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At least 1,477 records · Page 82

A model to assess Zircaloy’s mechanical property changes following a transient beyond critical heat flux

Maintaining the integrity of nuclear fuel rods is essential for ensuring public health and safety in nuclear power generation. During reactor operation, this integrity is confirmed by demonstrating compliance with established regulatory acceptance criteria. For moderate-frequency events, such as limiting transients and anticipated operational occurrences (AOOs), the current fuel integrity criterion is based on preventing boiling transition. This criterion assumes that prevention of boiling transition will prevent excessive cladding heating and, thus, fuel failure during normal operations. While conservative, this approach places significant constraints on core design, fuel cycle economics, and a plant’s ability to perform major power uprates, leading to suboptimal fuel utilization and inefficient carbon-free energy production. A more efficient approach could be achieved by revising the failure criterion to a material-specific limit rather than strictly preventing the boiling transition, since boiling transition per se is not a cause of fuel cladding failure. Here, as a result, a new licensing framework based on material properties, termed time-at-temperature (t@T), is needed. This approach would allow for brief periods of post–critical heat flux operation during an AOO without compromising safety. Implementing the t@T licensing strategy requires a robust technical foundation in material properties, which must be established through comprehensive data collection on both unirradiated and irradiated fuel and cladding materials. This foundation would enable the development of a safety basis that ensures safe operation while providing greater flexibility and efficiency for reactor operation. This paper documents a thorough review of the available data to establish a baseline knowledge that can inform the development of cladding mechanical models, as well as identify experimental data gaps that need to be addressed in future research. Machine learning and data informatics were utilized to extract the importance of parameters on the t@T parameter. Industry tools were used to perform baseline analyses to define the relevant transient conditions for data analysis. The subsequent review successfully identified applicable experimental data, as well as sufficient data to evaluate changes in cladding mechanical properties following an AOO transient. Rather than developing new models, this work coupled existing irradiation annealing and recrystallization models to calculate changes in hardness, yield stress, and ultimate tensile stress following an AOO event. The findings from this review were summarized to highlight the experimental data needs required to fill remaining gaps and support the development of future t@T licensing methodologies.

Cladding performance↗

Sequential Inference of Hospitalization Electronic Health Records Using Probabilistic Models

In the dynamic hospital setting, decision support can be a valuable tool for improving patient outcomes. Data-driven inference of future outcomes is challenging in this dynamic setting, where long sequences such as laboratory tests and medications are updated frequently. This is due in part to heterogeneity of data types and mixed-sequence types contained in variable length sequences. In this work we design a probabilistic unsupervised model for multiple arbitrary-length sequences contained in hospitalization Electronic Health Record (EHR) data. The model uses a latent variable structure and captures complex relationships between medications, diagnoses, laboratory tests, neurological assessments, and medications. It can be trained on original data, without requiring any lossy transformations or time binning. Inference algorithms are derived that use partial data to infer properties of the complete sequences, including their length and presence of specific values. We train this model on data from subjects receiving medical care in the Kaiser Permanente Northern California integrated healthcare delivery system. The results are evaluated against held-out data for predicting the length of sequences and presence of Intensive Care Unit (ICU) in hospitalization bed sequences. Our method outperforms a baseline approach, showing that in these experiments the trained model captures information in the sequences that is informative of their future values.

97 MATHEMATICS AND COMPUTING↗

Terrestrial bodies orbiter, LUNAR - A system for detailed global measurements of a planet's properties

The NASA Lunar Polar Orbiter, to be launched by a Delta vehicle in 1980, is designed to perform a global exploration of such moon properties as the gravity field, figure, and surface composition, as well as a lunar resource survey. The paper reviews the mission, spacecraft, and data system concepts in terms of baseline mission sequence, choice of orbits, spacecraft configuration requirements, mission sequence requirements and data system and operations. Scientific experiments planned for the Orbiter mission include geophysical altimetry and gravity experiments, heat flow experiment, magnetic field experiments, measurements of the moon's natural gamma-ray spectrum, X-ray fluorescence of lunar surface materials, sunlight reflectance spectroscopy, and spectro-stereo imaging. Characteristics of instruments designed for use in these investigations are examined. Through the use of advanced sensors and data-system techniques, coupled with well-developed spacecraft systems, the mission promises to return a very large quantity and variety of lunar data at a cost comparable with that of simpler missions in the past.

