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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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Results from hemispherical TNT simulations that I ran for my dissertation. It includes the impact of finite-rate chemistry and thermal particle radiation on the post-detonation flow.
These measurements are provided by a differential mobility analyzer operated as a scanning mobility particle sizer, a printed particle optical spectrometer (POPS), and a continuous flow diffusion cloud condensation nuclei (CCN) counter. The instruments sample from either a counterflow virtual impactor inlet or an isokinetic inlet. The measurements provide the mobility aerosol size distribution (30-360 nm), optical size distribution (150 - 6000 nm), size-resolved CCN distribution (30-360 nm) at 0.2, 0.4, 0.6, 0.8, and 1.0% supersaturation. CCN measurements are performed in denuded and undenuded configuration, where denuded refers to the removal of low molecular weight organic vapors. A detailed NetCDF header is included with the datafiles. Users of these measurements are encouraged to consult with the authors about appropriate interpretation before submitting for publication, offering coauthorship where appropriate.
Pumped Counterflow Virtual Impactors (PCVI) are designed to separate aerosols based on aerodynamic diameter, which is particularly useful for isolating cloud droplets and ice crystals from smaller particles. However, the PCVI transmission efficiency (TE) values reported in the literature show considerable variability, and little information is available on the TEs for cloud liquid droplets. Here, we determined the optimal flow conditions for PCVI sampling for different activation ratios from the MTU Pi-cloud chamber, highlighting the conditions that maximize droplet residual sampling while minimizing interstitial transmission. Even for a lower limit cloud activation ratio = 1:10, an add flow of 1.5 LPM achieves a residual fraction greater than 0.80, with a droplet TE of ∼15% for typical Pi-Chamber droplets with diameters between 3.5 to 10 µm. This framework can be adapted for field cloud measurements based on the cloud conditions of interest. TE for cloud droplets under flow conditions at which ∼99% of the unactivated submicron particles were removed was substantially lower between 8 and 16% than for supermicron dry particles (∼30 to 40% for 3 µm polystyrene latex spheres). In addition, we conducted a comparison of the performances of three similar PCVI units to assess repeatability for dry aerosols and cloud droplets. All three PCVIs performed similarly in rejecting submicron particles smaller than the desired cutoff diameter. One of the units showed lower TEs due to a misalignment of the internal orifice. We discuss a procedure that improved alignment and performance.
Electron transport in complex fluids, biology, and soft matter is a valuable characteristic in processes ranging from redox reactions to electrochemical energy storage. These processes often employ conductor–insulator composites in which electron transport properties are fundamentally linked to the microstructure and dynamics of the conductive phase. While microstructure and dynamics are well recognized as key determinants of the electrical properties, a unified description of their effect has yet to be determined, especially under flowing conditions. In this work, the conductivity and shear viscosity are measured for conductive colloidal suspensions to build a unified description by exploiting both recent quantification of the effect of flow-induced dynamics on electron transport and well-established relationships between electrical properties, microstructure, and flow. These model suspensions consist of conductive carbon black (CB) particles dispersed in fluids of varying viscosities and dielectric constants. In a stable, well-characterized shear rate regime where all suspensions undergo self-similar agglomerate breakup, competing relationships between conductivity and shear rate were observed. To account for the role of variable agglomerate size, equivalent microstructural states were identified using a dimensionless fluid Mason number, Mn f , which allowed for isolation of the role of dynamics on the flow-induced electron transport rate. At equivalent microstructural states, shear-enhanced particle–particle collisions are found to dominate the electron transport rate. This work rationalizes seemingly contradictory experimental observations in literature concerning the shear-dependent electrical properties of CB suspensions and can be extended to other flowing composite systems.
Abstract Magnetic reconnection changes the magnetic field topology and facilitates the energy and particle exchange at magnetospheric boundaries such as the Earth's magnetopause. The flow shear perpendicular to the reconnecting plane prevails at the flank magnetopause under southward interplanetary magnetic field conditions. However, the effect of the out‐of‐plane flow shear on asymmetric reconnection is an open question. In this study, we utilize kinetic simulations to investigate the impact of the out‐of‐plane flow shear on asymmetric reconnection. By systematically varying the flow shear strength, we analyze the flow shear effects on the reconnection rate, the diffusion region structure, and the energy conversion rate. We find that the reconnection rate increases with the upstream out‐of‐plane flow shear, and for the same upstream conditions, it is higher at the dusk side than at the dawn side. The diffusion region is squeezed in the outflow direction due to magnetic pressure which is proportional to the square of the Alfvén Mach number of the shear flow. The out‐of‐plane flow shear increases the energy conversion rate , and for the same upstream conditions, the magnitude of is larger at the dusk side than at the dawn side. This study reveals that out‐of‐plane flow shear not only enhances the reconnection rate but also significantly boosts energy conversion, with more pronounced effects on the dusk‐side flank than on the dawn‐side flank. These insights pave the way for better understanding the solar wind‐magnetosphere interactions.
