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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The ocean model for E3SM global applications: Omega version 0.1.0 – a new high-performance computing code for exascale architectures

This paper introduces Omega, the Ocean Model for E3SM Global Applications. Omega is a new ocean model designed to run efficiently on high performance computing (HPC) platforms, including exascale heterogeneous architectures with accelerators, such as Graphics Processing Units (GPUs). Omega is written in C and uses the Kokkos performance portability library. These were chosen because they are well-supported and will help future-proof Omega for upcoming HPC architectures. Omega will eventually replace the Model for Prediction Across Scales-Ocean (MPAS-Ocean) in the US Department of Energy's (DOE's) Energy Exascale Earth System Model (E3SM). Omega runs on unstructured horizontal meshes with variable-resolution capability and implements the same horizontal discretization as MPAS-Ocean. This work documents the design and performance of Omega Version 0.1.0 (Omega-V0), which solves the shallow water equations with passive tracers and is the first step towards the full primitive equation ocean model. On Central Processing Units (CPUs), Omega-V0 is 1.4 times faster than MPAS-Ocean with the same configuration. Omega-V0 is more efficient on GPUs than CPUs on a per-watt basis – by a factor of 5.3 on Frontier and 3.6 on Aurora, two of the world's fastest exascale computers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Power Curve Working Group's assessment of wind turbine power performance prediction methods

Wind turbine power production deviates from the reference power curve in real-world atmospheric conditions. Correctly predicting turbine power performance requires models to be validated for a wide range of wind turbines using inflow in different locations. The Share-3 exercise is the most recent intelligence-sharing exercise of the Power Curve Working Group, which aims to advance the modeling of turbine performance. The goal of the exercise is to search for modeling methods that reduce error and uncertainty in power prediction when wind shear and turbulence digress from design conditions. Herein, we analyze data from 55 wind turbine power performance tests from nine contributing organizations with statistical tests to quantify the skills of the prediction-correction methods. We assess the accuracy and precision of four proposed trial methods against the baseline method, which uses the conventional definition of a power curve with wind speed and air density at hub height. The trial methods reduce power-production prediction errors compared to the baseline method at high wind speeds, which contribute heavily to power production; however, the trial methods fail to significantly reduce prediction uncertainty in most meteorological conditions. For the meteorological conditions when a wind turbine produces less than the power its reference power curve suggests, using power deviation matrices leads to more accurate power prediction. We also determine that for more than half of the submissions, the data set has a large influence on the effectiveness of a trial method. Overall, this work affirms the value of data-sharing efforts in advancing power curve modeling and establishes the groundwork for future collaborations.

17 WIND ENERGY↗
DOE OSTI2021

PV Field Performance Including Fleet and Bifacial Field Data

This presentation provides a review of two recent presentations - the 2021 PV Fleet Performance Data Initiative covered by the PVRW presentation, and bifacial system performance presented to a February DuraMAT working group. Details include degradation rate distributions from >6000 inverter channels, monthly performance vs expected, bifacial field studies of energy gain and field degradation.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Optimization of Mitigating System Performance Index to Improve Nuclear Power Plant Safety and Efficiency

MSPI (Mitigation System Performance Index) is one of the risk-informed, plant-specific performance indicators of NRC’s Reactor Oversight Process. MSPI is used by the regulator and nuclear industry to monitor and assess the performance of plant mitigating systems. In this project, a calculation tool has been developed by incorporating the plant operation data, Probabilistic Risk Assessment (PRA) data, and industry baseline values to automate the calculation process of MSPI and the generation of the report. This is the first stage in an effort to optimize the MSPI through advanced artificial intelligence (AI) and machine learning (ML) techniques to improve nuclear power plant safety and efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Nuclear Science User Facilities High Performance Computing: Provide a Science Gateway for HPC Users

Idaho National Laboratory (INL), supported by the Department of Energy Office of Nuclear Energy (DOE-NE) through the Nuclear Science User Facilities (NSUF), provides direct access to the Barracuda Virtual Reactor and 18 Multiphysics Object-Oriented Simulation Environment (MOOSE) applications via a web-based science gateway developed using Open Ondemand on the INL high performance computing (HPC) systems. This gateway features the computational tools of the Nuclear Computational Resource Center (NCRC) and the computing resources of the INL high performance computing systems. These computational tools are a key foundation of collaboration and innovation in nuclear energy systems research. High performance computing resources and INL staff directly support the mission and objectives of DOE-NE. The Barracuda Virtual Reactor was the first science gateway deployed in Jan 2021 to support NSUF users. In July 2021, the science gateway was expanded to support access to NCRC codes for use across all supported INL HPC systems. The HPC science gateway currently supports 20 total applications. The gateway also includes access to training resources specific to NCRC tools.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

