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At least 865 records · Page 48

On the Use and Validation of Mosaic Heterogeneity in Atmospheric Numerical Models

The mosaic land modeling approach allows for the representation of multiple surface types in a single atmospheric general circulation model grid box. Each surface type, collectively called 'tiles' correspond to different sets of surface characteristics (e.g. for grass, crop or forest). Typically, the tile space data is averaged to grid space by weighting the tiles with their fractional cover. While grid space data is routinely evaluated, little attention has been given to the tile space data. The present paper explores uses of the tile space surface data in validation with station observations. The results indicate the limitations that the mosaic heterogeneity parameterization has in reproducing variations observed between stations at the Atmospheric Radiation Measurement Southern Great Plains field site.

Bosilovich, Michael G.↗

Real-Time Lunar Prospector Data Visualization Using Web-Based Java

The Lunar Prospector was co-developed by NASA Ames Research Center and Lockheed Martin, and was launched on January 6th, 1998. Its mission is to search for water ice and various elements in the Moon's surface, map its magnetic and gravity fields, and detect volcanic activity. For the first time, the World Wide Web is being used to graphically display near-real-time data from a planetary exploration mission to the global public. Science data from the craft's instruments, as well as engineering data for the spacecraft subsystems, are continuously displayed in time-varying XY plots. The craft's current location is displayed relative to the whole Moon, and as an off-craft observer would see in the reference frame of the craft, with the lunar terrain scrolling underneath. These features are implemented as Java applets. Analyzed data (element and mass distribution) is presented as 3D lunar maps using VRML and Javascript. During the development phase, implementations of the Java Virtual Machine were just beginning to mature enough to adequately accommodate our target featureset; incomplete and varying implementations were the biggest bottleneck to our ideal of ubiquitous browser access. Bottlenecks notwithstanding, the reaction from the Internet community was overwhelmingly enthusiastic.

Deardorff, D. Glenn↗

Ensemble Kalman inversion of induced polarization data

SUMMARY This paper explores the applicability of ensemble Kalman inversion (EKI) with level-set parametrization for solving geophysical inverse problems. In particular, we focus on its extension to induced polarization (IP) data with uncertainty quantification. IP data may provide rich information on characteristics of geological materials due to its sensitivity to characteristics of the pore–grain interface. In many IP studies, different geological units are juxtaposed and the goal is to delineate these units and obtain estimates of unit properties with uncertainty bounds. Conventional inversion of IP data does not resolve well sharp interfaces and tends to reduce and smooth resistivity variations, while not readily providing uncertainty estimates. Recently, it has been shown for DC resistivity that EKI is an efficient solver for inverse problems which provides uncertainty quantification, and its combination with level set parametrization can delineate arbitrary interfaces well. In this contribution, we demonstrate the extension of EKI to IP data using a sequential approach, where the mean field obtained from DC resistivity inversion is used as input for a separate phase angle inversion. We illustrate our workflow using a series of synthetic and field examples. Variations with uncertainty bounds in both DC resistivity and phase angles are recovered by EKI, which provides useful information for hydrogeological site characterization. Although phase angles are less well-resolved than DC resistivity, partly due to their smaller range and higher percentage data errors, it complements DC resistivity for site characterization. Overall, EKI with level set parametrization provides a practical approach forward for efficient hydrogeophysical imaging under uncertainty.

Geochemistry & Geophysics↗

Capturing the Physics of MaNGA Galaxies with Self-supervised Machine Learning

As available data sets grow in size and complexity, advanced visualization tools enabling their exploration and analysis become more important. In modern astronomy, integral field spectroscopic galaxy surveys are a clear example of increasing high dimensionality and complex data sets, which challenges the traditional methods used to extract the physical information they contain. Here, we present the use of a novel self-supervised machine-learning method to visualize the multidimensional information on stellar population and kinematics in the MaNGA survey in a 2D plane. Our framework is insensitive to nonphysical properties such as the size of the integral field unit and is therefore able to order galaxies according to their resolved physical properties. Using the extracted representations, we study how galaxies distribute based on their resolved and global physical properties. We show that even when exclusively using information about the internal structure, galaxies naturally cluster into two well-known categories, rotating main-sequence disks and massive slow rotators, from a purely data-driven perspective, hence confirming distinct assembly channels. Low-mass rotation-dominated quenched galaxies appear as a third cluster only if information about the integrated physical properties is preserved, suggesting a mixture of assembly processes for these galaxies without any particular signature in their internal kinematics that distinguishes them from the two main groups. The framework for data exploration is publicly released with this publication, ready to be used with the MaNGA or other integral field data sets.

