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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Observation of Double Excitations in the Resonant Inelastic X-ray Scattering of Nitric Oxide

The nitrogen K-edge resonant inelastic X-ray scattering (RIXS) map of nitric oxide (NO) has been measured and simulated to provide a detailed analysis of the observed features. High-resolution experimental RIXS maps were collected using an in situ gas flow cell and a high-transmission soft X-ray spectrometer. Accurate descriptions of the ground, excited, and core-excited states are based upon restricted active space self-consistent-field calculations using second order multiconfigurational perturbation theory. The nitrogen K-edge RIXS map of NO shows a range of features that can be assigned to intermediate states arising from 1s → π* and 1s → Rydberg excitations; additional bands are attributed to doubly excited intermediate states comprising 1s → π* and π → π* excitations. These results provide a detailed picture of RIXS for an open-shell molecule and an extensive description of the core-excited electronic structure of NO, an important molecule in many chemical and biological processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

USEEIO v2.0, The US Environmentally-Extended Input-Output Model v2.0

USEEIO v2.0 is an environmental-economic model of US goods and services that can be used for life cycle assessment, footprinting, national prioritization, and related applications. This paper describes the development of the model and accompanies the release of a full model dataset as well as various supporting datasets of national environmental totals by US industry. Novel methodological elements since USEEIO v1 models include waste sector disaggregation, final demand vectors for US consumption and production, a domestic form of the model that can be used to separate domestic and foreign impacts, and price adjustment matrices for converting outputs to purchaser price and in various US dollar years. Improvements in modeling national totals of industry and environmental flows are described. The model is validated through reproduction of national totals from input data sources and through analysis of changes from the most recent complete USEEIO model that can be explained based on data updates or method changes. The model datasets can all be reproduced with open source software packages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Nonlinear error field response in the presence of plasma rotation and real frequencies due to favorable curvature

This works describes the interaction of an phenomenon known to arise in tokamak fusion experiments with the magnetic perturbations that can arise at the edge of such experiments. We present nonlinear NIMROD resistive MHD simulations of the response of a rotating plasma to an error field when the plasma has weakly damped linear tearing modes (TMs), stabilized by a pressure gradient and favorable curvature. The favorable curvature leads to the Glasser effect: the occurrence of real frequencies and stabilization with positive stability index Δ'.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Comparison of edge turbulence characteristics between DIII-D and C-Mod simulations with XGC1

The physical processes taking place at the separatrix and scrape-off layer regions are crucial for the operation of tokamaks as they govern the interaction of hot plasma with the vessel walls. Numerical modeling of the edge with state-of-the-art codes attempts to elucidate the complex interactions between neoclassical drifts, turbulence, poloidal and parallel flows that control the physical set-up of the SOL region. Here, we present post-processing analysis of simulation results from the gyrokinetic code XGC1, comparing and contrasting edge turbulence characteristics from a simulation of the DIII-D tokamak against a simulation of the Alcator C-Mod tokamak. We find that the equilibrium ExB flux across the separatrix has a similar poloidal pattern in both discharges which can be explained by rB-drifts and trapped ion excursions. Furthermore, collisionality is noted to play a major role in the way that it prevents local charge accumulations from having more global effects in the C-Mod case. In both cases, turbulent electron heat flux is observed to be higher than the ion one and is possibly related to the need of electrons to maintain quasineutrality through the only channel available to them for exiting the confinement. By Fourier analysis, we identify turbulent frequencies and growth rates of the dominant mode in both simulations. In the case of C-Mod, these numbers point to the presence of a drift wave. In the DIII-D case, further linear simulations with the Gene code reveal a trapped electron mode. Furthermore, using a blob detection and tracking tool, we present the amplitude and size distributions of the blobs from both simulations. The amplitude distributions are in qualitative agreement with experimental observations while the size distributions are consistent with the fact that most of the blobs are not connecting to the divertor plates and suggest that they are generated by the shearing of the turbulent modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Thermal conductivity modeling of monodispersed microspheres using discrete element method

Particle beds are widely used in various systems and processes, such as particle heat exchangers, granular flow reactors, and additive manufacturing. Accurate modeling of the thermal conductivity of particle beds and understanding of their heat transfer mechanisms are important. However, previous models were based on simple cubic packing of particles, which could not accurately represent the actual heat transfer processes under certain conditions. Here, we examine the effect of the packing structure on the thermal conductivity of particle beds. We use monodispersed silica microspheres with average particle sizes ranging from 23 to 330 μm as a model material. We employ a transient hot-wire technique to measure the thermal conductivity of the particle beds with packing density of 43%–57% within a temperature range of room temperature to 500 °C and under N2 gaseous pressures of 20–760 Torr. We then use a discrete element method (DEM) to obtain the realistic packing structure of the particles, which is then fed into a finite-element model (FEM) to calculate the thermal conductivity, with the consideration of solid conduction, gas conduction, and radiation heat transfer. Our results show that the thermal conductivity model based on the more realistic random packing structure derived from the DEM shows better agreement with the experimental data compared to that based on the simple cubic-packing structure. The combined DEM and FEM methodology can serve as a useful tool to predict the effective thermal conductivity of particle beds and to quantify different heat transfer mechanisms under various conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

