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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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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Precision Information Environment (PIE) for International Safeguards: Pre-Demonstration Development Use Cases

In FY2013, the PIE International Safeguards team demonstrated our development progress to U.S. Department of Energy (DOE) staff from the Office of Nonproliferation and International Security (NA-24, our client) and the Office of Defense Nuclear Nonproliferation Research and Development (NA-22). Following the demonstration, the team was asked by our client to complete additional development prior to a planned demonstration at the International Atomic Energy Agency (IAEA), scheduled tentatively for January or spring of 2014. The team discussed four potential areas for development (in priority order), and will develop them as time and funding permit prior to an IAEA demonstration. The four capability areas are: 1. Addition of equipment manuals to PIE-accessible files 2. Optical character recognition (OCR) of photographed text 3. Barcode reader with information look-up from a database 4. Add Facilities to Data Model 5. Geospatial capabilities with information integration Each area will be described below in a use case.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2013

Integrated Distribution Management System for Alabama Principal Investigator

Southern Company Services, under contract with the Department of Energy, along with Alabama Power, Alstom Grid (formerly AREVA T&D) and others moved the work product developed in the first phase of the Integrated Distribution Management System (IDMS) from “Proof of Concept” to true deployment through the activity described in this Final Report. This Project – Integrated Distribution Management Systems in Alabama – advanced earlier developed proof of concept activities into actual implementation and furthermore completed additional requirements to fully realize the benefits of an IDMS. These tasks include development and implementation of a Distribution System based Model that enables data access and enterprise application integration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Interim Report on Concrete Degradation Mechanisms and Online Monitoring Techniques

The existing nuclear power plants in the United States have initial operating licenses of 40 years, though most of these plants have applied for and received license extensions. As plant structures, systems, and components age, their useful life—considering both structural integrity and performance—is reduced as a result of deterioration of the materials. The research on online monitoring of concrete structures conducted under the Advanced Instrumentation, Information, and Control Systems Technologies Pathway of the Light Water Reactor Sustainability Program at Idaho National Laboratory will develop and demonstrate concrete structures health monitoring capabilities. Assessment and management of aging concrete structures in nuclear plants require a more systematic approach than simple reliance on existing code margins of safety. Therefore, structural health monitoring is required to produce actionable information regarding structural integrity that supports operational and maintenance decisions. Through this research project, several national laboratories and Vanderbilt University propose to develop a framework of research activities for the health monitoring of nuclear power plant concrete structures that includes the integration of four elements—damage modeling, monitoring, data analytics, and uncertainty quantification. This report briefly discusses available techniques and ongoing challenges in each of the four elements of the proposed framework with emphasis on degradation mechanisms and online monitoring techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Online Monitoring of Concrete Structures in Nuclear Power Plants: Interim Report

The existing fleet of nuclear power plants in the United States have initial operating licenses of 40 years, and many of these plants have applied for and received license extensions. As plant structures, systems, and components age, their useful life—considering both structural integrity and performance—is reduced as a result of deterioration of the materials. Assessment and management of aging concrete structures in nuclear plants require a more systematic approach than simple reliance on existing code-based design margins of safety. Structural health monitoring is required to produce actionable information regarding structural integrity that supports operational and maintenance decisions. The online monitoring of concrete structures project conducted under the Advanced Instrumentation, Information, and Control Technologies Pathway of the Light Water Reactor Sustainability program at Idaho National Laboratory is seeking to develop and demonstrate capabilities for concrete structures health monitoring. Through this research project, several national laboratories and Vanderbilt University propose to develop a framework of research activities for the health monitoring of nuclear power plant concrete structures that includes the integration of four elements—damage modeling, monitoring, data analytics, and uncertainty quantification. This report briefly discusses activities in this project during October-December, 2014. The most significant activity during this period was the organizing of a two-day workshop on research needs in online monitoring of concrete structures, hosted by Vanderbilt University in November 2014. Thirty invitees from academia, industry and government participated in the workshop. The presentations and discussions at the workshop surveyed current activities related to concrete structures deterioration modeling and monitoring, and identified the challenges, knowledge gaps, and opportunities for advancing the state of the art; these discussions are summarized in this report