79 ASTRONOMY AND ASTROPHYSICS↗

The Space and Earth Science Data Compression Workshop

This document is the proceedings from a Space and Earth Science Data Compression Workshop, which was held on March 27, 1992, at the Snowbird Conference Center in Snowbird, Utah. This workshop was held in conjunction with the 1992 Data Compression Conference (DCC '92), which was held at the same location, March 24-26, 1992. The workshop explored opportunities for data compression to enhance the collection and analysis of space and Earth science data. The workshop consisted of eleven papers presented in four sessions. These papers describe research that is integrated into, or has the potential of being integrated into, a particular space and/or Earth science data information system. Presenters were encouraged to take into account the scientists's data requirements, and the constraints imposed by the data collection, transmission, distribution, and archival system.

Tilton, James C.↗

Geology

Papers from private industry reporting applications of remote sensing to oil and gas exploration were presented. Digitally processed LANDSAT images were successfully employed in several geologic interpretations. A growing interest in digital image processing among the geologic user community was shown. The papers covered a wide geographic range and a wide technical and application range. Topics included: (1) oil and gas exploration, by use of radar and multisensor studies as well as by use of LANDSAT imagery or LANDSAT digital data, (2) mineral exploration, by mapping from LANDSAT and Skylab imagery and by LANDSAT digital processing, (3) geothermal energy studies with Skylab imagery, (4) environmental and engineering geology, by use of radar or LANDSAT and Skylab imagery, (5) regional mapping and interpretation, and digital and spectral methods.

Stewart, R. K.↗

Remote sensing techniques used in hydrocarbon exploration - A state-of-the-art review

Lintz (1972) has defined remote sensing for petroleum exploration as the detection from a distance of variations of the earth's surface or properties. Possibilities foreseen by Lintz could be realized with the Lander satellite. When used in 'phase-one' exploration programs, Landsat data have been effective in 'zeroing-in' on potential hydrocarbon traps, and later, when supplemented by more conventional exploration procedures, have led to the discovery of these resources. The present investigation is concerned with an overview of the methods utilized in 'phase-one' hydrocarbon exploration programs. The considered methods are to serve as an initial tool to aid the more conventional exploration procedures. Attention is given to visual interpretations, digital image processing, lineament analysis, surface anomalies, and geomorphology and topography.

Gonzales, R. W.↗

Data Production on Past and Future NASA Missions

Data return is a metric that is commonly publicized for all space science missions. In the early days of the Space Program, this figure was small, and could be described in bits or maybe even megabits. But now, missions are capable of returning data volumes two or three orders of magnitude larger. For example, Voyager 1 and 2 combined produced a little over 5 Terabits of data in 39 years of operation. In contrast, the Cassini mission, launched two decades after Voyager, produced about one and a half times those data volumes in half the time. NISAR, an Earth Science Mission currently in implementation, plans to produce over 28 Petabits of raw data in just 3 years. This means that NISAR will produce about as many data in 30 days as the combined data production of nearly all planetary missions to date. These increases in capability are a result of technology enhancements in two main areas: telecommunications architecture (both space and ground segments) and data storage technology. This paper describes the progression of these two technologies over the course of more than three decades of space missions and provides additional insight into the design of the end-to-end NISAR Data System Architecture. Trends in the data are briefly explored and compared to Moore’s Law which provides only a qualitative model for memory growth but not for data production. In summary, early missions are found to be driven by unrefined processes while later missions, having utilized earlier lessons learned, focus more on improvements to flight and ground capabilities. Data return seems to fall into three categories. First, deep space missions are driven by the large distances that limit data return to the Earth. Next, the orbiter infrastructure around Mars helps these missions generate more data than other deep space spacecraft. Finally, near-Earth missions have the greatest capabilities for the studied metrics due to their close proximity to Earth and the ground network availability.