Accelerating multilevel Markov Chain Monte Carlo using machine learning models

Here, this work presents an efficient approach for accelerating multilevel Markov Chain Monte Carlo (MCMC) sampling for large-scale problems using low-fidelity machine learning models. While conventional techniques for large-scale Bayesian inference often substitute computationally expensive high-fidelity models with machine learning models, thereby introducing approximation errors, our approach offers a computationally efficient alternative by augmenting high-fidelity models with low-fidelity ones within a hierarchical framework. The multilevel approach utilizes the low-fidelity machine learning model (MLM) for inexpensive evaluation of proposed samples thereby improving the acceptance of samples by the high-fidelity model. The hierarchy in our multilevel algorithm is derived from geometric multigrid hierarchy. We utilize an MLM to accelerate the coarse level sampling. Training machine learning model for the coarsest level significantly reduces the computational cost associated with generating training data and training the model. We present an MCMC algorithm to accelerate the coarsest level sampling using MLM and account for the approximation error introduced. We provide theoretical proofs of detailed balance and demonstrate that our multilevel approach constitutes a consistent MCMC algorithm. Additionally, we derive the expression for cost reduction due to machine learning model to facilitate cost analysis of the hierarchical sampling algorithm. Our technique is demonstrated on a standard benchmark inference problem in groundwater flow, where we estimate the probability density of a quantity of interest using a four-level MCMC algorithm. Our proposed algorithm accelerates multilevel sampling by a factor of two while achieving similar accuracy compared to sampling using the standard multilevel algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Overview of FLORIS updates

In this paper, we review updates made to the FLORIS (FLOw Redirection and Induction in Steady State) open-source framework for wind farm control modeling, design and analysis. The updates are focused on improvements for large arrays of turbines - including heterogenous inflows and incorporating second-order wake steering effects - design, and analysis tools for practical application of wind farm control, and improvements to the software architecture for best practices in modularization and cooperative development.

17 WIND ENERGY↗
DOE OSTI2024

Response of salt intrusion in a tidal estuary to regional climatic forcing

Abstract Salinity distribution in a large tidal estuary is subject to estuarine adjustment under the influences of multiple physical drivers such as freshwater pulses and sea level rise, and is crucial to upstream water quality, aquaculture, and ecosystem functions of the estuary. To better understand the estuarine salinity response to climate change, the unstructured-grid Finite Volume Community Ocean Model was implemented to simulate the salt intrusion in the Delaware Bay Estuary. The model was first validated by multiple observational data sets and subsequently applied in an idealized setting to examine the response of salt front to freshwater pulses in high flow conditions, followed by a long-term drought condition supported by a multi-decadal streamflow drought analysis in the estuary. The model results showed that after the freshwater pulses the salt front location moved further upstream with sea level rise. Under the simulated long-term drought condition, the adjustment timescale of salt intrusion varies nonlinearly with sea level rise. With a significant increase in sea level rise, the adjustment timescale starts to decrease. This shift suggests a transition into a different regime where the estuary becomes more stratified, as indicated by an increasing bulk Simpson number with rising sea levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Importance of gyrokinetic exact Fokker-Planck collisions in fusion plasma turbulence

Gyrokinetic simulations of turbulence are fundamental to understanding and predicting particle and energy loss in magnetic fusion devices. Previous works have used model collision operators with approximate field-particle terms of unknown accuracy and/or have neglected collisional finite Larmor radius effects. This research moves beyond models to demonstrate important corrections using a gyrokinetic Fokker-Planck collision operator with the exact field-particle terms, in realistic simulations of turbulence in magnetically confined fusion plasmas. The exact operator shows significant corrections for temperature-gradient-driven trapped electron mode turbulence and zonal flow damping, and for microtearing modes in a Joint European Torus pedestal under ITER-like wall conditions. Analysis of the corrections using parameter scans motivates an accurate model which closely reproduces the exact results while reducing computational demands.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Phase 1 Specifications and preliminary sensitivity analyses of the OECD-NRC liquid metal fast reactor core thermal-hydraulics benchmark

