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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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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mortality of older construction and craft workers employed at Department of Energy (DOE) nuclear sites: Follow‐up through 2021

Background To determine if construction and trades workers formerly employed at US Department of Energy (DOE) nuclear weapons sites are at significant risk for occupational diseases, we studied the mortality experience of participants in the Building Trades National Medical Screening Program (BTMed). Methods The cohort included 26,922 participants enrolled between 1998 and 2021 and 8367 deaths. Standardized mortality ratios were calculated based on US death rates. Cox models compared construction workers (n = 22,747; 7487 deaths) to two nonconstruction subpopulations: administrative, scientific and security workers (n = 1894; 330 deaths), and all other nonconstruction workers (n = 2218; 550 deaths). Results Mortality was elevated for all causes, all cancers, cancers of the trachea, bronchus, lung, kidneys, and lymphatic and hematopoietic system, mesothelioma, chronic obstructive pulmonary disease (COPD), asbestosis, transportation injuries, and other injuries, particularly accidental poisonings. There were 167 deaths from coronavirus disease 2019 (COVID-19), which was lower than expected using US death rates. Overall cause-specific mortality was significantly higher among construction workers than for internal comparison groups. Conclusions Construction workers employed at DOE sites have a significantly increased risk for occupational illnesses. Apart from COVID-19 deaths, this update: (1) found that mortality among construction workers is significantly elevated compared to the US population and significantly higher than in the internal comparison populations, and (2) confirmed excess risk for these workers for first employment after 1990. Cancer mortality risks are similar to the cancers identified for DOE compensation from radiation exposures. In conclusion, the high lung cancer risk supports the value of early lung cancer detection. Continued medical surveillance is important.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2026

CONUS-wide Projected Flood Frequency and Uncertainty Estimates, Version 1.0

This dataset presents a large-ensemble of CONUS-wide projected flood frequency and uncertainty estimates across ~2.7 million NHDPlusV2 river reaches over the CONUS. The framework producing this dataset leverages a multi-model, uncertainty-aware modeling framework that allows evaluating shifts in flood frequences at the stream reach level across the CONUS. CONUS-wide ensemble streamflow projections generated from hydrologic simulations driven by downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) outputs are used to derive these flood frequency and uncertainty estimates over the period 1980 - 2099. A spatially consistent regional L-moment algorithm is applied across clusters defined by the US Hydrologic Unit Code Subregions (HUC4s and HUC8s) and NHDPlusV2 stream orders to estimate flood frequencies. The dataset also includes at-site based flood estimates that allow for the comparison between local and regional approach-based estimates, assess projected changes, and characterize their uncertainties. For more reliable estimation of rare flood frequencies such as 500 and 1000-year return periods, super-ensemble based estimates are also included in the dataset. This dataset is derived to support the "Impact-Informed Dam Safety Risk Assessment for Securing Hydropower Assests" project for the US Department of Energy (DOE) Hydropower and Hydrokinetic Office (H2O). For further details, refer to Kao et al. (2022), Ghimire et al. (2023), Ghimire et al. (2025), and Hosking and Wallis (1997).