Xaypraseuth, Peter↗

Next Generation System Analysis Model Recently Added Features and Future Plans - Abstract

The Nuclear Waste Policy Act of 1982, as amended (NWPA 1982), established the federal government’s responsibility to accept spent nuclear fuel (SNF) and high-level radioactive waste (HLW) from waste owners and generators for ultimate disposition. SNF generated by the current fleet of commercial nuclear reactors is being stored at the reactor sites in spent fuel pools (SFPs) and in dry independent spent fuel storage installations (ISFSIs). The US Department of Energy Office of Nuclear Energy (DOE-NE) is developing an Integrated Waste Management Program (IWMP) comprising a suite of options and supporting analyses to enable future informed choices. The IWMP is applying integrated waste management system architecture analysis, system engineering, and decision analysis principles to inform potential future decisions regarding potential nuclear waste management system architectures. Architecture analyses of the IWM system are being conducted to support the future deployment of a comprehensive system for managing nuclear waste that considers all major aspects of the back end of the nuclear fuel cycle (i.e., transportation, storage, and disposal). The Next Generation System Analysis Model (NGSAM) is an agent-based simulation software tool designed for the express purpose of modeling the IWM system. NGSAM imports data from the Oak Ridge National Laboratory (ORNL) Unified Database (e.g., historic assembly information, thermal profiles for assembly heat, at-reactor dry storage loadings) to ensure that the simulation initializes with a realistic representation of the state of commercial SNF in the United States. Recent major enhancements that have been implemented into NGSAM since NGSAM was last presented at the WM2019 conference include: • Tracking of railroad escort and buffer car acquisition. • Addition of heavy haul and barge routes for some sites, as well as support for user-defined inter-modal routes. • Updates to the logic that checks the thermal maps prior to package transport. • Addition of an allocation method that predicts when reactor sites will pack assemblies from their pools for dry storage and allocates packages to those reactor sites in the preceding periods, favoring direct transport packages and reducing the number of packages that reactor sites pack for dry storage at their ISFSIs. • Addition of reactor site family operational limits, which are used to limit the number of loads from the pool and from dry storage at a given reactor site per year. • Support has been added for multiple canister loading maps and packages having multiple compatible transportation overpacks. • Updates in the handling of non-commercial fuel, including a new database containing data to support the updates. • Support for repackaging at reactor sites. • Implementing additional output reports or modifying existing reports. • User edits can now be created and edited via the NGSAM website. • Ability to load packages for dry storage at ISF pools. • Same-type package blending at DOE sites. • Support for multi-mode transloading at reactor sites. These new features have improved NGSAM capabilities and/or improve the user experience with the model and will be discussed in more detail. The initial NGSAM requirements for advanced reactor fuels, reprocessing, treatment, and conditioning are preliminary and are described at a high level in this paper: analysts will provide more specific requirements to the NGSAM team in the future. Additionally, there are many data needs associated with modeling advanced reactors in NGSAM, but many of the data or plans are still in progress and/or yet to be fully defined. However, this document describes an initial exploration of the data relevant to this program. Advanced reactor data will likely require revision as concepts evolve and new considerations are made. This is a technical paper that does not take into account contractual limitations or obligations under the Standard Contract for Disposal of Spent Nuclear Fuel and/or High-Level Radioactive Waste (Standard Contract) (10 CFR Part 961). For example, under the provisions of the Standard Contract, spent nuclear fuel in multi-assembly canisters is not an acceptable waste form, absent a mutually agreed to contract amendment. To the extent discussions or recommendations in this paper conflict with the provisions of the Standard Contract, the Standard Contract governs the obligations of the parties, and this paper in no manner supersedes, overrides, or amends the Standard Contract. This paper reflects technical work which could support future decision making by DOE. No inferences should be drawn from this paper regarding future actions by DOE, which are limited both by the terms of the Standard Contract and Congressional appropriations for the Department to fulfill its obligations under the Nuclear Waste Policy Act including licensing and construction of a spent nuclear fuel repository.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A constraint-logic based implementation of the coarse-grained approach to data acquisition scheduling of the International Ultraviolet Explorer orbiting observatory

The International Ultraviolet Explorer (IUE) satellite observatory has been in operation continuously since 1978. It typically carries out several thousand observations per year for over a hundred different science projects. These observations, which can occur in one of four different data-taking modes, fall under several satellite-related constraints and many other constraints which derive from the science goals of the projects being undertaken. One strategy which has made the scheduling problem tractable has been that of 'coarse-graining' the time into discrete blocks of equal size (8 hours), each of which is devoted to a single science program, and each of which is sufficiently long for several observations to be carried out. We call it 'coarse-graining' because the schedule is done at a 'coarse' level which ignores fine structure; i.e., no attempt is made to plan the sequence of observations occurring within each time block. We have incorporated the IUE's coarse-grained approach in new software which examines the science needs of the observations and produces a limited set of alternative schedules which meet all of the instrument and science-related constraints. With this algorithm, the IUE can still be scheduled by a single person using a standard workstation, as it has been. We believe that this software could could be adapted to a more complex mission while retaining the IUE's high flexibility and efficiency and scientific return of future satellite missions.

