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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 55 records · Page 3

IceVal DatAssistant: An Interactive, Automated Icing Data Management System

As with any scientific endeavor, the foundation of icing research at the NASA Glenn Research Center (GRC) is the data acquired during experimental testing. In the case of the GRC Icing Branch, an important part of this data consists of ice tracings taken following tests carried out in the GRC Icing Research Tunnel (IRT), as well as the associated operational and environmental conditions during those tests. Over the years, the large number of experimental runs completed has served to emphasize the need for a consistent strategy to manage the resulting data. To address this situation, the Icing Branch has recently elected to implement the IceVal DatAssistant automated data management system. With the release of this system, all publicly available IRT-generated experimental ice shapes with complete and verifiable conditions have now been compiled into one electronically-searchable database; and simulation software results for the equivalent conditions, generated using the latest version of the LEWICE ice shape prediction code, are likewise included and linked to the corresponding experimental runs. In addition to this comprehensive database, the IceVal system also includes a graphically-oriented database access utility, which provides reliable and easy access to all data contained in the database. In this paper, the issues surrounding historical icing data management practices are discussed, as well as the anticipated benefits to be achieved as a result of migrating to the new system. A detailed description of the software system features and database content is also provided; and, finally, known issues and plans for future work are presented.

Levinson, Laurie H.↗

IceVal DatAssistant: An Interactive, Automated Icing Data Management System

As with any scientific endeavor, the foundation of icing research at the NASA Glenn Research Center (GRC) is the data acquired during experimental testing. In the case of the GRC Icing Branch, an important part of this data consists of ice tracings taken following tests carried out in the GRC Icing Research Tunnel (IRT), as well as the associated operational and environmental conditions documented during these tests. Over the years, the large number of experimental runs completed has served to emphasize the need for a consistent strategy for managing this data. To address the situation, the Icing Branch has recently elected to implement the IceVal DatAssistant automated data management system. With the release of this system, all publicly available IRT-generated experimental ice shapes with complete and verifiable conditions have now been compiled into one electronically-searchable database. Simulation software results for the equivalent conditions, generated using the latest version of the LEWICE ice shape prediction code, are likewise included and are linked to the corresponding experimental runs. In addition to this comprehensive database, the IceVal system also includes a graphically-oriented database access utility, which provides reliable and easy access to all data contained in the database. In this paper, the issues surrounding historical icing data management practices are discussed, as well as the anticipated benefits to be achieved as a result of migrating to the new system. A detailed description of the software system features and database content is also provided; and, finally, known issues and plans for future work are presented.

Levinson, Laurie H.↗

Analysis of Fuel Cell Markets in Japan and the US: Experience Curve Development and Cost Reduction Disaggregation

Fuel cells are both a longstanding and emerging technology for stationary and transportation applications, and their future use will likely be critical for the deep decarbonization of global energy systems. As we look into future applications, a key challenge for policy-makers and technology market forecasters who seek to track and/or accelerate their market adoption is the ability to forecast market costs of the fuel cells as technology innovations are incorporated into market products. Specifically, there is a need to estimate technology learning rates, which are rates of cost reduction versus production volume. Unfortunately, no literature exists for forecasting future learning rates for fuel cells. In this paper, we look retrospectively to estimate learning rates for two fuel cell deployment programs: (1) the micro-combined heat and power (CHP) program in Japan, and (2) the Self-Generation Incentive Program (SGIP) in California. These two examples have a relatively broad set of historical market data and thus provide an informative and international comparison of distinct fuel cell technologies and government deployment programs. We develop a generalized procedure for disaggregating experience-curve cost-reductions in order to disaggregate the Japanese fuel cell micro-CHP market into its constituent components, and we derive and present a range of learning rates that may explain observed market trends. Finally, we explore the differences in the technology development ecosystem and market conditions that may have contributed to the observed differences in cost reduction and draw policy observations for the market adoption of future fuel cell technologies. The scientific and policy contributions of this paper are the first comparative experience curve analysis of past fuel cell technologies in two distinct markets, and the first quantitative comparison of a detailed cost model of fuel cell systems with actual market data. The resulting approach is applicable to analyzing other fuel cell markets and other energy-related technologies, and highlights the data needed for cost modeling and quantitative assessment of key cost reduction components.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

