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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An Approach to Dynamic Human Reliability Analysis Using the EMRALD Dynamic Risk Assessment Tool

There is a need for research into dynamic human reliability analysis (HRA) (i.e., simulation- or computation-based HRA), as many researchers have emphasized the importance of applying dynamic approaches to probabilistic safety assessments (PSAs). This study proposes the Procedure-based Investigation Method of EMRALD Risk Assessment – Human Reliability Analysis (PRIMERA-HRA), a dynamic HRA approach based on the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software developed by Idaho National Laboratory (INL). This study suggests how this software can be used to model human actions and evaluate error probabilities. The applicability of this approach is also be investigated in light of an extended loss of AC power (ELAP) scenario. This paper then discusses the major insights derived by comparing this dynamic HRA approach against the static one.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Turbulence-Resolving Simulations of Hurricane Laura (2020): Insights Into Extreme Winds and Eyewall Turbulence

Extreme weather events pose significant risks to coastal and offshore energy infrastructure. In this work, we investigate the structure of mean winds and turbulence near the surface ( z < 300 m) that occurred during Hurricane Laura in 2020 on the US Gulf Coast. To this end, we perform turbulence-resolving simulations (..delta..x = 33.33 m) that encompass the entire eyewall of Hurricane Laura by introducing a novel method that we will refer to as Moving-Mesoscale to Static-LES Integrated Coupling (MOSAIC). The simulation results are validated against surface, boundary-layer, and mid-tropospheric observations. Our analysis of the extreme wind conditions near the surface indicates that the mean wind and turbulence profiles vary greatly at and near the eyewall, resulting in extreme values of mean wind speed (U > 50 m * s-1) and turbulence kinetic energy (k ~ 50 m2 * s-2) at altitudes above 50 m . To investigate in detail the nature of turbulence within the eyewall of the storm, we conduct higher-resolution simulations (..delta..x = 11.11 m) of a portion of the hurricane. We provide a comprehensive statistical description of turbulence in the eyewall region, highlighting the need to employ ..delta..x ~ 10 m grid spacing to capture the integral length-scales near the surface, second- and higher-order central moments (i.e., skewness and kurtosis), and spectral coherence in the flow accurately. These numerical simulations provide the most detailed description of mean winds and turbulent conditions within the eyewall of a historical tropical cyclone to date, illustrating how high-resolution simulations can enhance limited turbulence measurements in hurricanes and giving insight into the extreme conditions threatening offshore and coastal infrastructure.

17 WIND ENERGY↗
DOE OSTI2022

Instability and turbulent relaxation in a stochastic magnetic field

An analysis of instability dynamics in a stochastic magnetic field is presented for the tractable case of the resistive interchange. Externally prescribed static magnetic perturbations convert the eigenmode problem to a stochastic differential equation, which is solved by the method of averaging. The dynamics are rendered multi-scale, due to the size disparity between the test mode and magnetic perturbations. Maintaining quasi-neutrality at all orders requires that small-scale convective cell turbulence be driven by disparate scale interaction. Here, the cells in turn produce turbulent mixing of vorticity and pressure, which is calculated by fluctuation-dissipation type analyses, and are relevant to pump-out phenomena. The development of correlation between the ambient magnetic perturbations and the cells is demonstrated, showing that turbulence will 'lock on' to ambient stochasticity. Magnetic perturbations are shown to produce a magnetic braking effect on vorticity generation at large scale. Detailed testable predictions are presented. The relations of these findings to the results of available simulations and recent experiments are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Influence of Realistic, Cyclic Atmospheric Cycles on the Pitting Corrosion of Austenitic Stainless Steels

Pitting corrosion was evaluated on stainless steels 304H, 304, and 316L the surfaces of which had ASTM seawater printed on them as a function of surface roughness after exposure to an exemplar realistic atmospheric diurnal cycle for up to one year. Methods to evaluate pitting damage included optical imaging, scanning electron microscopy imaging, profilometry analysis, and polarization scans. The developed cyclic exposure environment did not significantly influence pitting morphology nor depth in comparison to prior static exposure environments. Cross-hatching was observed in a majority of pits for all material compositions with the roughest surface finish (#4 finish) and in all surface finishes for the 304H composition. Evidence is provided that cross-hatched pit morphologies are caused by slip bands produced during the grinding process for the #4 finish or by material processing. Additionally, micro-cracking was observed in pits formed on samples with the #4 surface finish and was greatly reduced or absent for pits formed on samples with smooth surface finishes. This suggests that both a low RH leading to an MgCl 2 -dominated environment and a rough surface containing significant residual stress are necessary for micro-cracking. Finally, the use of various characterization techniques and cross sectioning was employed to both qualitatively and quantitatively assess pitting damage across all SS compositions and surface finishes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗
DOE OSTI2021

