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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Accelerating Science Impact through Big Data Workflow Management and Supercomputing

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. ATLAS, one of the largest collaborations ever assembled in the the history of science, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. To manage the workflow for all data processing on hundreds of data centers the PanDA (Production and Distributed Analysis)Workload Management System is used. An ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF), is realizing within BigPanDA and megaPanDA projects. These projects are now exploring how PanDA might be used for managing computing jobs that run on supercomputers including OLCF’s Titan and NRC-KI HPC2. The main idea is to reuse, as much as possible, existing components of the PanDA system that are already deployed on the LHC Grid for analysis of physics data. The next generation of PanDA will allow many data-intensive sciences employing a variety of computing platforms to benefit from ATLAS experience and proven tools in highly scalable processing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A biological perspective towards a standard for information exchange and reporting in XAS

The complex structural landscape of biological samples and their sensitivity to X-ray exposure leads to specific challenges in biological X-ray absorption spectroscopy (bio-XAS) research, which in turn has necessitated standardization of various aspects of bio-XAS data measurement, analysis and interpretation. The bio-XAS community is therefore well suited for the development of a data-reporting standard with the specific aim of creating a feedback loop for improving/standardizing data analysis protocols and optionally to make published data available to collaborators/researchers in a meaningful and quantitative format. The XIF (XAFS information file) reporting format presented here contains key experimental and analysis parameters, useful in developing a consistent platform for bio-XAS research worldwide. Such a reporting standard, enforced by the user community and publishing groups alike, can be an important step towards the standardization of data measurement and analysis techniques in bio-XAS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Workflows Community Summit: Tightening the Integration between Computing Facilities and Scientific Workflows

Scientific workflows are used almost universally across science domains for solving complex and largescale computing and data analysis problems. The importance of workflows is highlighted by the fact that they have underpinned some of the most significant discoveries of the past decades. Many of these workflows have significant computational, storage, and communication demands, and thus must execute on a range of large-scale computer systems, from local clusters to public clouds and upcoming exascale HPC platforms. Managing these executions is often a significant undertaking, requiring a sophisticated and versatile software infrastructure. Historically, infrastructures for workflow execution consisted of complex, integrated systems, developed in-house by workflow practitioners with strong dependencies on a range of legacy technologies—even including sets of ad hoc scripts. Due to the increasing need to support workflows, dedicated workflow systems were developed to provide abstractions for creating, executing, and adapting workflows conveniently and efficiently while ensuring portability. While these efforts are all worthwhile individually, there are now hundreds of independent workflow systems. These workflow systems are created and used by thousands of researchers and developers, leading to a rapidly growing corpus of workflows research publications. The resulting workflow system technology landscape is fragmented, which may present significant barriers for future workflow users due to many seemingly comparable, yet usually mutually incompatible, systems that exist. In order to tackle some of the challenges described above, the DOE-funded ExaWorks and NSF-funded WorkflowsRI projects have organized in 2021 a series of events entitled the “Workflows Community Summit”. The third edition of the “Workflows Community Summit” explored workflows challenges and opportunities from the perspective of computing centers and facilities. This third summit builds on two prior summits (https://workflowsri.org/summits) that (i) established a high level vision for workflows research; and (ii) explored technical approaches for realizing that vision. The third summit brought together a small group of facilities representatives with the aim to understand how workflows are currently being used at each facility, how facilities would like to interact with workflow developers and users, how workflows fit with facility roadmaps, and what opportunities there are for tighter integration between facilities and workflows. This report documents and organizes the wealth of information provided by the participants before, during, and after the summit.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2017

Software Defined Radios - Architectures, Systems and Functions

Software Defined Radio (SDR) technology has been proven in the commercial sector since the early 90's. Today's rapid advancement in mobile telephone reliability and power management capabilities exemplifies the effectiveness of the SDR technology for the modern communications market. SDR technology offers potential to revolutionize satellite transponder technology by increasing science data through-put capability by at least an order of magnitude. While the SDR is adaptive in nature and is "One-size-fits-all" by design, conventional transponders are built to a specific platform and must be redesigned for every new bus. The SDR uses a minimum amount of analog/Radio Frequency (RF) components to up/down-convert the RF signal to/from a digital format. Once analog data is digitized, all processing is performed using hardware logic. Typical SDR processes include; filtering, modulation, up/down converting and demodulation. These innovations have reduced the cost of transceivers, a decrease in power requirements and a commensurate reduction in volume. An additional pay-off is the increased flexibility of the SDR: allowing the same hardware to implement multiple transponder types by altering hardware logic -no change of analog hardware is required -all of which can be ultimately accomplished in orbit.

