C-SAPR2 CMAC 2.0 level c1 data.
C-SAPR2 data processed and corrected from the CACTI campaign, using CMAC2.0.
54 ENVIRONMENTAL SCIENCES↗
SEARCH · Engineering Papers
Results for “science data processing”
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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Improvements to the operational efficiency of the Portsmouth 'Blue Box' Assay system - 15162
The 'Blue Box' in Building 326 at Portsmouth comprises a dual cargo container lined with high density polyethylene with 5% (elemental) boron that acts as a neutron shield. This construction provides a low environmental neutron background to support the capability to attain low values of minimal detectable activity (MDA). A Non-destructive Assay (NDA) measurement platform known as the Fluor B and W Portsmouth Slab Counter (FBPSC) is housed inside the Blue Box. This comprises four neutron slab detectors supported with an electronic system supplying power and associated signal processing. The system is operated by a laptop computer which has data acquisition and analysis capabilities. Each slab contains five {sup 3}He proportional counters embedded in polyethylene. The system is designed to measure the mass of U-235 in coolers from the Portsmouth site using passive neutron counting. The system was calibrated by taking measurements with {sup 252}Cf sources attached to various positions on the outside surfaces of a surrogate cooler. In addition, Monte-Carlo N-Particle (MCNP) simulations were performed to extend the baseline calibration for coolers of various sizes used in the gaseous-diffusion process. The basic principle of operation is to measure the total neutron emission from the item and determine the mass of {sup 235}U using the system efficiency (determined from MCNP calculations combined with the calibration measurements) combined with known isotopic information ({sup 235}U enrichment and U-235/U-234 ratio), assumed chemical composition, and gross cooler mass. The FBPSC analysis program calculates the mass of U-235 within the cooler being assayed, together with the associated Total Measurement Uncertainty (TMU). A background correction is performed that accounts for the measured environmental background with a cosmic-ray spallation correction (based on the cooler's gross weight). The software suite developed for the system also includes the capability to track and trend measurement control data in order to quickly identify conditions where the system has drifted outside of its quality control envelope. The MDA of the system has been determined to be less the 15 g of U-235 for count times that are typically less than 5 minutes (depending on the uranium isotopics). This is primarily the result of the low neutron background rate inside the Blue Box (approximately 3 times lower than at nearby locations outside the box). Additionally, various software features have been designed to yield optimum counting performance for the system including count time adjustment and interval filtering to reject statistical outliers that are usually associated with cosmic spallation events. The operation of the system has proven to be very efficient, with the short measurement time providing a high throughput rate of coolers through the Blue Box NDA system. Significant operational benefits and improved data traceability have been yielded compared to the previous measurement process, which involved operators taking measurement with counter/scalers and manually entering data into spreadsheets. As of August 2014, this system successfully measured all coolers required to support completion of a contractually-required Performance Milestone. There are approximately 1900 coolers available for measurement. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
FPGA-based prototype of portable environmental radiation monitor
This new portable radiological environmental monitor consists of 2 main components, Gamma ionization chamber and a FPGA-based electronic enclosure linked to convivial software for treatment and analyzing. The HPIC ion chamber is the heart of this radiation measurement system and is running in range from 0 to 100 mR/h, so that the sensitivity at the output is 20 mV/μR/h, with a nearly flat energy response from 0,07 to 10 MEV. This paper presents a contribution for developing a new nuclear measurement data acquisition system based on Cyclone III FPGA Starter Kit ALTERA, and a user-friendly software to run real-time control and data processing. It was developed to substitute the older radiation monitor RSS-112 PIC installed in CNESTEN's Laboratory in order to improve some of its functionalities related to acquisition time and data memory capacity. As for the associated acquisition software, it was conceived under the virtual LabView platform from National Instrument, and offers a variety of system setup for radiation environmental monitoring. It gives choice to display both the statistical data and the dose rate. Statistical data shows a summary of current data, current time/date and dose integrator values, and the dose rate displays the current dose rate in large numbers for viewing from a distance as well as the date and time. The prototype version of this new instrument and its data processing software has been successfully tested and validated for viewing and monitoring the environmental radiation of Moroccan nuclear center. (authors)
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Heliophysics: The New Science of the Sun-Solar System Connection. Recommended Roadmap for Science and Technology 2005-2035
This is a Roadmap to understanding the environment of our Earth, from its life-sustaining Sun out past the frontiers of the solar system. A collection of spacecraft now patrols this space, revealing not a placid star and isolated planets, but an immense, dynamic, interconnected system within which our home planet is embedded and through which space explorers must journey. These spacecraft already form a great observatory with which the Heliophysics program can study the Sun, the heliosphere, the Earth, and other planetary environments as elements of a system--one that contains dynamic space weather and evolves in response to solar, planetary, and interstellar variability. NASA continually evolves the Heliophysics Great Observatory by adding new missions and instruments in order to answer the challenging questions confronting us now and in the future as humans explore the solar system. The three heliophysics science objectives: opening the frontier to space environment prediction; understanding the nature of our home in space, and safeguarding the journey of exploration, require sustained research programs that depend on combining new data, theory, analysis, simulation, and modeling. Our program pursues a deeper understanding of the fundamental physical processes that underlie the exotic phenomena of space.
