Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “production data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27

Estimation of backgrounds from jets misidentified as τ-leptons using the Universal Fake Factor method with the ATLAS detector

Processes with τ$$\tau $$-leptons in the final state are important for Standard Model measurements and searches for physics beyond the Standard Model. The ATLAS experiment at the Large Hadron Collider observes τ$$\tau $$-leptons produced in proton–proton collisions only through their decay products. Data analyses involving hadronically decaying τ$$\tau $$-leptons face challenges due to backgrounds from jets misidentified as τ$$\tau $$-leptons that are not modelled reliably by Monte Carlo simulations. Data-driven methods such as the fake-factor method allow such misidentified backgrounds to be predicted by measuring transfer factors, known as fake factors, in data from dedicated regions. This paper describes a refined technique for determining the fake factors, the Universal Fake Factor method. It evaluates the fake factors for a signal region by using fake factors from samples enriched in different sources of jets misidentified as τ$$\tau $$-leptons (light-quark, gluon, b-quark, and pile-up jets). Each fake factor is calculated as a linear combination of fake factors measured in these different enriched samples. For the full Run 2 data set, the systematic uncertainty of the calculated fake factors, evaluated using W(μν)$$W(\mu u )$$ enriched event sample, ranges from 15 to 35% depending on the τ$$\tau $$-lepton’s transverse momentum and charged-particle decay multiplicity.

Aad, G↗

Dynamics of QCD matter — current status

In this study, there are 18 sections discussing various current topics in the field of relativistic heavy-ion collisions and related phenomena, which will serve as a snapshot of the current state of the art. Section 1 reviews experimental results of some recent light-flavored particle production data from ALICE collaboration. Other sections are mostly theoretical in nature. Very strong but transient magnetic field created in relativistic heavy-ion collisions could have important observational consequences.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Streaming Data from Experimental Facilities to Supercomputers for Real-Time Data Processing

In this paper we demonstrate direct data streaming from instruments and detectors at a large-scale experimental facility to a supercomputer for real-time data processing and feedback. Streaming data to supercomputers introduces the potential for novel scientific applications and workflow models, including the ability to provide real-time feedback from very large datasets during an experiment and the integration of real-time ML training and inference at scale. We discuss a successful demonstration for real-time processing of data from the Advanced Photon Source (APS) on the Polaris supercomputer using an EPICS-based streaming framework. We describe the capabilities of the streaming framework itself, and outline the architecture that allows us to process experimentally derived data on a supercomputer without file-based data transfers. We present throughput measurements that are indicative of system performance capable of sustaining the expected data production rates of the facility, as well as discuss some outstanding challenges and our future directions.

real-time processing↗

Scoreboard

Emerging HPC machines have given rise to enhanced compute power that far outstrips the machine's ability to save large scale results for post-processing. To combat this, in situ data analysis techniques are slowly being adopted. With in situ data management favoring workflows composed of multiple simulations and analyses connected in transit on heterogeneous machines, scientists and engineers need a tool that enables them to create data extracts, visualizations, and interactively monitor and steer their simulations. Scoreboard Phase II is a next generation analysis software that supports composite in transit workflows on heterogeneous architectures and restores interactivity to in situ data analysis through simulation monitoring and computational steering. Scoreboard provides a simulation dashboard with graphs of metrics over time, controls for setting custom simulation steering parameters, controls for managing the set of data extracts being produced in the simulation, as well as the ability to explore data extracts, all from a web browser. Realizing the vision outlined in this project required research into making a system that integrates end to end from simulations all the way to the user. In situ tools generally suffer from complexity and excessive software dependencies. Scoreboard, by contrast, is easy to build and integrate into simulation codes and it provides first class FORTRAN support. The Scoreboard library is capable of in situ and in transit data analysis that can produce data extracts commonly needed for Computational Fluid Dynamics (CFD) analysis. Simulations can transparently stage data in transit to a Scoreboard Endpoint program, which can accept their data and produce the requested data extracts. This lets simulations return to their work while the Endpoint works on the analysis. Efficiently staging the data at scale was a topic of this research. Scoreboard provides the means to let the user manage data extracts and monitor/steer many simulations from a web browser. This area of the research focused on discovery of in transit network components to expose and control their steering parameters within an interactive browser-based user interface that includes: system topology, gathered metrics, notifications, dynamically-generated steering controls, and exploration of visualization data products.

Whitlock, BradJoseph [Intelligent Light] (00000001↗

pvOps v.0.1

This python package contains a series of functions to facilitate fusion of text-based and time series production data collected at photovoltaic sites. The package also contains example datasets and tutorials to help demonstrate how the functions can be used. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1554 O

Gunda, Thushara↗

Meld: A project for exploring how to meet DUNE's framework needs

Existing data-processing frameworks for HEP experiments are largely based on collider-physics concepts, which may be based on rigid, event-based data hierarchies. These data organizations are not always helpful for neutrino experiments, which must sometimes work around such restrictions by manually splitting apart events into constructs that are better suited for neutrino physics. The purpose of Meld is to explore more flexible data organizations by treating a frameworks job as: (1) A graph of data-product sequences connected by (2) User-defined functions that serve as operations to (3) Framework-provided higher-order functions.

