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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Theoretical Coupling of Free-Flowing Ions and Magnetically Insulated Electrons

Magnetic insulation of electrons prevents losses and can be applied to generating radiation or electron sources for high current and high power applications. Ion emission from the anode may degrade magnetic insulation. We develop equilibrium theory, self-consistently coupling magnetically insulated electron flow with free-flowing injected ions. Generally, ion injection is self-limiting from space charge; however, once insulation strength drops below about 1.2x the magnetic insulation threshold, ion space-charge limits vanish. Further, the gap effectively short-circuits and the electron flow layer asymptotically approaches the anode. In this regime a quasineutral, nonthermal plasma manifests, effectively reducing gap distance and suggesting quasiequilibrium gap closure evolution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Membrane Profiling by Free Flow Electrophoresis and SWATH-MS to Characterize Subcellular Compartment Proteomes in Mesembryanthemum crystallinum

The study of subcellular membrane structure and function facilitates investigations into how biological processes are divided within the cell. However, work in this area has been hampered by the limited techniques available to fractionate the different membranes. Free Flow Electrophoresis (FFE) allows for the fractionation of membranes based on their different surface charges, a property made up primarily of their varied lipid and protein compositions. In this study, high-resolution plant membrane fractionation by FFE, combined with mass spectrometry-based proteomics, allowed the simultaneous profiling of multiple cellular membranes from the leaf tissue of the plant Mesembryanthemum crystallinum. Comparisons of the fractionated membranes’ protein profile to that of known markers for specific cellular compartments sheds light on the functions of proteins, as well as provides new evidence for multiple subcellular localization of several proteins, including those involved in lipid metabolism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Transient cycling of nitrogen, organic carbon and oxygen within the free-flowing Columbia River corridor: Linking exposure time dependent biogeochemical reactions to river stage fluctuations (Final project report)

The objective of this project was to develop next-generation techniques for representing the transformations of complex reaction networks like those impacting transient river-corridors, then apply them to develop upscaling tools. The project contributed significantly to the development of Lagrangian “mass transfer particle tracking” (MTPT) tools that are the first numerical framework that explicitly separates mixing and spreading processes; a crucial distinction for accurate representations of reaction rates across scales. The MTPT approach uses an operator splitting scheme where physical transport processes are simulated using classical random walk methods and each particle is treated as a “container” that carries with it any number of chemical species. Mixing between particles is simulated using a colocation-probability based mass transfer kernel and reactions are evaluated on each particle after mixing. The method is stable, accurate, and also allows the explicit modeling of residence time distributions of the individual containers of mass. The MTPT scheme allowed us to explore several research questions related to reactive transport in river corridors and complex reaction networks. We found that it is possible to quantify the exposure time distributions (ETDs) of reactants and that this does suggest some pathways to upscaling. However, comparable approximations can be obtained using simplified (reduced dimensionality) MTPT simulations in less time with similar uncertainty, so development of extensive ETD-based methods was not productive. The major findings are that i) the MTPT schemes are robust and highly accurate across a range of arbitrarily complex reactions, ii) the methods can be efficiently parallelized and the parallel performance characteristics of MTPT are predictable, and iii) the MTPT tools allow simultaneous tracking of residence time. The development of these research tools into efficient software packages continues. The methods are already available to the community because open-source, working examples have been included with all publications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

High-order matrix-free incompressible flow solvers with GPU acceleration and low-order refined preconditioners

In this work, we present a matrix-free flow solver for high-order finite element discretizations of the incompressible Navier-Stokes and Stokes equations with GPU acceleration. For high polynomial degrees, assembling the matrix for the linear systems resulting from the finite element discretization can be prohibitively expensive, both in terms of computational complexity and memory. For this reason, it is necessary to develop matrix-free operators and preconditioners, which can be used to efficiently solve these linear systems without access to the matrix entries themselves. The matrix-free operator evaluations utilize GPU-accelerated sum-factorization techniques to minimize memory movement and maximize throughput. The preconditioners developed in this work are based on a low-order refined methodology with parallel subspace corrections, as described for diffusion problems in [1]. The saddle-point Stokes system is solved using block-preconditioning techniques, which are robust in mesh size, polynomial degree, time step, and viscosity. For the incompressible Navier-Stokes equations, we make use of projection (fractional step) methods, which require Helmholtz and Poisson solves at each time step. The performance of our flow solvers is assessed on several benchmark problems in two and three spatial dimensions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A weighted Shifted Boundary Method for free surface flow problems