TRISO Fuel Performance Evaluation

TRISO Fuel Performance Evaluation outlining design and radionuclide source term, fuel performance during normal operation, fuel performance during core heatup accidents, other accident scenarios, and GenIV VHTR Fuel and Fuel Cycle PMB.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Panel Session 80: Interagency Community of Practice in Risk and Performance Assessment

This panel focused on the status of the Inter-agency Performance and Risk Assessment Community of Practice (P and RA COP). Representatives from the P and RA COP and subject matter experts discussed lessons learned and provided feedback on building the P and RA COP to support risk-informed environmental decision making. Panelists with presentations: Understanding Mechanisms to Manage Uncertainty and Risk in Waste Containment Systems (Craig Benson, University of Virginia - CRESP (USA) Scaling for Performance Assessments (Paul Black, Katie Catlett, Doug Anderson, Paul Duffy, Tom Stockton, Sam Van Sickle, John Carson); Interagency Community of Practice in Rick and Performance Assessment (Horst Monken Fernandes); Institutional Controls as a Risk Management Tool (David Esh); Superfund: Explanation of Screening and PRG's for Risk and Dose Assessment (Stuart Walker)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Fuel Performance Modeling Plan to Support the Advance Gas Reactor Program

This report documents the current status of the fuel performance modeling initiative to support the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program in the development of tristructural-isotropic-coated fuel particles. It includes a brief summary of the codes that have been developed to support tristructural isotropic modeling along with a summary of the behavior of fuel particles during irradiation and the modeling used to capture these effects. In addition, this report identifies further modeling and material property needs for further development based on experience from previously performed AGR experiments. In general, the remaining activities to support fuel performance modeling for the AGR program include continued AGR experiment support for AGR-3/4 and AGR-5/6/7 as well as modeling improvements identified throughout the course of the program. These modeling improvements can be summarized as thermomechanical particle behavior and fission product transport. Additional modeling needs may be identified while processing the data collected during the AGR post-irradiation examination campaign and may lead to further improvements that are not included in this report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Development of a Performance Portable Non-Equilibrium Plasma Fluid Solver on Adaptive Grids

This presentation will describe the numerical techniques, programming paradigms, verification, and performance of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures. Our plasma fluid model solves the conservation equations for self-consistent electrostatic Poisson, electron and heavy species transport, and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive mesh management library, AMReX (Zhang et al., JOSS, 4 (37) 1370, 2019), and can be built and run on widely available vendor specific GPU architectures (NVIDIA/AMD/Intel). We utilize a non-subcycled second order semi-implicit time-stepping method where all adaptive mesh refinement (AMR) levels are advanced with the same time step. The composite multi-level multigrid solver from within AMReX is used for each of the governing equations that are cast into a Helmholtz equation form. We have also developed a python based chemical mechanism parser framework that uses a similar format as CANTERA (Goodwin et al., Zenodo, 2018) yaml files as input. Our custom parser reads the yaml file and provides C++ files with transport and production rate functions that can be executed on both host (CPU) and device (GPU). We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on low-pressure capacitive and high-pressure streamer discharges. Our initial performance studies indicate 10X speed-up using 20 NVIDIA GPUs versus 200 CPUs for an atmospheric streamer discharge problem solved on a 512 x 1024 x 512 grid.