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Advanced Fuel Cycle Cost Basis – 2017 Edition

This report, commissioned by the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), provides a comprehensive set of cost data supporting a cost analysis for the relative economic comparison of options for use in the DOE Nuclear Technology Research and Development (NTRD) Program (previously the Fuel Cycle Research and Development (FCRD) and the Advanced Fuel Cycle Initiative (AFCI)). The report describes the NTRD cost basis development process, reference information on NTRD cost modules, a procedure for estimating fuel cycle costs, economic evaluation guidelines, and a discussion on the integration of cost data into economic computer models. This report contains reference cost data for numerous fuel cycle cost modules (modules A-O) as well as cost modules for a number of reactor types (R modules). The fuel cycle cost modules were developed in the areas of natural uranium mining and milling, thorium mining and milling, conversion, enrichment, depleted uranium disposition, fuel fabrication, interim spent fuel storage, reprocessing, waste conditioning, spent nuclear fuel (SNF) packaging, long-term monitored retrievable storage, managed decay storage, recycled product storage, near surface disposal of low-level waste (LLW), geologic repository and other disposal concepts, and transportation processes for nuclear fuel, LLW, SNF, transuranic, and high-level waste. Since its inception, this report has been periodically updated. The last such internal document was published in August 2015 while the last external edition was published in December of 2009 as INL/EXT-07-12107 and is available on the Web at URL: www.inl.gov/technicalpublications/Documents/4536700.pdf. This current report (Sept 2017) is planned to be reviewed for external release, at which time it will replace the 2009 report as an external publication. This information is used in the ongoing evaluation of nuclear fuel cycles by the NE NTRD program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Machine-Learning-Assisted Hybrid Earth System Modelling

We propose a novel hybrid modeling approach that combines a physics-based, numerical model of the Earth system with a machine learning model. We also envision to integrate the hybrid model training with a data assimilation cycle, so that new observations update both the state estimate used as initial conditions and the machine learning model parameters.

58 GEOSCIENCES↗
DOE OSTI2023

NNSA-IAEC Area: Workshop on Nuclear Waste Management and Subsurface Science (8-10 November 2022)

The 7 th workshop of the NNSA-IAEC collaboration was conducted on November 8-10 2022. The workshop was held at the geologic survey of Israel, Jerusalem. The IAEC hosted the workshop. The main topic of the workshop evolved around the results of the characterization borehole drilled in the Yamin plain during 2022 and associated experimental work and modeling results. The new data will be integrated for the applicability analysis of intermediate depth borehole (IDB) disposal for spent fuel in the Yamin plain. The first day of the workshop (November 8 th ) was dedicated to a geological field trip in the Judea desert depicting a similar cross section to that found in the Yamin plain. During the 9 th and 10 th of November the characterization BH results were presented, results of new work on the Miocene Hazeva fm. were presented, and this year’s outcome of the different collaboration groups were given.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Physics Informed Neural Networks as Computational Physics Emulators

This report is a brief overview and evaluation of Physics Informed Neural Networks (PINNs). Karniadakis and co-workers, e.g., Karniadakis et al. (2021) assert that the PINNs approach integrates seamlessly both data and mathematical physics models, even in partially understood, uncertain and high-dimensional contexts. They further claim that PINNs are effective and efficient for ill-posed and inverse problems, and when combined with domain decomposition, are scalable to large problems and a tool to discover hidden physics. While they demonstrate the capabilities in specific academic instances, their overarching claims about PINNs seem to be an overstatement, at least at the current time. We have briefly considered a few of the limitations of PINNs in this investigation. It is not clear to us if the PINNs approach can ever be competitive with approaches that use specialized algorithms to achieve high-accuracy solutions of governing equations and other techniques that can combine observational data with such solutions. As an example of the latter, consistent with the principles of Bayesian inference, data assimilation, or more generally data-model fusion, is a process that fuses observational data typically with a computational model that respects certain constraints such as conservation laws. For example, improvements in observational network combined with data assimilation have been key in improving weather predictions over the past four decades Kalnay (2003).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty [Brochure]

