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At least 1,459 records · Page 81

Sequence Polishing Library (SPL) v10.0

The Sequence Polishing Library (SPL) is a suite of software tools in order to automate "Design for Synthesis and Assembly" workflows. Specifically: The SPL "Converter" tool converts files among the following sequence data exchange formats: CSV, FASTA, GenBank, and Synthetic Biology Open Language (SBOL); The SPL "Juggler" tool optimizes the codon usages of DNA coding sequences according to an optimization strategy, a user-specific codon usage table and genetic code. In addition, the SPL "Juggler" can translate amino acid sequences into DNA sequences.:The SPL "Polisher" verifies NA sequences against DNA synthesis constraints, such as GC content, repeating k-mers, and restriction sites. In case of violations, the "Polisher" reports the violations in a comprehensive manner. The "Polisher" tool can also modify the violating regions according to an optimization strategy, a user-specific codon usage table and genetic code;The SPL "Partitioner" decomposes large DNA sequences into smaller building blocks with partial overlaps that enable an efficient assembly. The "Partitioner" enables the user to configure the characteristics of the overlaps, which are mostly determined by the utilized assembly protocol, such as length, GC content, or melting temperature.

Oberortner, Ernst↗

Distributing Data from Desktop to Hand-Held Computers

A system of server and client software formats and redistributes data from commercially available desktop to commercially available hand-held computers via both wired and wireless networks. This software is an inexpensive means of enabling engineers and technicians to gain access to current sensor data while working in locations in which such data would otherwise be inaccessible. The sensor data are first gathered by a data-acquisition server computer, then transmitted via a wired network to a data-distribution computer that executes the server portion of the present software. Data in all sensor channels -- both raw sensor outputs in millivolt units and results of conversion to engineering units -- are made available for distribution. Selected subsets of the data are transmitted to each hand-held computer via the wired and then a wireless network. The selection of the subsets and the choice of the sequences and formats for displaying the data is made by means of a user interface generated by the client portion of the software. The data displayed on the screens of hand-held units can be updated at rates from 1 to