Burke, J. D.↗

Insolation data for solar energy conversion derived from satellite measurements of earth radiance

Detailed knowledge of the irradiance of the sun at ground locations is essential for the design and evaluation of solar energy conversion systems. The primary source of such data is the global network of weather stations. Such stations are often too far apart and for most locations the data available are only daily total irradiance or monthly averages. Solar energy conversion programs require insolation data with considerably higher geographical and temporal resolution. Meteorological satellites gather routinely extensive data on the energy reflected and scattered into space by the earth-atmosphere system. A program has been initiated to use such data for deriving ground insolation for energy conversion. Some of the preliminary results of this program will be discussed.

Thekaekara, M. P.↗

Responsibilities and practical limitations in the operation of an astronomical data center

The operation of an astronomical data center requires that many decisions be made concerning the handling of the astronomical catalogs and data distributed. Should a data center be, as Wilkins (1977) described it, passive, in that catalogs and data are collected and distributed blackbox-wise upon request, or should a data center be active and have experts in various fields to scrutinize, correct, reformat, and document data where necessary. These questions will be addressed and illustrated by describing the current operations and future goals of the Astronomical Data Center at NASA/GSFC.

Warren, W. H., Jr.↗

High spectral resolution remote sensing of the land

Spectral remote sensing has been practiced on a large scale since the launch of Landsat 1 in 1972. The limited information contained in this spectrally undersampled data set has led to the development of sophisticated statistical-inferential methods for data analysis. The results are usually limited by the availability of ground truth information. Recent technological developments have made it feasible to create narrow-band, contiguous, spectral image data sets that make possible the identification of surface cover materials based on the complete reflectance spectrum for each picture element. This capability will revolutionize the use of remote sensing data and require new deterministic image processing techniques to extract the full information content from the data. Sensors, based on the concept of imaging spectrometry and the new technology of area array infrared detectors, have been constructed and are candidates for Shuttle and space platform flights.

Goetz, A. F. H.↗

The application of connectionism to query planning/scheduling in intelligent user interfaces

In the mid nineties, the Earth Observing System (EOS) will generate an estimated 10 terabytes of data per day. This enormous amount of data will require the use of sophisticated technologies from real time distributed Artificial Intelligence (AI) and data management. Without regard to the overall problems in distributed AI, efficient models were developed for doing query planning and/or scheduling in intelligent user interfaces that reside in a network environment. Before intelligent query/planning can be done, a model for real time AI planning and/or scheduling must be developed. As Connectionist Models (CM) have shown promise in increasing run times, a connectionist approach to AI planning and/or scheduling is proposed. The solution involves merging a CM rule based system to a general spreading activation model for the generation and selection of plans. The system was implemented in the Rochester Connectionist Simulator and runs on a Sun 3/260.

Short, Nicholas, Jr.↗

High rate information systems - Architectural trends in support of the interdisciplinary investigator

Data systems requirements in the Earth Observing System (EOS) Space Station Freedom (SSF) eras indicate increasing data volume, increased discipline interplay, higher complexity and broader data integration and interpretation. A response to the needs of the interdisciplinary investigator is proposed, considering the increasing complexity and rising costs of scientific investigation. The EOS Data Information System, conceived to be a widely distributed system with reliable communication links between central processing and the science user community, is described. Details are provided on information architecture, system models, intelligent data management of large complex databases, and standards for archiving ancillary data, using a research library, a laboratory and collaboration services.

Handley, Thomas H., Jr.↗

LV software support for supersonic flow analysis

The software for configuring a Laser Velocimeter (LV) counter processor system was developed using structured design. The LV system includes up to three counter processors and a rotary encoder. The software for configuring and testing the LV system was developed, tested, and included in an overall software package for data acquisition, analysis, and reduction. Error handling routines respond to both operator and instrument errors which often arise in the course of measuring complex, high-speed flows. The use of networking capabilities greatly facilitates the software development process by allowing software development and testing from a remote site. In addition, high-speed transfers allow graphics files or commands to provide viewing of the data from a remote site. Further advances in data analysis require corresponding advances in procedures for statistical and time series analysis of nonuniformly sampled data.