Here, the spout-bed fluidization behavior of nonspherical, 140 μm SiC feedstock was quantified via particle image velocimetry for varying gas distributor geometries. A bench-scale, room-temperature fluidization setup was assembled to model a 50 mm fluidized bed chemical vapor deposition (FB-CVD) system, and fluidized bed motion was captured using a high-speed camera. Modular tips with varying inlet geometries were 3D printed and tested on the bench-scale rig using identical feedstock and gas flow rates in the range of 3.0–9.0 L/min. Fluidization behavior was quantified by extracting parameters of the bed velocity, frequency, dead time, and other measurements, which were ranked for each inlet geometry configuration tested. The results from this work demonstrate that changing the path of inlet gas flow can significantly change the hydrodynamics within a spout-fluidized bed under identical feedstock, loading, and flow rate conditions, potentially enabling experimental control of particle fluidization behavior for a given condition. Moreover, composite rankings of fluidization behavior for unique distributor geometries hold potential to guide the design of FB-CVD experiments for various engineering and scientific applications.
In magnetically confined fusion plasmas, the role played by zonal 𝐸 x 𝐵 flow shear layers in the suppression of turbulent transport is relatively well understood. However, less is understood about the role played by the weak shear regions that arise in the non-monotonic radial electric field profiles often associated with these shear layers. In electrostatic simulations from the global total-𝑓 gyrokinetic particle-in-cell code XGC, we demonstrate how shearless regions with non-zero flow curvature form zonal ‘jets’ that, in conjunction with neighbouring regions of shear, can act as robust barriers to particle transport and turbulence spreading. By isolating quasi-coherent fluctuations radially localised to the zonal jets, we construct a map model for the Lagrangian dynamics of gyrokinetic test particles in the presence of drift waves. We identify the presence of shearless invariant tori in this model and verify that these tori act as partial phase-space transport barriers in the simulations. We also demonstrate how avalanches impinging on these shearless tori cause eddy detachment events that form ‘cold/warm core ring’ structures analogous to those found in oceanic jets, facilitating transport across the barriers without destroying them completely. We discuss how shearless tori may generically arise from tertiary instabilities or other types of discrete eigenmodes, suggesting their potential relevance to broader classes of turbulent fluctuations.
Self-assembled swarms of interactive active units, which are adaptive and dynamically reconfigurable to accommodate different functionalities, represent a promising platform for the development of next-generation robotics. Here, we utilize the emergent collective behavior of active magnetic colloids confined in quasi-two-dimensional arrays of overlapping wells to demonstrate the self-organization of a colloidal swarm into a dynamic pump architecture capable of controlled transport of passive cargo particles. This dynamic architecture provides a global unidirectional looping flow pattern along the entire length of the system. We show that the flow direction of the dynamic swarm-based pump can be externally controlled by a phase shift of a driving magnetic field energizing the swarm. The experimental observations are supported by computational modeling based on phenomenological coarse-grained particle dynamics coupled to shallow-water Navier-Stokes hydrodynamics. In conclusion, our findings demonstrate how the emergent collective behavior of a swarm can be orchestrated into a desired functionality by exploiting the interplay between activity and confinement potentials.
Magnetic reconnection in current layers that form intermittently in radiatively inefficient accretion flows onto black holes is a promising mechanism for particle acceleration and high-energy emission. It has been recently proposed that such layers, arising during flux eruption events, can power the rapid TeV flares observed from the core of M87. In this scenario, inverse-Compton scattering of soft radiation from the accretion flow by energetic electron–positron pairs produced near the reconnection layer was suggested as the primary emission mechanism. However, detailed calculations show that radiation from pairs alone cannot account for the GeV emission detected by the Fermi observatory. In this work, we combine analytic estimates with 3D radiative particle-in-cell simulations of pair–proton plasmas to show that the GeV emission can be naturally explained by synchrotron radiation from protons accelerated in the current sheet. Although the exact proton content of the layer is uncertain, our model remains robust across a broad range of proton-to-pair number density ratios. While protons are subdominant in number compared to pairs, our simulations demonstrate that they can be accelerated more efficiently, leading to a self-regulated steady state in which protons dominate the energy budget. Ultimately, proton synchrotron emission accounts for approximately 5%–20% of the total dissipation power. The majority is radiated as MeV photons via pair synchrotron emission, with a smaller fraction emitted as TeV photons through inverse-Compton scattering.