Mesoscale Convective Systems Dominate the Energetics of the South Asian Summer Monsoon Onset

The onset of the South Asian summer monsoon (SASM) is featured as an abrupt increase of precipitation and atmospheric column-integrated moist static energy (MSE). Using convection permitting simulations, a novel cloud tracking technique, and an MSE budget, the relative roles of mesoscale convective systems (MCSs) and non-MCS isolated deep convection in the SASM onset are studied. The analysis shows MCSs play a crucial role in the sudden increases of rainfall, diabatic MSE sources, and the subsequent enhanced export of column-integrated MSE during the onset. A “diabatic sources-energy export” plane analysis delineates the different roles of MCSs and non-MCS deep convection in the SASM onset. Although deep convection always leads to a net energy export, mesoscale organization of deep convection dominates the convection associated positive feedbacks that accelerate the energy cycle of the SASM onset. Sensitivity experiment shows that the results are insensitive to the model resolutions.

Chen, Xingchao↗
DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Neutronic Characteristics of ENDF/B-VIII.0 Compared to ENDF/B-VII.1 for Light-Water Reactor Analysis

The Evaluated Nuclear Data File (ENDF)/B-VIII.0 data library was released in 2018. To assess the new data during development and shortly after release, many validation calculations were performed with static, room-temperature benchmarks. Recently, when performing validation of ENDF/B-VIII.0 for pressurized water reactor depletion calculations, a regression in performance compared to ENDF/B-VII.1 was observed. This paper documents extensive benchmark calculations for light-water reactors performed using continuous energy Monte Carlo code with ENDF/B-VII.1 and -VIII.0 and neutronic characteristics of ENDF/B-VIII.0 are discussed and compared to those of ENDF/B-VII.1. It is our recommendation that ENDF/B data library assessment should include reactor-specific benchmark assessments, including depletion cases, such that these types of regressions may be caught earlier in the data development cycle.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Framework for a Digital Documented Safety Analysis

This framework is developed to progress the digital implementation of digital tools applied to the DOE authorization process, with future applications to NRC SAR development/review, to accelerate the design and review processes of advanced nuclear reactors. The engineering design and licensing process for nuclear reactors is currently burdened by a document-based approach that leads to duplications and errors due to a lack of traceability among numerous static documents. Changes to design information require labor-intensive manual tracing through these documents, creating a high potential for human error. The adoption of a digital ecosystem, utilizing a digital thread to link various aspects of project design and analysis, promises dynamic documentation generation, automatic updates, and error reduction. Model Based Definition (MBD) and Product Lifecycle Management (PLM) tools are central to this digital transformation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Illuminating Ligand Field Contributions to Molecular Qubit Spin Relaxation via T 1 Anisotropy

Electron spin relaxation in paramagnetic transition metal complexes constitutes a key limitation on the growth of molecular quantum information science. However, there exist very few experimental observables for probing spin relaxation mechanisms, leading to a proliferation of inconsistent theoretical models. Here we demonstrate that spin relaxation anisotropy in pulsed electron paramagnetic resonance is a powerful spectroscopic probe for molecular spin dynamics across a library of highly coherent Cu(II) and V(IV) complexes. Here, neither the static spin Hamiltonian anisotropy nor contemporary computational models of spin relaxation are able to account for the experimental T 1 anisotropy. Through analysis of the spin-orbit coupled wavefunctions, we derive an analytical theory for the T 1 anisotropy that accurately reproduces the average experimental anisotropy of 2.5. Furthermore, compound-by-compound deviations from the average anisotropy provide a promising approach for observing specific ligand field and vibronic excited state coupling effects on spin relaxation. Finally, we present a simple density functional theory workflow for computationally predicting T 1 anisotropy. Analysis of spin relaxation anisotropy leads to deeper fundamental understanding of spin-phonon coupling and relaxation mechanisms, promising to complement temperature-dependent relaxation rates as a key metric for understanding molecular spin qubits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Cable-Driven Parallel Robot (CDPR) for Panelized Envelope Retrofits: Feasible Workspace Analysis

Recent decades have seen remarkable progress in the field of robotic-assisted construction. Cable-driven parallel robots (CDPRs) emerge as promising tools for automating construction processes, due to their advantageous features such as scalability, reconfigurability, compact design, and high payload-to-weight ratio. This paper uses a simple static model to determine the feasibility of a CDPR for overclad panel installation in building envelope retrofits. Given that the building facade needs to be a subset of the CDPR’s wrench-feasible workspace, we focus on the sensitivity of the workspace concerning various cable arrangements and CDPR frame sizes (e.g., height and width extensions). Our analysis indicates that no cable arrangement satisfies the requirement of complete facade coverage and avoids cable-to-panel collisions. Thus, frame extension is needed to enhance coverage. However, in densely populated areas where width extension is limited by space constraints, height extension alone is insufficient to guarantee full facade coverage. This paper pioneers the investigation of CDPRs for panelized envelope retrofits, showcasing their advantages and limitations and paving the way for further research and development.