The developments in wire-wrapped fuel bundle thermal-hydraulics research have become increasingly diverse and this makes comparisons across studies difficult. This paper describes an ongoing benchmark that will address this issue by directly comparing computational results with experimental data from two unique wire-wrapped thermal-hydraulic facilities. Preliminary subchannel sensitivity / uncertainty analyses show largely expected behavior for the presented cases, where rod diameter and friction factor show the greatest sensitivities to geometrical perturbations. Guidelines for computational fluid dynamics evaluations have been prepared and highlight the need for consolidated modeling strategies. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Observation, Analysis, and Recommendations for ND Management Reviews (W88-0/Mk5 ALT 370 Program Report)

Progress and status reviews allow teams to provide updates and targeted information designed to inform the customer of progress and to help the customer understand current risks and challenges. Both presenters and the customer should have well-calibrated expectations for the level of content and information. However, what needs to be covered in systems-level management reviews can too often be poorly defined. These unclear expectations can lead teams to overpreparing or attempting to guess what information the customer considers as most critical. This aspect of the review process is stressful, disruptive, and bad for morale – and time spent overpreparing reports is time spent not focusing on the technical work necessary to stay on schedule. To define and address these issues, this report was designed to observe various aspects of development program coordination and review activities for NNSA and Navy customers, and then to conduct unbiased, independent Human Factors observation and analysis from an outside perspective. The report concludes with suggestions and recommendations for improving the efficiency of information flow related to reviews, with the goals of increasing productivity and benefitting both Sandia and the customer.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Response Of Salt Intrusion In A Tidal Estuary To Regional Climatic Forcing (FVCOM Output for the baseline scenario)

Salinity distribution in a large tidal estuary is subject to estuarine adjustment under the influences of multiple physical drivers such as freshwater pulses and sea level rise, and is crucial to upstream water quality, aquaculture, and ecosystem functions of the estuary. To better understand the estuarine salinity response to climate change, the unstructured-grid Finite Volume Community Ocean Model was implemented to simulate the salt intrusion in the Delaware Bay Estuary. The model was first validated by multiple observational data sets and subsequently applied in an idealized setting to examine the response of salt front to freshwater pulses in high flow conditions, followed by a long-term drought condition supported by a multi-decadal streamflow drought analysis in the estuary. The model results showed that after the freshwater pulses the salt front location moved further upstream with sea level rise. Under the simulated long-term drought condition, the adjustment timescale of salt intrusion varies nonlinearly with sea level rise. With a significant increase in sea level rise, the adjustment timescale starts to decrease. This shift suggests a transition into a different regime where the estuary becomes more stratified, as indicated by an increasing bulk Simpson number with rising sea levels. These findings have been summarized into a journal manuscript. The data included in this information release request are FVCOM model output associated with the numerical simulations described in the journal manuscript.

Liu, Jinliang↗
DOE OSTI2020

PFLOTRAN-SIP: A PFLOTRAN Module for Simulating Spectral-Induced Polarization of Electrical Impedance Data

Spectral induced polarization (SIP) is a non-intrusive geophysical method that collects chargeability information (the ability of a material to retain charge) in the time domain or its phase shift in the frequency domain. Although SIP is a temporal method, it cannot measure the dynamics of flow and solute/species transport in the subsurface over long times (i.e., 10–100 s of years). Data collected with the SIP technique need to be coupled with fluid flow and reactive-transport models in order to capture long-term dynamics. To address this challenge, PFLOTRAN-SIP was built to couple SIP data to fluid flow and solute transport processes. Specifically, this framework couples the subsurface flow and transport simulator PFLOTRAN and geoelectrical simulator E4D without sacrificing computational performance. PFLOTRAN solves the coupled flow and solute-transport process models in order to estimate solute concentrations, which were used in Archie’s model to compute bulk electrical conductivities at near-zero frequency. These bulk electrical conductivities were modified while using the Cole–Cole model to account for frequency dependence. Using the estimated frequency-dependent bulk conductivities, E4D simulated the real and complex electrical potential signals for selected frequencies for SIP. These frequency-dependent bulk conductivities contain information that is relevant to geochemical changes in the system. This study demonstrated that the PFLOTRAN-SIP framework is able to detect the presence of a tracer in the subsurface. SIP offers a significant benefit over ERT in the form of greater information content. It provided multiple datasets at different frequencies that better constrained the tracer distribution in the subsurface. Consequently, this framework allows for practitioners of environmental hydrogeophysics and biogeophysics to monitor the subsurface with improved resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Extreme wind shear events in US offshore wind energy areas and the role of induced stratification