Heliophysics↗
Fast Plasma Investigation for MMS: Simulation of the Burst Triggering System
The Magnetospheric Multiscale (MMS) mission will study small-scale reconnection structures and their rapid motions from closely spaced platforms using instruments capable of high angular, energy, and time resolution measurements. To meet these requirements, the Fast Plasma Instrument (FPI) consists of eight (8) identical half top-hat electron sensors and eight (8) identical ion sensors and an Instrument Data Processing Unit (IDPU). The sensors (electron or ion) are grouped into pairs whose 6 degree x 180 degree fields-of-view (FOV) are set 90 degrees apart. Each sensor is equipped with electrostatic aperture steering to allow the sensor to scan a 45 degree x 180 degree fan about the its nominal viewing (0 deflection) direction. Each pair of sensors, known as the Dual Electron Spectrometer (DES) and the Dual Ion Spectrometer (DIS), occupies a quadrant on the MMS spacecraft and the combination of the eight electron/ion sensors, employing aperture steering, image the full-sky every 30-ms (electrons) and 150-ms (ions), respectively. To probe the diffusion regions of reconnection, the highest temporal/spatial resolution mode of FPI results in the DES complement of a given spacecraft generating 6.5-Mb (raised dot) per second of electron data while the DIS generates 1.1-Mb (raised dot) per second of ion data yielding an FPI total data rate of 6.6-Mb (raised dot) per second. The FPI electron/ion data is collected by the IDPU then transmitted to the Central Data Instrument Processor (CIDP) on the spacecraft for science interest ranking. Only data sequences that contain the greatest amount of temporal/spatial structure will be intelligently down-linked by the spacecraft. This requires a data ranking process known as the burst trigger system. The burst trigger system uses pseudo physical quantities to approximate the local plasma environments. As each pseudo quantity will have a different value, a set of two scaling factors is employed for each pseudo term. These pseudo quantities are then combined at the instrument, spacecraft, and observatory level leading to a final ranking of data based on expected scientific interest. Here, we present simulations of the fixed point burst trigger system for the FPI. A variety of data sets based on previous mission data as well as analytical formulations are tested. Comparisons of floating point calculations versus the fixed point hardware simulation are shown. Analysis of the potential sources of error from overflows, quantization, etc. are examined and mitigation methods are presented. Finally a series of calibration curves are presented, showing the expected error in pseudo quantities based solely on the scale parameters chosen and the expected data range. We conclude with a presentation of the current base-lined FPI burst trigger approach.