Bell, William A.↗

LV software support for supersonic flow analysis

The software for configuring an LV counter processor system has been developed using structured design. The LV system includes up to three counter processors and a rotary encoder. The software for configuring and testing the LV system has been developed, tested, and included in an overall software package for data acquisition, analysis, and reduction. Error handling routines respond to both operator and instrument errors which often arise in the course of measuring complex, high-speed flows. The use of networking capabilities greatly facilitates the software development process by allowing software development and testing from a remote site. In addition, high-speed transfers allow graphics files or commands to provide viewing of the data from a remote site. Further advances in data analysis require corresponding advances in procedures for statistical and time series analysis of nonuniformly sampled data.

Bell, W. A.↗

A comparison of spectral decorrelation techniques and performance evaluation metrics for a wavelet-based, multispectral data compression algorithm

Future space-based, remote sensing systems will have data transmission requirements that exceed available downlinks necessitating the use of lossy compression techniques for multispectral data. In this paper, we describe several algorithms for lossy compression of multispectral data which combine spectral decorrelation techniques with an adaptive, wavelet-based, image compression algorithm to exploit both spectral and spatial correlation. We compare the performance of several different spectral decorrelation techniques including wavelet transformation in the spectral dimension. The performance of each technique is evaluated at compression ratios ranging from 4:1 to 16:1. Performance measures used are visual examination, conventional distortion measures, and multispectral classification results. We also introduce a family of distortion metrics that are designed to quantify and predict the effect of compression artifacts on multi spectral classification of the reconstructed data.

Matic, Roy M.↗

Preliminary design for Arctic atmospheric radiative transfer experiments

If current plans are realized, within the next few years, an extraordinary set of coordinated research efforts focusing on energy flows in the Arctic will be implemented. All are motivated by the prospect of global climate change. SHEBA (Surface Energy Budget of the Arctic Ocean), led by the National Science Foundation (NSF) and the Office of Naval Research (ONR), involves instrumenting an ice camp in the perennial Arctic ice pack, and taking data for 12-18 months. The ARM (Atmospheric Radiation Measurement) North Slope of Alaska and Adjacent Arctic Ocean (NSA/AAO) Cloud and Radiation Testbed (CART) focuses on atmospheric radiative transport, especially in the presence of clouds. The NSA/AAO CART involves instrumenting a sizeable area on the North Slope of Alaska and adjacent waters in the vicinity of Barrow, and acquiring data over a period of about 10 years. FIRE (First ISCCP (International Satellite Cloud Climatology Program) Regional Experiment) Phase 3 is a program led by the National Aeronautics and Space Administration (NASA) which focuses on Arctic clouds, and which is coordinated with SHEBA and ARM. FIRE has historically emphasized data from airborne and satellite platforms. All three program anticipate initiating Arctic data acquisition during spring, 1997. In light of his historic opportunity, the authors discuss a strawman atmospheric radiative transfer experimental plan that identifies which features of the radiative transport models they think should be tested, what experimental data are required for each type of test, the platforms and instrumentation necessary to acquire those data, and in general terms, how the experiments could be conducted. Aspects of the plan are applicable to all three programs.

Zak, B. D.↗

Evaluation of MODIS Albedo Product (MCD43A) over Grassland, Agriculture and Forest Surface Types During Dormant and Snow-Covered Periods

This study assesses the Moderate-resolution Imaging Spectroradiometer (MODIS) BRDF/albedo 8 day standard product and products from the daily Direct Broadcast BRDF/albedo algorithm, and shows that these products agree well with ground-based albedo measurements during the more difficult periods of vegetation dormancy and snow cover. Cropland, grassland, deciduous and coniferous forests are considered. Using an integrated validation strategy, analyses of the representativeness of the surface heterogeneity under both dormant and snow-covered situations are performed to decide whether direct comparisons between ground measurements and 500-m satellite observations can be made or whether finer spatial resolution airborne or spaceborne data are required to scale the results at each location. Landsat Enhanced Thematic Mapper Plus (ETM +) data are used to generate finer scale representations of albedo at each location to fully link ground data with satellite data. In general, results indicate the root mean square errors (RMSEs) are less than 0.030 over spatially representative sites of agriculture/grassland during the dormant periods and less than 0.050 during the snow-covered periods for MCD43A albedo products. For forest, the RMSEs are less than 0.020 during the dormant period and 0.025 during the snow-covered periods. However, a daily retrieval strategy is necessary to capture ephemeral snow events or rapidly changing situations such as the spring snow melt.