Elmore, Jason L.↗

Potosi Reservoir Modeling; History and Recommendations

As a part of a larger project co-funded by the United States Department of Energy (US DOE) to evaluate the potential of formations within the Cambro-Ordovician strata above the Mt. Simon as potential targets for carbon sequestration in the Illinois and Michigan Basins, the Illinois Clean Coal Institute (ICCI) requested Schlumberger to evaluate the potential injectivity and carbon dioxide (CO₂) plume size of the Cambrian Potosi Formation. The evaluation of this formation was accomplished using wireline data, core data, pressure data, and seismic data from two projects: the US DOE-funded Illinois Basin–Decatur Project being conducted by the Midwest Geological Sequestration Consortium in Macon County, Illinois, as well as data from the Illinois – Industrial Carbon Capture and Sequestration (IL-ICCS) project funded through the American Recovery and Reinvestment Act. In 2010, technical performance evaluations on the Cambrian Potosi Formation were performed through reservoir modeling. The data included formation tops from mud logs, well logs from the Verification Well 1 (VW1) and the Injection Well (CCS1), structural and stratigraphic formation from three dimensional (3D) seismic data, and field data from several waste water injection wells for the Potosi Formation. The intention was for two million tonnes per annum (MTPA) of CO₂ to be injected for 20 years into the Potosi Formation. In 2013, updated reservoir models for the Cambrian Potosi Formation were evaluated. The data included formation tops from mud logs, well logs from the CCS1, VW1, and Verification Well 2 (VW2) wells, structural and stratigraphic formation from a larger 3D seismic survey, and field data from several waste water injection wells for Potosi Formation. The objective is to simulate the injection of CO₂ at a rate 3.5 million tons per annum (3.2 million tonnes per annum [MTPA]) for 30 years 106 million tons (96 MT total) into the Potosi Formation. The Potosi geomodeling efforts have evolved from using data from a single well in 2010 to the inclusion of data from three wells in 2013 which largely leverage the porosity and permeability logs plus knowledge of lost circulation zones. The first Potosi model (Potosi Geobody Model 2010) attempted to use the available seismic inversion data to inform the geomodel and predict vugular zones in advance of drilling VW1. Lost circulation zones in VW1 came in as the geologists predicted. The model was not implemented in subsequent simulation work. To date, reservoir models used for flow simulation work have relied predominately on Gaussian distributed properties (porosity and permeability) and have employed a single injection well. Potosi Model 2013b incorporated the new VW2 logs, and exhibited an extra level of sophistication by delineating the vugular intervals. This method added further realism that likely represents the best reservoir approximation to date. Where the 2010 reservoir models were 10 by 10 mi (16 by 16 km) in area, the 2013 models were expanded in size to 30 by 30 mi (48 by 48 km). The latest reservoir simulations show that a minimum of four injectors might be required to meet target injection rates. Still, there is data that requires further scrutiny and modeling methodologies that require testing for the Potosi Formation. This work is currently ongoing, and the next phase of the reservoir modeling intends to implement valuable data like porosity derived from seismic inversion, seismically derived geobodies, or a combination of both to further define vugular zones and the porosity distribution within the Potosi Formation. Understanding the dual porosity, dual permeability character of the Potosi remains the greatest challenge in representing this formation. Further analysis of the FMI* fullbore formation microimager data may aid in assessing this uncertainty. The Potosi Formation is indeed an interesting formation, and recommendations to further characterize it are included in the following list: - Data acquisition to identify the vugs permeability, distribution, and interconnectivity could be considered to perform a more rigorous evaluation of the Potosi Formation injectivity and capacity. This could be achieved by performing an injection test on a vugular interval to determine the vugs permeability, and an interference test between wells to evaluate the local vugs extent and interconnectivity. - A thorough study of the available FMI data may reveal specifics on estimating the vug to matrix ratio. This estimate could be used to further condition the porosity distribution. Porosity logs alone might underestimate the formation’s porosity associated with vugs. Porosity mapping derived from the seismic inversion could also be used in the succeeding task to characterize the lateral porosity distribution within the reservoir. This could involve the geobody methodology previously attempted in 2010. With or without seismic inversion porosity mapping, it is worth exploring whether increased lateral heterogeneity plays a significant role in Potosi injectivity. Investigations on vugular, dolomitic outcrops suggest that there may be significantly greater lateral heterogeneity than what has been modeled here. - The FMI data also reveals the presence of and helps describe open fractures. The presence of fractures will further enhance the formation’s permeability. The task of leveraging this data in the geomodeling effort still remains. Under the best of circumstances, this data describing open fractures may be combined with seismic attributes to delineate fracture corridors. Fracture modeling would certainly add another layer of sophistication to the model. Its contribution and applicability remain to be explored. - Facies modeling within the Potosi has yet to be thoroughly addressed. The carbonates during the time of deposition are believed to be regionally extensive. However, it may be worth delineating the reservoir with other regional wells or modern day analogues to understand the extent of the Potosi. More specifically, the model could incorporate lateral changes or trends if deemed necessary to represent facies transition. - Currently there is no fracture gradient data available for the Potosi in the Decatur project area. The acquisition of the fracture pressure data could be considered to determine an appropriate maximum allowable bottomhole injection pressure. This would allow the evaluation of injectivity and the required number of wells in a more precise manner. - Special core analysis (SCAL) to determine the relative permeability and capillary pressure of the vugs and matrix could be considered to have a better estimation of the reservoir injectivity and plume extent. - Formation water sampling and analysis could be considered for the Potosi to estimate the water salinity and properties. A vertical flow performance evaluation could be considered for the succeeding task to determine the appropriate tubing size, the required injection tubing head pressure, and to investigate whether the corresponding well injection rate falls within the tubing erosional velocity limit. - A simulation using several injectors could also be considered to determine the required number of wells to achieve the injection target while taking into account the pressure interference.

Smith, Valerie↗

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗

WHOLESCALE: Seismic Survey Metadata from San Emidio Nevada 2021

This is a collection of metadata from the 2021 seismic survey at the San Emidio geothermal field in Nevada. In April and May 2021, 37 tri-axial short period seismographs were deployed in a 1.8km diameter cluster centered on 40.367278 deg N, 119.409019 deg W. The first data record started at 2021-04-06T07:09:10Z UTC and the last record ended 2021-05-11T02:58:52Z UTC. The 37 stations included 29 SmartSolo IGU-16HR 3C all-in-one 5 Hz seismographs and 8 DataCube seismographs with 4.5 Hz HGS HG-6(B coil) tri-axial geophones. The raw format (level 0) data includes 353 GB of 500 sps SmartSolo data in native DLD format, 113 GB of 400 sps DataCube data in native DataCube format, and 3.4 GB of GPS data collected during the RTK GPS survey. The SAC data (level 1) files include 564 GB of hourly SAC files. The experiment was designed to monitor seismic activity before, during, and after the planned three-day plant maintenance shutdown April 19-21, 2021. The pumping stopped at 2021/04/19 12:51:45 UTC and resumed about 2021/04/21 21:00:00 UTC. The raw and processed data are in an associated GDR submission, linked below. The metadata here includes files containing experiment details, station locations, seismic data logger specifications, instrumentation specifications, and descriptions of data. Also included are data and metadata from a 2016 seismic survey at the same site.