Barrie, A. C.↗
Bayesian tomography and integrated data analysis in fusion diagnostics
In this article, a Bayesian tomography method using non-stationary Gaussian process for a prior has been introduced. The Bayesian formalism allows quantities which bear uncertainty to be expressed in the probabilistic form so that the uncertainty of a final solution can be fully resolved from the confidence interval of a posterior probability. Moreover, a consistency check of that solution can be performed by checking whether the misfits between predicted and measured data are reasonably within an assumed data error. In particular, the accuracy of reconstructions is significantly improved by using the non-stationary Gaussian process that can adapt to the varying smoothness of emission distribution. The implementation of this method to a soft X-ray diagnostics on HL-2A has been used to explore relevant physics in equilibrium and MHD instability modes. This project is carried out within a large size inference framework, aiming at an integrated analysis of heterogeneous diagnostics.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
An Integrated Platform for Mission Performance: Goddard Space Flight Center's Meta Information System
Successful management of NASA Goddard Space Flight Centers portfolio of mission projects (i.e. spacecraft, spacecraft instruments / subsystems, and ground systems) depends upon numerous processes, data and information resources coming together throughout the life-cycle of the projects to enable sound decision-making, risk reduction, conformance with requirements and continual improvement. In the summer of 2012, GSFC SMA management recognized that the set of legacy data systems used to support the SMA mission and responsibilities at GSFC were not effective, integrated nor on par with best practices. Accordingly, GSFC SMA management launched a project to transform the GSFC electronic management system to create and deploy an integrated, state-of-the-market information system for process performance, data management and analytics that is currently operating in support of GSFC overall mission performance. The information system, known as Meta, provides controlled, process-based applications, integrated data management, and analytics for a robust set of integrated applications. Since the inception of the project, a lean, award-winning SMA project team has thus far designed, configured and managed the system to serve as an integrated platform for 18 applications that support key processes for GSFC and the Science Mission Directorate at NASA headquarters, such as internal Management System assessments, Supplier Assessments, Supplier Research & Analysis, Problem Reporting for in-house mission projects, On-orbit Anomaly Reporting for GSFC-operated spacecraft, GSFC Project Life-Cycle Reviews, Risk Management and Reporting, and SMA Project Team Reporting. The system has experienced steady growth in utilization with 1,917 users (NASA employees and support contractor personnel) and 44 gigabytes of data and related files managed by the system as of the end of April 2018. Overall, Meta has achieved increasing levels of process management and real-time data / information integration to enable improved process performance, richer analytics and informed decision-making. This paper will present and examine the need, goals, approach and design driving the management and operation of the Meta information system and its ongoing growth as an integrated platform for advancing NASA mission performance.
Integration↗
Data systems and computer science: Neural networks base R/T program overview
The research base, in the U.S. and abroad, for the development of neural network technology is discussed. The technical objectives are to develop and demonstrate adaptive, neural information processing concepts. The leveraging of external funding is also discussed.
Gulati, Sandeep↗
The Atmospheric Channels of GLAS: Near Real-Time Global Lidar Remote Sensing of Clouds and Aerosols from Space
The Geoscience Laser Altimeter System (GLAS) will be placed into orbit in 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESat). From its nearly polar orbit (94 degree inclination), GLAS will provide continuous global measurements of the vertical distribution of clouds and aerosols while simultaneously providing high accuracy topographic profiling of surface features. During the mission, which is slated to last 3 to 5 years, the data collected by GLAS will be in near-real time to produce level 1 and 2 data products at the NASA GLAS Science Computing Facility (SCF) at Goddard Space Flight Center in Greenbelt, Maryland. The atmospheric products include cloud and aerosol layer heights, planetary boundary layer depth, polar stratospheric clouds and thin cloud and aerosol optical depth. These products will be made available to the science community within days of their creation. The processing algorithms must be robust, adaptive, efficient, and clever enough to run autonomously for the widely varying atmospheric conditions that will be encountered. This paper presents an overview of the GLAS atmospheric data products and briefly discusses the design of the processing algorithms.
Palm, Stephen P.↗
A comparison of Gaussian processes and neural networks for computer model emulation and calibration
The Department of Energy relies on complex physics simulations for prediction in domains like cosmology, nuclear theory, and materials science. These simulations are often extremely computationally intensive, with some requiring days or weeks for a single simulation. In order to assure their accuracy, these models are calibrated against observational data in order to estimate inputs and systematic biases. Because of their great computational complexity, this process typically requires the construction of an emulator, a fast approximation to the simulation. In this paper, two emulator approaches are compared: Gaussian process regression and neural networks. Their emulation accuracy and calibration performance on three real problems of Department of Energy interest is considered. On these problems, the Gaussian process emulator tends to be more accurate with narrower, but still well-calibrated uncertainty estimates. The neural network emulator is accurate, but tends to have large uncertainty on its predictions. Finally, as a result, calibration with the Gaussian process emulator produces more constrained posteriors that still perform well in prediction.