MODIS↗

NNREPAIR: Constraint-based Repair of Neural Network Classifiers

We present NNREPAIR, a constraint-based technique for repairing neural network classifiers by i) fixing the logic of the network at an intermediate layer, and ii) fixing the decision conditions of the network at the last layer. NNREPAIR first uses fault localization to find potentially faulty network parameters (specifically weights) and then performs repair using constraint solving to apply small modifications to remedy the defects. We present novel strategies to enable precise yet efficient repair such as inferring correctness specifications to act as oracles for intermediate layer repair, and generation of experts wrt each class. We demonstrate the technique in the context of three different scenarios: (1) Improving the over all accuracy of a model, (2) Fixing security vulnerabilities caused by poisoning of training data and (3) Improving the robustness of the network against adversarial attacks. Our evaluation on MNIST and CIFAR-10 models shows that NNREPAIR can improve the accuracy by 45.56% on poisoned data and 11.11% on adversarial data. NNREPAIR also provides improvement, albeit modest, in the overall accuracy of models, without requiring new data or re-training.

Repair↗

Extreme Weather Events and PV Systems Impact

The impact of extreme weather events on PV performance was studied by comparing the National Oceanic and Atmospheric Administration database on severe weather with the National Renewable Energy Laboratory's (NREL) PV Fleet database on continuous PV performance. We identified 170 systems that were immediately impacted by weather events. These severe weather events lead to a median loss of only 1 % of annual production. However, flooding and high wind events were found to have an extremely long tail extending to 60 % loss, showing that these discrete events can pose a substantial risk to PV systems. Besides the short-term impact of lost production due to outages, we also found a statistically significant increased performance loss rate (PLR) for high wind events above 90 kilometer/hour, by comparing PLR before and after these events. Similarly, hail events caused higher PLR for hail sizes of and above 25 mm indicating that more stringent hail testing for PV modules is required. In addition, very high snow loads may also cause increased PLRs, but more data are required to better quantify the impact. These findings illustrate the substantial risk extreme weather events pose short-and long-term to fielded PV installations.

extreme weather↗

A prediction model of the depth-of-discharge effect on the cycle life of a storage cell

Cycle life requirements are very high for batteries used in aerospace applications in low Earth orbit. The data base required to establish confidence in a particular cell design is thus both extensive and expensive. Reliable accelerated cycle life testing and performance decay modeling represent attractive alternatives to real-time tests of cycle life. In light of certain long-term cycle life test results, this paper examines a very simple performance decay model developed earlier. Application of that model to available data demonstrates a rigid relationship between a battery's expected cycle life and the depth of discharge of cycling. Further, modeling analysis of the data suggests that a significantly improved cycle life can be obtained with advanced components, materials, and designs; and that cycle life can be reliably predicted from the results of accelerated testing.

Thaller, Lawrence H.↗

A prediction model of the depth-of-discharge effect on the cycle life of a storge cell

Cycle life requirements are very high for batteries used in aerospace applications in low earth orbit. The data base required to establish confidence in a particular cell design is thus both extensive and expensive. Reliable accelerated cycle life testing and performance decay modeling represent attractive alternatives to real-time tests of cycle life. In light of certain long-term cycle life test results, this paper examines a very simple performance decay model developed earlier. Application of that model to available data demonstrates a rigid relationship between a battery's expected cycle life and the depth of discharge of cycling. Further, modeling analysis of the data suggests that a significantly improved cycle life can be obtained with advanced components, materials, and designs; and that cycle life can be reliably predicted from the results of accelerated testing.

Thaller, Lawrence H.↗

Earth resources data acquisition sensor study

The minimum data collection and data processing requirements are investigated for the development of water monitoring systems, which disregard redundant and irrelevant data and process only those data predictive of the onset of significant pollution events. Two approaches are immediately suggested: (1) adaptation of a presently available ambient air monitoring system developed by TVA, and (2) consideration of an air, water, and radiological monitoring system developed by the Georgia Tech Experiment Station. In order to apply monitoring systems, threshold values and maximum allowable rates of change of critical parameters such as dissolved oxygen and temperature are required.

Grohse, E. W.↗