NREL assisted the BRIDGE project led by the University of Colorado (CU), Boulder, on developing granular flow and heat transfer simulation tool to serve for an enclosed particle-receiver design. NREL will provide the particle receiver design configuration and operating condition to assist the model setup and may provide certain testing results for model verifications. NREL will attend project reviewing meeting and provide application back-ground including concentrating solar energy technology to collaborate with CU researchers.
The computational study of strongly-coupled, gas–solid flows at scales relevant to most environmental and engineering applications requires the use of ‘coarse-grained’ methodologies such as the two-fluid model, particle-in-cell approach or the multiphase Reynolds Averaged Navier–Stokes equations. While these strategies enable computations at desirable length- and time-scales, they rely heavily on models to capture important flow physics that occur at scales smaller than the mesh. To date, the models that do exist are based on a limited set of flow conditions, such as very dilute particle phase. To this end, we leverage a large-scale repository of CFD-DEM data to develop filter-size dependent models for the mean variance in particle volume fraction, a quantity commonly used to assess the degree of clustering, and the granular temperature, a key quantity for accurately predicting gas–solid flows. In conclusion, because of its filter-size dependence, the granular temperature model can be directly translated to coarse-grained approaches and tied directly to grid size.
Fluidized bed reactors are used across a variety of industries, including for energy processes like pyrolysis that result in low-cost energy products. Design and scale-up of fluidized beds is de-risked by modeling and simulation, utilizing tools like NETL’s MFIX-Exa High-Performance Computing (HPC) code for reacting multiphase flow. This report summarizes an investigation into the breadth of problems to which MFIX-Exa may be applied, specifically with regard to low fluid velocities and the onset of fluidization. A simple fluidization study is conducted both experimentally and numerically for particles of interest, then reactor simulations are compared to cold flow experiments for uniform distributor plates. Approaches for modeling bubble caps are also presented.
Flowable carbon slurry electrodes promise continuous, scalable electrochemical desalination and energy storage when their rheology (flow and stability) and electronic connectivity are jointly optimized. This report integrates six complementary thrusts that we executed under the Laboratory Directed Research and Development (LDRD) project: (i) a fast, ex situ, centrifuge-compatible method to quantify pellet (packed slurry) electronic conductivity, with a validated cell constant (“shape factor”) and quantitative structure–property insights for carbon mixtures; (ii) a controlled circulation study showing that peristaltic pumping can irreversibly alter particle size and morphology over laboratory-relevant durations; (iii) development of a miniature jet pump that preserves particle integrity while achieving entrainment ratios of 2–4 at practical flow rates; (iv) a comprehensive mapping of how a representative non-ionic surfactant (Tween 20) collapses the carbon gel network, separating network-percolation losses from intrinsic particle contact resistance; (v) in-situ visualization revealing how gravitational settling and flow-driven mixing compete to control charge transport, with dynamic bed layers preventing saturation while achieving 30-fold local concentration enhancement; and (vi) a simple, widely adoptable fabrication route to structured, gas-nitrided titanium nitride (TiN) titanium current collectors that dramatically lower interfacial losses and enable geometry-driven performance gains. Together, these results provide a coherent toolchain and design rules to accelerate formulation screening, de-risk device prototyping, and standardize characterization for carbon slurry electrodes in flow-electrode capacitive deionization (FCDI), electrochemical flow capacitor (EFC), and related systems.
The overarching goal of this project is to produce comprehensive experimental and numerical datasets for gas-solid flows in well-controlled settings to understand the aerodynamic drag of non-spherical particles in the dense regime. The datasets and the gained knowledge will be utilized to train deep neural networks in TensorFlow to formulate a general drag model for use directly in NETL MFiX-DEM module in order to help to advance the accuracy and prediction fidelity of the computational tools that will be used in designing and optimizing fluidized beds and chemical looping reactors.