Sims, Herb↗
DOE OSTI2019

Lidar Mapping and Surveillance of Nuclear Infrastructure

Wear is unavoidable, whether it occurs in a nuclear facility or abridge on the highway its detection is crucial to preventing the failure of a system. While tools capable of detecting localized damage exist, industry lacks methods to evaluate the health of larger infrastructure. Routine inspection of nuclear facilities must be undertaken to ensure the safety of personnel and proper containment of nuclear materials. Most systems in a nuclear facility are designated as radioactive and confined spaces. To constantly monitor such systems in person would be hazardous but with a remote inspection tool it can be done in a safer and easier way. Lidar: Operates by emitting a laser pulse and looking for the reflected light. Allows user to gain 3D information of the environment. Project Objective: To develop an inspection tool for evaluating the health of large scale infrastructure using Lidar and machine learning. Autonomous Platform + Lidar + Data Fusion + Big Data. Use SLAM to build a 2D map of the environment. Point cloud created by transforming the points between reference frames. Point cloud to Surface: Inherent representation of surface geometry; Difficult to process with conventional techniques. Point cloud to Image: Easily processed by conventional machine learning algorithms. The quantity of data generated will necessitate a big data framework to manage the data for processing. Additional Sensors: Detecting the temperature (a) chemical makeup (b) and radiation emission (c) of a surface could assist in detecting problems. Human inspection can detect irregularities in both physical objects and their point-cloud representations. This is a good indication that mapping nuclear sites using Lidar will provide qualitative insight into the health of the facility. If deep learning can be used to automatically identify problem areas then the completed tool could become an invaluable asset.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

System-Level Integration of Modular Language Models for Real-Time Risk Assessment in Third-Party Risk Management Systems

Large enterprises typically rely on dedicated teams to govern and implement security measures throughout their supply chains, ensuring compliance with enterprise security procedures. There is a significant reliance on Third-Party Risk Management (TPRM) platforms, which often require complete, highly structured information from potential vendors. The review and compliance assurance processes are time- and labor intensive, often requiring several rounds of review between the supply chain security risk management teams, business users, and potential vendors, leading to delays in the supply chain processing and consumer experience. Significant challenges in the risk management paradigm include handling unstructured data in various formats and providing real-time feedback to users to reduce the required review time. This paper presents a novel solution to these challenges. A modular multi-step system architecture is proposed using advances in language processing, specifically for unstructured responses and provides real-time feedback (i.e., 3 seconds) so that users can improve their responses before the TPSRM team review. This novel system architecture will increase information accuracy and significantly reduce time and labor during the review process.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models feature diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific workflows with the convenience of a few mouse clicks while hiding the implementation and technical details from end users. Particularly, we will consider two types of applications with distinct performance requirements: data-centric and service-centric applications. For data-centric applications, the main workflow task involves large-volume data generation, catalog, storage, and movement typically from supercomputers or experimental facilities to a team of geographically distributed users; while for service-centric applications, the main focus of workflow is on data archiving, preprocessing, filtering, synthesis, visualization, and other application-specific analysis. We will conduct a comprehensive comparison of existing workflow systems and choose the best suited one with open-source code, a flexible system structure, and a large user base as the starting point for our development. Based on the chosen system, we will develop and integrate new components including a black box design of computing modules, performance monitoring and prediction, and workflow optimization and reconfiguration, which are missing from existing workflow systems. A modular design for separating specification, execution, and monitoring aspects will be adopted to establish a common generic infrastructure suited for a wide spectrum of science applications. We will further design and develop efficient workflow mapping and scheduling algorithms to optimize the workflow performance in terms of minimum end-to-end delay, maximum frame rate, and highest reliability. We will develop and demonstrate the SWAMP system in a local environment, the grid network, and the 100Gpbs Advanced Network Initiative (ANI) testbed. The demonstration will target scientific applications in climate modeling and high energy physics and the functions to be demonstrated include workflow deployment, execution, steering, and reconfiguration. Throughout the project period, we will work closely with the science communities in the fields of climate modeling and high energy physics including Spallation Neutron Source (SNS) and Large Hadron Collider (LHC) projects to mature the system for production use.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

An evaluation of the carbon sequestration potential of the Cambro-Ordovician Strata of the Illinois and Michigan basins