What is Success? Evaluating S'COOL, an Educational Outreach Project Focused on NASA's CERES Program

The Students' Cloud Observations On-Line (S'COOL) Project involved students in K-16 as ground truth observers for a NASA Earth-Observing satellite instrument. The Clouds and Earth's Radiant Energy System (CERES) instrument allows scientists to study the Earth's energy budget and how clouds affect it. Student reports of cloud conditions help scientists verify their algorithms and allow students to be involved in obtaining and analyzing real scientific data. The presentation contains 23 slides.

Chambers, Lin H.↗

Exploiting the Free Landsat Archive for Operational Monitoring of Ecosystem Condition and Change Across the Chesapeake Bay Watershed

For the first time, all imagery acquired by the Landsat series of satellites is being made available by the USGS to users at no cost. This represents a key opportunity to use Landsat in a truly operational monitoring framework: large regions of the U.S. such as the Chesapeake Bay Watershed can now be analyzed using "wall-to-wall" imagery at timescales from approximately 1 month to several years. With the future launch of the Landsat Data Continuity Mission (LDCM) and Decadal Survey missions such as the hyperspectral HyspIRI, it is imperative to develop robust processing systems to perform annual ecosystem assessments over large regions such as the Chesapeake Bay. We have been working at NASA's Goddard Space Flight Center (GSFC) to develop an integrative framework for inserting 30m, annual, Landsat based data and derived products into the existing decision support system for the Bay, with a particular focus on ecosystem condition and changes over the entire watershed. The basic goal is to use a 'stack' of Landsat imagery with 40% or less cloud cover to produce multi-date (2005-2009 period), cloud/shadow/gap-free composited surface reflectance products that will support the creation of watershed scale land cover/ use products and the monitoring of ecosystem change across the Bay. Our scientific focus extends beyond the conventional definition of land cover (i.e. a classification of vegetation type) as we propose to monitor both changes in surface type (e.g. forest to urban), vegetation structure (e.g. forest disturbance due to logging or insect damage), as well as winter crop cover. These processes represent a continuum from large, interannual changes in land cover type, to subtler, intra-annual changes associated with short-term disturbance. The free Landsat data are being processed to surface reflectance and composited using the existing Landsat Ecosystem Disturbance Adaptive Processing System here at NASA/ GSFC, and land cover products (type, tree cover, impervious cover, winter cover) are being produced using well-established decision tree and regression tree algorithms. The goal of this session is to present the data products that we have been developing to the Bay science community and to discuss potential avenues for improvements and usage of the products for decision support.

BrowndeColstoun, Eric↗

Modular Autonomous Experimentation for Biological Applications

The Modular Autonomous Research System (MARS) was created to address a key challenge in scientific discovery: experiments are often slow, require significant manual labor, and generate data that is not easily integrated across different tools. This limits how quickly scientists can explore new materials, processes, and chemical reactions. Our motivation was to design a system that makes research faster, more reliable, and adaptable by combining automation with artificial intelligence. By doing so, we aimed to reduce human error, accelerate discovery, and allow researchers to quickly test many possibilities that would otherwise take months or years. Our approach was to build a flexible platform that connects laboratory robots, measurement instruments, and a central data system, all guided by artificial intelligence. MARS integrates liquid handling robots, robotic arms, and plate readers with an intelligent decision-making system that chooses the most informative experiments to run next. This creates a closed loop where experiments are performed automatically, the data is analyzed in real time, and new conditions are immediately tested. Through this work, we demonstrated that MARS can carry out multiple experiments with little or no human intervention, adapt to different scientific problems, and handle uncertain or noisy measurements in a robust way. The results show that modular and intelligent automation can significantly accelerate the pace of discovery, providing a model for future self-driving laboratories. This approach addresses the growing scientific need for adaptable, data-driven research platforms that can keep up with the complexity and scale of modern science.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning Models for GPU Error Prediction in a Large Scale HPC System

GPUs are widely deployed on large-scale HPC systems to provide powerful computational capability for scientific applications from various domains. As those applications are normally long-running, investigating the characteristics of GPU errors becomes imperative for reliability. In this paper, we first study the system conditions that trigger GPU errors using six-month trace data collected from a large-scale, operational HPC system. Then, we use machine learning to predict the occurrence of GPU errors, by taking advantage of temporal and spatial dependencies of the trace data. The resulting machine learning prediction framework is robust and accurate under different workloads.

