Search NASA⌕ Search

SEARCH · Search NASA

Results for “ESS”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Energy Storage Sizing and Operation of an Integrated Utility-Scale PV+ESS Power Plant

Integration of an energy storage system (ESS) into a large-scale grid-connected photovoltaic (PV) power plant is highly desirable to improve performance of the system and overcome the stochastic nature of PV power generation. Algorithms to size ESS within an integrated PV and ESS ( PV+ESS) power plant, conventionally, require a large number of high-resolution samples of PV generation. These algorithms are computationally expensive. In this paper, a two-day optimization algorithm that utilizes n-step constant power output dispatch every day from the PV+ESS power plant is proposed to size the ESS. Additionally, an n-step power dispatch every day through the one-year timeframe based optimization of the size of ESS is also performed. The proposed methods are computationally cheaper and provide acceptable accuracy with respect to the conventional sizing methods. The economics identified from the proposed methods are compared with the typical day-ahead hourly dispatch-based power production from the PV+ESS power plant. This comparison has shown similar economic performance showcasing the accuracy of the proposed methods in sizing the ESS. It also shows the potential for operating PV+ESS power plant in n-step constant power generation mode.

Xia, Qian↗
DOE OSTI2022

ESS-DIVE Reporting Format for Dataset Package Metadata

ESS-DIVE’s (Environmental Systems Science Data Infrastructure for a Virtual Ecosystem) dataset metadata reporting format is intended to compile information about a dataset (e.g., title, description, funding sources) that can enable reuse of data submitted to the ESS-DIVE data repository. The files contained in this dataset include instructions (dataset_metadata_guide.md and README.md) that can be used to understand the types of metadata ESS-DIVE collects. The data dictionary (dd.csv) follows ESS-DIVE’s file-level metadata reporting format and includes brief descriptions about each element of the dataset metadata reporting format. This dataset also includes a terminology crosswalk (dataset_metadata_crosswalk.csv) that shows how ESS-DIVE’s metadata reporting format maps onto other existing metadata standards and reporting formats.Data contributors to ESS-DIVE can provide this metadata by manual entry using a web form or programmatically via ESS-DIVE’s API (Application Programming Interface). A metadata template (dataset_metadata_template.docx or dataset_metadata_template.pdf) can be used to collaboratively compile metadata before providing it to ESS-DIVE.Since being incorporated into ESS-DIVE’s data submission user interface, ESS-DIVE’s dataset metadata reporting format, has enabled features like automated metadata quality checks, and dissemination of ESS-DIVE datasets onto other data platforms including Google Dataset Search and DataCite.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

10 Boron-film-based gas detectors at ESS

The development of detectors for the European Spallation Source is an important parallel element to the effort put into the design and construction of the neutron source and instruments. The 10Boron-film-based detector developments that started over a decade ago as basic detector concepts have now reached technical maturity after intense prototyping work and numerous testing campaigns. Several of the ESS beamlines that will soon enter the commissioning phase started welcoming the detector systems built with the 10 B-film converter technology. The real-size demonstrators evolved in the last 2–3 years into a diverse suite of gas proportional counters for use in diffraction, reflectometry and small-angle scattering studies in spite of the operational complexity posed by the requirements for large-area coverage, low material budget and robustness for operation in the high-flux and high-radiation environment of ESS. The detectors are now being shipped to ESS or undergoing the last performance and calibration tests before being handed over to the instrument teams for installation in the host beamlines. A common feature of these detector systems is the very large number of readout channels that they are instrumented with in order to fulfill the demanding requirements for sensitivity, spatial resolution and count-rate capability. Across all of the detector types that will operate at ESS, the integration, testing and commissioning of the read-out technologies and software tools for data reduction, calibration and analysis are the focus of the detector and integration teams. These will yield a wealth of knowledge about their operation as well as initial results on the in-situ performance, a very important asset to ensure rapid commissioning of the detectors when neutrons from the ESS source become available. In this paper we will give an overview of the 10 B-film-based detector technologies included in the ESS detector suite that are currently facing the transition from the production phase to installation and integration with the other beamline components, which comes with its own specific challenges of both organizational and technical nature.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