Liu, Yifang↗
DOE OSTI2024

Heliostat Consortium: Gap Analysis on State of the Art in Wind Load Design

Wind loads are a major driver of heliostat cost. Standardized methods and tools are needed for a more detailed understanding of the static and dynamic loads of a heliostat design. This will enable cost reduction of wind-dependent heliostats to avoid unnecessarily conservative heliostat designs and increase field efficiency and reliability to reduce the risk of component failures due to high-wind events. Gaps related to wind load include lack of site characterization for wind measurements, insufficient critical load cases for heliostat design, insufficient understanding of turbulence impacts on heliostat tracking error, lack of knowledge on wind load under various heliostat array configurations, and underexplored heliostat field wind-load reduction and operating strategies. Recommended pathway forward is to develop wind load and site characterization guidelines for heliostat design and develop heliostat field wind-load models with optical performance impacts.

aerodynamics↗
DOE OSTI2022

Multi-Probe 22A: Post shot Data and Analysis

The Multi-Probe 22A experiments took place on the Omega EP laser in March 2022. The goal was to discover issues with simultaneous x-ray and proton radiography of static and dynamic test objects. The x-ray and proton probes were generated by short-pulse laser-matter interactions. Significant crosstalk between the proton beam and x-ray detector was observed. Several static radiographs were made, including a set of proton images made with different laser energies. No dynamic objects were radiographed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Microwave-induced selective decomposition of cellulose: Computational and experimental mechanistic study

Understanding microwave-material interactions will help facilitate the utilization of microwave technology in gasification and renewable energy production. In this study, cellulose was used as a model compound to simulate the organic matter in biomass, and its catalytic decomposition under a microwave (MW) field was studied to identify structural changes from the reaction. The study was conducted using a MW source coupled to a fixed-bed gas-flow reactor, mass spectroscopic, and Fourier transform infrared spectroscopy post-reaction analysis. Zeolite 13X was chosen as a microwave absorber to study the catalytic enhancement of the decomposition of cellulose. Density functional theory (DFT) was used to gain insights into the molecular transformations occurring in the presence of a static electric field, which was used to simulate the electric field component of the microwave electromagnetic radiation. Theoretical calculations demonstrated that both the positive and negative portion of the electric field interact with the permanent dipoles of the cellulose effecting the decomposition through the glycosidic bond breaking mechanism. The theoretical result was verified using infrared spectroscopic analysis of the pure cellulose during microwave heating. The theoretical calculations suggest only the positive electric field component may be active for the cellulose decomposition in the presence of Zeolite 13X. Physically mixing Zeolite 13X with the cellulose led to a significant enhancement in the decomposition rate of the glycosidic bond. Zeolite 13X enhanced the glycosidic O-C decomposition at lower MW power (lower temperatures), whereas the O-H functional group required higher MW power (higher temperature) for its decomposition. The DFT study coupled with the reaction studies revealed that the electric field polarizability is dependent upon both the direction and the orientation of the cellulose. Gas products revealed that applying 250 W of MW power led to the production of CO, H 2 , along with some CO 2 , CH 4 , and benzene at 305 °C. Finally, reaction under 500, 750, and 1000 W of power at constant temperature (305 °C) revealed that higher power led to the complete decomposition of cellulose to mostly CO, H 2 , and CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Corrosion Response of Ni-19Cr-5Fe in Molten NaCl-MgCl 2 Salt

Ni-based alloys are strong candidates for use in high-temperature molten salt reactors due to their superior corrosion resistance and mechanical stability compared to stainless steels. In this study, the static corrosion behavior of a Ni-19Cr-5Fe model alloy was systematically evaluated in a purified molten NaCl-MgCl 2 salt at 700°C for 30, 240, and 500 h. Post-exposure analyses were conducted to assess microstructural evolution, corrosion depth, and elemental depletion profiles. Corrosion rates, quantified by chromium depletion depth, followed an inverse power-law trend with increasing exposure time, indicating diffusion-limited kinetics. This trend is attributed to limitations in mass transport in the static salt and to the progressive local depletion of reactive chromium species. Coupled electron backscatter diffraction and energy dispersive X-ray spectroscopy analysis further revealed that the grain boundary character significantly influences corrosion susceptibility: high-angle grain boundaries exhibited pronounced Cr depletion and pitting, while low-angle and Σ3 boundaries remained comparatively resistant. These results offer valuable insight into the role of microstructure in corrosion processes and reinforce the importance of time-dependent material evaluation in molten salt environments relevant to advanced reactor designs.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Detecting and tracking drift in quantum information processors