Nie, Bin↗

Life Extension of Nuclear Plant Facilities through Monitoring and Detailed Analysis - 16175

The UK has accumulated a substantial legacy of radioactive waste from various civil nuclear and defence programmes. Presently, however most of the UK radioactive waste is generated from nine power stations which generate approximately one sixth of the of the country's electricity. Irradiated fuel is removed from these reactors and safe management of the radioactive solid and liquid effluents is required. The safe management of these effluents is essential. Sellafield, in West Cumbria UK, contains two reprocessing plants, one designed to process nuclear fuel from Magnox reactors (CO{sub 2} cooled with Uranium bar fuel) and the other to process nuclear fuel from Advanced Gas cooled Reactors and Pressurized Water Reactors. The reprocessing stage enables extraction of fissile material for recycling. This leaves a volume of dilute but high-level waste. The high-level radioactive liquid waste is concentrated to reduce its volume and then incorporated into borosilicate glass, using a process called vitrification. The glass is then poured into stainless steel containers and placed in long term storage. This required concentration of HLW liquor is achieved using a suite of aging evaporators. All evaporators are of similar design constructed from corrosion resistant stainless steel having dimensions height ∼11 m, internal diameter 3.05 m and capable of holding 13.7 m{sup 3} of liquor. The basic principle of operation is to heat the dilute liquor under partial vacuum, at constant volume, until the target concentration is achieved. Heating of the liquor is achieved using steam heated coils within the evaporator, and steam in the jacket which surrounds the lower half of the evaporator vessel. The evaporator is then brought to atmospheric pressure and the concentrated liquor is ejected whilst hot. The evaporator is then cooled with water cooled coils and a water filled jacket. New dilute liquor is then added for a new batch. The process is then repeated. As the evaporators reach the end of their original design life accurate prediction of the current condition of nuclear plant facilities is essential to safely justify continued plant operation by ensuring structural integrity. This poses a significant challenge as many aging UK nuclear facilities were not inherently built with inspection in mind. The potential life limiting components of the HA evaporators at Sellafield are the surfaces that contact the product liquor at elevated temperatures i.e. the steam heated surfaces of the coils within the evaporator vessel and the vessel base and wall surrounded by the steam jacket. Each heating component is critical to the operational life of the evaporator - the removal from service of a coil heating component significantly reduces the operational flexibility and remnant life of this plant. Over the last decade a variety of cutting-edge expertise and methodologies have been utilised to accurately measure and then predict the current condition of the plant and also to predict its remnant life. This paper provides an overview of the development of several techniques deployed, namely non-destructive testing/inspection, in-house software development and finite element modelling. These methods have been validated by lab-scale or full-scale experiments along with historical plant data. These techniques have been evolved and refined for over a decade, providing vital insights into the physical behaviour of this complex reprocessing system. This enables not only accurate assessment of the current condition of the plant equipment but also allows scientifically underpinned predictions to be made of how it will behave into the future. This is critical for Sellafield as this knowledge feeds into their safety case to the Office of Nuclear Regulation to justify continued operation. It is concluded that this integrated approach provides a robust analysis tool which has driven change and optimisation of plant procedures ensuring continued safe operation whilst extending the life of the facility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Experimental methods to test photoionized plasma models in emission