97 MATHEMATICS AND COMPUTING↗
Learning the solution operator of parametric partial differential equations with physics-informed DeepONets
Partial differential equations (PDEs) play a central role in the mathematical analysis and modeling of complex dynamic processes across all corners of science and engineering. Their solution often requires laborious analytical or computational tools, associated with a cost that is markedly amplified when different scenarios need to be investigated, for example, corresponding to different initial or boundary conditions, different inputs, etc. In this work, we introduce physics-informed DeepONets, a deep learning framework for learning the solution operator of arbitrary PDEs, even in the absence of any paired input-output training data. We illustrate the effectiveness of the proposed framework in rapidly predicting the solution of various types of parametric PDEs up to three orders of magnitude faster compared to conventional PDE solvers, setting a previously unexplored paradigm for modeling and simulation of nonlinear and nonequilibrium processes in science and engineering.
97 MATHEMATICS AND COMPUTING↗
Organic matter concentration and composition of experimentally burned open air and muffle furnace vegetation chars across differing burn severity and feedstock types from Pacific Northwest, USA (v4).
This dataset represents results from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and feedstock materials. The dataset provides both solid and dissolved phase bulk concentration and organic matter characterization data from experimentally generated chars. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. This data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), fourteen burn table videos, burn table video metadata and three folders containing (A) data; (B) metadata and protocols; and (C) photos. The folder names and the file name of the data package readme include a version number which will be updated with future iterations of this data package. The data folder includes (1) solid carbon and solid nitrogen; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) and total dissolved nitrogen (TN); (3) pH; (4) thermocouple time series temperature; (5) methods codes; (6) installation methods; (7) excitation emissions matrix (EEM) methods information; (8) a folder of excitation emissions matrix (EEM) fluorescence and absorbance spectra in dissolved organic matter and EEMs processing instructions; (9) solid state carbon-13 and solution state phosphorus nuclear magnetic resonance (13-C NMR and 31-P NMR) data and methods; (10) benzene polycarboxylic acid (BPCA) concentration and stable isotope data; (11) FTICR-MS methods; (12) Inductively coupled plasma (ICP) data for total calcium, magnesium, iron, aluminum, potassium, phosphorus, sodium, and sulfur along with sodium hydroxide-ethylenediaminetetraacetic acid (sodium hydroxide-EDTA) extractable calcium, magnesium, iron, aluminum, potassium, phosphorus, and sulfur; (13) a folder of phosphorus, carbon, and nitrogen X-ray absorption near edge structure (P-XANES, N-XANES, C-XANES) data for samples and standards; (14) P-XANES, N-XANES, C-XANES methods; (15) molybdate reactive phosphorus; and (16) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains .txt data files and a subfolder containing instruments for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. The metadata and protocols folder includes (1) international geo-sample number (IGSN) mapping file (2) burn and laboratory metadata; (3) burn protocol; (4) laboratory protocol; (5) vegetation collection metadata; and (6) vegetation collection protocol. The folder contains photos of the solid chars. All files are .csv, .txt, .pdf, .jpg, .jpeg, .R, .ref, or .mp4. The data package was originally published October 2022 (v1). It was updated April 2023 (v2; new data files), September 2023 (v3; new and corrected data files), and September 2024 (v4; new and added/updated files). Metadata files were also updated to reflect these changes. See the change history section in the readme for more details.
54 ENVIRONMENTAL SCIENCES↗
Progress on TRANSCEND Theme 1: Integrated Waste Management - 20194
The management of radioactive waste includes mobilisation, processing, packaging, storage, transport and final disposal. Research in the Integrated Waste Management theme of TRANSCEND focuses on underpinning science and engineering in areas of relevance to hazard reduction and decommissioning and the objectives are to: (1) develop new materials for effluent decontamination; (2) demonstrate predictive modelling of sludge/slurry removal, underpinned by experimental data; (3) transform understanding of radiation-driven processes in nuclear waste sludges; and (4) provide underpinning studies to develop innovative processes and wasteform materials. This paper gives overviews of the 16 research projects that will be done over the next 3 years in this theme. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Onboard Processing of Multispectral and Hyperspectral Data of Volcanic Activity for Future Earth-Orbiting and Planetary Missions
Autonomous onboard processing of data allows rapid response to detections of dynamic, changing processes. Software that can detect volcanic eruptions from thermal emission has been used to retask the Earth Observing 1 spacecraft to obtain additional data of the eruption. Rapid transmission of these data to the ground, and the automatic processing of the data to generated images, estimates of eruption parameters and maps of thermal structure, has allowed these products to be delivered rapidly to volcanologists to aid them in assessing eruption risk and hazard. Such applications will enhance science return from future Earth-orbiting spacecraft and also from spacecraft exploring the Solar System, or beyond, which hope to image dynamic processes. Especially in the latter case, long communication times between the spacecraft and Earth exclude a rapid response to what may be a transient process - only using onboard autonomy can the spacecraft react quickly to such an event.