Ghimire, Ganesh [ORNL] (ORCID:0000000242843941)↗
DOE OSTI2023

Techno-Economic Impact of a Smart Battery Sorting System

Create analytical framework to capture costs and benefits of the automated sorting into battery recycling including the development and deployment of various types of battery recycling technologies such as pyrometallurgical, hydrometallurgical, and direct recycling. Li Industries, Inc. is a Virginia startup company focused on reinventing how lithium-ion batteries (LIBs) are recycled. Li Industries is focused on developing direct LIB recycling and automated battery sorting technologies in order to reduce the environmental impact of the LIB lifecycle. This work is to be conducted in support of the American-Made Challenges Lithium-Ion Battery Recycling Prize. Li Industries and NREL will work together to understand how novel technologies, such as those being developed by Li Industries, can impact the development and economics of the battery recycling industry. This voucher is being used to evaluate the profitability of an automated sorting system developed by Li Industries and the potential effect this increased value could have on the domestic lithium-ion battery (LIB) recycling industries in the United States. NREL has developed the Lithium-Ion Battery Resources Assessment (LIBRA) system dynamics model to project the future viability of the US LIB manufacturing and recycling industries under varying technoeconomic conditions and battery adoption scenarios over the coming decades. Additional logic was added to LIBRA to analyze the role automated sorting of recycling feedstock could play in the buildout of the industry and the impacts it has on the recovery of end-of-life (EOL) battery materials. This report summarizes the outcomes of this modeling analysis in the US context through a series of sensitivity analyses run for a range of values of a given input dimension and compared across the unsorted or automated sorting cases for LIB recycling feedstock. For greater detail on the process and analysis, the researchers are publishing a forthcoming journal article titled Techno-Economic Impact of a Smart Battery Sorting System for Lithium-Ion Battery Recycling and Mineral Recovery in the United States by Weigl, et al. In the event the article is not accepted by any currently seeking publication in academic or industry journal, it may be published by NREL. CRADA benefit to DOE, Participant, and US Taxpayer: assists laboratory in achieving programmatic scope competencies, uses the laboratory's core competencies.

25 ENERGY STORAGE↗
DOE OSTI2024

Nuclear Physics Network Requirements Review (Final Report)

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. ESnet interconnects DOE national laboratories, user facilities, and major experiments so that scientists can use remote instruments and computing resources as well as share data with collaborators, transfer large datasets, and access distributed data repositories. ESnet is specifically built to provide Between July 2023 and October 2023, ESnet and the Nuclear Physics program (NP) of the DOE SC organized an ESnet requirements review of NP-supported activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the NP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

High Energy Physics Network Requirements Review: Two-Year Update

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. ESnet interconnects DOE national laboratories, user facilities, and major experiments so that scientists can use remote instruments and computing resources as well as share data with collaborators, transfer large datasets, and access distributed data repositories. ESnet is specifically built to provide a range of network services tailored to meet the unique requirements of the DOE’s data-intensive science. In July 2023, the Energy Sciences Network (ESnet) and the High Energy Physics program (HEP) of the DOE SC organized an interim ESnet requirements review of HEP-supported activities, to follow up on the work started during the 2020 HEP Network Requirements Review. Preparation for these events included checking back with the key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare updates to their previously submitted case study documents, so that ESnet could update the understanding of any changes to the current, near-term, and long-term status, expectations, and processes that will support the science activities of the program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Annual Site Environment Report for Calendar Year 2023 - Princeton Plasma Physics Laboratory

This report provides the US Department of Energy (DOE) and the public with information on the level of radioactive and non-radioactive pollutants (if any) that are added to the environment as a result of Princeton Plasma Physics Laboratory’s (PPPL) operations. This report fulfills the annual public reporting requirements of DOE Order 231.1B. The results of PPPL’s 2023 environmental surveillance and monitoring program are presented and discussed. The report also summarizes environmental initiatives, assessments, and community involvement programs that were undertaken in 2023. This report provides the US Department of Energy (DOE) and the public with information on the level of radioactive and non-radioactive pollutants (if any) that are added to the environment as a result of Princeton Plasma Physics Laboratory’s (PPPL) operations. This report fulfills the annual public reporting requirements of DOE Order 231.1B. The results of PPPL’s 2023 environmental surveillance and monitoring program are presented and discussed. The report also summarizes environmental initiatives, assessments, and community involvement programs that were undertaken in 2023. In 2023, PPPL’s radiological environmental monitoring program measured tritium in the air at onsite sampling stations. Using highly sensitive air monitors, PPPL is capable of detecting small changes in the ambient levels of tritium. The operation of monitors located on D-site is used to demonstrate compliance with the National Emission Standard for Hazardous Air Pollutants (NESHAPs) regulations. Also included in PPPL’s radiological environmental monitoring program, are water monitoring – ground, surface, and waste waters. PPPL’s radiological monitoring program characterized the background levels of tritium in the environment and those data are presented in this report. Ground water monitoring continued under New Jersey Department of Environmental Protection’s (NJDEP) Site Remediation Program regulations. PPPL monitored for non-radiological contaminants, mainly volatile organic compounds (components of common degreasing solvents). In 2023, PPPL complied with permit limits for surface water and sanitary wastewater discharges. PPPL was honored with an award for EPEAT-certified electronics purchasing from the Global Electronics Council on July 27, 2023.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