ESS-DIVE Unoccupied Aerial Systems (UAS) Reporting Format v1

Here we present documentation of the ESS-DIVE reporting format for Unoccupied Aerial System (UAS) data and metadata. This reporting format provides guidance to data contributors on how to store data to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format provides templates and guidance for the reporting of metadata for UAS experimental campaigns, individual flights, platform and sensor description. To improve data access and discoverability, the reporting format proposes a data description scheme of Levels based on the degree of processing, where Level 0 includes raw data, through to Level 3 being derived data end products. A range of examples of data types for each Level are given, with suggested file naming schemes. The reporting format presented here is intended to form a foundation for future development that will accommodate new UAS technologies and approaches to data access and use in the future. The reporting format documentation is maintained and updated on the ESS-DIVE Community Space GitHub at https://github.com/ess-dive-community/essdive-uas. This data package is the first published version of this reporting format, and comprises a zip file of the complete content of https://github.com/ess-dive-community/essdive-uas v1.0. The zip contains the reporting format description, instructions and variable definitions in GitHub markdown language (*.md) and metadata templates in csv format. The reporting format is designed to be compatible with other ESS-DIVE formats, and it is specifically recommended that this reporting format be used in conjunction with the File-level metadata (FLMD) and comma separated values (csv) reporting formats for submission to the ESS-DIVE repository.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Neural Network-Based Power Mismatch Elimination Strategy for Integrated Solar and ESS AC/DC Systems (MARS)

The multiport autonomous reconfigurable solar power plant (MARS) is a promising concept for the integration of photovoltaic (PV) and energy storage system (ESS) to the transmission ac grid and a high-voltage direct current (HVdc) link. The presence of PV and ESS in each arm of the MARS results in uneven distribution of active power among different submodules (SMs), thereby leading to unbalanced SM capacitor voltages and potentially compromising the system stability. Moreover, in the case of partial shadings, shaded PV SMs will suffer from decreased power injections causing power mismatch in the MARS system. To address this issue, a neural-network-based power mismatch elimination (NNPME) strategy is proposed in this article. The proposed NNPME strategy optimizes ESS usage and leverages both dc and ac circulating currents to facilitate power transfer among the SMs, arms, and phases of the MARS system. Simulation and control hardware-in-the-loop (cHIL) experiments demonstrate the effectiveness of the proposed NNPME strategy. Compared with the traditional approaches, the proposed NNPME strategy can significantly enhance system efficiency and ensure stable and continuous operation, even in the presence of uneven power distribution within the MARS system.

14 SOLAR ENERGY↗
DOE OSTI2021

ESS-DIVE Reporting Format for File-level Metadata

The ESS-DIVE reporting format for file-level metadata (FLMD) provides granular information at the data file level to describe the contents, scope, and structure of the data file to enable comparison of data files within a data package. The FLMD are fully consistent with and augment the metadata collected at the data package level. We developed the FLMD template based on a review of a small number of existing FLMD in use at other agencies and repositories with valuable input from the Environmental Systems Science (ESS) Community. Also included is a template for a CSV Data Dictionary where users can provide file-level information about the contents of a CSV data file (e.g., define column names, provide units). Files are in .csv, .xlsx, and .md. Templates are in both .csv and .xlsx (open with e.g. Microsoft Excel, LibreOffice, or Google Sheets). Open the .md files by downloading and using a text editor (e.g. Notepad or TextEdit). Though we provide Excel templates for the file-level metadata reporting format, our instructions encourage users to 'Save the FLMD template as a CSV following the CSV Reporting Format guidance'. In addition, we developed the ESS-DIVE File Level Metadata Extractor which is a lightweight python script that can extract some FLMD fields following the recommended FLMD format and structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

ESS-DIVE Reporting Format for Comma-separated Values (CSV) File Structure

The ESS-DIVE reporting format for Comma-separated Values (CSV) file structure is based on a combination of existing guidelines and recommendations including some found within the Earth Science Community with valuable input from the Environmental Systems Science (ESS) Community. The CSV reporting format is designed to promote interoperability and machine-readability of CSV data files while also facilitating the collection of some file-level metadata content. Tabular data in the form of rows and columns should be archived in its simplest form, and we recommend submitting these tabular data following the ESS-DIVE reporting format for generic comma-separated values (CSV) text format files. In general, the CSV file format is more likely accessible by future systems when compared to a proprietary format and CSV files are preferred because this format is easier to exchange between different programs increasing the interoperability of a data file. By defining the reporting format and providing guidelines for how to structure CSV files and some field content within, this can increase the machine-readability of the data file for extracting, compiling, and comparing the data across files and systems.Data package files are in .csv, .png, and .md. Open the .csv with e.g. Microsoft Excel, LibreOffice, or Google Sheets. Open the .md files by downloading and using a text editor (e.g., notepad or TextEdit). Open the .png in e.g. a web browser, photo viewer/editor, or Google Drive.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Results of the Extraction-Scrub-Strip (ESS) Tests With Solvent Using IBC BOBCalix