graphics processing units↗
DOE OSTI2026

MARVEL Reactor Fuel Performance Report

The Microreactor Applications Research Validation and EvaLuation (MARVEL) project is producing a high temperature liquid metal-cooled nuclear test bed at Idaho National Laboratory (INL) to ultimately improve the integration of microreactors to end-user applications. This ambitious effort seeks to design, authorize, construct, test, and operate the reactor within five years. In order to construct and operate the MARVEL reactor in a timely manner, the system will utilize materials and component designs which have already been used, qualified, or licensed from previous reactors. The MARVEL reactor will be located at the INL Transient Reactor Test (TREAT) facility in the north high-bay equipment pit and will use the existing 304 stainless steel-clad U-ZrH1.6 pin-type fuel system developed by General Atomics and purchased from TRIGA International. This fuel has been previously qualified under the United States Department of Energy’s (US DOE) Reduced Enrichment for Research and Test Reactors (RERTR) Program. Even though the regulator of the MARVEL reactor is the US DOE, the standards and overall approach recommended by the Nuclear Regulatory Commission is well-defined and utilized here. Following NUREG-1537 regulatory guidance, this report documents the authorization case for the MARVEL fuel system’s application to MARVEL and establishes stable and predictable fuel performance during the most thermophysically unfavorable conditions achievable in the MARVEL reactor. To that end, this report provides a comprehensive survey of the known thermophysical properties, performance, and quantitative relationships associated with the MARVEL reactor fuel element and uses this information to determine its mechanical integrity and risk of reaching unacceptable conditions during the most extreme accident scenarios predicted for the reactor using the most conservative assumptions available. The information contained herein is compiled from a combination of historical reports and peer reviewed scientific publication manuscripts. Known mechanisms under which the fuel is susceptible to failure are highlighted and compared to conditions that could exist in the MARVEL reactor during an unanticipated transient or accident scenario. The two scenarios considered for analysis in this report are (1) an unprotected loss of flow accident and (2) a hypothetical unprotected loss of coolant accident during the loss of flow accident. Preliminary 2D steady-state analyses herein indicate that both fuel-cladding chemical interactions and fuel-cladding mechanical interactions are negligible throughout the fuel’s operational cycle under both normal and high temperature accident scenario conditions. Although higher fidelity 3D time-dependent modeling and simulations are planned, the following may be concluded presently. The MARVEL fuel element maintains its geometric stability and structural integrity during the most extreme accident scenarios predicted for the MARVEL reactor. The hoop stress during the unprotected loss of flow accident reaches about -1.27 MPa; this negative stress indicates that it is compressive rather than tensile. The compressive stress is a result of the NaK pressure on the outside of the fuel element, caused by the restricted thermal expansion of the NaK coolant, exceeding the internal pressures generated inside of the fuel element. The hoop stress generated in the cladding during the unprotected loss of coolant accident reaches a maximum of about approximately 10 MPa, which is nearly an order of magnitude less than the predicted yield strength of the cladding under high-temperature accident scenario conditions. Calculations were compared with results from high performance computational simulations using BISON and are in very close agreement. A conservative MARVEL fuel meat peak temperature limit of 900 °C is recommended presently, which is about 180 °C higher than the peak fuel temperature predicted to occur during the most extreme accident. Based on the known properties and behavior of the MARVEL fuel element, the fuel successfully meets its design and safety requirements under normal and most extreme accident conditions with a large safety margin.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Investigation of the Performance and Explainability Tradeoffs for Machine-Learning Models for Predictive Maintenance of Circulating Water Systems in Nuclear Power Plants

Predictive maintenance (PdM) has shown great potential for achieving substantial cost savings and enhancing the economic competitiveness of nuclear power plants (NPPs) in today's energy market. Among the different modeling approaches that exist, machine learning (ML) tools in particular have a demonstrated ability to handle high dimensional and multivariate data and to extract hidden relationships within data in industrial environments. While ML methods show great potential, their lack of explainability---especially for black-box models---is a major hurdle to their adoption. Moreover, considering the supposed trade-off between explainability and performance challenges, careful consideration must be made as to which of these quality aspects takes precedence in light of multiple modeling options, resource availability, and domain characteristics. The present work evaluates the performance of six ML models, each with a different degree of explainability, in classifying the conditions of circulating water pumps (CWPs) by utilizing sensor data from nuclear power plants. To determine the drivers behind the trade-offs presented by this array of models, this work also tests different combinations of CWP units as the training and testing data, degrees of data imbalance, and objective functions for hyperparameter tuning. It was found that black-box models tend to afford superior performance in cases where there are far more instances of one type of labeled data than of any other type. It is recommended that a guided procedure be followed for designing and delivering an ML system that is sufficiently explainable to all involved stakeholders.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Review of Technical Photovoltaic Key Performance Indicators and the Importance of Data Quality Routines