As the offshore wind industry emerges on the US East Coast, a comprehensive understanding of the wind resource – particularly extreme events – is vital to the industry's success. Such understanding has been hindered by a lack of publicly available wind profile observations in offshore wind energy areas. However, the New York State Energy Research and Development Authority recently funded the deployment of two floating lidars within two current lease areas off the coast of New Jersey. These floating lidars provide publicly available wind speed data from 20 to 200 m height with a 20 m vertical resolution. In this study, we leverage a year of these lidar data to quantify and characterize the frequent occurrence of high-wind-shear and low-level-jet events, both of which will have a considerable impact on turbine operation. In designing a detection algorithm for these events, we find that the typical, non-dimensional power-law-based wind shear exponent is insufficient to identify many of these extreme, high-wind-speed events. Rather, we find that the simple vertical gradient of wind speed better captures the events. Based on this detection method, we find that almost 100 independent events occur throughout the year with mean wind speed at 100 m height and wind speed gradient of 16 m s -1 and 0.05 s -1 , respectively. The events have strong seasonal variability, with the highest number of events in summer and the lowest in winter. A detailed analysis reveals that these events are enabled by an induced stable stratification when warmer air from the south flows over the colder mid-Atlantic waters, leading to a positive air–sea temperature difference.

17 WIND ENERGY↗
DOE OSTI2020

The Role of Innovation in the Circularity of EV Lithium-Ion Batteries

This case study analysis highlights the role of innovations in EV battery design (cells, modules, and packs), reverse supply chain, and recycling processes in yielding value for the economics of recycling (and have the largest impact on the circularity of LIBs). Part of the assessment of value will be a semi-quantitative evaluation of the value of resilience in the rapidly evolving LIB market – i.e., there are a variety of risks that recyclers would face in making a financial commitment to a recycling facility including; the possibility that batteries would not be collected in sufficient quantities, the market for key constituents (e.g., cobalt) might decrease because of changes in battery chemistry, battery manufacturers may not be willing to pay as much for recycled material, etc. The analysis would be semi-quantitative in that two simple models would be used to assess 1. material flows using a previously developed excel-based reverse supply chain flows model, and 2. A LIB recycling process material and energy balance cost model that will be used to qualitatively assess the cost impacts of process innovations and changes in feed streams. Both sets of models are highly speculative in that they rely on a multitude of assumptions and input values (e.g., EV adoption rates) that vary widely in the literature. Additionally, the initial process flow diagrams and equipment lists for the recycling cost model are based on the Argonne EverBatt model, which is still under development. However, in combination with a critical review of the literature, economic modeling can yield valuable insights into the role of innovation in the circularity of LIBs and high-technology (“energy relevant”) products in general.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2024

Radiatively cooled magnetic reconnection experiments driven by pulsed power

We present evidence for strong radiative cooling in a pulsed-power-driven magnetic reconnection experiment. Two aluminum exploding wire arrays, driven by a 20 MA peak current, 300 ns rise time pulse from the Z machine (Sandia National Laboratories), generate strongly driven plasma flows (MA≈7) with anti-parallel magnetic fields, which form a reconnection layer (SL≈120) at the mid-plane. The net cooling rate far exceeds the Alfvénic transit rate (τcool−1/τA−1≫1), leading to strong cooling of the reconnection layer. We determine the advected magnetic field and flow velocity using inductive probes positioned in the inflow to the layer, and inflow ion density and temperature from analysis of visible emission spectroscopy. A sharp decrease in x-ray emission from the reconnection layer, measured using filtered diodes and time-gated x-ray imaging, provides evidence for strong cooling of the reconnection layer after its initial formation. X-ray images also show localized hotspots, regions of strong x-ray emission, with velocities comparable to the expected outflow velocity from the reconnection layer. These hotspots are consistent with plasmoids observed in 3D radiative resistive magnetohydrodynamic simulations of the experiment. X-ray spectroscopy further indicates that the hotspots have a temperature (170 eV) much higher than the bulk layer (≤75 eV) and inflow temperatures (about 2 eV) and that these hotspots generate the majority of the high-energy (>1 keV) emission.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Experimental and modeling study of the effect of confinement on the thermal decomposition of organic materials

Simultaneous Thermal Analysis is widely used to study thermal decomposition of a variety of organic materials, and the choice of experimental conditions is very important to obtain reliable mass loss and heat flow curves. Here in this work we investigate the effect of confinement on the thermal decomposition of organic materials. As an example, we explore high-density polyethylene (HDPE) and one of its pyrolysis products, namely eicosane (C 20 H 42 ), through experiments and modeling in open crucibles and crucibles closed with a pierced lid. A new model is developed for evaporation and sublimation from open and pinhole thermal-analysis pans. It considers the kinetic resistance of evaporation at the liquid-vapor interface, inhibition of evaporation by buildup of vapor inside the pan, thermal expansion of vapor inside the pan, and diffusion of vapor from the pan. The model is validated using simultaneous heat-flow and mass-loss measurements of n-eicosane evaporation for various pinhole sizes, down to 50 µm. The importance of product evaporation inhibition for measuring polymer decomposition was demonstrated using HDPE. This study sheds light on the effect of confinement on the mass loss rate of organic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