The expanding foil photoionized plasma platform was developed on the Z-machine at Sandia National Laboratories to produce terrestrial photoionized plasmas at some of the same conditions as those observed in astrophysical black hole accretion disks. The specific scientific goals of the platform are motivated by long-standing astrophysical puzzles related to accreting black hole systems. Ultimately, the experimental goal is to inform the supersolar Fe abundance problem by testing photoionized plasma models in emission with at-parameter laboratory data. High quality high resolution emission data with absolute intensity calibration from a laboratory photoionized plasma have never been collected prior to the experiments described here, providing broader motivation. A robust test of the model predictions requires the successful production of a laboratory photoionized plasma along with measurements of the supporting model inputs including the radiation drive spectrum used to create the photoionized plasma, the electron density, and the temperature. The measured absolute spectral radiance in emission collected from the independently diagnosed plasma can be compared against model calculations performed using the measured inputs. In this paper, we focus on the experimental platform and the model inputs, specifically detailing the methodology used to measure the plasma conditions. The moderate electron temperature of ∼41 eV ± 15 eV and electron density of ∼1e19 ± 1.6e18 e−/cm3 and the ∼3e12 W/cm2 x-ray irradiance at the sample confirm that photoionization dominates the plasma ionization and spectra.

Cho, P. B. (ORCID:0000000291632905)↗

A Physical Validation Program for the GPM Mission

The GPM mission is currently planned for start in the late 2007 - early 2008 time frame. Its main scientific goal is to help answer pressing scientific problems arising within the context of global and regional water cycling. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe -- continuously. The constellation's orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. A major requirement before the retrieved rainfall information generated by the GPM mission can be used effectively by prognostic models to improve weather forecasts, hydrometeorological forecasts, and climate model reanalysis simulations is a capability to quantify the error characteristics of the retrievals. A solution for this problem has been upheld in past precipitation missions because of the lack of suitable error modeling systems incorporated into the validation programs and data distribution systems. An overview of how NASA intends to overcome this problem for the GPM mission using a physically-based error modeling approach within a multi-faceted validation program is described. The solution is to first identify specific user requirements and then determine the most stringent of these requirements that embodies all essential error characterization information needed by the entire user community. In the context of NASA s scientific agenda for the GPM mission, the most stringent user requirement is found within the data assimilation community. The fundamental theory of data assimilation vis-a-vis ingesting satellite precipitation information into the pre-forecast initializations is based on quantifying the conditional bias and precision errors of individual rain retrievals, and the space-time structure of the precision error (i.e., the spatial-temporal error covariance). By generating the hardware and software capability to produce this information in a near real-time fashion, and to couple the derived quantitative error properties to the actual retrieved rainrates, all key validation users can be satisfied. The talk will describe the essential components of the hardware and software systems needed to generate such near real-time error properties, as well as the various paradigm shifts needed within the validation community to produce a validation program relevant to the precipitation user community.

Smith, Eric A.↗

The CELSS Test Facility Project - An example of a CELSS flight experiment system

The design of the facility is described in terms of its use as an investigation tool for evaluating crop growth in space with reference to required emerging technologies. NASA's CELSS Test Facility (CTF) is designed to permit the measurement of crop-plant productivity under microgravity conditions including biomass production, food production, water transpiration, and O2/CO2 exchanges. Crucial hardware tests and qualifications are identified to assure the operation of CTF technologies in space including the nutrient-delivery, water-condensation, and gas-liquid-mixing subsystems. The design concept and related scientific requirements are described and shown to provide microgravity crop research. The CTF is expected to provide data for plant research and for concepts for bioregenerative life-support systems for applications to Martian, lunar, and space-station missions.

Macelroy, R. D.↗

Vectorcardiograph

A system for quantitating the cardiac electrical activity of Skylab crewmen was required for three medical experiments (M092, Lower Body Negative Pressure; M171, Metabolic Activity; and M093, In-flight Vectorcardiogram) designed to evaluate the effects of space flight on the human cardiovascular system. A Frank lead vectorcardiograph system was chosen for this task because of its general acceptability in the scientific community and its data quantification capabilities. To be used effectively in space flight, however, the system had to meet certain other requirements. The system was required to meet the specifications recommended by the American Heart Association. The vectorcardiograph had to withstand the extreme conditions of the space environment. The system had to provide features that permitted ease of use in the orbital environment. The vectorcardiograph system performed its intended function throughout all the Skylab missions without a failure. A description of this system follows.

