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Experiment designs for collecting human factors engineering data on advanced space systems maintenance
SUMMARY An underground nuclear explosion (UNE) couples mechanical energy into crustal rock, which propagates as seismic and acoustic waves. These different physical phenomena transport, by different pathways, to standoff detectors at varying distances. The transport pathways attenuate the original signal but in different ways. Enabled by correct statistical weighting, signal attenuation models can be used to combine these disparate sensor data to estimate the yield of an UNE. Contemporaneous statistical models, used in yield estimation, can be improved with an advanced partition of error for these physical signal propagation models. We present an advanced multivariate approach to error modelling of multiphenomenology physical signatures. In addition to measurement error, our error model represents physical model biases as random with a physics-based covariance structure. To illustrate this proposed framework, we demonstrate the estimation of explosion yield using openly available seismic and acoustic data from chemical single-point explosions.
This is Volume 1, NASA Resources 1958-1968, of a multi-volume series providing a 20-year compilation of summary statistical and other data descriptive of NASA's programs in aeronautics and manned and unmanned spaceflight. This series is an important component of NASA published historical reference works, used by NASA personnel, managers, external researchers, and other government agencies.
Premise Recent advances in generating large‐scale phylogenies enable broad‐scale estimation of species diversification. These now common approaches typically are characterized by (1) incomplete species coverage without explicit sampling methodologies and/or (2) sparse backbone representation, and usually rely on presumed phylogenetic placements to account for species without molecular data. We used empirical examples to examine the effects of incomplete sampling on diversification estimation and provide constructive suggestions to ecologists and evolutionary biologists based on those results. Methods We used a supermatrix for rosids and one well‐sampled subclade (Cucurbitaceae) as empirical case studies. We compared results using these large phylogenies with those based on a previously inferred, smaller supermatrix and on a synthetic tree resource with complete taxonomic coverage. Finally, we simulated random and representative taxon sampling and explored the impact of sampling on three commonly used methods, both parametric (RPANDA and BAMM) and semiparametric (DR). Results We found that the impact of sampling on diversification estimates was idiosyncratic and often strong. Compared to full empirical sampling, representative and random sampling schemes either depressed or inflated speciation rates, depending on methods and sampling schemes. No method was entirely robust to poor sampling, but BAMM was least sensitive to moderate levels of missing taxa. Conclusions We suggest caution against uncritical modeling of missing taxa using taxonomic data for poorly sampled trees and in the use of summary backbone trees and other data sets with high representative bias, and we stress the importance of explicit sampling methodologies in macroevolutionary studies.
A brief summary is presented of user requirements for the Shuttle synthetic aperture radar (SAR) to be flown on a sortie mission of 7 to 10 days in duration, based on information collected from survey of the literature and direct user contacts. This information suggests selection of a dual frequency (L and X band) dual polarization SAR capable of meeting most user requirements. Particular attention is given to the SAR system specifications and the data handling capability expected to be available during the 1980s for the tracking and data relay satellite system (TDRSS). The data link requirements of the majority of Shuttle experiments will eventually determine whether the necessary high-capacity Shuttle-TDRSS return link will be part of the intrinsic Shuttle capability or will be part of the SAR payload.
In order to address the need for published data, considerable effort has gone into formalizing the process of data publication. From funding agencies to publishers, data publication has rapidly become a requirement. Digital Object Identifiers (DOI) and data citations have enhanced the integration and availability of data. The challenge facing data publishers now is to deal with the increased number of publishable data products and most importantly the difficulties of publishing diverse data products into an online archive. The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), a NASA-funded data center, faces these challenges as it deals with data products created by individual investigators. This paper summarizes the challenges of curating data and provides a summary of a workflow solution that ORNL DAAC researcher and technical staffs have created to deal with publication of the diverse data products. Finally, the workflow solution presented here is generic and can be applied to data from any scientific domain and data located at any data center.
This is Volume 2, Programs and Projects 1958-1968, of a multi-volume series providing a 20-year compilation of summary statistical and other data descriptive of NASA's programs in aeronautics and manned and unmanned spaceflight. This series is an important component of NASA published historical reference works, used by NASA personnel, managers, external researchers, and other government agencies.