Two Extraction, Scrub, and Strip (ESS) tests were performed on two BOBCalix solvent samples prepared using BOBCalix from IBC Advanced Technologies (“IBC”). The purpose of testing this sample is to confirm if the newly sourced BOBCalix displays the correct extraction and stripping behavior with cesium. The first batch of BOBCalix solvent was prepared using IBC lot#220310KC-1. The second batch was prepared using IBC lot#220615KC-3A. The ESS tests showed acceptable performance of the solvent for extraction, scrub, and strip operations. The extraction D (Cs) values for the tests were 12.9 and 13.6. This value is consistent with results from previous ESS tests using similar solvent formulations. Similarly, the strip cesium distribution ratios (0.0588/0.0342/0.0258 and 0.0575/0.0335/0.0262) fell within acceptable ranges.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1996

NCMS ESS 2000 Project

ESS 2000 has the vision of enhancing the knowledge necessary to implement cost-effective, leading-edge ESS technologies and procedures in order to increase U.S. electronics industry competitiveness. This paper defines EES and discusses the factors driving the project, the objectives of the project, its participants, the three phases of the project, the technologies involved, and project deliverables.

ESS environmental stress screening electronics ind↗
DOE OSTI2020

ESS-DIVE reporting format for leaf-level gas exchange data and metadata

Here we present documentation of the ESS-DIVE reporting format for leaf-level gas exchange data and metadata. This reporting format provides guidance to data contributors on how to store data to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format documentation is maintained and updated on the ESS-DIVE Community Space GitHub. This data package is the first published version of this reporting format, and comprises a zip file of the complete content of https://github.com/ess-dive-community/essdive-leaf-gas-exchange v1.0. The zip contains the reporting format description, guidelines, variable tables and instructions in GitHub markdown language (*.md) and 2 metadata templates as spreadsheets with drop down options (*.xlsx files, also function in GoogleSheets).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

ESS-DIVE Reporting Format for Hydrologic Monitoring Data and Metadata

The ESS-DIVE Reporting Format (RF) for Hydrologic Monitoring Data and Metadata was designed for water level, temperature, electrical conductivity, specific conductance, dissolved oxygen, and pH measured in situ using sensors deployed in water bodies. It can also be applied to a broader suite of variables beyond its original scope. The RF is intended to provide clear and easy guidance to data generators aiming to upload consistent findable, accessible, interoperable, and reusable (FAIR) datasets. The RF includes instructions (pdf), a term guide (csv), templates (csv and xlsx), and a list of recommended vocabulary (csv) to equip the data generator with all of the tools needed to successfully apply the RF. There is also a crosswalk to some key data resources and standards (csv). Users should cite this dataset when using the RF but are encouraged to access the RF files on GitHub (https://github.com/ess-dive-community/essdive-hydrologic-monitoring) where the RF documentation is maintained and updated on the ESS-DIVE Community Space GitHub. Questions and suggestions for improvement can be submitted as GitHub issues.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

ESS-DIVE Reporting Format for Location Metadata

The ESS-DIVE location metadata reporting format provides instructions and templates for reporting a minimum set of metadata for discrete point locations in geographic space represented by x, y, and z coordinates. This format was created based on a need for earth and environmental science researchers to more consistently provide metadata about locations where they conduct studies. To create the format, we incorporated elements from ESS-DIVE’s community reporting formats as well as 12 additional data standards or other data resources (e.g., databases, data systems, or repositories). In the template, we ask researchers to indicate unique locations using Location IDs and indicate hierarchies of locations through parent location IDs. We also provide additional optional fields for researchers to indicate how they measured the point location and the date and time that the location was first used as a research siteThis dataset contains support documentation for the reporting format (README.md and instructions.md), a terminology guide (guide.md), a crosswalk indicating how this reporting format relates to existing standards and data resources (Location_metadata_crosswalk.csv), a data dictionary (dd.csv), file-level metadata (flmd.csv), and the location metadata templates in both CSV (Location_metadata_template.csv) and Excel formats (Location_metadata_template.xlsx).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

GE 1.5 ESS Wind Turbine Retrofit Controller Development (CRADA Final Report)

National Renewable Energy Laboratory (NREL) and Bachmann electronic corp. will collaborate on the development of a software application to be used on an existing aftermarket Bachmann controller, utilizing and existing Bachmann software platform, which will be used on the General Electric (GE) 1.5 ESS wind turbine. This retrofit will significantly enhance NREL’s ability to control experiments it is planning to conduct on the GE 1.5 wind turbine as part of the Gearbox Reliability Collaborative, Atmosphere to Electrons and other future R&D. The proposed work is leveraging ongoing Department of Energy (DOE) Annual Operating Plan activities on the GE 1.5 ESS wind turbine at the National Wind Technology Center.