Lintott, J.↗

A Study of the Curation Protocol by Sample Analysis Working Team (SAWT) in Martian Moons eXploration (MMX) Project

Japan Aerospace Exploration Agency (JAXA) will launch a spacecraft in 2024 for a sample return mission from Phobos (Martian Moons eXploration: MMX). The major scientific goals of MMX are to constrain (1) the origin of Phobos and Deimos and (2) the evolution of the Mars-moon system [1]. The touchdown operations are planned to be performed twice at different landing sites on the Phobos surface to collect > 10 g of the surface materials [2]. After the return to the Earth, the Phobos samples will be collected from the individual sample canisters and introduced to the clean chamber installed at ISAS (Institute of Space and Astronautical Science). The Sample Analysis Working Team (SAWT) of MMX designed the procedure of Phobos sample analysis mainly conducted by the initial analysis teams [3]. For the next step, the SAWT will define the procedure of the curation process (mostly non-destructive analysis) of the Phobos samples, which will be presented here. The protocols of the Phobos sample curation is illustrated in figure 1. First, the headspace gas from the sample container will be collected during the Quick Analysis phase. The Quick Analysis will be operated by the sampler and curation teams in ISAS/JAXA. The terrestrial leak and contamination from the sampling systems will be tested using a quadrupole mass spectrometer equipped with a gas sampling system. Second, the bulk Phobos sample will be observed in the clean chamber under purified-N2 gas with an ambient condition (Pre-basic Characterization). This phase will be operated by the curation team in ISAS/JAXA and the instrument team of the MMX mission. The consistency between the data from the instruments in the clean chamber and the spacecraft will then be evaluated. Subsequently, the curation will distribute the small amount of Phobos samples to the Initial analysis team of MMX to conduct the "Preliminary Examination". The objectives of the preliminary examination are to provide (1) feedback on the subsequent sample allocation process, (2) preliminary scientific results that will address parts of MMX mission goals, and (3) evaluation of the sampling system and terrestrial alteration on Phobos samples. Because multiple models are proposed for the origin of Phobos [1] (e.g., giant impact, the capture of asteroids), the chemical and mineralogical characteristics of Phobos must be assessed before the allocation of the samples to the individual initial analysis teams. Simultaneously, the curation team in JAXA will observe the individual grains and aliquots of the samples in the clean chamber (Basic Characterization).

R Fukai↗

Aerosols and Particulates Workshop Sampling Procedures and Venues Working Group Summary