The studies summarized herein were conducted during 2009–2014 to investigate the utility of the Knox Group and St. Peter Sandstone deeply buried geologic strata for underground storage of carbon dioxide (CO 2 ), a practice called CO 2 sequestration (CCS). In the subsurface of the midwestern United States, the Knox and associated strata extend continuously over an area approaching 500,000 sq. km, about three times as large as the State of Illinois. Although parts of this region are underlain by the deeper Mt. Simon Sandstone, which has been proven by other Department of Energy-funded research as a resource for CCS, the Knox strata may be an additional CCS resource for some parts of the Midwest and may be the sole geologic storage (GS) resource for other parts. One group of studies assembles, analyzes, and presents regional-scale and point-scale geologic information that bears on the suitability of the geologic formations of the Knox for a CCS project. New geologic and geo-engineering information was developed through a small-scale test of CO 2 injection into a part of the Knox, conducted in western Kentucky. These studies and tests establish the expectation that, at least in some locations, geologic formations within the Knox will (a) accept a commercial-scale flow rate of CO 2 injected through a drilled well; (b) hold a commercial-scale mass of CO 2 (at least 30 million tons) that is injected over decades; and (c) seal the injected CO 2 within the injection formations for hundreds to thousands of years. In CCS literature, these three key CCS-related attributes are called injectivity, capacity, and containment. The regional-scale studies show that reservoir and seal properties adequate for commercial-scale CCS in a Knox reservoir are likely to extend generally throughout the Illinois and Michigan Basins. Information distinguishing less prospective subregions from more prospective fairways is included in this report. Another group of studies report the results of reservoir flow simulations that estimate the progress and outcomes of hypothetical CCS projects carried out within the Knox (particularly within the Potosi Dolomite subunit, which, in places, is highly permeable) and within the overlying St. Peter Sandstone. In these studies, the regional-scale information and a limited amount of detailed data from specific boreholes is used as the basis for modeling the CO 2 injection process (dynamic modeling). The simulation studies were conducted progressively, with each successive study designed to refine the conclusions of the preceding one or to answer additional questions. The simulation studies conclude that at Decatur, Illinois or a geologically similar site, the Potosi Dolomite reservoir may provide adequate injectivity and capacity for commercial-scale injection through a single injection well. This conclusion depends on inferences from seismic-data attributes that certain highly permeable horizons observed in the wells represent laterally persistent, porous vuggy zones that are vertically more common than initially evident from wellbore data. Lateral persistence of vuggy zones is supported by isotopic evidence that the conditions that caused vug development (near-surface processes) were of regional rather than local scale. Other studies address aspects of executing and managing a CCS project that targets a Knox reservoir. These studies cover well drilling, public interactions, representation of datasets and conclusions using geographic information system (GIS) platforms, and risk management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Retrospective on decadal progress of the NOAA/NPS ocean noise reference station network

The National Oceanic and Atmospheric Administration (NOAA), in partnership with the U.S. National Park Service (NPS), established the Ocean Noise Reference Station Network (NRS) in 2014 as a foundational component of NOAA’s Ocean Noise Strategy. This long-term effort aims to characterize baseline ocean ambient sound conditions across diverse marine environments and to inform management of noise impacts on protected species and habitats within U.S. waters. The NRS is now composed of 13 autonomous passive acoustic monitoring stations strategically positioned across the U.S. Exclusive Economic Zone (EEZ), extending from Arctic regions to tropical waters in depths ranging from 33 to 4,790 m. These locations include several National Marine Sanctuaries and National Parks, such as the recently designated Chumash Heritage National Marine Sanctuary off the coast of California. Each station is equipped to continuously sample low-frequency underwater sound at five kHz, enabling the detection of anthropogenic, geophysical, and biological acoustic signals. To date the network has sampled over 72 years of calibrated acoustic data. The spatial breadth and consistent methodology of the NRS allow for comparative acoustic assessments across diverse marine ecosystems. In addition to applied research functions, the NRS has served as a platform for education and training, offering opportunities for students to develop skills for marine science and data analysis. Looking forward, the NRS project team is focused on network expansion, improved data delivery, and broader integration with collaborative scientific initiatives. NRS recordings are being archived in partnership with NOAA’s National Centers for Environmental Information to enhance accessibility and long-term utility. Efforts are underway to develop standardized metadata and summary products to accompany raw audio files, making the data more usable for a wide range of stakeholders in the ocean science community. The NRS is evolving into a fully integrated national framework for ocean sound monitoring that supports scientific inquiry, management decision-making, national security interests, and public engagement with ocean acoustic environments.