Knoepfel, KyleJ. [Fermi National Accelerator Labor↗

Rubin Observatory LSST Tutorials

A collection of tutorials -- both Jupyter notebooks and documentation-based --- demonstrating data access, analysis, and visualization techniques for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). These tutorials are intended for astronomers, educators, and data scientists working with LSST data products.

Vera C. Rubin Observatory, NSF-DOE↗

AbacusSummit Halo Light Cone Catalogs

This is a set of halo light cone catalogs from the AbacusSummit suite of cosmological N-body simulations (abacussummit.readthedocs.io/). They are a value-added data product provided by post-processing the simulation output. The main application of the halo light cone catalogs is the construction of realistic mock galaxy catalogues and weak lensing maps on the sky. The algorithm (described in Hadzhiyska et al. 2021) associates CompaSO halos from 29 redshift epochs spanning z = 0.1-2.5 with their particles at the time of light-cone crossing. It then records the halo and particle information into an easily accessible product, which can be read with the CompaSO reader. The 25 base resolution boxes at fiducial cosmology have a halo light cone catalog covering an octant of the sky to z approx 0.8 and about 2000 deg2 extending to z approx 2.4. The huge boxes provide light cone information of the full sky until z approx 2.18 and extend further towards the corners of the box (available until z = 2.25). Galaxy mock catalogs on the sky can be generated easily though the AbacusHOD script providing an extended HOD framework (see Yuan et al. 2021, for details), which has been modified to work with the halo light cone catalogs. The available tracers are luminous red galaxies (LRGs), emission-line galaxies (ELGs), and quasi-stellar objects (QSOs).

79 ASTRONOMY AND ASTROPHYSICS↗

Soil moisture and temperature data along the northeast facing hillslope at the Lower Montane site in the East River Watershed, Colorado

Soil moisture, temperature and electrical conductivity have been monitored with 5TE sensors (Decagon Inc.) located at 10 and 50 cm depth at 4 different locations along the northeast-facing slope at the Lower Montane site in the East River Watershed, Colorado from Oct 2016 to Oct 2018. The purpose of this data is to inform hydrobiogeochemical analyses for the Watershed Function Scientific Focus Area (SFA). The data is reported in 4 csv files labeled their by location identifiers (ER-SMN1-5) and location metadata is provided in SM_loc.csv. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales.

54 ENVIRONMENTAL SCIENCES↗

Water Level Data from Wells PLM1 and PLM6 for the East River Watershed, Colorado

This dataset (Williams et al., 2020) contains the original un-QA/QC-ed water level data for PLM1 and PLM6 and has been obsoleted. The data contained within this dataset is not to be used. Refer to Faybishenko et al., 2022 (DOI: 10.15485/1866836) for the latest QA/QC-ed data available via ESS-DIVE.This data set contains water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location. These wells used to monitor subsurface water and carbon inventories and fluxes at the East River Watershed, Colorado, USA. Complete metadata information on the PLM1 and PLM6 wells are available in the related data package reference Varadharajan C, et al (2020). https://doi.org/10.15485/1660962.Data are reported in .csv files per well. The latitude and longitude of each location are given in a file called locations.csv. These data are used for determining the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry can be used to estimate rates of solute export from the hillslope to the floodplain and river.These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales.

54 ENVIRONMENTAL SCIENCES↗

Subsurface electrical conductivity across the BEO site inferred using a capacitively coupled resistivity survey in May 2013, Utqiagvik, Alaska

Multiple transects across and around the Barrow Environmental Observatory (BEO) site were surveyed using a capacitively coupled resistivity tool to infer the subsurface electrical conductivity in the top ~6 m in order to improve the understanding of heterogeneity in ice and salinity content. This work was led by the environmental geophysics team from Lawrence Berkeley National Laboratory as part of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). The acquisition was performed in May 2013 using a capacitively coupled resistivity tool (OhmMapper from Geometrics, Inc) mounted behind a sled hooked to a snowmobile. Twenty-eight ~750 m long transects cover the NGEE intensive site (polygon areas A, B, C, D) in the BEO with a measurement (apparent resistivity for 5 different geometries) taken every 1.5 to 2 m. The survey also includes other transects that have been acquired along Electrical Resistivity Tomography (ERT) transects previously acquired at the site (Site 0, AB, and BD), and several long transects (up to 7 km each) around the BEO site crossing several Drained Thawed Lake Basins (DTLB). The various transects acquired during this survey cover a distance of about 100 km. All the datasets are provided with the acquisition geometry and the associated subsurface apparent electrical conductivity. In addition, the 28 transects at the BEO intensive site were inverted to infer the subsurface electrical conductivity. Unprocessed and processed data products are included in this package. This metadata document contains a description of the survey and processing steps and the inferred products.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska, and 2) multiple areas in the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Soil moisture and temperature from 2019 to 2024 along northeast- and southwest-facing hillslopes at the Lower Montane site in the East River Watershed, Colorado