The Sampling Procedures and Venues Workgroup discussed the potential venues available and issues associated with obtaining measurements. Some of the issues included Incoming Air Quality, Sampling Locations, Probes and Sample Systems. The following is a summary of the discussion of the issues and venues. The influence of inlet air to the measurement of exhaust species, especially trace chemical species, must be considered. Analysis procedures for current engine exhaust emissions regulatory measurements require adjustments for air inlet humidity. As a matter of course in scientific investigations, it is recommended that "background" measurements for any species, particulate or chemical, be performed during inlet air flow before initiation of combustion, if possible, and during the engine test period as feasible and practical. For current regulatory measurements, this would be equivalent to setting the "zero" level for conventional gas analyzers. As a minimum, it is recommended that measurements of the humidity and particulates in the incoming air be taken at the start and end of each test run. Additional measurement points taken during the run are desirable if they can be practically obtained. It was felt that the presence of trace gases in the incoming air is not a significant problem. However, investigators should consider the ambient levels and influences of local air pollution for species of interest. Desired measurement locations depend upon the investigation requirements. A complete investigation of phenomenology of particulate formation and growth requires measurements at a number of locations both within the engine and in the exhaust field downstream of the nozzle exit plane. Desirable locations for both extractive and in situ measurements include: (1) Combustion Zone (Multiple axial locations); (2) Combustor Exit (Multiple radial locations for annular combustors); (3) Turbine Stage (Inlet and exit of the stage); (4) Exit Nozzle (Multiple axial locations downstream of the nozzle). Actual locations with potential for extractive or non-intrusive measurements depend upon the test article and test configuration. Committee members expressed the importance of making investigators aware of various ports that could allow access to various stages of the existing engines. Port locations are engine si)ecific and might allow extractive sampling or innovative hybrid optical-probe access. The turbine stage region was one the most desirable locations for obtaining samples and might be accessed through boroscope ports available in some engine designs. Discussions of probes and sampling systems quickly identified issues dependent on particular measurement quantities. With general consensus, the group recommends SAE procedures for measurements and data analyses of currently regulated exhaust species (CO2, CO, THC, NO(x),) using conventional gas sampling techniques. Special procedures following sound scientific practices must be developed as required for species and/or measurement conditions not covered by SAE standards. Several issues arose concerning short lived radicals and highly reactive species. For conventional sampling, there are concerns of perturbing the sample during extraction, line losses, line-wall reactions, and chemical reactions during the sample transport to the analyzers. Sample lines coated with quartz.or other materials should be investigated for minimization of such effects. The group advocates the development of innovative probe techniques and non-intrusive optical techniques for measurement of short lived radicals and highly reactive species that cannot be sampled accurately otherwise. Two innovative probe concepts were discussed. One concept uses specially designed probes to transfer optical beams to and from a region of flow inaccessible by traditional ports or windows. The probe can perturb the flow field but must have a negligible impact on the region to be optically sampled. Such probes are referred to as hybrid probes and are under development at AEDC for measurement in the high pressure, high temperature of a combustor under development for power generation. The other concept consists of coupling an instrument directly to the probe. The probe would isolate a representative sample stream, freeze chemical reactions and direct the sample into the analyzer portion of the probe. Thus, the measurement would be performed in situ without sample line losses due either to reactions or binding at the wall surfaces. This concept was used to develop a fast, in situ, time-of-flight mass spectrometer measurement system for temporal quantification of NO in the IMPULSE facility at AEDC. Additional work is required in this area to determine the best probe and sampling technique for each species measurement requirement identified by the Trace Chemistry Working Group. A partial list of Venues was used as a baseline for discussion. Additional venues were added to the list and the list was broken out into the following categories: (1)Engines (a) Sea Level Test Stands (b) Altitude Chambers; (2) Annular Combustor Test Stands, (3) Sector Flametube Test Stands, (4) Fundamentals Rigs/Experiments.

Pachlhofer, Peter↗

Predictive Data-driven Platform for Subsurface Energy Production

Subsurface energy activities such as unconventional resource recovery, enhanced geothermal energy systems, and geologic carbon storage require fast and reliable methods to account for complex, multiphysical processes in heterogeneous fractured and porous media. Although reservoir simulation is considered the industry standard for simulating these subsurface systems with injection and/or extraction operations, reservoir simulation requires spatio-temporal “Big Data” into the simulation model, which is typically a major challenge during model development and computational phase. In this work, we developed and applied various deep neural network-based approaches to (1) process multiscale image segmentation, (2) generate ensemble members of drainage networks, flow channels, and porous media using deep convolutional generative adversarial network, (3) construct multiple hybrid neural networks such as convolutional LSTM and convolutional neural network-LSTM to develop fast and accurate reduced order models for shale gas extraction, and (4) physics-informed neural network and deep Q-learning for flow and energy production. We hypothesized that physicsbased machine learning/deep learning can overcome the shortcomings of traditional machine learning methods where data-driven models have faltered beyond the data and physical conditions used for training and validation. We improved and developed novel approaches to demonstrate that physics-based ML can allow us to incorporate physical constraints (e.g., scientific domain knowledge) into ML framework. Outcomes of this project will be readily applicable for many energy and national security problems that are particularly defined by multiscale features and network systems.