This is Volume 3, Programs and Projects 1969-1978, of a multi-volume series providing a 20-year compilation of summary statistical and other data descriptive of NASA's programs in aeronautics and manned and unmanned spaceflight. This series is an important component of NASA published historical reference works, used by NASA personnel, managers, external researchers, and other government agencies.
The Strategic Defense Initiative Organization has created data centers for midcourse, plumes, and backgrounds phenomenologies. The Backgrounds Data Center (BDC) has been designated as the prime archive for data collected by SDIO programs. The BDC maintains a Summary Catalog that contains 'metadata,' that is, information about data, such as when the data were obtained, what the spectral range of the data is, and what region of the Earth or sky was observed. Queries to this catalog result in a listing of all data sets (from all experiments in the Summary Catalog) that satisfy the specified criteria. Thus, the user can identify different experiments that made similar observations and order them from the BDC for analysis. On-site users can use the Science Analysis Facility (SAFE for this purpose. For some programs, the BDC maintains a Program Catalog, which can classify data in as many ways as desired (rather than just by position, time, and spectral range as in the Summary Catalog). For example, data sets could be tagged with such diverse parameters as solar illumination angle, signal level, or the value of a particular spectral ratio, as long as these quantities can be read from the digital record or calculated from it by the ingest program. All unclassified catalogs and unclassified data will be remotely accessible.
Summary There has been substantial controversy concerning the role of geological carbon storage (GCS) in sequestering anthropogenic carbon emissions to mitigate climate change and global warming. Arguments center on the inability to monitor a geological storage site precisely and continuously, especially highlighting the associated costs and spatiotemporal trade-offs when using conventional subsurface monitoring techniques (well logs, core samples, chemical tracers, and 4D seismics). Active surveillance of GCS sites is essential for managing and mitigating potential leaks but is also required by regulation. With the goal of enhancing the monitoring capability at GCS sites, we present a rock physics-based joint data assimilation model to study a popular GCS site at Cranfield, Mississippi, USA. Synthetic continuous active-source seismic monitoring (CASSM) data (in the form of Vp and Qp measurements) and wellbore pressure monitoring data are assimilated with an ensemble of reservoir realizations to monitor gas saturation and reservoir pressure changes over a period of 100 years. Synthetic seismic attributes are generated using rock physics models (RPMs) and wellbore pressure monitoring data are extracted from the ground truth. Two assimilation methods, ensemble Kalman filter (EnKF) and ensemble Kalman smoother (EnKS), are tested in an observation system simulation experiment (OSSE) environment to assess the prediction accuracy of the individual and composite observation systems. The joint monitoring system achieves more accurate estimates of gas saturation and pressure, across the time span from start of injection to end of forecast, as compared to a single type of monitoring tool and irrespective of data assimilation algorithm choice. These results indicate that jointly assimilated data from two types of sensors (in this case, crosswell seismic and downhole pressure) may lead to a more risk-reducing monitoring design. One would expect that more data, vis-à-vis inclusion of a new sensor type, will improve the accuracy of any GCS monitoring system. However, from a practical standpoint, one important question is whether such a gain in accuracy is worth the additional cost associated with the new sensor. This paper focuses on quantifying the gain in accuracy, such that a practitioner can answer this question.
This is a summary of the constant-load, constant-temperature mechanical creep data that has been collected on PBX 9502 in tension and compression over the last 5+ years. This work was primarily funded by the Enhanced Surveillance Campaign (C-8).
This presentation contains a summary of ongoing work within the physics-based modeling and data analytics work package within the Nuclear Materials Discovery and Qualification initiative (NMDQi). Topics include work on MOOSE-based crystal plasticity, molecular dynamics modeling of recombination in metals and alloys, the MOOSE Stochastic Tools Module, and machine learning and atomistic modeling to predict thermo-kinetic properties of nuclear structural materials.
These data include a comprehensive summary of all residential and commercial buildings in the Las Vegas Assessors office dataset as it was on Feb 28th 2021. Building level data has been summarized to the US Census 2020 Block Group geographies.
