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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

3D modelling of MHD mixed convection flow in a vertical duct with transverse magnetic field and volumetric or surface heating

Understanding phenomena associated with the multiple effects/interactions of the fusion nuclear environment on liquid metal flow is required to correctly design liquid metal (LM) blankets for fusion facilities. These effects are investigated in the present work by numerically simulating 3D LM MHD flow. The simulated geometry consists of a straight, vertical duct which runs perpendicular to a strong, fringing applied magnetic field. There is also a region of applied heating as the primary goal is to explore buoyancy effects in MHD duct flows. Results are presented for both buoyancy assisted (upwards) and buoyancy opposed (downwards) flows in conducting and insulating ducts for a range of Hartmann numbers (Ha) up to 100, Reynolds numbers (Re) from 10 3 to 10 4 and Grashof (Gr) numbers from 10 7 to 10 8 . While increasing Gr or decreasing Re increases buoyancy effects, increasing Ha was shown to increase maximum temperature through turbulence reduction. The extent to which the MHD mixed convection flows are quasi-2D is analyzed and buoyant effects, in competition with electromagnetic forces, are shown to bring about 3D flow features not seen in purely MHD flows. Volumetric nuclear heating with steep gradients is applied to the vertical MHD flows for comparison to flows with surface heating only. Finally, surface heating generates stronger buoyancy effects than volumetric heating of the same total power; however, many of the same phenomena occur. Therefore, surface heating, the only option for lab experiments, can provide indication of the effects of volumetric heating in MHD flows.

42 ENGINEERING↗
DOE OSTI2020

Adaptive Multirate Mass Transfer (aMMT) Model: A New Approach to Upscale Regional‐Scale Transport Under Transient Flow Conditions

Abstract The long‐term evaluation of regional‐scale groundwater quality needs efficient upscaling methods for transient flow. Upscaling techniques, such as the Multirate Mass Transfer (MRMT) method with constant upscaling parameters, have been used for transport with steady‐state flow, yet the upscaling parameters (i.e., rate coefficients) may be time dependent. This study proposed and validated an adaptive MRMT (aMMT) method by allowing the mass transfer coefficients in MRMT to change with the flow field. Advective‐dispersive contaminant transport simulated in a 3‐D heterogeneous medium was used as a reference solution. Equivalent transport under homogeneous flow conditions was evaluated by applying the MRMT and aMMT models for upscaling. The relationship between mass transfer coefficients and flow rates was fitted under steady‐state flow driven by various hydraulic gradients. A power law relationship was obtained, which was then used to update the mass transfer coefficients in each stress period under transient flow conditions in the aMMT method. Results indicated that for advection‐dominated transport, both the MRMT and aMMT methods can upscale the anomalous transport dynamics affected by subgrid heterogeneity under transient flow conditions. Whereas for diffusion‐dominated systems, the MRMT model failed to capture the tails of tracer breakthrough curves after the boundary condition changed, but the results from the aMMT model were significantly improved. However, if the overall flow direction changed, both MRMT and aMMT failed to represent the breakthrough curve tail generated by the heterogeneous system. The results point toward a promising path for upscaling transport in complex aquifers with transient flow.

Guo, Zhilin↗
DOE OSTI2022

Uranium Oxide Elutriation at Higher Flow Rates and Longer Times

This work supports the recovery of high-assay low-enriched uranium (i.e., U enriched in 235 U to >5% and <20%) from used nuclear fuel. One step includes elutriating triuranium octoxide (U 3 O 8 ) from a fluidized bed of alumina (Al 2 O 3 ) that fills the main reaction chamber. The experiments outlined in this report assessed the effects of the time and flow rate on the elutriation of U 3 O 8 powder from the reaction vessel. Testing at Oak Ridge National Laboratory (ORNL) was performed in a one-fourth scale experimental apparatus based on a pilot-scale system, which is the Material Recovery Pilot Plant (MRPP) at Idaho National Laboratory (INL). The experimental system comprises a supply of pressurized nitrogen (N 2 ), a gas heater, the reaction vessel, a knock-out pot, and a water trap where elutriated particles are collected for sampling. An Al 2 O 3 fluidized bed is contained within the reaction vessel. A bed of Al 2 O 3 with a nominal size of 180 µm and U 3 O 8 with a nominal size of 7 µm was fluidized at 2 different flow rates so the U 3 O 8 physically separated from the bed. The apparatus was simple and had no valves or sharp bends downstream from the reactor. The flow exited the reactor through a side port at the top. The flow passed through a knock-out vessel before the flow was passed through a bubbler to capture the U 3 O 8 . Seven tests were completed with U 3 O 8 using an elutriating gas of N 2 heated to 200°C. Tests were performed with bed loadings that comprise 25.0 g of U 3 O 8 , or 3.6 wt% of the bed mass. Except for one test performed at 12 SLPM, the gas flow rate through the bed for the other experiments was set at 10 SLPM as measured by the mass flow meter. Linear velocities through the bed were calculated as 28 and 34 cm/s, or 0.9 and 1.1 ft·s -1 . The duration of the tests ranged from 20 to 180 min, and one test had a flow cycled between 0 and 5 SLPM every 5 min for 40 min. The testing successfully demonstrated elutriation of U 3 O 8 from the fluidized bed as up to a 100% of the U 3 O 8 was transferred out of the bed. The removal of U 3 O 8 had a logarithmic dependence on flow rate. The design changes made the apparatus easier to clean, and the mass balances were better than those used in previous studies. Some elutriated Al 2 O 3 collected in the tubing that connected the reactor to the knock-out pot, but the amount of Al 2 O 3 was minimal for 10 SLPM. The flow at 12 SLPM showed considerable transport of Al 2 O 3 bed material into the reaction-vessel headspace and the transfer line to the knock-out pot.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Flow control valve