Jupiter↗
Advances in interpretation of subsurface processes with time-lapse electrical imaging
Electrical geophysical methods, including electrical resistivity, time-domain induced polarization, and complex resistivity, have become commonly used to image the near subsurface. Here, we outline their utility for time-lapse imaging of hydrological, geochemical, and biogeochemical processes, focusing on new instrumentation, processing, and analysis techniques specific to monitoring. We review data collection procedures, parameters measured, and petrophysical relationships and then outline the state of the science with respect to inversion methodologies, including coupled inversion. We conclude by highlighting recent research focused on innovative applications of time-lapse imaging in hydrology, biology, ecology, and geochemistry, among other areas of interest.
COMPLEX CONDUCTIVITY↗
Towards physics-informed explainable machine learning and causal models for materials research
From emergent material descriptions to estimation of properties stemming from structures to optimization of process parameters for achieving best performance – all key facets of materials science and related fields have experienced tremendous growth with the introduction of data-driven models. This gradual progression goes at par with developments of machine learning workflows, from purely data-driven shallow models to those that are well-capable in encoding more complex graphs, symbolic representations, invariances, and positional embeddings. Furthermore, this perspective aims at summarizing strategic aspects of such transitions while providing insights into the requirements of bringing in explainable, interpretable predictive models, and causal learning to aid in materials design and discovery. Although the focus remains on a variety of functional materials by providing a handful of case studies, the applications of such integrated methodologies are universal to facilitate fundamental understandings of materials physics while enabling autonomous experiments.
36 MATERIALS SCIENCE↗
Advances in utilizing event based data structures for neutron scattering experiments
This article strives to expand on existing work to demonstrate advancements in data processing made available using event mode measurements. Most spallation neutron sources in the world have data acquisition systems that provide event recording. The new science that is enabled by utilizing event mode has only begun to be explored. In the past, these studies were difficult to perform because histograms forced dealing with either large chunks of time or a large number of files. With event based data collection, data can be explored and rebinned long after the measurement has completed. This article will review some of the principles of event data and how the method opens up new possibilities for in situ measurements, highlighting techniques that can be used to explore changes in the data. We also demonstrate the statistical basis for determining data quality and address the challenge of determining how long to measure mid-measurement. Lastly, we demonstrate a model independent method of grouping data via hierarchical clustering methods that can be used to improve calibration, reduction, and data exploration.
74 ATOMIC AND MOLECULAR PHYSICS↗
COLLABORATIVE RESEARCH: Study of Aerosol Sources and Processing at the GVAX Pantnagar Supersite
This project was part of a collaborative campaign, including the participation of scientists from seven research groups as part of the Winter Intensive Operating Period (January-February 2012) of the Clean Air for London (ClearfLo) campaign at a rural site in Detling, UK, 45 km southeast of central London to study wintertime sources of urban particulate matter. The UW contribution by PI Thornton’s group was to make the first deployment of a chemical ionization mass spectrometer instrument (MOVI-CI-ToFMS) to measure both particle and gas phase organic acids. The new instrument ran nearly continuously during the ClearfLo WINTER IOP at the Detling site, producing a first-ever data set of molecular composition information that can be used for source apportionment and process studies. The UW group published a paper in Environmental Science and Technology and contributed to another (Bohnenstengel et al BAMS 2015) detailing a direct molecular connection between biomass/biofuel burning particles and aerosol light absorption. The ES&T paper (Mohr, et al ES&T 2013) has received 42 citations in just 3 years indicative of its significant impact on the field. These measurements of urban and rural aerosol properties will contribute to improved modeling of regional aerosol emissions, and of atmospheric aging and removal.
54 ENVIRONMENTAL SCIENCES↗