15 GEOTHERMAL ENERGY↗

WHOLESCALE: Seismic Survey Data from San Emidio Nevada 2021

This dataset includes raw and processed seismic data from the 2021 seismic survey at the San Emidio geothermal field in Nevada. In April and May 2021, 37 tri-axial short period seismographs were deployed in a 1.8km diameter cluster centered on 40.367278 N, 119.409019 W. The first data record started at 2021-04-06T07:09:10Z UTC and the last record ended at 2021-05-11T02:58:52Z UTC. The 37 stations included 29 SmartSolo IGU-16HR 3C all-in-one 5 Hz seismographs and 8 DataCube seismographs with 4.5 Hz HGS HG-6(B coil) tri-axial geophones. The raw format (level 0) data includes 353 GB of 500 sps SmartSolo data in native DLD format, 113 GB of 400 sps DataCube data in native DataCube format, and 3.4 GB of GPS data collected during the RTK GPS survey. The SAC data (level 1) files include 564 GB of hourly SAC files. The experiment was designed to monitor seismic activity before, during, and after the planned three-day plant maintenance shutdown April 19-21, 2021. The pumping stopped at 2021/04/19 12:51:45 UTC and resumed about 2021/04/21 21:00:00 UTC. The dataset is hosted in an AWS data lake, with an associated GDR data set providing the metadata. Links to both of these resources are included below. Additionally, this collection features data and metadata from a 2016 seismic survey at the same site for comparative analysis.

15 GEOTHERMAL ENERGY↗

Photogrammetric Characterization of a Brownout Cloud

Brownout is a dangerous problem for rotorcraft operating in arid and dusty environments such as the current operating theaters in Iraq and Afghanistan. Although the interest in brownout has increased in the past decade, the fundamental physics that govern the shape and size of the cloud are not yet well understood. Many computational and scaled experimental studies have been performed in an attempt to further this understanding and to simulate and predict the brownout cloud formation. However, the phenomenon significantly lacks experimental data, particularly at full-scale, which is needed to help validate the brownout simulations being performed. In an effort to increase the data set needed for this validation, tests were performed at the US Army Yuma Proving Ground using photogrammetry to obtain brownout cloud data of an EH-60L Black Hawk. Particle testing was performed on a sample of sand from the landing zone to gain more understanding on the nature of the soil. The photogrammetry technique applied to obtaining data on the formation and evolution of a brownout cloud was verified in an earlier study. The data for a landing approach was examined in greater detail and enabled velocity components of points on the cloud to be determined, as well as the dimensions of structures within the cloud.

Tanner, Philip E.↗

WELLBASE - An Interactive Platform for Wellbore Material Assessment

This project seeks to build an open-source wellbore material data repository with adequate material performance and contextual data to support Geological Carbon Storage (GCS). By appropriately evaluating the data types as mentioned earlier made available by the WELLBASE tool, stakeholders can make more informed decisions regarding well selections, risk assessment, and economic analysis for geologic carbon storage projects. Advanced Natural Language Processing models and other custom python scripts will be deployed in an automated process to extract unstructured data from documents, reports, and web applications and subsequently parse to more usable formats. The processed data will then be integrated into a robust and comprehensive database architecture, optimizing data accessibility, and usability for analytical purposes. The final data products will be accessible through a user-friendly visualization platform that will allow users to query and visualize the data, as well as download data in usable formats.