The Shifted Boundary Method (SBM) belongs to the class of unfitted (or immersed, or embedded) finite element methods and was recently introduced for the Poisson, linear advection/diffusion, Stokes, Navier-Stokes, acoustics, and shallow-water equations. By reformulating the original boundary value problem over a surrogate (approximate) computational domain, the SBM avoids integration over cut cells and the associated problematic issues regarding numerical stability and matrix conditioning. Accuracy is maintained by modifying the original boundary conditions using Taylor expansions. Hence the name of the method, that shifts the location and values of the boundary conditions. In this article, we extend the SBM to the simulation of incompressible Navier-Stokes flows with moving free-surfaces, by appropriately weighting its variational form with the elemental volume fraction of active fluid. This approach prevents spurious pressure oscillations in time, which would otherwise be produced if the total active fluid volume were to change abruptly over a time step. In fact, the proposed weighted SBM method induces small mass (i.e., volume) conservation errors, which converge quadratically in the case of piecewise-linear finite element interpolations, as the grid is refined. Finally, we present an extensive set of two- and three-dimensional tests to demonstrate the robustness and accuracy of the method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Balancing renewable energy and river resources by moving from individual assessments of hydropower projects to energy system planning

As governments and non-state actors strive to minimize global warming, a primary strategy is the decarbonization of power systems which will require a massive increase in renewable electricity generation. Leading energy agencies forecast a doubling of global hydropower capacity as part of that necessary expansion of renewables. While hydropower provides generally low-carbon generation and can integrate variable renewables, such as wind and solar, into electrical grids, hydropower dams are one of the primary reasons that only one-third of the world’s major rivers remain free-flowing. This loss of free-flowing rivers has contributed to dramatic declines of migratory fish and sediment delivery to agriculturally productive deltas. Further, the reservoirs behind dams have displaced tens of millions of people. Thus, hydropower challenges the world’s efforts to meet climate targets while simultaneously achieving other Sustainable Development Goals. In this paper, we explore strategies to achieve the needed renewable energy expansion while sustaining the diverse social and environmental benefits of rivers. These strategies can be implemented at scales ranging from the individual project (environmental flows, fish passage and other site-level mitigation) to hydropower cascades to river basins and regional electrical power systems. While we review evidence that project-level management and mitigation can reduce environmental and social costs, we posit that the most effective scale for finding balanced solutions occurs at the scale of power systems. We further hypothesize that the pursuit of solutions at the system scale can also provide benefits for investors, developers and governments; evidence of benefits to these actors will be necessary for achieving broad uptake of the approaches described in this paper. We test this hypothesis through cases from Chile and Uganda that demonstrate the potential for system-scale power planning to allow countries to meet low-carbon energy targets with power systems that avoid damming high priority rivers (e.g., those that would cause conflicts with other social and environmental benefits) for a similar system cost as status quo approaches. We also show that, through reduction of risk and potential conflict, strategic planning of hydropower site selection can improve financial performance for investors and developers, with a case study from Colombia.

Opperman, Jeffrey J.↗
DOE OSTI2021

Three-Dimensional Free Gas Flow Focuses Basin-Wide Microbial Methane to Concentrated Methane Hydrate Reservoirs in Geological System

Here, we present a systematic model that links the generation, migration, phase partitioning, and accumulation of methane into a closed loop as the sediment is deposited from the seafloor and buried through the base of hydrate stability zone (BHSZ). In our model, methane is generated by biodegradation of organic carbon in muds. Hydrate does not form and methane is not trapped until a coarse-grained layer is deposited, because the small pores prevent hydrate formation in muds. Instead, methane diffuses into sands/silts where methane solidifies into hydrate. As hydrate-bearing sands/silts pass through the BHSZ during sediment burial, methane hydrate dissociates, and releases free gas. The released and the newly generated free gas below the BHSZ concentrates into a vertical/dipping zone with low capillary entry pressure and high permeability and flows upward driven its buoyancy. When free gas reaches the hydrate stability zone (HSZ), capillary forces drive free gas to flow laterally, preferentially enter sands/silts, feed hydrate growth, and elevate hydrate saturation. With three-dimensional focused free gas flow, microbial methane that is generated from a much larger fetch area of the entire basin, both above and below the BHSZ, is concentrated into coarse-grained layers at structural closures for hydrate formation. Our model illustrates how geological evolution, microbial methane generation, and gas flow by buoyancy couple to generate concentrated hydrate deposits in geological system. These insights can be used to explore for high-concentration methane hydrate and are important for understanding the methane budget and carbon cycle under the seafloor.