The four priority research directions outlined in this brochure represent a cohesive vision for advancing the science of inverse problems for complex systems under uncertainty. Together, they address the critical challenges of: discovering, exploiting, and preserving physical and problem structure; overcoming model limitations; integrating disparate, multimodal, and/or dynamic data; and tailoring the solution of inverse problems to downstream tasks. While each PRD focuses on a distinct aspect of inverse-problem research, their interconnected nature highlights the importance of a holistic approach that leverages progress across all areas to achieve transformative solutions. This agenda calls for research across mathematics, statistics, and computer science disciplines, which are guided and complemented by rapid advances in artificial intelligence, high-performance computing, and experimental facilities, to unlock new capabilities, maximize scientific impact, and meet the growing demands of inverse problems that arise across applications that are critical to DOE's mission.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

White Paper: Scalable Digital Twin Capabilities for Aging and Surveillance of Engineered Systems

This white paper presents a multi-year initiative to develop practical, secure, and scalable digital twin capabilities for engineered systems in aging and surveillance contexts—an approach pioneered at the National Nuclear Security Administration (NNSA) Lawrence Livermore National Laboratory (LLNL) that maps directly onto the needs and ambitions of the Navy for ship- and fleet-level digital twins. LLNL’s work in building part- and process-level digital twins for advanced manufacturing, with a vision to scale up to entire factory floors and, ultimately, enterprise-wide digital twins, offers an adaptable pathway for the Navy as it seeks to modernize lifecycle management, readiness, and predictive maintenance across ships and fleets. For our application, we integrate physics-based modeling with automated data ingestion, processing, and AI-driven calibration, creating hybrid models that are both interpretable and data responsive. We modernized legacy workflows, established centralized data infrastructure, automated experimental pipelines, and demonstrated end-to-end coupling of accelerated aging data with finite element simulations via optimization and surrogate modeling. The result is a generalizable framework that supports part-level digital twins today and lays the groundwork for future system-level twins suitable for Navy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions

Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.

Biomass Co-firing↗
DOE OSTI2022

Sample IEEE123 Bus system for OEDI SI

Time series load and PV data from an IEEE123 bus system. An example electrical system, named the OEDI SI feeder, is used to test the workflow in a co-simulation. The system used is the IEEE123 test system, which is a well studied test system (see link below to IEEE PES Test Feeder), but some modifications were made to it to add some solar power modules and measurements on the system. The aim of this project is to create an easy-to-use platform where various types of analytics can be performed on a wide range of electrical grid datasets. The aim is to establish an open-source library of algorithms that universities, national labs and other developers can contribute to which can be used on both open-source and proprietary grid data to improve the analysis of electrical distribution systems for the grid modeling community. OEDI Systems Integration (SI) is a grid algorithms and data analytics API created to standardize how data is sent between different modules that are run as part of a co-simulation. The readme file included in the S3 bucket provides information about the directory structure and how to use the algorithms. The sensors.json file is used to define the measurement locations.

123 bus↗
DOE OSTI2026

Prediction of non-intuitive metabolic targets with bayesian metabolic control analysis to improve 3-hydroxypropionic acid production in Aspergillus niger