Technical key performance indicators (KPIs) are important metrics used to assess and quantitatively summarize various aspects of photovoltaic (PV) systems, including long-term performance, economic viability, and carbon footprint. Herein, a group of experts of the International Energy Agency's Photovoltaic Power Systems Programme Task 13 collect and describ the most important technical KPIs used in the industry. Thereby, a set of best practices for reliably handling PV system data is presented and the impact of data quality and climatic variability on KPI calculation is investigated. Further, the effective use of technical KPIs allows triggering data-driven and informed decisions to optimize PV systems and providing a comprehensive overview of how PV systems operate across different conditions and climates. With the worldwide growth of the PV industry, more companies operate/own PV systems in different regions, where the climatic and seasonal profiles differ. This requires context-aware evaluation of KPIs, or the judicious application of multiple KPIs, to ensure that each asset is evaluated correctly. Beyond that, there is untapped potential in the utilization of KPIs through geospatial mapping and extrapolation of fleet KPIs. This study demonstrates that the uncertainty in KPI estimation is not well understood and depends on data quality, climatic variability, and system configuration.

14 SOLAR ENERGY↗
DOE OSTI2021

RITE Gen5 KHPS Performance - Period B

Includes Kinetic Hydropower System (KHPS) Turbine performance data from the RITE Gen5 KHPS turbine at the 5 meter size. This data was collected over 16 days in May 2021 during Period B operation. Along with performance data, the data includes setup data, project metadata, and characteristic data for RITE Gen5 KHPS (5m) turbine.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

Re-Engineering Poly(Acrylic Acid) Binder toward Optimized Electrochemical Performance for Silicon Lithium-Ion Batteries: Branching Architecture Leads to Balanced Properties of Polymeric Binders

Silicon is a promising anode material for lithium-ion batteries with its superior capacity. However, the drastic volume changes during lithiation/delithiation cycles hinder the cycling performance, resulting in particle pulverization, conductivity loss, and an unstable electrode-electrolyte interface. In this work, a series of synthetic polymeric binders, poly(acrylic acid-co-tetra(ethylene glycol) diacrylate)-featuring a poly(acrylic acid) (PAA) backbone branched via tetra(ethylene glycol) diacrylate (TEGDA)-are developed that edge toward evidencing well-balanced properties to confront capacity fading in Si-based electrodes. The incorporation of ether chain not only leads to the branching architecture of the PAA backbone, thus affecting its mechanical properties, but also promotes the conductivity of Li ions. As a result, a synergistic performance improvement is observed in both half and full cells. The best-performing cell using a branched PAA binder (bPAA) with a feeding molar ratio ([TEGDA]:[acrylic acid(AA)]) of 0.2 results in a 10% increase in initial capacity and a 31% increase in capacity retention over 100 cycles compared to the linear PAA cell. The cross-sectional microscopic images of the cycled electrodes reveal that bPAA binders can drastically reduce the electrode expansion. This improvement results from the well-balanced properties of the polymer design, which could guide further development for more advanced binder materials.

25 ENERGY STORAGE↗
DOE OSTI2021

A Difluoro‐Monobromo End Group Enables High‐Performance Polymer Acceptor and Efficient All‐Polymer Solar Cells Processable with Green Solvent under Ambient Condition

Abstract In this paper, a difluoro‐monobromo end group is designed and synthesized, which is then used to construct a novel polymer acceptor (named PY2F‐T) yielding high‐performance all‐polymer solar cells with 15.22% efficiency. The fluorination strategy can increase the intramolecular charge transfer and interchain packing of the previous PY‐T based acceptor, and significantly improve photon harvesting and charge mobility of the resulting polymer acceptor. In addition, detailed morphology investigations reveal that the PY2F‐T‐based blend shows smaller domain spacing and higher domain purity, which significantly suppress charge recombination as supported by time‐resolved techniques. These polymer properties enable simultaneously enhanced J SC and FF of the PY2F‐T‐based devices, eventually delivering device efficiencies of over 15%, significantly outperforming that of the devices based on the non‐fluorinated PY‐T polymer (13%). More importantly, the PY2F‐T‐based active layers can be processed under ambient conditions and still achieve a 14.37% efficiency. They can also be processed using non‐halogenated solvent o ‐xylene (no additive) and yield a decent performance of 13.05%. This work demonstrates the success of the fluorination strategy in the design of high‐performance polymer acceptors, which provide guidelines for developing new all‐PSCs with better efficiencies and stabilities for commercial applications.