Tetteh, Daniel A.↗

Metadata Authoring with Versatility and Extensibility

NASA's Global Change Master Directory (GCMD) assists the scientific community in the discovery of and linkage to Earth science data sets and related services. The GCMD holds over 13,800 data set descriptions in Directory Interchange Format (DIF) and 700 data service descriptions in Service Entry Resource Format (SERF), encompassing the disciplines of geology, hydrology, oceanography, meteorology, and ecology. Data descriptions also contain geographic coverage information and direct links to the data, thus allowing researchers to discover data pertaining to a geographic location of interest, then quickly acquire those data. The GCMD strives to be the preferred data locator for world-wide directory-level metadata. In this vein, scientists and data providers must have access to intuitive and efficient metadata authoring tools. Existing GCMD tools are attracting widespread usage; however, a need for tools that are portable, customizable and versatile still exists. With tool usage directly influencing metadata population, it has become apparent that new tools are needed to fill these voids. As a result, the GCMD has released a new authoring tool allowing for both web-based and stand-alone authoring of descriptions. Furthermore, this tool incorporates the ability to plug-and-play the metadata format of choice, offering users options of DIF, SERF, FGDC, ISO or any other defined standard. Allowing data holders to work with their preferred format, as well as an option of a stand-alone application or web-based environment, docBUlLDER will assist the scientific community in efficiently creating quality data and services metadata.

Pollack, Janine↗

BOREAS TE-1 Soils Data Over The SSA Tower Sites in Raster Format

The BOREAS TE-1 team collected various data to characterize the soil-plant systems in the BOREAS SSA. This data set was gridded from vector layers of soil maps that were received from Dr. Darwin Anderson (TE-1), who did the original soil mapping in the field during 1994. The vector layers were gridded into raster files that cover approximately 1 square kilometer over each of the tower sites in the SSA. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

IECM calibration and data reduction requirements

The induced environment contamination monitor (IECM) tape recorder format, as it relates to the ouput of meaningful data from the IECM instrument, is explained. Eight-bit words (or bytes) generate numbers that represent voltage levels of electronic detection probes for each experiment. This information is amalgamated by the IECM Data Acquisition and Control System (DACS). In some cases bits represent certain status situations concerning an experiment, such as whether a valve is opened or closed. Voltages are transformed into meaningful physical phenomena through equations of calibration. Data formats and plots are generated as requested for each IECM experimenter.

Wills, F. D.↗

Lunar Impact Basins: Stratigraphy, Sequence and Ages from Superposed Impact Crater Populations Measured from Lunar Orbiter Laser Altimeter (LOLA) Data

Impact basin formation is a fundamental process in the evolution of the Moon and records the history of impactors in the early solar system. In order to assess the stratigraphy, sequence, and ages of impact basins and the impactor population as a function of time, we have used topography from the Lunar Orbiter Laser Altimeter (LOLA) on the Lunar Reconnaissance Orbiter (LRO) to measure the superposed impact crater size-frequency distributions for 30 lunar basins (D ≥ 300 km). These data generally support the widely used Wilhelms sequence of lunar basins, although we find significantly higher densities of superposed craters on many lunar basins than derived by Wilhelms (50% higher densities). Our data also provide new insight into the timing of the transition between distinct crater populations characteristic of ancient and young lunar terrains. The transition from a lunar impact flux dominated by Population 1 to Population 2 occurred before the mid-Nectarian. This is before the end of the period of rapid cratering, and potentially before the end of the hypothesized Late Heavy Bombardment. LOLA-derived crater densities also suggest that many Pre-Nectarian basins, such as South Pole-Aitken, have been cratered to saturation equilibrium. Finally, both crater counts and stratigraphic observations based on LOLA data are applicable to specific basin stratigraphic problems of interest; for example, using these data, we suggest that Serenitatis is older than Nectaris, and Humboldtianum is younger than Crisium. Sample return missions to specific basins can anchor these measurements to a Pre-Imbrian absolute chronology.

Fassett, C. I.↗

An airborne meteorological data collection system using satellite relay /ASDAR/

The paper describes the aircraft to satellite data relay (ASDAR) project which processes information collected by the navigation and data systems of widebody jet aircraft which cross data-sparse areas of the tropics and southern hemisphere. The ASDAR system consists of a data acquisition and control unit to acquire, store, and format latitude, longitude, altitude, wind speed, wind direction, and outside air temperature data; a transmitter to relay the formatted data via satellite to the ground; and a clock to time the data sampling and transmission periods.

Bagwell, J. W.↗

Transferable Output ASCII Data (TOAD) gateway: Version 1.0 user's guide

The Transferable Output ASCII Data (TOAD) Gateway, release 1.0 is described. This is a software tool for converting tabular data from one format into another via the TOAD format. This initial release of the Gateway allows free data interchange among the following file formats: TOAD; Standard Interface File (SIF); Program to Optimize Simulated Trajectories (POST) input; Comma Separated Value (TSV); and a general free-form file format. As required, additional formats can be accommodated quickly and easily.