Development of efficient bioconversion processes is limited by the ability to predictably improve metabolic flux. Here we deployed Bayesian Metabolic Control Analysis as a platform to integrate multi-omics data with metabolic modeling and evaluated its ability to predict genetic interventions that improve metabolic flux. Global Metabolomics and proteomics data was collected from 17 Aspergillus niger strains engineered to produce the platform biochemical 3-hydroxypropionic acid from which seven actional genetic interventions were predicted from significant flux control coefficients. Of the suggested genetic interventions, two were present within the intuitively designed strains used for training (malonic semialdehyde dehydrogenase and pyruvate carboxylase) while five predicted targets were present within non-intuitive areas of the metabolic network including 5-formyltetrahydrofolate deformylase and four mitochondrial enzymes, alcohol dehydrogenase, succinyl-CoA ligase, aspartate aminotransferase, and malate dehydrogenase. Six of the targets were validated in the highest performing 3-HP strain used for multi-omics data generation which contained a prior disruption of the highest scoring target malonic semialdehyde dehydrogenase. Predicted directional perturbation of five of the six tested targets significantly improved titer and rate of 3-HP production and two significantly improved yield. The greatest improvements were observed following disruption of the non-intuitive target succinyl-CoA ligase which increased titer by 39% and yield by 29% (to 20.4 g/L 3-HP and 0.31 g 3-HP/g glucose) over the strains used for training. This study demonstrates the utility of Bayesian Metabolic Control Analysis and highlights the ability to predict meaningful genetic targets in unexpected areas of metabolism to improve engineered strains for bioconversion.

3-hydroxypropionic acid↗
DOE OSTI2016

Kinematic properties of double-barred galaxies: simulations versus integral-field observations

Using high-resolution N-body simulations, we recently reported that a dynamically cool inner disk embedded in a hotter outer disk can naturally generate a steady double-barred (S2B) structure. Here we study the kinematics of these S2B simulations, and compare them to integral-field observations from ATLAS {sup 3D} and SAURON. We show that S2B galaxies exhibit several distinct kinematic features, namely: (1) significantly distorted isovelocity contours at the transition region between the two bars, (2) peaks in σ {sub LOS} along the minor axis of inner bars, which we term “σ-humps,” that are often accompanied by ring/spiral-like features of increased σ {sub LOS}, (3) h{sub 3}-- v-bar anti-correlations in the region of the inner bar for certain orientations, and (4) rings of positive h {sub 4} when viewed at low inclinations. The most impressive of these features are the σ-humps; these evolve with the inner bar, oscillating in strength just as the inner bar does as it rotates relative to the outer bar. We show that, in cylindrical coordinates, the inner bar has similar streaming motions and velocity dispersion properties as normal large-scale bars, except for σ {sub z}, which exhibits peaks on the minor axis, i.e., humps. These σ {sub z} humps are responsible for producing the σ-humps. For three well-resolved early-type S2Bs (NGC 2859, NGC 2950, and NGC 3941) and a potential S2B candidate (NGC 3384), the S2B model qualitatively matches the integral-field data well, including the “σ-hollows” previously identified. We also discuss the kinematic effect of a nuclear disk in S2Bs.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

Lithologic mapping in a sedimentary environment using multipolarization SAR images

Multipolarization Synthetic Aperture Radar (SAR) data from the NASA/JPL aircraft SAR were used in conjunction with LANDSAT Thematic Mapper (TM), Thermal Infrared Multispectral Scanner (TIMS), and Airborne Imaging Spectrometer (AIS) data as part of a three-year research program to evaluate the utility of remote sensing measurements for analysis of sedimentary basins. The purpose of this research effort is to construct stratigraphic columns, map variations in the lithology, geometry, and structure of sedimentary rocks in the Wind River/Bighorn Basin area, Wyoming, and to integrate remote sensing data with conventional rain models of basin formation and evolution.