58 GEOSCIENCES↗
DOE OSTI2022

High-energy and low-cost membrane-free chlorine flow battery

Abstract Grid-scale energy storage is essential for reliable electricity transmission and renewable energy integration. Redox flow batteries (RFB) provide affordable and scalable solutions for stationary energy storage. However, most of the current RFB chemistries are based on expensive transition metal ions or synthetic organics. Here, we report a reversible chlorine redox flow battery starting from the electrolysis of aqueous NaCl electrolyte and the as-produced Cl 2 is extracted and stored in the carbon tetrachloride (CCl 4 ) or mineral spirit flow. The immiscibility between the CCl 4 or mineral spirit and NaCl electrolyte enables a membrane-free design with an energy efficiency of >91% at 10 mA/cm 2 and an energy density of 125.7 Wh/L. The chlorine flow battery can meet the stringent price and reliability target for stationary energy storage with the inherently low-cost active materials (~$5/kWh) and the highly reversible Cl 2 /Cl − redox reaction.

25 ENERGY STORAGE↗
DOE OSTI2022

Metal-free polypeptide redox flow batteries

Metal-free redox flow batteries with TEMPO-based polypeptide catholytes and viologen-based polypeptide anolytes were demonstrated. Post-cycling analysis indicated the main source of capacity fade was degradation of the redox-active pendant groups.

Liang, Zhiming↗
DOE OSTI2025

Lithium Divertor Targets and Walls for the ASTER Liquid Stellarator Reactor, Distributed Divertor

Stellarators may have advantages for certain liquid metal options as Plasma Facing Components (PFC) for divertor targets and first walls due to the wide range of possible magnetic configurations, which additionally are free of disruptions and fast field variations. In a previous work (V. Queral et al., IEEE Trans. Plasma Sci. 52, 2024), a concept of stellarator reactor (ASTER-CP) based on swirling Li-molten salts and liquid lithium floating on the molten salt as PFC was presented. The divertor matters were not studied then and, thus, they are being studied and experimentally tested now. The ASTER-CP reactor concept, the initial liquid metal experiments and potential concepts for the ASTER-CP divertor and first wall are reported. Concerning the experiments, several small scale experiments of galinstan in a small rotating cylinder under magnetic field have been produced, including one experiment with high viscosity galinstan-mixture for increased thickness of layer. An experiment of floating lithium on the molten salt LiCl-PbCl2 gave fast volatilization/decomposition of the molten salt. Particularly for divertors, the traditional free-flow, Capillary Porous Systems and ‘divertorlets’ have been studied for application to ASTER-CP. Surface waves (hot spots), lack of enough surface fluid turbulence and excessive fluid speed are the main issues found in fast free-flow. The perhaps original concept of Distributed Divertor and Equi-power Surface is tentatively proposed and studied, taking advantage of stellarator fields and low recycling regime.

distributed divertor↗
DOE OSTI2024

Enriching OpenStreetMap network data for transportation applications: Insights into the impact of urban congestion on accessibility

OpenStreetMap (OSM) data is a valuable open-source resource for various transportation, traffic, and planning applications. However, OSM network data lack operating traffic speed information, which is critical for transport planning and operations. Addressing this shortcoming, this study leverages commercial vendor data (to serve as ground truth) with exogenous, open-source variables characterizing local transport infrastructure, land use, and demographic information to predict average congested traffic speeds on OSM networks. Three machine-learning models were tested and estimated for OSM links with and without speed limit information in the Denver metropolitan region. Among these, XGBoost performed best, with mean absolute errors of 3.27 and 3.62 mph for links with and without speed limits, respectively. The developed models accurately predicted traffic speeds for different hours and days of the week compared to ground truth data. Using these predicted speeds, drive accessibility scores were computed for the Denver region for different time periods using the Mobility Energy Productivity (MEP) metric to understand the impact of congestion on energy-efficient accessibility. Results show that congestion-adjusted drive accessibility can be significantly lower compared to accessibility calculated using free flow speeds. Specifically, weekday evening hours saw a 42 % drop in accessibility due to reduced speeds, particularly around downtown Denver. Across the Denver metro region, approximately half as many opportunities and jobs are accessible in under 20 min by car during the evening peak period relative to free flow conditions. These findings underscore the importance of using congestion-adjusted operating speeds rather than speed limits in accessibility calculations, as reliance on speed limits can substantially overestimate energy-efficient drive accessibility in large, car-centric cities susceptible to significant congestion. In conclusion, the methodology presented here could further enrich OSM network data, making them useful for an even broader range of transportation applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Implications of stop-and-go traffic on training learning-based car-following control