Abstract If quantum information processors are to fulfill their potential, the diverse errors that affect them must be understood and suppressed. But errors typically fluctuate over time, and the most widely used tools for characterizing them assume static error modes and rates. This mismatch can cause unheralded failures, misidentified error modes, and wasted experimental effort. Here, we demonstrate a spectral analysis technique for resolving time dependence in quantum processors. Our method is fast, simple, and statistically sound. It can be applied to time-series data from any quantum processor experiment. We use data from simulations and trapped-ion qubit experiments to show how our method can resolve time dependence when applied to popular characterization protocols, including randomized benchmarking, gate set tomography, and Ramsey spectroscopy. In the experiments, we detect instability and localize its source, implement drift control techniques to compensate for this instability, and then demonstrate that the instability has been suppressed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Possible quadrupole-order-driven commensurate-incommensurate phase transition in B20 CoGe

For this study, the B20-type cobalt germanide CoGe was investigated by measuring the specific heat, resistivity, and 59 Co nuclear magnetic resonance (NMR). We observed a phase transition at T Q = 13.7 K, evidenced by a very narrow peak of the specific heat and sharp changes of the nuclear spin-spin (T 2 –1 ) and spin-lattice ( T 1 – 1 ) relaxation rates. The fact that the entropy release is extremely small and the Knight shift is almost independent of temperature down to low temperatures as anticipated in a paramagnetic metal indicates that the T Q transition is of nonmagnetic origin. In addition, we detected a crossover scale T 0 ~ 30 K below which the resistivity and the NMR linewidth increase, and T 1 –1 is progressively distributed in space, that is, a static and dynamical spatial inhomogeneity develops. While the order parameter for the T Q transition remains an open question, a group-theoretical analysis suggests that the finite electric quadrupole density arising from the low local site symmetry at cobalt sites could drive the crystal symmetry lowering from the P2 1 3 symmetry that is commensurate to the R3 symmetry with an incommensurate wave vector, which fairly well accounts for the T Q transition. The quadrupole-order-driven commensurate-incommensurate phase transition may be another remarkable phenomenon arising from the structural chirality inherent in the noncentrosymmetric B20 family.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Enabling Cybersecurity, Situational Awareness and Resilience in Distribution Grids with High Penetration of Photovoltaics (CARE-PV) (Final Report)

Since legacy distribution systems have very limited visibility beyond the substation, high penetration of PV at the grid edge presents some unique operational challenges. One approach to address these challenges is to use information from advanced metering infrastructure (AMI) and µPMUs. However, exploiting this information is impacted by a number of factors, including multi-timescale measurements, volume of data generated, communication network impairments (e.g., information loss and latency) and susceptibility to cyber-attacks. Therefore, one of the critical tasks involved in the management of a distribution grid is to develop complete situational awareness by integrating cyber-security mechanisms with state estimation strategies and leveraging this situational awareness to assure energy services at strategic locations while exploiting AMI/PV inverter/ µPMU data. This CARE-PV project addresses the fundamental challenges in situational awareness and resilience to cyber and physical vectors by exploiting the synergy between innovative modeling, estimation, data analytics, testing and validation using smart PV inverters designed at K-State and facilities at NREL. Specifically, the project involved the development, testing and validation of the following novel enabling technologies: (Thrust 1) Resilience to cyber vectors that impact data integrity was addressed via a two-level defense strategy that combines cyber intrusion detection using self-learning, cooperative smart PV inverters, and a novel moving target defense framework to combat data integrity attacks. (Thrust 2) Resilience to cyber-physical vectors that impact situational awareness by limiting data availability was addressed via novel centralized and decentralized, sparsity-based static and dynamic state estimation approaches that enhance observability even when the underlying system is unobservable. (Thrust 3) Leveraging a unique probabilistic sensitivity analysis approach accompanied by one-of-a-kind dominant influencer set computation, the vulnerability of critical infrastructure at strategic locations was evaluated so that proactive PV-based control strategies can be used to support operations under normal/outage scenarios. These CARE-PV project innovations were demonstrated on both small-scale IEEE and larger utility-scale testbeds (Thrust 4). Feedback from Industry Advisory Board members was used to formulate a commercialization pathway for a subset of CARE-PV technologies. These CARE-PV technologies will ultimately lead to reliable and secure, large-scale integration of renewable energy and mitigate the risk of energy disruption resulting from cyber incidents and other emerging threats within the energy environment.

14 SOLAR ENERGY↗