Mccollum, Bruce↗

Ion temperature troughs and interhemispheric transport observed in the equatorial ionosphere

Ion temperature and ion drift velocity data from Atmosphere Explorer D have verified the existence of interhemispheric plasma transport and ion temperature troughs in the topside equatorial ionosphere. The data were taken during solar minimum conditions at night where the exospheric temperature was typically 700 K and the O(+)-H(+) transition height was 520 km. Large field-aligned ion velocities were observed above about 700 km, where the H(+)/O(+) number density ratio was about 3. Model calculations have shown that the ion temperature decrease is produced by quasi-adiabatic expansion of the plasma, but the expansion cooling mechanism is less efficient at solar minimum than at solar maximum owing to the lower O(+)-H(+) transition height. Ion temperature troughs greater than 400 K were not observed even when the field-aligned ion velocity was greater than 700 m/s. Most of the expansion occurs below the transition height, and during sunspot minimum, thermal coupling to the neutral atmosphere is much more effective in quenching the cooling which the field-aligned transport tends to produce.

Heelis, R. A.↗

Unified Software Architecture for Advanced Materials and Manufacturing Technologies Data Management and Processing: FY 2023 Multidimensional Data Correlation Platform

This report details the various digital manufacturing activities ongoing at ORNL as part of the Advanced Materials and Manufacturing Technologies (AMMT) program. The AMMT program is exploring a data-driven approach to demonstrate the use of AM for the fabrication of components for nuclear applications, with the goal of providing a greater understanding of manufacturing quality outcomes that would pave the way toward the development of standards for certification and qualification. The objective of this work package is to establish a digital manufacturing discipline common to all participants of the AMMT program to improve the performance, reliability, and lifetime of nuclear components. As part of this effort, we will develop a unified software architecture for AMMT data management and processing, deploy the digital platform across AMMT participants’ facilities, and generate pedigreed datasets in a common format across multiple labs and facilities. To this end, the MDDC work package has focused on three activities during FY23. First, the MDF Digital Tool was overhauled to better serve the needs of the AMMT program. Next, multiple laser powder bed fusion (L-PBF) systems at the MDF were upgraded to a common sensor package for collecting comparable in situ data across machines. Finally, various improvements relevant to the AMMT program were implemented in the ORNL-developed software tool, Peregrine. This report marks the completion of FY23 milestone M3CR-22OR0403051: Report Describing the Architecture of the Digital Platform to Support AMMT Activities.

36 MATERIALS SCIENCE↗

MSD CoP Webinar: AI and Extreme Events - Overcoming Data Challenges for Improved Characterization of Climate Extremes

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Artificial Intelligence (AI) models require large volumes of data for training and testing. Data requirements present challenges for using AI to explore extreme events with limited observational data. This webinar will showcase two innovative methods developed by part of the European Climate Intelligence (CLINT) project to overcome data challenges and harness AI to improve our understanding of climate extremes. Dr. Ascenso will present his research on data augmentation methods to improve estimates of tropical cyclones using satellite data. His presentation will review established methods for data augmentation and explore opportunities and challenges for using generative AI to generate images of extreme, life-threatening tropical cyclones. Next, Dr. Plesiat will present his research on deep learning techniques to overcome limited observational data sets. His presentation will illustrate deep learning methods to develop AI reconstructions of four climate indices across Europe. Presenters : Dr. Guido Ascenso (post-doctoral researcher, Politecnico di Milano); Dr. Étienne Plésiat (German Climate Computing Centre - DKRZ) Moderator(s): Stefano Galelli (MSD CoP WG Co-Lead), David Gold (MSD CoP WG Co-Lead), Jillian Sturtevant (MSD CoP WG Communications Officer), Matteo Giuliani (Politecnico di Milano, MSD CoP WG Member, Moderator and Organizer) This webinar was held on: October 11, 2024 from 11AM - 1PM ET

AI↗

Investigating User Experiences with Data Abstractions on High Performance Computing Systems