As the nuclear industry explores new fuel designs to accommodate increased burnup, studying fuel behavior during loss-of-coolant accidents is essential for ensuring the safe operation of light-water reactors. Here, this study presents a computational model to simulate the intricate three-phase flow dynamics of fuel dispersal following cladding breach, where solid fuel particles and carrier fission gases interact with the surrounding liquid or gas medium. The model utilizes a Eulerian three-fluid framework to depict the phase interaction within interpenetrating continua, treating fragmented fuel as granular material. Closure relationships for bulk-flow properties of the solid phase and detailed interfacial exchange terms in high-temperature, high-speed gas-solid-liquid flow scenarios are proposed. The model was validated using adiabatic experimental results in the literature, focusing on characterizing fuel dispersal behavior during loss-of-coolant accidents conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched probability density functions reported in experimental studies. Key highlights of this study include the theoretical description of a coupled three-phase flow with phase change, interpretation of the high-pressure boundary conditions and insights into the transient behavior of gas-solid-liquid phase dynamics during a simulated high-speed dispersal event.
Measurements of the 𝑝 T -dependent flow vector fluctuations in Pb–Pb collisions at $\sqrt{S_{NN}}$ = 5.02 TeV using azimuthal correlations with the ALICE experiment at the Large Hadron Collider are presented. A four-particle correlation approach [ALICE Collaboration, Phys. Rev. C 107, L051901 (2023)] is used to quantify the effects of flow angle and magnitude fluctuations separately. This paper extends previous studies to additional centrality intervals and provides measurements of the 𝑝 T -dependent flow vector fluctuations at $\sqrt{S_{NN}}$ = 5.02 TeV with two-particle correlations. Significant 𝑝 T -dependent fluctuations of the $\vec{𝑉}$ 2 flow vector in Pb–Pb collisions are found across different centrality ranges, with the largest fluctuations of up to ∼15% being present in the 5% most central collisions. In parallel, no evidence of significant 𝑝 T -dependent fluctuations of $\vec{𝑉}$ 3 or $\vec{𝑉}$ 4 is found. Additionally, evidence of flow angle and magnitude fluctuations is observed with more than 5𝜎 significance in central collisions. These observations in Pb–Pb collisions indicate where the classical picture of hydrodynamic modeling with a common symmetry plane breaks down. This has implications for hard probes at high 𝑝 T , which might be biased by 𝑝 T -dependent flow angle fluctuations of at least 23% in central collisions. Given the presented results, existing theoretical models should be reexamined to improve our understanding of initial conditions, quark–gluon plasma properties, and the dynamic evolution of the created system.
The correlations between event-by-event fluctuations of symmetry planes are measured in Pb-Pb collisions at a center-of-mass energy per nucleon pair $\sqrt{s_{NN}}$ = 5.02 TeV recorded by the ALICE detector at the Large Hadron Collider. This analysis is conducted using the Gaussian estimator technique, which is insensitive to biases from correlations between different flow amplitudes. The study presents, for the first time, the centrality dependence of correlations involving up to five different symmetry planes. The correlation strength varies depending on the harmonic order of the symmetry plane and the collision centrality. Comparisons with measurements from lower energies indicate no significant differences within uncertainties. Additionally, the results are compared with hydrodynamic model calculations. Although the model predictions provide a qualitative explanation of the experimental results, they overestimate the data for some observables. This is particularly true for correlators that are sensitive to the nonlinear response of the medium to initial-state anisotropies in the collision system. As these new correlators provide unique information—independent of flow amplitudes—their usage in future model developments can further constrain the properties of the strongly interacting matter created in ultrarelativistic heavy-ion collisions.
Significant knowledge gaps remain in our understanding of turbulence–cloud–aerosol interactions in the Earth's atmosphere, and direct numerical simulation (DNS) has increasingly become an indispensable tool to fill such critical knowledge gaps. Here, this study is an extension of our previous DNS model [Gao et al., J. Geophys. Res.: Atmos., 123(4), 2194–2214 (2018)], with a focus on the activation of aerosol particles into cloud droplets and deactivation of cloud droplets into aerosol particles in a microscale cloud environment. The effects of turbulence intensity, particle curvature, and solute, as well as the initial distributions of the aerosol particles (monodisperse or polydisperse) are investigated. The governing equations for the flow of air, temperature, and water vapor mixing ratio are solved numerically in the Eulerian fashion, assuming homogeneous and isotropic turbulence. The dynamics of the aerosol and cloud particles are calculated with the Lagrangian particle tracking method. The results show that the deviations of the thermodynamic variables from their respective means are significantly reduced, the activation process appears to be delayed, and the deactivation process occurs more rapidly, as the turbulence intensity is increased. The inclusion of particle curvature and solute effects, as well as polydispersity, tends to retard the activation of aerosols into cloud droplets. It is also observed that fluctuations in supersaturation broaden the spread of particle radii, and the broadening is followed by a narrowing as turbulent homogenization reduces thermodynamic fluctuations over time.