Visual exploration of large multi-dimensional datasets has seen tremendous progress in recent years, allowing users to express rich data queries that produce informative visual summaries, all in real time. Techniques based on data cubes are some of the most promising approaches. However, these techniques usually require a large memory footprint for large datasets. To tackle this problem, we present NeuralCubes: neural networks that predict results for aggregate queries, similar to data cubes. NeuralCubes learns a function that takes as input a given query, for instance, a geographic region and temporal interval, and outputs the result of the query. The learned function serves as a real-time, low-memory approximator for aggregation queries. Our models are small enough to be sent to the client side (e.g. the web browser for a web-based application) for evaluation, enabling data exploration of large datasets without database/network connection. Here, we demonstrate the effectiveness of NeuralCubes through extensive experiments on a variety of datasets and discuss how NeuralCubes opens up opportunities for new types of visualization and interaction.
The TIROS IV Meteorological Satellite contains a medium resolution scanning radiometer. Two of the channels of this instrument are sensitive to reflected solar radiation and the remaining two respond to emitted thermal radiation from the earth and its atmosphere. The two thermal channels are calibrated in terms of equivalent blackbody temperatures, and the reflected solar radiation channels in terms of effective radiant emittances. The calibration data, along with orbital and attitude data and the radiation data from the satellite, were incorporated in a computer program for an IBM 7090 which was used to produce, in binary form, the "Final Meteorological Radiation Tape" which is the basic repository of all radiation data. After launch, the radiometer displaye d the same degradation of response characteristics as did its predecessors in TIROS II and TIROS III. The onset of degradation results in a departure of the data from the prelaunch laboratory calibration. The cause of degradation has not been determined, and the matter is still being studied at the Goddard Space Flight Center. Before work with the TIROS IV radiation data is attempted, an understanding of the radiometer, its calibration, and the problems encountered in the experiment, especially from response degradation, is essential. The instrumentation design, development work, and the calibrations herein described were performed by the Goddard Space Flight Center Staff, whereas the computer and programming efforts were carried out jointly by the staffs of the National Weather Satellite Center, U. S. Weather Bureau, and the Goddard Space Flight Center. In this Catalog-Manual, the radiometer an d its calibration, data processing, the "Final Meteorological Radiation Tape", the observed degradation patterns, and possible corrections for degradation are discussed. The Catalog-Manual also includes, in two forms, documentation of each orbit of successfully reduced radiation data acquired by TIROS IV. One method of presentation is the Index of Final Meteorological Radiation Tapes and the other is a Subpoint Track, Summary of Available Radiation Data in diagrammatic form.
The use of the Aerospace Price Book, a cost index, and conceptual cost estimating for cost-effective design and construction of space facilities is discussed. The price book consists of over 200 commonly used conceptual elements and 100 systems summaries of projects such as launch pads, processing facilities, and air locks. The cost index is composed of three divisions: (1) bid summaries of major Shuttle projects, (2) budget cost data sheets, and (3) cost management summaries; each of these divisions is described. Conceptual estimates of facilities and ground support equipment are required to provide the most probable project cost for budget, funding, and project approval purposes. Similar buildings, systems, and elements already designed are located in the cost index in order to make the best rough order of magnitude conceptual estimates for development of Space Shuttle facilities. An example displaying the applicability of the conceptual cost estimating procedure for the development of the KSC facilities is presented.
Abstract The Soybean Free Air Concentration Enrichment (SoyFACE) facility is the longest running open-air carbon dioxide and ozone enrichment facility in the world. For over two decades, soybean, maize, and other crops have been exposed to the elevated carbon dioxide and ozone concentrations anticipated for late this century. The facility, located in East Central Illinois, USA, exposes crops to different atmospheric concentrations in replicated octagonal ~280 m 2 Free Air Concentration Enrichment (FACE) treatment plots. Each FACE plot is paired with an untreated control (ambient) plot. The experiment provides important ground truth data for predicting future crop productivity. Fumigation data from SoyFACE were collected every four seconds throughout each growing season for over two decades. Here, we organize, quality control, and collate 20 years of data to facilitate trend analysis and crop modeling efforts. This paper provides the rationale for and a description of the SoyFACE experiments, along with a summary of the fumigation data and collation process, weather and ambient data collection procedures, and explanations of air pollution metrics and calculations.
Not provided.