing intellectual property and sharing challenges related to collaborative algorithm development and sharing of data and algorithms. MAAP products can be explored on the MAAP Dashboard at https://earthdata.nasa.gov/maap-biomass or the joint platform entrance at scimaap.net. MAAP also can be accessed through individual NASA (https://maap-project.org) and ESA (https://esa-maap.org/) landing pages.

cloud computing↗

TimeSet: A computer program that accesses five atomic time services on two continents

TimeSet is a shareware program for accessing digital time services by telephone. At its initial release, it was capable of capturing time signals only from the U.S. Naval Observatory to set a computer's clock. Later the ability to synchronize with the National Institute of Standards and Technology was added. Now, in Version 7.10, TimeSet is able to access three additional telephone time services in Europe - in Sweden, Austria, and Italy - making a total of five official services addressable by the program. A companion program, TimeGen, allows yet another source of telephone time data strings for callers equipped with TimeSet version 7.10. TimeGen synthesizes UTC time data strings in the Naval Observatory's format from an accurately set and maintained DOS computer clock, and transmits them to callers. This allows an unlimited number of 'freelance' time generating stations to be created. Timesetting from TimeGen is made feasible by the advent of Becker's RighTime, a shareware program that learns the drift characteristics of a computer's clock and continuously applies a correction to keep it accurate, and also brings .01 second resolution to the DOS clock. With clock regulation by RighTime and periodic update calls by the TimeGen station to an official time source via TimeSet, TimeGen offers the same degree of accuracy within the resolution of the computer clock as any official atomic time source.

Petrakis, P. L.↗

Some injector element detail effects on screech in hydrogen-oxygen rockets

An experimental investigation was conducted to learn more about how the specific details of a concentric tube injection element affect the screech characteristics of a hydrogen-oxygen rocket engine. The four variables investigated were (1) impingement angle, (2) oxidizer tube blunt base thickness, (3) oxidizer tube recess and extension, and (4) oxidizer tube-annulus concentricity. Tests were made using a 27.34-cm (10.77-in.) diameter heat sink combustor at nominally 300-psia chamber pressure. All of the test variables were investigated using a 157 element circular pattern injector. Additional oxidizer tube recess tests were made with a 421 element hexagonal pattern injector. Tests were conducted over the oxidant-fuel ratio range of 4 to 6. Stability evaluation for each configuration was made using the hydrogen temperature rating technique. Several element configurations were also cold flow tested using nitrogen and water as simulants. The element detail changes resulted in changes in hydrogen injector pressure drop even though the physical injection area was constant for all similar tests in both hot firing and cold flow tests. These changes in injector pressure drop produced changes in combustion stability. The data were correlated with a modified version of a previously reported injection area ratio correlation. By interpreting changes in injector pressure drop as changes in injector hydrogen flow resistance, the data were compared with a hydrogen flow response stability model and were found to be in agreement.

Hannum, N. P.↗