Long-term monitoring↗
NASA NTRS2016

Planetary Balloon-Based Science Platform Evaluation and Program Implementation

This report describes a study evaluating the potential for a balloon-based optical telescope as a planetary science asset to achieve decadal class science. The study considered potential science achievable and science traceability relative to the most recent planetary science decadal survey, potential platform features, and demonstration flights in the evaluation process. Science Potential and Benefits: This study confirms the cost the-benefit value for planetary science purposes. Forty-four (44) important questions of the decadal survey are at least partially addressable through balloon based capabilities. Planetary science through balloon observations can provide significant science through observations in the 300 nm to 5 m range and at longer wavelengths as well. Additionally, balloon missions have demonstrated the ability to progress from concept to observation to publication much faster than a space mission increasing the speed of science return. Planetary science from a balloon-borne platform is a relatively low-cost approach to new science measurements. This is particularly relevant within a cost-constrained planetary science budget. Repeated flights further reduce the cost of the per unit science data. Such flights offer observing time at a very competitive cost. Another advantage for planetary scientists is that a dedicated asset could provide significant new viewing opportunities not possible from the ground and allow unprecedented access to observations that cannot be realized with the time allocation pressures faced by current observing assets. In addition, flight systems that have a relatively short life cycle and where hardware is generally recovered, are excellent opportunities to train early career scientists, engineers, and project managers. The fact that balloon-borne payloads, unlike space missions, are generally recovered offers an excellent tool to test and mature instruments and other space craft systems. Desired Gondola Features: Potential gondola characteristics are assessed in this study and a concept is recommended, the Gondola for High-Altitude Planetary Science (GHAPS). This first generation platform is designed around a 1 m or larger aperture, narrow-field telescope with pointing accuracies better than one arc-second. A classical Cassegrain, or variant like Ritchey-Chretien, telescope is recommended for the primary telescope. The gondola should be designed for multiple flights so it must be robust and readily processed at recovery. It must be light-weighted to the extent possible to allow for long-duration flights on super-pressure balloons. Demonstration Flights: Recent demonstration flights achieved several significant accomplishments that can feed forward to a GHAPS gondola project. Science results included the first ever Earth-based measurements for CO2 in a comet, first measurements for CO2 and H2O in an Oort cloud comet, and the first measurement of 1 Ceres at 2.73 m to refine the shape of the infrared water absorption feature. The performance of the Fine Steering Mirror (FSM) was also demonstrated. The BOPPS platform can continue to be leveraged on future flights even as GHAPS is being developed. The study affirms the planetary decadal recommendations, and shows that a number of Top Priority science questions can be achieved. A combination GHAPS and BOPPS would provide the best value for PSD for realizing that science.

Dankanich, John W.↗
NASA NTRS2003

MODIS Validation, Data Merger and Other Activities Accomplished by the SIMBIOS Project: 2002-2003

The purpose of this technical report is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities, satellite data processing, and data product validation. This documentation is necessary to ensure that critical information is related to the scientific community and NASA management. This critical information includes the technical difficulties and challenges of validating and combining ocean color data from an array of independent satellite systems to form consistent and accurate global bio-optical time series products. This technical report focuses on the SIMBIOS Project s efforts in support of the Moderate-Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) Terra platform (similar evaluations of MODIS/Aqua are underway). This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational project.

Fargion, Giulietta S.↗
NASA NTRS2010

Configuration Management (CM) Support for KM Processes at NASA/Johnson Space Center (JSC)

Collection and processing of information are critical aspects of every business activity from raw data to information to an executable decision. Configuration Management (CM) supports KM practices through its automated business practices and its integrated operations within the organization. This presentation delivers an overview of JSC/Space Life Sciences Directorate (SLSD) and its methods to encourage innovation through collaboration and participation. Specifically, this presentation will illustrate how SLSD CM creates an embedded KM activity with an established IT platform to control and update baselines, requirements, documents, schedules, budgets, while tracking changes essentially managing critical knowledge elements.