Soil moisture, temperature, and electrical conductivity have been monitored at multiple depths (between 10 and 50 cm) at 4 locations along a northeast-facing slope and 3 locations on the opposite southwest-facing slope at the Lower Montane site in the East River Watershed, Colorado, from Oct 2019 to Oct 2024. The purpose of this data is to inform hydro-biogeochemical analyses for the Watershed Function Scientific Focus Area (SFA). Two locations on the northeast-facing slope were reinstalled in 2020 due to damage from wildlife, and thus data for these sites are provided in two distinct files. Overall, the data are reported in 9 CSV files containing the measurements, and the locations are provided in the Sensor_Location.csv file. There is a total of 10 *.csv data files and 3 *.csv metadata files. Older datasets associated with the northeast-facing slope are provided in another archive (see reference). These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales. Feel free to contact the author with any questions or collaboration interests.

54 ENVIRONMENTAL SCIENCES↗

Panama tropical forest digital camera imagery for vegetation phenology, Dec2016-May2019, PA-SLZ, PA-PNM, PA-BCI

Tropical forest phenology monitoring undertaken by use of Wingscapes timelapse cameras (phenocams) at three tropical evergreen forests in Panama: San Lorenzo, Parque Natural Metropolitano, and Barro Colorado Island. Following installation in December 2016, images were acquired every 10 minutes from 10 am to 2 pm daily, ending in May 2019. A total of 37 cameras were mounted on towers and tree branches, and view sunlit canopy or understory forest as follows: PA-SLZ, 11 canopy, 14 understory; PA-PNM, 6 canopy, 2 understory, PA-BCI, 4 canopy (trees also monitored for sap flow). This data package contains a full data description, metadata, species identification guides and summary files showing example fields of view from each camera location as csv and pdf files. The data description provides instructions for download of the full resolution image files, and other summary data products stored on external servers.

54 ENVIRONMENTAL SCIENCES↗

DeepBench: A simulation package for physical benchmarking data

We introduce **DeepBench**, a python library that generates simple simulated image data from first principles, such as basic geometric shapes and astronomical objects. These data are highly valuable for developing (calibration, testing, and benchmarking) statistical and machine learning models because they make it possible to connect the final data product to physically interpretable inputs. This software includes tools to curate and store the datasets to maximize reproducibility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Sea Asymmetry from Polarized W Boson Production

We present the results of a global QCD analysis of helicity parton distribution functions (PDFs) that includes the latest polarized W-lepton production data from the STAR collaboration at the Relativistic Heavy-Ion Collider (RHIC). This data allows the first extraction of a nonzero helicity light-quark sea asymmetry within a simultaneous global QCD analysis of unpolarized and helicity PDFs.

Cocuzza, Christopher↗

Fast Data Processing for Hyperspectral Sensors on Small Platforms

Hyperspectral imaging is a very promising technology for nuclear proliferation detection. However, due to size and weight restrictions, small hyperspectral platforms such as satellites and small drones lack the on-board computing resources for accurate, real-time analysis of the enormous flow of data that a continuously operating hyperspectral sensor generates. This severely limits satellite systems, which can collect far more data than what they can telemeter, and hinders the ability of all platforms to adapt their missions on the fly in response to observations. This program addresses the hyperspectral data processing challenge through development of new, fast and accurate algorithms that produce data products in real time. The algorithms circumvent the major computational bottlenecks in existing processing streams, and would be incorporated in lightweight, power-efficient single-board computer systems. The toolkit of fast algorithms will be immediately useful in current and future hyperspectral systems being built by the Government and by private industry, including drone-based systems and satellite constellations that acquire timely global imagery.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Addressing Soiling: From Interface Chemistry to Practicality

Natural soiling has reduced the energy output of photovoltaic (PV) systems since the technology was first used. Projecting even a small average annual soiling loss translates to billions of dollars in annual lost revenue worldwide. Production losses due to soiling can be very high in some locations, substantially increasing the levelized cost of electricity (LCOE) due to lost power production, increased operating and maintenance costs, and/or increased finance cost due to the uncertainty. Furthermore, although soiling has been discussed in the literature for more than 70 years, solutions to many problems are still needed. The National Renewable Energy Laboratory (NREL) is working with the PV industry to develop the tools/knowledge so that the effects of soiling can be predicted for different environmental conditions and cost-effective mitigation can be implemented. For this project, NREL performed a number of research and development tasks/subtasks in the following general areas to 1) predict PV module soiling losses based on environmental factors at a PV installation and from its energy production data, 2) quantitatively measure the adhesion forces to understand the physics enabling soiling, and 3) develop related standards on PV module coatings and artificial soiling. At the inception of the project, the PV industry considered these efforts to be the most important and immediate soiling issues that we could address to have the highest impact on LCOE. These focused efforts have led to outstanding accomplishments that have been communicated and very well received by the community.

14 SOLAR ENERGY↗