Yu, Han↗
DOE OSTI2021

In Situ Synthesis of Graphene-Coated Silicon Monoxide Anodes from Coa-Derived Humic Acid for High-Performance Lithium-Ion Batteries

Silicon monoxide (SiO) is attaining extensive interest amongst silicon-based materials due to its high capacity and long cycle life; however, its low intrinsic electrical conductivity and poor coulombic efficiency strictly limit its commercial applications. Here low-cost coal-derived humic acid (HA) is used as a feedstock to synthesize in-situ graphene-coated disproportionated SiO (D-SiO@G) anode with a facile method. HRTEM and XRD confirm the well-coated graphene layers on an SiO surface. Scanning Transmission X-ray Microscopy (STXM) and X-ray Absorption Near-Edge Structure (XANES) spectra analysis indicate that the graphene coating effectively hinders the side-reactions between the electrolyte and SiO particles . As a result, the D-SiO@G anode presents an initial discharge capacity of 1937.6 mAh g -1 at 0.1 A g -1 and an initial coulombic efficiency (ICE) of 78.2%. High reversible capacity (1023 mAh g -1 at 2.0 A g -1 ), excellent cycling performance ( 72.4% capacity retention after 500 cycles at 2.0 A g -1 ), and rate capability (774 mAh g -1 at 5 A g -1 ) results are substantial. Full coin cells assembled with LiFePO 4 electrodes and D-SiO@G electrodes display impressive rate performance. These results indicate a promising potential for practical use in high-performance lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Unravelling the Role of Electron Acceptors for the Universal Enhancement of Charge Transport in Quinoid-Donor-Acceptor Polymers for High-Performance Transistors

The quinoid-donor-acceptor (Q-D-A) strategy has recently emerged as a promising approach for constructing high mobility semiconducting polymers. In order to fully explore the potential of this strategy in improving the charge transport and elucidating the structure-property-performance relationships in Q-D-A polymers, a series of new polymers with different electron acceptor units and backbone coplanarity have been synthesized and characterized. In this work, all of the resulting Q-D-A polymers exhibit much more planar backbone conformations in comparison to their donor-acceptor (D-A) counterparts. Moreover, organic field-effect transistors based on Q-D-A polymers exhibit excellent effective hole mobilities in a range of 0.44 to 3.35 cm 2 V –1 s –1 , most of which are orders of magnitude higher than those of their corresponding D-A polymers. Notably, the hole mobility of 3.35 cm 2 V –1 s –1 is among the highest for the quinoidal-aromatic polymers characterized by conventional spin-coating methods. Furthermore, the role of electron acceptors in Q-D-A polymers has been comprehensively investigated. Polymers with stronger acceptor units are more inclined to deliver edge-on lamellas, high film crystallinity, small effective hole masses, and decent operational stability. The detailed structure-property-device performance relationship will pave the way toward high performance semiconducting polymers using the potent Q-D-A strategy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Impact of Linker Engineering in Core‐Linked Dimeric Acceptors for High‐Performance Organic Solar Cells

Abstract The dimerization of small molecule acceptors (SMAs) is a promising strategy for enhancing the long‐term stability and power conversion efficiency (PCE) of organic solar cells (OSCs). However, the reported DSMAs are primarily limited to end‐linked molecular configurations, highlighting the need for further exploration of various dimer architectures. Herein, the development of two distinct core‐linked dimerized SMAs (DYF‐V and DYF‐E) are reported with tailored linker structures (vinylene and ethynyl, respectively), achieving high‐performance OSCs (PCE = 18.53%). Interestingly, a subtle change in the linker structures results in markedly different molecular properties and photovoltaic performances of the dimer acceptors. DYF‐E with an ethynyl linker exhibits more twisted backbone conformation and mitigated aggregation property compared to DYF‐V, inducing desirable blend morphologies with a polymer donor including high crystallinity, face‐on oriented packing structures, and well‐intermixed domains. Thus, the DYF‐E‐based OSCs exhibit a high PCE (17.02%), which significantly outperforms the DYF‐V‐based OSCs (PCE = 9.98%). Furthermore, the ternary OSCs based on DYF‐E achieve a higher PCE of 18.53%. Thus, this study highlights the significance of selecting an appropriate linker in core‐linked dimerized SMAs for producing high‐performance OSCs.

Oh, Shinbee↗