High Energy Physics Network Requirements Review: One-Year Update

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education (R&E) networking community. In April 2022, ESnet and the Office of High Energy Physics (HEP) of the DOE SC organized an ESnet requirements review of HEP-supported activities. Preparation for the review included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about the group’s relationship to the HEP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward. A series of pre-planning meetings better prepared case study authors for this task, along with guidance on how the review would proceed in a virtual fashion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Biological and Environmental Research Network Requirements Review (Final Report)

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education (R&E) networking community. Between August 2022 and April 2023, ESnet and the Office of Biological and Environmental Research (BER) of the DOE SC organized an ESnet requirements review of BER-supported activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the BER ESS program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward. A series of pre-planning meetings better prepared case study authors for this task, along with guidance on how the review would proceed in a virtual fashion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Turbine Aero-Thermal Technologies for 65% Combined Cycle Efficiency (Phase I Final Report)

GE Power (GEP), a division of General Electric Company, performed a gas turbine technology development program that integrated Aerodynamic and Heat Transfer advances as an important and innovative step towards the DOE goal of 65% combined cycle efficiency. Improved efficiency will also contribute towards the reduction in the cost of electricity identified by the DOE for the US through reduced fuel consumption, and through lowering the capital cost of the generating equipment. It is currently predicted that the result of this project will enable 0.40~0.65 pt in combined cycle efficiency improvement. This technology will be directly applicable to gas turbines utilizing coal gasification processes where hydrogen-rich coal-derived synthesis gas is produced with natural gas being the developmental fuel.

03 NATURAL GAS↗
DOE OSTI2020

Self-Assembly of Virus Particle Based Materials for Hydrogen Catalysis

Viruses are sophisticated protein-based containers and their self-assembly from a small number of subunits into symmetrical, monodisperse architectures has inspired the work performed under this award. We have taken advantage of the robust self-assembly of the bacteriophage P22 for the encapsulation of enzymatic cargo materials and studied their activity in energy harvesting systems. The large internal cavity of the P22 is ideal for high-capacity loading of enzymes resulting in very high local catalyst concentrations. We have exploited the self-assembly properties of the bacteriophage P22 system for the packaging of a number of different enzymes, including a [NiFe] hydrogenase as well as enzymes capable of butanol biosynthesis, to create active and stable individual “nano-reactors”. Individual viral capsid-based nanoreactors are also ideal building blocks for the construction of higher order assemblies. We have demonstrated the construction of ordered 3-D arrays from active nanoparticle building blocks to form materials with collective behavior and properties beyond those of the individual particles and capable of catalyzing multi-step reactions. The successful implementation of the work performed under this DOE grant provides us with a great deal of knowledge about directed self-assembly at multiple lengthscales for the development of bioinspired catalytic materials for energy harvesting.

