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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Computational fluid dynamics analysis of char conversion in Sandia’s pressurized entrained flow reactor

Design and analysis of practical reactors utilizing solid feedstocks rely on reaction rate parameters that are typically generated in lab-scale reactors. Evaluation of the reaction rate information often relies on assumptions of uniform temperature, velocity, and species distributions in the reactor, in lieu of detailed measurements that provide local information. This assumption might be a source of substantial error, since reactor designs can impose significant inhomogeneities, leading to data misinterpretation. Spatially resolved reactor simulations help understand the key processes within the reactor and support the identification of severe variations of temperature, velocity, and species distributions. In this work, Sandia’s pressurized entrained flow reactor is modeled to identify inhomogeneities in the reaction zone. Tracer particles are tracked through the reactor to estimate the residence times and burnout ratio of introduced coal char particles in gasifying environments. The results reveal a complex mixing environment for the cool gas and particles entering the reactor along the centerline and the main high-speed hot gas reactor flow. Furthermore, the computational fluid dynamics (CFD) results show that flow asymmetries are introduced through the use of a horizontal gas pre-heating section that connects to the vertical reactor tube. Computed particle temperatures and residence times in the reactor differ substantially from the idealized plug flow conditions typically evoked in interpreting experimental measurements. Furthermore, experimental measurements and CFD analysis of heat flow through porous refractory insulation suggest that for the investigated conditions (1350 °C, <20 atm), the thermal conductivity of the insulation does not increase substantially with increasing pressure.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

A three-dimensional pore-scale model for redox flow battery electrode design analysis

A three-dimensional (3-D) pore-scale model has been developed to construct multiscale fibrous electrodes for redox flow batteries (RFB). New designs, such as biporous electrodes modify electrode structures by creating secondary pores on single carbon fiber to reduce internal battery resistance. Existing pore-scale models only resolve electrodes to the single carbon fiber scale and cannot incorporate recent multiscale electrode designs into numerical models. Our new model aims to bridge this gap and provide a tool to rapidly screen new electrode configurations. Two multiscale electrodes, laser-perforated and biporous electrodes, were investigated at varying operation conditions with the proposed 3-D pore-scale models. The laser-perforated electrode exhibits a reduced pressure drop, but follows the same permeability correlation compared to the corresponding pristine electrode. For the biporous electrode, the added specific surface area and faster reaction kinetics from the secondary pores are the most influential factors leading to improved battery efficiency. However, operating the biporous electrode in limiting current density conditions should be avoided due to the decreased mass transfer efficiency and a more significant voltage loss. Finally, we believe that our 3-D pore-scale model can accelerate the flow battery electrode design process and provide new insights into electrode geometry optimizations.

25 ENERGY STORAGE↗
DOE OSTI2023

VISILIENCE: An Interactive Visualization Framework for Resilience Analysis using Control-Flow Graph

Soft errors have become one of the major concerns for the error resilience of HPC applications, as those errors can cause HPC applications to generate serious outcomes such as Silent Data Corruptions (SDCs). A large body of approaches has been proposed to analyze the resilience of HPC applications. However, existing studies rarely address the challenges of the analysis result perception. Specifically, resilience analysis techniques often produce a massive volume of unstructured data, making it difficult for programmers to conduct the resilience analysis due to non-intuitive raw data. Furthermore, different analysis models produce diverse results with multiple levels of details, which may create hurdles to compare and explore the resilience of HPC program execution. To this end, we present VISILIENCE, an interactive VISual resILIENCE analysis framework to allow programmers to facilitate the resilience analysis of HPC applications. In particular, VISILIENCE leverages an effective visualization approach Control Flow Graph (CFG) to present a function execution. In addition, three widely-used models for resilience analysis (i.e., Y-Branch, IPAS, and TRIDENT) are seamlessly embedded into the framework for resilience analysis and result comparison. Multiple case studies have been conducted to demonstrate the effectiveness of our proposed framework VISILIENCE.