58 GEOSCIENCES↗

CY2013 Annual Report for DOE-ITU INERI 2010-006-E

New concepts for nuclear energy development are considered in both the USA and Europe within the framework of the Generation-IV International Forum (GIF) as well as in various US-DOE programs (e.g. the Fuel Cycle Research and Development - FCRD) and as part of the European Sustainable Nuclear Energy Technology Platform (SNE-TP). Since most new fuel cycle concepts envisage the adoption of a closed nuclear fuel cycle employing fast reactors, the fuel behavior characteristics of the various proposed advanced fuel forms must be effectively investigated using state of the art experimental techniques before implementation. More rapid progress can be achieved if effective synergy with advanced (multi-scale) modeling efforts can be achieved. The fuel systems to be considered include minor actinide (MA) transmutation fuel types such as advanced MOX, advanced metal alloy, inert matrix fuel (IMF), and other ceramic fuels like nitrides, carbides, etc., for fast neutronic spectrum conditions. Most of the advanced fuel compounds have already been the object of past examination programs, which included irradiations in research reactors. The knowledge derived from previous experience constitutes a significant, albeit incomplete body of data. New or upgraded experimental tools are available today that can extend the scientific and technological knowledge towards achieving the objectives associated with the new generation of nuclear reactors and fuels. The objectives of this project will be three-fold: (1) to extend the available knowledge on properties and irradiation behavior of high burnup and minor actinide bearing advanced fuel systems; (2) to establish a synergy with multi-scale and code development efforts in which experimental data and expertise on the irradiation behavior of nuclear fuels is properly conveyed for the upgrade/development of advanced modeling tools; (3) to promote the effective use of international resources to the characterization of irradiated fuel through exchange of expertise and information among leading experimental facilities. The priorities in this project will be set according to the down selection procedure of U.S. and European development programs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Safety on Earth From MARSS

ENSCO, Inc., developed the Meteorological and Atmospheric Real-time Safety Support (MARSS) system for real-time assessment of meteorological data displays and toxic material spills. MARSS also provides mock scenarios to guide preparations for emergencies involving meteorological hazards and toxic substances. Developed under a Small Business Innovation Research (SBIR) contract with Kennedy Space Center, MARSS was designed to measure how safe NASA and Air Force range safety personnel are while performing weather sensitive operations around launch pads. The system augments a ground operations safety plan that limits certain work operations to very specific weather conditions. It also provides toxic hazard prediction models to assist safety managers in planning for and reacting to releases of hazardous materials. MARSS can be used in agricultural, industrial, and scientific applications that require weather forecasts and predictions of toxic smoke movement. MARSS is also designed to protect urban areas, seaports, rail facilities, and airports from airborne releases of hazardous chemical substances. The system can integrate with local facility protection units and provide instant threat detection and assessment data that is reportable for local and national distribution.

Source record↗

Biosatellite II mission

Biosatellite B was launched from Cape Kennedy, Florida, on a two-stage DELTA launch vehicle at 6:04 p.m. on 7 September, 1967. Approximately nine minutes later the 435 kg spacecraft biological laboratory was placed into a satisfactory 315 km near-circular earth orbit, successfully separated from the launch vehicle's second stage and was designated Biosatellite II. The scientific payload consisting of thirteen selected general biology and radiation experiments were subjected to planned, carefully controlled environmental conditions during 45 hours of earth-orbital flight. The decision was made to abbreviate the scheduled 3-day mission by approximately one day because of a threatening tropical storm in the recovery area, and a problem of communication with the spacecraft from the tracking stations. Highest priority was placed on recovery which was essential to obtain the scientific results on all the experiments. The operational phase of the mission came to a successful conclusion with the deorbit of the recovery capsule, deployment of the parachute system and air recovery by the United States Air Force. The 127 kg recovery capsule was returned to biology laboratories at Hickam Air Force Base, Hawaii, for disassembly and immediate inspection and analysis of the biological materials by the experimenters. It was evident immediately that the quality of the biology was excellent and this fact gave promise of a high return of scientific data. The environmental conditions provided to the experimental material in the spacecraft, provisions for experimental controls, and operational considerations are presented as they relate to interpretation of the experimental results.

Biosatellite 2 Project↗