08 HYDROGEN↗
DOE OSTI2022

American Made Challenges Battery Voucher Program Cooperative Research and Development Agreement (Cooperative Research and Development Final Report, CRADA Number CRD-21-17533)

Renewance is a Phase II winner of the U.S. Department of Energy Lithium-ion Battery Recycling Prize. The Prize is designed to incentivize American entrepreneurs to develop and demonstrate processes that, when scaled, have the potential to profitably capture 90% of all discarded or spent lithium-based batteries (LIB) in the Unites States for eventual recovery of key materials for re-introductions into the U.S. supply chain. The objective of this work is to enable a more efficient evaluation of battery sources for second life applications prior to ultimately being recycled, through evaluation of chemistry characteristics, projected battery lifetime, and application history. This work will develop the capability to identify groups of batteries that may be useful for second life and reduce the cost of end-of-life (EOL) LIB evaluation and repurposing. To meet the objective, NREL will use existing and new data to create a refined algorithm that could be used to evaluate batches of batteries for potential reuse based on manufacturing date and historical use characteristics. Based on current battery market prices and compiled literature data, a starting-point estimate of the market value of the batteries for reuse based on expected lifetime will be included in the algorithm. With the projected surge in LIB demand, battery second life is a new area ripe for development and investment from companies like Renewance. With so few large format batteries reaching EOL to date, this is a new market with a variety of areas for optimization and adding value. This work with Renewance is an example of how existing expertise in battery degradation at NREL can be used to reduce the cost of shifting a battery into a second life application. With these cost reductions, this work is also facilitating the development of a battery circular economy in the United States. A robust circular economy can maximize the utilization of critical metals demanded by battery technology such as nickel and cobalt while also reducing the costs of batteries in the marketplace for the many end-uses needed for the green energy transition. The supply of these metals is limited, and we face a supply chain shortage both domestically and globally unless we can ensure they are being used to their maximum potential. This research can improve the economics of a battery circular economy to make it a more likely path for EOL batteries with critical metals. CRADA benefit to DOE, Participant, and US Taxpayer: assists laboratory in achieving programmatic scope competencies, uses the laboratory's core competencies.

25 ENERGY STORAGE↗
DOE OSTI2020

U.S. HL-LHC Accelerator Upgrade Project: Q1/Q3 Cryostat Assembly and Horizontal Test (Final Design Report)

The Inner Triplet (IT) quadrupoles are the magnetic system for reaching low beta functions around the Interaction Point (IP). The triplet is made of three optical elements: Q1, Q2, and Q3. The upgrade of the Inner Triplets in the high luminosity insertions is the cornerstone of the LHC upgrade. The decision for HL-LHC heavily relies on the success of the advanced Nb 3 Sn technology that provides access to magnetic fields well beyond 9 T, allowing the maximization of the aperture of the IT quadrupoles. A 15-year-long study led by the DOE in the US under the auspices of the U.S. LARP program, and lately by other EU programs, has shown the feasibility of Nb 3 Sn accelerator magnets. The HL-LHC is expected to be the first application of accelerator-quality Nb 3 Sn magnet technology in an operating particle accelerator.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Battery State of Health Estimator: Cooperative Research and Development Final Report

NREL has developed a software tool to enable Renewance to estimate the degradation of batteries from basic information such as the type of battery and the application of that battery during its first life, so that used batteries may be evaluated for potential repurposing at low cost. This software tool utilizes NREL's BLAST-Lite battery degradation modeling code, which was updated with additional models for commercially produced lithium-ion batteries as a part of this CRADA. The software tool enables users to input details such as battery type and application so that lifetime estimates can be made without any programming or expert battery knowledge. The application input loads in saved values for parameters such as cycles per year, depth-of-discharge, and other battery operating parameters from a file defined by Renewance. These parameters may be modified to refine simulations for specific batteries. The software tool also incorporates a degradation model optimization tool, whereby existing battery degradation models may be tuned according to measured battery health. This ensures that new models still predict degradation behaviors expected from a certain battery chemistry, but with the overall degradation rate tuned to a specific battery make and model. The new model can then be saved for estimating the degradation of other similar batteries. An additional task was planned to utilize machine-learning to enable battery health diagnosis from rapid EIS measurements to accelerate the screening of used batteries. This task was not completed due to lack of available data for training a machine-learning model. CRADA benefit to DOE, Participant, and US Taxpayer: Further development of open-source software tool BLAST-Lite for predicting the lifetime of commercially produced Lithium-ion batteries (NREL SWR-22-69).