Jiang, Hailong↗
DOE OSTI2025

S AP F LOWER : an automated tool for sap flow data preprocessing, gap-filling, and analysis using deep learning

Sap flow, a critical process in plant water use and ecosystem water cycles, is often measured using thermal dissipation probes (TDP) due to their ease of installation and continuous data collection. However, sap flow data frequently include noise, outliers, and gaps, creating challenges for analysis and requiring substantial manual processing. We developed S AP F LOWER , a tool that automates data preprocessing, model training, gap-filling, sapwood area scaling and modeling, and water use analysis. It integrates autocleaning, machine learning and deep learning models (e.g. random forest, Gaussian process regression, long short-term memory (LSTM), bidirectional LSTM (BiLSTM)), and efficient workflows to process sap flow data. S AP F LOWER can remove over 90% of noisy data while preserving legitimate variations and achieve high accuracy in gap-filling based on user-determined parameters. Random forest, LSTM, and BiLSTM models reduced root mean square error to 10% or less for long-term gaps. Model training and prediction can be performed efficiently within seconds. S AP F LOWER significantly enhances the efficiency and accessibility of TDP data analysis by automating complex tasks, enabling researchers without programming expertise to employ advanced techniques. Future improvements will focus on species-specific corrections for TDP and support for additional measurement methods. S AP F LOWER is openly available on GitHub (https://github.com/JiaxinWang123/SapFlower) and Zenodo (doi: 10.5281/zenodo.13665919).

ecosystem water balance↗
DOE OSTI2024

Analysis and design of fast flow liquid Li divertor for fusion nuclear science facility (FNSF) using coupled plasma boundary and LM MHD/heat transfer codes *

The SOLPS-ITER code is utilized to analyze the boundary plasma associated with a fast-flow lithium (Li) divertor configuration in the fusion nuclear science facility (FNSF) tokamak and identify operational regimes with acceptable divertor and core conditions. Plasma transport from the SOLPS-ITER code has been coupled with a liquid metal (LM) MHD/heat transfer code to model a Li open-surface divertor design and assess its impact on the scrape-off-layer (SOL) and core plasma performance. Simulations with only Neon (Ne) impurity seeding have been conducted to evaluate its impact on meeting FNSF design demands for the divertor and upstream plasma parameters. Simulation results indicate that Ne seeding significantly mitigates divertor heat flux but potentially reduces both upstream electron and main ion density due to fuel dilution. The combined application of Ne seeding and deuterium (D 2 ) puffing is required to satisfy the FNSF design requirements on upstream density ($n^{OMP}_{e,sep}$~1× 10 20 m -3 ) and divertor energy flux ($q^{Odiv}_{\bot,max}$<10 MW m -2 ). D 2 puffing plays a role in counteracting upstream density drops and augmenting energy and momentum losses through atomic and molecular processes. The inlet Li flow velocity is systematically varied across a wide range to identify acceptable flows and corresponding LM surface temperatures. This comprehensive analysis identifies the acceptable Li flow parameters, LM surface temperature, and emitted Li fluxes necessary to meet the major design constraints. The emitted Li fluxes exhibit minimal impact on the main plasma at surface temperatures up to approximately ~525 °C, corresponding emitted Li fluxes of up to φ Li ~2X10 23 atoms s -1 . Uncertainties in the Li emission processes from the surface are also investigated, primarily influencing Li loss in the lower surface temperature range (<525 °C), with simulation results indicating a minor impact on the divertor and upstream plasma. Conversely, evaporation predominantly drives the Li loss processes at higher surface temperature ranges (>525 °C), contaminating both the divertor and upstream plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Flow Injection Electrochemical Quartz Crystal Microbalance with ICP-OES Detection: Electroprecipitation and Stripping of Lanthanum and Neodymium in a Flow Cell

We used an improved version of our hyphenated analysis technique, flow injection electrochemical quartz crystal microbalance (EQCM) with inductively coupled optical emission spectroscopy, to investigate the electroprecipitation of lanthanum and neodymium from flowing solutions. The improved version has two independent flow injection circuits, allowing different conditions for electrochemical precipitation (pH=4.3 or 2.6) and quick stripping (2% HNO3) with EQCM mass detection and ICP-OES elemental analysis. Lanthanum or neodymium ions in a 500 uL sample were injected into a carrier stream and deposited onto an EQCM housed in a micro flow cell, owing to a localized high-pH layer. The deposits are subsequently stripped from the electrode using HNO3 and analyzed downstream using an ICP-OES. We found that using acidic solutions without supporting electrolyte leads to an increase of the amount of lanthanum detected by 4-fold. The enhanced deposition can be attributed to enhanced mass transfer by migration. Furthermore, we showed that by applying chronopotentiometry, we can detect a change in the hydrogen evolution reaction mechanism that enables the precipitation of lanthanides on the surface of the electrode. Understanding and enhancing the deposition of lanthanides is relevant for elemental or isotopic detection in nuclear forensics.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Supply Chain Energy and Greenhouse Gas Analysis Using the Materials Flows through Industry (MFI) Tool: Examination of Decarbonization Technology Scenarios for the U.S. Glass Manufacturing Sector