Evans, D. L.↗
NASA NTRS1999

Examining Mars with SPICE

The International Mars Conference highlights the wealth of scientific data now and soon to be acquired from an international armada of Mars-bound robotic spacecraft. Underlying the planning and interpretation of these scientific observations around and upon Mars are ancillary data and associated software needed to deal with trajectories or locations, instrument pointing, timing and Mars cartographic models. The NASA planetary community has adopted the SPICE system of ancillary data standards and allied tools to fill the need for consistent, reliable access to these basic data and a near limitless range of derived parameters. After substantial rapid growth in its formative years, the SPICE system continues to evolve today to meet new needs and improve ease of use. Adaptations to handle landers and rovers were prototyped on the Mars pathfinder mission and will next be used on Mars '01-'05. Incorporation of new methods to readily handle non-inertial reference frames has vastly extended the capability and simplified many computations. A translation of the SPICE Toolkit software suite to the C language has just been announced. To further support cartographic calculations associated with Mars exploration the SPICE developers at JPL have recently been asked by NASA to work with cartographers to develop standards and allied software for storing and accessing control net and shape model data sets; these will be highly integrated with existing SPICE components. NASA specifically supports the widest possible utilization of SPICE capabilities throughout the international space science community. With NASA backing the Russian Space Agency and Russian Academy of Science adopted the SPICE standards for the Mars 96 mission. The SPICE ephemeris component will shortly become the international standard for agencies using the Deep Space Network. U.S. and European scientists hope that ESA will employ SPICE standards on the Mars Express mission. SPICE is an open set of standards, and all related specifications and software are freely distributed around the world. This poster describes the current state of SPICE system development, with special emphasis on current and planned support for Mars exploration missions.

Acton, Charles H.↗
NASA NTRS1994

Simulating Local and Intercontinental Pollutant Effects of Biomass Burning: Integration of Several Remotely Sensed Datasets

Burning to clear land for crops and to destroy pests is an integral and largely unavoidable part of tropical agriculture. It is easy to note but difficult to quantify using remote sensing. This report describes our efforts to integrate remotely sensed data into our computer model of tropical chemical trace-gas emissions, weather, and reaction chemistry (using the MM5 mesoscale model and our own Global-Regional Atmospheric Chemistry Simulator). The effects of burning over the continents of Africa and South America have been noticed in observations from several satellites. Smoke plumes hundreds of kilometers long may be seen individually, or may merge into a large smoke pall over thousands of kilometers of these continents. These features are related to intense pollution in the much more confined regions with heavy burning. These emissions also translocate nitrogen thousands of kilometers in the tropical ecosystems, with large fixed-nitrogen losses balanced partially by locally intense fertilization downwind, where nitric acid is rained out. At a much larger scale, various satellite measurements have indicated the escape of carbon monoxide and ozone into large filaments which extend across the Tropical and Southern Atlantic Ocean. Our work relates the source emissions, estimated in part from remote sensing, in part from conventional surface reports, to the concentrations of these gases over these intercontinental regions. We will mention work in progress to use meteorological satellite data (AVHRR, GOES, and Meteosat) to estimate the surface temperature and extent and height of clouds, and explain why these uses are so important in our computer simulations of global biogeochemistry. We will compare our simulations and interpretation of remote observations to the international cooperation involving Brazil, South Africa, and the USA in the TRACE-A (Transport and Atmospheric Chemistry near the Equator - Atlantic) and SAFARI (Southern Africa Fire Atmosphere Research Initiative) and remote-sensing /aircraft/ecosystem observational campaigns.

Chatfield, Robert B.↗
NASA NTRS2007

Measuring a Precise Ultra-Lightweight Spaceflight Mirror on Earth: The Analysis of the SHARPI PM Mirror Figure Data during Mirror Processing at GSFC

The SHARPI (Solar High Angular Resolution Photometric Imager) primary mirror is a 5kg, 0.5m paraboloid, diffraction limited at FUV wavelengths when placed in a 0-G environment. The ULE sandwich honeycomb mirror and the attached mount pads were delivered by ITT (then Kodak) in 2003 to NASA s Goddard Space Flight Center (GSFC). At GSFC, we accepted, coated, mounted, and vibration tested this mirror in preparation for flight on the PICTURES (Planet Imaging Concept Testbed Using a Rocket Experiment) mission. At each step, the integrated analysis of interferometer data and FEA models was essential to quantify the 0-G mirror figure. This task required separating nanometer sized variations from hundreds of nanometers of gravity induced distortion. The ability to isolate such features allowed in-situ monitoring of mirror figure, diagnosis of perturbations, and remediation of process errors. In this paper, we describe the technical approach used to achieve these measurements and overcome the various difficulties maintaining UV diffraction-limited performance with this aggressively lightweighted mirror.

Antonille, Scott↗