25 ENERGY STORAGE↗
DOE OSTI2023

NCSU Flux Tower Data

NCSU Flux Tower Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument descripotion Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Sonic Anemometer, 3 Condensation Particle Counters, 1 SP2, 1 POPS Start Date: 2022-06-01 End Date: 2022-9-26 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The NCSU flux tower was located next to the AMF sampling pad. The flux tower consisted of a 10 m telescoping tower. Mounted at the top of the tower was a sonic anemometer (RM Young 8000) and a Krypton Hygrometer. A sample line (¼” conductive tubing) and communication line was laid to a trailer located underneath and slightly adjacent to the tower. The sample line brought aerosol inside the trailer at 4.5 L min-1, where it was distributed between 3 CPCs (TSI 3776c, Dc ~ 2.5 nm, TSI 3771, Dc ~10nm, and TSI 3772, Dc ~40 nm) with different size cuts. Also sampling was a printed particle optical spectrometer (POPS) and a single particle soot photometer (SP2). Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

NCSU RDMA data

NCSU RDMA Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument description Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Nano-Scanning Mobility Particle (SMPS); A Radial Differential Mobility Analyzer (RDMA) coupled with 1 Condensation Particle Counter Start Date: 2022-06-01 End Date: 2022-9-26 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The NCSU RDMA was operated at a sheath-to-sample flow ratio of 5:1.5 L min−1. The RDMA was configured to scan from 5 to 55 nm. It was located into the temperature-controlled trailer adjacent to the NCSU Flux Tower to observe size distributions of the aerosols.The sample line was dried with three silica-gel driers in series, and then neutralized with X-ray neutralizer. Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

NCSU HTDMA data

NCSU HTDMA data Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument description Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Humidified Tandem Differential Mobility Analyzer; 2 Differential Mobility Analyzers (DMA1 and DMA2). Start Date: 2022-06-01 End Date: 2022-09-26 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The NCSU HTDMA was operated at a sheath-to-sample flow ratio of 5:1 L min−1. The HTDMA was configured to measure hygroscopic growth factors of dry particles with mobility diameters of D = 15, 20, 30, 40, and 50 nm at RH ~ 70%. A complete cycle for all diameters took ~30 minutes. A sample line brought aerosol inside the trailer at 2.5 L min-1, where it was distributed between NCSU RDMA (1.5 L min-1) and NCSU HTDMA (1 L min-1) lines. The sample line was dried with three silica-gel driers in series, and then neutralized with X-ray neutralizer. The sample line entered DMA1 (operated as an electrostatic classifier). Monodisperse particles with certain fractions were humidified with temperature controlled Nafion membrane immersed in water before entering DMA2 (operated in scanning mobility particle sizer). Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

NCSU Black Carbon (SP2) Data

NCSU SP2 Data Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument description Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Single Particle Soot Photometer (SP2) Start Date: 2022-06-01 End Date: 2022-09-27 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The SP2 was located in the temperature-controlled trailer adjacent to the NCSU Flux Tower to observe refractory black carbon (rBC) number concentration and mixing states of black carbon. The sample line brought aerosol inside the trailer at 4.5 L min-1, where it was distributed between 3 CPCs (TSI 3776c, Dc ~ 2.5 nm, TSI 3771, Dc ~10nm, and TSI 3772, Dc ~40 nm) with different size cuts, a printed particle optical spectrometer (POPS), and SP2. Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

ARIES Network Requirements Review

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all of its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. On May 1, 2021, ESnet and the DOE Office of Energy Efficiency and Renewable Energy (EERE), organized an ESnet requirements review of the ARIES (Advanced Research on Integrated Energy Systems) platform. Preparation for this event included identification of key stakeholders to the process: program and facility management, research groups, technology providers, and a number of external observers. These individuals were asked to prepare formal case study documents in order to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