Glass manufacturing is a major part of the U.S. economy, and glass products in multiple sectors - flat glass, container glass, and fiberglass - are a part of everyday life. Despite glass manufacturing's long history, there are still many opportunities for glass production to improve in terms of both in overall energy consumption and greenhouse gas (GHG) emission reduction. Scenarios for the flat, container, and fiberglass sectors show the effect that each improvement has on primary energy demand and GHG emissions, starting from an industry baseline that reflects current manufacturing practices. Using the National Renewable Energy Laboratory's Material Flows through Industry tool, multiple scenarios are examined for each glass sector by applying a combination of energy reduction, increased electrification, hydrogen cofiring, a more renewable electric grid, and increased use of cullet. Additional decarbonization options are possible for glass but are left for later analysis due to cost, feasibility, or data issues. Primary energy demand can be reduced by 75%-83% compared to baseline inputs, depending on the sector, and GHG emissions are reduced by 82%-86%. Applying the maximum level of improvements listed here has the potential to save over 300 million GJ and 25 million metric tons of GHGs by 2050.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Manipulation and statistical analysis of the fluid flow of polymer semiconductor solutions during meniscus-guided coating

Recent work in structure–processing relationships of polymer semiconductors have demonstrated the versatility and control of thin-film microstructure offered by meniscusguided coating (MGC) techniques. Here, we analyze the qualitative and quantitative aspects of solution shearing, a model MGC method, using coating blades augmented with arrays of pillars. The pillars induce local regions of high strain rates—both shear and extensional—not otherwise possible with unmodified blades, and we use fluid mechanical simulations to model and study a variety of pillar spacings and densities. We then perform a statistical analysis of 130 simulation variables to find correlations with three dependent variables of interest: thin-film degree of crystallinity and transistor field-effect mobilities for charge-transport parallel (Μ para ) and perpendicular (Μ perp ) to the coating direction. Our study suggests that simple fluid mechanical models can reproduce substantive correlations between the induced fluid flow and important performance metrics, providing a methodology for optimizing blade design.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Wind Conditions for Solar Energy Facility Design Based on Field Measurements at Nevada Solar One

This study characterises near-surface wind conditions at the Nevada Solar One (NSO) concentrated solar power plant using two years of measurements from a 15-m mast located 30 m west of the solar arrays. The surrounding terrain is fairly flat within 3 km, but nearby solar photovoltaic (PV) and concentrated solar power (CSP) installations introduce strong directional wind inhomogeneity, which motivates a sector-based analysis that distinguishes undisturbed inflow from waked flow. The analysis uses data from three sonic anemometers to assess whether turbulence in the surface layer can be represented as Gaussian and whether standard surface-layer scaling remains valid below 10 m height. The roughness length and displacement height are estimated for twelve directional sectors under near-neutral wind conditions, and all three velocity components show departures from Gaussian behaviour. Spectral analysis indicates that the turbulence contains low-frequency fluctuations with amplitudes higher than those predicted by standard models such as the Kaimal model or the Simiu and Scanlan model. The study introduces a new turbulence spectral model based on the eddy-surface-layer framework to better represent near-surface wind turbulence. The analysis further quantifies the influence of the surrounding power plants on mean wind profiles, one-point spectra, and vertical coherence for all velocity components. The solar collector arrays located 30 m east of the mast significantly modify the turbulence structure, whereas PV installations situated a few hundred metres away have only a limited influence on the turbulence measured at the mast. These findings highlight the limitations of conventional turbulence models for near-surface wind over solar infrastructure and provide improved parameterisations to support the structural design. The implications for the structural response of parabolic troughs and PV modules to such turbulence remain uncertain and require further investigation.

14 SOLAR ENERGY↗
DOE OSTI2024

Open aperture flow cells for on-line optical analysis of process fluids

A flow cell system includes a vessel and a fluid located in the vessel. A fluid surface of the fluid can be vented to a first gas pressure. The fluid surface can have a first cross-sectional area. The flow cell system includes a conduit in fluid communication with the vessel and positioned downstream of the vessel. The conduit can have a region that includes one or more orifices and has a second cross-sectional area. The second cross-sectional area can be less than the first cross-sectional area. The one or more orifices can be vented to a second gas pressure. The second gas pressure can be equal to or greater than the first gas pressure. Methods for analyzing a process fluid can include characterizing the fluid in the conduit.