Learning-based car-following control (LCC) of connected and autonomous vehicles (CAVs) is gaining significant attention with the advancement of computing power and data accessibility. While the flexibility and large model capacity of model-free architecture enable LCC to potentially outperform the model-based car-following (CF) model in improving traffic efficiency and mitigating congestion, the generalizability of LCC for traffic conditions different from the training environment/dataset is not well-understood. Herein, this study seeks to explore the impact of stop-and-go traffic in the training dataset on the generalizability of LCC. It uses the characteristics of lead vehicle trajectories to describe stop-and-go traffic, and links the theory of identifiability (i.e., obtaining a unique parameter estimation result using sensor measurements) to the generalizability of behavior cloning (BC) and policy-based deep reinforcement learning (DRL). Correspondingly, the study shows theoretically that: (i) stop-and-go traffic can enable the property of identifiability and enhance the control performance of BC-based LCC in different traffic conditions; (ii) stop-and-go traffic is not necessary for DRL-based LCC to generalize to different traffic conditions; (iii) DRL-based LCC trained with only constant-speed lead vehicle trajectories (not sufficient to ensure identifiability) can be generalized to different traffic conditions; and (iv) stop-and-go traffic increases variance in the training dataset, which improves the convergence of parameter estimation while negatively impacting the convergence of DRL to the optimal control policy. Numerical experiments validate the above findings, illustrating that BC-based LCC entails comprehensive training datasets for generalizing to different traffic conditions, while DRL-based LCC can achieve generalization with simple free-flow traffic training environments. This further suggests DRL as a more promising and cost-effective LCC approach to reduce operational costs, mitigate traffic congestion, and enhance safety and mobility, which can accelerate the deployment and acceptance of CAVs.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Colloidal Three-Dimensional Covalent Organic Frameworks and Their Application as Porous Liquids

Developing solid porous materials into free-flowing liquids with permanent porosity is a promising strategy for overcoming certain limitations of conventional sorbent materials employed in gas storage and separation applications. The ability to control the pore size and chemical functionalities of organic frameworks gives these particular nanoporous materials distinct advantages over other small cage-like molecules or hollow particles that have been developed into porous liquids. Here, we describe the synthesis of a 3D imine-linked colloidal covalent organic framework (COF)-based porous liquid, designed for efficient size-exclusion of solvent, as well as for long-term stability. By tethering ionic liquids to the colloid surface, the colloids can be dried, purified, and resuspended in a variety of solvents without irreversible aggregation typically observed of COF colloids. Colloid size could be controlled between 50 and 400 nm, with surface areas as high as 800 m2/g. The 3D intertwining morphology of the colloids had pore sizes ranging from 5 to 14 Å, allowing them to efficiently sizeexclude bulky ionic liquids. The COF colloids were stable towards flocculation in an ionic liquid for > 1 year. Permanent porosity was confirmed with a combination of 19F NMR measurements and gas sorption techniques. CO2 and CH4 uptake in these porous liquids increased more than 10 and 20-fold, respectively, over non-porous, neat ionic liquid control samples. The work not only advances the state of COF-based colloid science but also represents a practical advance towards developing more robust, tunable framework-based porous liquid materials for a host of gas storage and separation applications.

Mow, Rachel E.↗
DOE OSTI2023

MOOSE Navier–Stokes module

The MOOSE Navier–Stokes module solves mass, momentum, energy, and passive scalar conservation equations in the context of fluid flow. The module supports solution of these equations in both free flow and porous medium contexts and for a range of fluid compressibility. The conservation equations can be discretized in space using continuous Galerkin finite elements or with cell centered finite volumes.

97 MATHEMATICS AND COMPUTING↗