Cioletti, Louis↗
NASA NTRSDate not supplied

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)↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗
NASA NTRS1972

Strapdown platforms using redundant two-degree-of-freedom gyros

A new concept of high reliability strapdown attitude sensing systems for space vehicles is presented. Each system utilizes a set of redundant two-degree-of-freedom gyros. An optimum system configuration is obtained for maximum system reliability and the best measurement accuracy. Improved accuracy of the final data is obtained by using the least-square data reduction technique. Each system possesses a sensor performance management feature which is capable of failure detection, faulty gyro identification, system reconfiguration, and possibly, sensor recalibration. Improvement in reliability as compared to other types of strapdown systems is demonstrated. Details of the development are described in terms of a system containing four gyros.

Hung, J. C.↗
DOE OSTI2017

Nitric-glycolic flowsheet evaluation with the slurry-fed melt rate furnace

The Savannah River National Laboratory (SRNL) was tasked to support validation of the Defense Waste Processing Facility (DWPF) melter offgas flammability model for the nitric-glycolic (NG) flowsheet. The work supports Deliverable 4 of the DWPF & Saltstone Facility Engineering Technical Task Request (TTR)1 and is supplemental to the Cold Cap Evaluation Furnace (CEF) testing conducted in 2014.2 The Slurry-fed Melt Rate Furnace (SMRF) was selected for the supplemental testing as it requires significantly less resources than the CEF and could provide a tool for more rapid analysis of melter feeds in the future. The SMRF platform has been used previously to evaluate melt rate behavior of DWPF glasses, but was modified to accommodate analysis of the offgas stream. Additionally, the Melt Rate Furnace (MRF) and Quartz Melt Rate Furnace (QMRF) were utilized for evaluations. MRF data was used exclusively for melt behavior observations and REDuction/OXidation (REDOX) prediction comparisons and will be briefly discussed in conjunction with its support of the SMRF testing. The QMRF was operated similarly to the SMRF for the same TTR task, but will be discussed in a separate future report. The overall objectives of the SMRF testing were to; 1) Evaluate the efficacy of the SMRF as a platform for steady state melter testing with continuous feeding and offgas analysis; and 2) Generate supplemental melter offgas flammability data to support the melter offgas flammability modelling effort for DWPF implementation of the NG flowsheet.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1973

High-reliability strapdown platforms using two-degree-of-freedom gyros.

This paper presents a new concept of high-reliability strapdown attitude sensing systems for space vehicles. Each system utilizes a set of redundant two-degree-of-freedom gyros. An optimum system configuration is obtained for maximum system reliability and the best measurement accuracy. Improved accuracy of the final data is obtained by using the least-square data reduction technique. Each system possesses a 'sensor performance management' feature which is capable of failure detection, faulty gyro identification, system reconfiguration, and, possibly, sensor recalibration. Improvement in reliability, as compared to other types of strapdown systems, is demonstrated. Details of the development are described in terms of a system containing four gyros.

Hung, J. C.↗
DOE OSTI2020

Leaf traits and canopy structure together explain canopy functional diversity: an airborne remote sensing approach

Plant functional diversity is strongly connected to photosynthetic carbon assimilation in terrestrial ecosystems. However, many of the plant functional traits that regulate photosynthetic capacity, including foliar nitrogen concentration and leaf mass per area, vary significantly between and within plant functional types and vertically through forest canopies, resulting in considerable landscape-scale heterogeneity in three dimensions. Hyperspectral imagery has been used extensively to quantify functional traits across a range of ecosystems but is generally limited to providing information for top-of-canopy leaves only. On the other hand, lidar data can be used to retrieve the vertical structure of forest canopies. Because these data are rarely collected at the same time, there are unanswered questions about the effect of forest structure on the 3-D spatial patterns of functional traits across ecosystems. In the United States, the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) provides an opportunity to address this structure-function relationship by collecting lidar and hyperspectral data together across a variety of ecoregions. With a fusion of hyperspectral and lidar data from the NEON AOP and field-collected foliar trait data, we assessed the impacts of forest structure on spatial patterns of N. In addition, we examine the influence of abiotic gradients and management regimes on top of canopy %N and total canopy N (i.e. the total amount of N (g/m 2 ) within a forest canopy) at a NEON site consisting of a mosaic of open longleaf pine and dense broadleaf deciduous forests. Here, our resulting maps suggest that in contrast with top-of-canopy values, total canopy N variation is dampened across this landscape resulting in relatively homogeneous spatial patterns. At the same time, we found that leaf functional diversity and canopy structural diversity showed distinct dendritic patterns related to the spatial distribution of plant functional types.

54 ENVIRONMENTAL SCIENCES↗