17 WIND ENERGY↗
DOE OSTI2025

NEUWAVE-12 at ESS: Workshop Series on Wavelength Dependent Neutron Imaging Back in Full Swing

The NEUWAVE workshop series, a cornerstone for advancements in energy- or wavelength-resolved neutron imaging, held its 12th meeting at the European Spallation Source (ESS) in Lund from September 1 to 5, 2024. The participants can be seen in Figure 1 during the site visit. The series focuses on developments in techniques using phenomena such as Bragg-edges, incoherent and inelastic scattering, or neutron absorption resonances as contrast mechanisms and is therefore far more specialized than more general conferences for neutron imaging such as the WCNR or ITMNR series [Citation1]. After a break during the pandemic and record attendance at NEUWAVE-11 in Tokyo in 2023, which underscored the immense interest in wavelength dependent neutron imaging, NEUWAVE returned to its roots with a focus on a smaller group of specialists meeting in a workshop format, allowing for in-depth discussions and the exchange of new ideas.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

ESS-DIVE guidelines for archiving terrestrial model data

This dataset contains supporting documents and images for ESS-DIVE terrestrial model data archiving guidelines.Terrestrial models are broadly defined as numerical models that couple both land dynamics and energy, water, carbon, or nutrient fluxes. We created these guidelines based on input from the U.S. Department of Energy’s Biological and Environmental Research land modeling community. The guidelines are intended to help modelers determine which components of their terrestrial model data associated with publication should be archived. Based on input from the land modeling community, the guidelines recommend archiving both model input and testing data, as well as code, script, and metadata. The guidelines also recommend archiving model data output, depending on the limitations set by data repositories. Lastly, we provide recommendations for bundling data files for publication as well as a discussion about tools that can facilitate model data archiving and reuse.This dataset is an archive of the associated GitHub repository for our model archiving guidelines (https://github.com/ess-dive-community/essdive-model-data-archiving-guidelines). The ‘README.pdf’ file gives a general introduction to the guidelines, and the ‘instructions.pdf’ file provides more detailed steps for following the guidelines. We also provide 2 figures in this data package: 1) a decision tree (model_data_guidelines_decision_tree.png) that can help users determine which components of their model data to archive. and 2) the ‘model_data_guidelines_flmd.png’ file depicts the different files that can be archived in addition to the model data itself. Lastly, we include 3 digitized tables from our associated manuscript and 3 CSV files with anonymized input from DOE scientists about the importance of different aspects of model data archiving from which we developed the guidelines.Dataset updates for v1.1.0: We updated this data package on 2021-11-22 in response to review comments on our related manuscript. In this update we removed one figure so that the model archiving guidelines are conveyed in text rather than an image. We updated the file-level metadata (FLMD) figure to be in accord with the most recent FLMD recommendations. We made minor edits to the README file to update the recommended citation and added two co-authors. We also added 6 new data files (3 are anonymized input from DOE scientists that helped to inform guidelines, and 3 are digitized tables from our manuscript.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

ESS-DIVE Reporting Format for Sample-based Water and Soil Chemistry Measurements

The ESS-DIVE (Environmental Systems Science Data Infrastructure for a Virtual Ecosystem) reporting format for sample-based water and soil chemistry measurements are written guidelines and spreadsheet templates, that facilitate archiving water/soil/sediment chemistry data. The templates and terminology lists provided as part of the reporting format can help organize data and potentially enable data reuse.The reporting format consists of a general instructions file (instructions.md) as well as more detailed instructions files for each template (files beginning “Detailed_Instructions_*.md). The “examples” folder includes an example of each data template with just the limited set of required fields filled out as well as other examples with both required and optional fields complete.The 'templates' folder contains CSV templates for data, methods, and terminology file templates. Similar to the examples folder, the blank templates are provided with versions for required fields only as well as required and optional fields. Lastly, the term list folder provides common terminology used in each of the templates as well as a definition and any constraints for the fields.

54 ENVIRONMENTAL SCIENCES↗