Scientific exploration generates expanding volumes of data that commonly require High Performance Computing (HPC) systems to facilitate research. HPC systems are complex ecosystems of hardware and software that frequently are not user friendly. The Usable Data Abstractions (UDA) project set out to build usable software for scientific workflows in HPC environments by undertaking multiple rounds of qualitative user research. Qualitative research investigates how individuals accomplish their work and our interview-based study surfaced a variety of insights about the experiences of working in and with HPC ecosystems. This report examines multiple facets to the experiences of scientists and developers using and supporting HPC systems. We discuss how stakeholders grasp the design and configuration of these systems, the impacts of abstraction layers on their ability to successfully do work, and the varied perceptions of time that shape this work. Examining the adoption of the Cori HPC at NERSC we explore the anticipations and lived experiences of users interacting with this system’s novel storage feature, the Burst Buffer. We present lessons learned from across these insights to illustrate just some of the challenges HPC facilities and their stakeholders need to account for when procuring and supporting these essential scientific resources to ensure their usability and utility to a variety of scientific practices.

97 MATHEMATICS AND COMPUTING↗

The Challenges of Integrating NASA's Human, Budget, and Data Capital within the Constellation Program's Exploration Launch Projects Office

The U.S. Vision for Space Exploration directs NASA to retire the Space Shuttle in 2010 and replace it with safe, reliable, and cost-effective space transportation systems for crew and cargo travel to the Moon, Mars, and beyond. Such emerging space transportation initiatives face massive organizational challenges, including building and nurturing an experienced, dedicated team with the right skills for the required tasks; allocating and tracking the fiscal capital invested in achieving technical progress against an integrated master schedule; and turning generated data into usehl knowledge that equips the team to design and develop superior products for customers and stakeholders. This paper discusses how NASA's Exploration Launch Projects Office, which is responsible for delivering these new launch vehicles, integrates these resources to create an engineering business environment that promotes mission success.

Kidd, Luanne↗

Properties of spikelike shear flow reversals observed in the auroral plasma by Atmosphere Explorer C

A study of the characteristics of pairs of oppositely directed spikes in ionospheric convection velocities (or shear flow reversals), as first described by Gurnett, has been conducted by using data from Atmosphere Explorer C. These phenomena tend to occur near the large-scale reversal from sunward to antisunward convection on the nightside of the earth. Generally, the spikelike shear flow reversals involve electric field components along the spacecraft orbit that are directed toward the region between them, in which inverted V type electron precipitation is observed. This relationship between the electron precipitation and the electric field spikes is consistent with an upward-flowing field-aligned current that is fed by Pedersen currents from the adjacent regions of strong convection. In one case a divergent equivalent electric field structure was observed, that is, with the spikelike electric fields pointing away from the region in between, which in this case exhibited a sharp electron flux dropout. This opposite configuration may be an example of counterparts to inverted V structures existing in regions of downward-flowing field-aligned currents.

Burch, J. L.↗

Comprehensive Analysis of RXTE Data from Cyg X-1. Spectral Index-Quasi-Periodic Oscillation Frequency-Luminosity Correlations

We present timing and spectral analysis of approx. 2.2 Ms of Rossi X-ray Time Explorer (RXTE) archival data from Cyg X-1. Using the generic Comptonization model we reveal that the spectrum of Cyg X-1 consists of three components: a thermal seed photon spectrum, a Comptonized part of the seed photon spectrum and the iron line. We find a strong correlation between 0.1-20 Hz frequencies of quasiperiodic oscillations (QPOs) and the spectral power-law index. Presence of two spectral phases (states) are clearly seen in the data when the spectral indices saturate at low and high values of QPO frequencies. This saturation effect was discovered earlier in a number of black hole candidate (BHC) sources and now we strongly confirm this phenomenon in Cyg X-1. In the soft state this index- QPO frequency correlation shows a saturation of the photon index Gamma approx. 2.1 at high values of the low frequency upsilon(sub L). The saturation level of Gamma approx. 2.1 is the lowest value found yet in BHCs. The bolometric luminosity does not show clear correlation with the index. We also show that Fe K(sub alpha) emission line strength (equivalent width, EW) correlates with the QPO frequency. EW increases from 200 eV in the low/hard state to 1.5 keV in the high/soft state. The revealed observational correlations allow us to propose a scenario for the spectral transition and iron line formation which occur in BHC sources. We also present the spectral state (the power-law index) evolution for eight years of Cyg X-1 observations by RXTE.

Shaposhnikov, Nickolai↗