Launiere, Cari A.↗
DOE OSTI2020

Wave function analysis with a maximum flow algorithm

An efficient algorithm for computing the maximum-flow path in a network is applied to the identification of the dominant configuration state functions (CSFs) in a graphically contracted function (GCF), configuration interaction, wave function. The flow network is a space of spin-adapted CSFs represented by a Shavitt graph, wherein the nodes correspond to orbital occupations and spin quantum numbers. The graph nodes are connected by arcs, and an arc density is defined as sums of the associated squared CSF coefficients. A max-min approach determines an upper bound to the maximum possible incoming flow for each graph node. A backtracking step generates a candidate walk and is followed by a limited search of alternative branching paths for the dominant CSF. The arc density contributions are removed from the graph, and the algorithm is reapplied to the updated graph. This list of generated walks can be partitioned in order to guarantee that the dominant CSFs have been identified. All of the steps in this algorithm are computationally efficient and do not depend on the potentially large dimension of the underlying linear CSF expansion space. An analysis of low-lying valence states of C-2 illustrates the method.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Dynamic Heat Flow and Current Distribution Analysis in the Bottom Anode of an Electric Arc Furnace Using Fiber-Optic Sensors

A reliable method for monitoring bottom anode wear during DC Electric Arc Furnace (DC-EAF) operation is of critical importance for safe and efficient steel production. Underestimation of bottom wear poses a serious safety risk that must be avoided, while overestimation of bottom wear also poses challenges, as premature anode replacement is expensive and affects EAF productivity. Previously, we demonstrated that fiber-optic sensors can be successfully deployed to create a spatially distributed temperature map to monitor the health of the anode. The present work explores the heat flow and current density distribution in bottom anode pins to predict bottom wear, steel penetration events, and monitor refractory erosion. Small dynamic variations in pin temperature induced by joule heating during arcing also provide a means to observe local current flows in each pin. When mapped, these measurements provide a real-time view of the non-uniform and dynamic current flow in the bottom anode during EAF operation that can affect bottom wear.

Bottom Anode↗
DOE OSTI2022

Closures for multicomponent reacting flows based on dispersion analysis

This work presents algebraic closure models associated with advective transport and nonlinear reactions in a Reynolds-averaged Navier-Stokes context for a system of species subject to binary reactions and transport by advection and diffusion. Expanding upon analysis originally developed for non-reactive transport in the context of Taylor dispersion of scalars, this work extends the modified gradient diffusion model explicated by Peters [N. Peters, Turbulent Combustion, Cambridge Monographs on Mechanics (Cambridge University Press, Cambridge, 2000)] and based on work by Corrsin [S. Corrsin, The reactant concentration spectrum in turbulent mixing with a first-order reaction, J. Fluid Mech. 11, 407 (1961)] beyond single-component transport phenomena and involving nonlinear reactions. The presented model forms, from this weakly nonlinear extension of the original dispersion theory, lead to an analytic expression for the eddy diffusivity matrix that explicitly captures the influence of the reaction kinetics on the closure operators. Furthermore, we demonstrate that the derived model form directly translates between flow topologies through a priori and a posteriori testing of a binary species system subject to homogeneous isotropic turbulence. Using two- and three-dimensional direct numerical simulations involving laminar and turbulent flows, it is shown that this framework improves prediction of mean quantities compared to previous results. Lastly, the presented model form, collapses to the earlier gradient diffusion and its modified version derived by Corrsin in the limits of nonreactive species and linear reactions, respectively.

42 ENGINEERING↗
DOE OSTI2025

Supply Chain Energy and Greenhouse Gas Analysis Using the Materials Flows Through Industry (MFI) Tool: Examination of Alternative Technology Scenarios for the U.S. Chemical Sector

Chemical manufacturing is a large and diverse sector of the U.S. economy, with products, fuels, and a wide assortment of materials used daily by both the public and businesses. Currently, several of the largest volume chemicals produced in the United States rely on fossil fuels as a feedstock, energy source, or both. The list of chemicals includes steam cracking products such as ethylene, propylene, benzene, and xylenes as well as products such as ammonia and methanol. The focus for this work is on platform chemicals that are both produced in the largest volume and have a high potential for subsequent processing into more specialized products. In this study, we explore several new pathways that reduce the overall energy consumption and greenhouse gas (GHG) emissions for each product. These pathways include energy efficiency measures applied to existing production methods, the use of bio‐based fuels and/or feedstocks as new production methods, and electrification of high‐energy‐input stages within current production methods. Scenarios for energy demand and GHG reduction were conducted with the National Renewable Energy Laboratory's Materials Flows through Industry tool. Projections of the energy demand and GHG emissions in 2030 and 2050 are included, using grid composition projections from the NREL ReEDS model. The alternative scenarios selected showcase the effect of realistic changes the industry could make, focusing on technologies with a high level of technical readiness.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