Bingel, Bradford D.↗

The compression–error trade-off for large gridded data sets

The netCDF-4 format is widely used for large gridded scientific data sets and includes several compression methods: lossy linear scaling and the non-lossy deflate and shuffle algorithms. Many multidimensional geoscientific data sets exhibit considerable variation over one or several spatial dimensions (e.g., vertically) with less variation in the remaining dimensions (e.g., horizontally). On such data sets, linear scaling with a single pair of scale and offset parameters often entails considerable loss of precision. We introduce an alternative compression method called "layer-packing" that simultaneously exploits lossy linear scaling and lossless compression. Layer-packing stores arrays (instead of a scalar pair) of scale and offset parameters. An implementation of this method is compared with lossless compression, storing data at fixed relative precision (bit-grooming) and scalar linear packing in terms of compression ratio, accuracy and speed. When viewed as a trade-off between compression and error, layer-packing yields similar results to bit-grooming (storing between 3 and 4 significant figures). Bit-grooming and layer-packing offer significantly better control of precision than scalar linear packing. Relative performance, in terms of compression and errors, of bit-groomed and layer-packed data were strongly predicted by the entropy of the exponent array, and lossless compression was well predicted by entropy of the original data array. Layer-packed data files must be "unpacked" to be readily usable. The compression and precision characteristics make layer-packing a competitive archive format for many scientific data sets.

58 GEOSCIENCES↗

Thermodynamic and mass transfer modeling of carbon dioxide absorption into aqueous 2-amino-2-methyl-1-propanol

Explanations for the mass transfer behavior of 2-amino-2-methyl-1-propanol (AMP) are conflicting, despite extensive study of the amine for CO 2 capture. At equilibrium, aqueous AMP reacts with CO 2 to give bicarbonate in a 1:1 ratio. While this is the same stoichiometry as a tertiary amine, the reaction rate of AMP is 100 times faster. This work aims to explain the mass transfer behavior of AMP, specifically the stoichiometry and kinetics. An eNRTL thermodynamic model was used to regress wetted-wall column mass transfer data with two activity-based reactions: formation of carbamate and formation of bicarbonate. Data spanned 40–100 C and 0.15–0.60 mol CO 2 /mol alk). The fitted carbamate rate constant is three orders of magnitude greater than the bicarbonate rate constant. Rapid carbamate formation explains the kinetics, while the stoichiometry is explained by the carbamate reverting in the bulk liquid to allow CO 2 to form bicarbonate. Understanding the role of carbamate formation and diffusion in hindered amines enables optimizing solvent amine concentration by balancing viscosity and free amine concentration. Furthermore, this improves absorber design for CO 2 capture.

20 FOSSIL-FUELED POWER PLANTS↗

A Nonrelational Data Warehouse for the Analysis of Field and Laboratory Data From Multiple Heterogeneous Photovoltaic Test Sites

A nonrelational, distributed computing, data warehouse, and analytics environment (Energy-CRADLE) was developed for the analysis of field and laboratory data from multiple heterogeneous photovoltaic (PV) test sites. This data informatics and analytics infrastructure was designed to process diverse formats of PV performance data and climatic telemetry time-series data collected from a PV outdoor test network, i.e., the Solar Durability and Lifetime Extension global SunFarm network, as well as point-in-time laboratory spectral and image measurements of PV material samples. Using Hadoop/HBase for the distributed data warehouse, Energy-CRADLE does not have a predefined data table schema, which enables ingestion of data in diverse and changing formats. For easy data ingestion and data retrieval, Energy-CRADLE utilizes Hadoop streaming to enable Python MapReduce and provides a graphical user interface, i.e., py-CRADLE. By developing the Hadoop distributed computing platform and the HBase NoSQL database schema for solar energy, Energy-CRADLE exemplifies an integrated, scalable, secure, and user-friendly data informatics and analytics system for PV researchers. Furthermore, an example of Energy-CRADLE enabled scalable, data-driven, analytics is presented, where machine learning is used for anomaly detection across 2.2 million real-world current-voltage (I–V) curves of PV modules in three distinct Koppen–Geiger climatic zones.

14 SOLAR ENERGY↗