Disclosed is a flow device including an inlet, an outlet, and a plurality of fluid flow paths hydraulically connected in parallel to the inlet and the outlet, wherein the plurality of fluid flow paths forms a first ring of fluid flow paths circumferentially arranged at a first radial distance from a centerline of the fluid flow device a second ring of fluid flow patch circumferentially arranged at a second radial distance from the centerline of the fluid flow device, each of the plurality of fluid flow paths has a first hydraulic resistance in a forward flow direction and a second hydraulic resistance in a reverse flow direction, and the second hydraulic resistance is greater than the first hydraulic resistance.

Siebert, Brett W.↗
DOE OSTI2022

Wedge-Shaped Hopper Design for Milled Woody Biomass Flow

The bioenergy industry has been challenged by unstable flow and transport of milled biomass in material handling operations. Handling issues such as hopper clogging and auger jamming are attributed to knowledge gaps between existing handling units designed for bulk solids and their suitability for milled biomass with high compressibility. This work investigates various flow behaviors of granular woody biomass in wedge-shaped hoppers. Herein, hopper flow physical experiments and numerical simulations are conducted to study the influence of the critical material attributes and critical processing parameters on the flow pattern, arching, and throughput. The results show that (1) the preferred flow pattern, mass flow, can be achieved by controlling the material’s internal friction angle, hopper inclination, and hopper wall friction; (2) hopper arching, governed by the competing gravity-driven force against flow resistance from material internal friction and material–wall friction, can be controlled by the hopper wall friction angle and the inclination angle; and (3) flow throughput can be accurately estimated from our empirical equation with inputs of hopper outlet geometry and particle-scale to bulk-scale material attributes. This study elucidates woody biomass flow physics and provides guidance for industrial equipment design.

09 BIOMASS FUELS↗
DOE OSTI2022

A 1D–0D–3D coupled model for simulating blood flow and transport processes in breast tissue

In this work, we present mixed dimensional models for simulating blood flow and transport processes in breast tissue and the vascular tree supplying it. These processes are considered, to start from the aortic inlet to the capillaries and tissue of the breast. Large variations in biophysical properties and flow conditions exist in this system necessitating the use of different flow models for different geometries and flow regimes. In total, we consider four different model types. First, a system of 1D nonlinear hyperbolic partial differential equations (PDEs) is considered to simulate blood flow in larger arteries with highly elastic vessel walls. Second, we assign 1D linearized hyperbolic PDEs to model the smaller arteries with stiffer vessel walls. The third model type consists of ODE systems (0D models). It is used to model the arterioles and peripheral circulation. Finally, homogenized 3D porous media models are considered to simulate flow and transport in capillaries and tissue within the breast volume. Sink terms are used to account for the influence of the venous and lymphatic systems. Combining the four model types, we obtain two different 1D–0D–3D coupled models for simulating blood flow and transport processes: The first model results in a fully coupled 1D–0D–3D model covering the complete path from the aorta to the breast combining a generic arterial network with a patient specific breast network and geometry. The second model is a reduced one based on the separation of the generic and patient specific parts. The information from a calibrated fully coupled model is used as inflow condition for the patient specific sub-model allowing a significant computational cost reduction. Several numerical experiments are conducted to calibrate the generic model parameters and to demonstrate realistic flow simulations compared to existing data on blood flow in the human breast and vascular system. Moreover, we use two different breast vasculature and tissue data sets to illustrate the robustness of our reduced sub-model approach.

multiscale blood flow models↗
DOE OSTI2021

Predicting Fluid Flow Regime, Permeability, and Diffusivity in Mudrocks from Multiscale Pore Characterisation

In geoenergy applications, mudrocks prevent fluids to leak from temporary (H 2 , CH 4 ) or permanent (CO 2 , radioactive waste) storage/disposal sites and serve as a source and reservoir for unconventional oil and gas. Understanding transport properties integrated with dominant fluid flow mechanisms in mudrocks is essential to better predict the performance of mudrocks within these applications. In this study, small-angle neutron scattering (SANS) experiments were conducted on 71 samples from 13 different sets of mudrocks across the globe to capture the pore structure of nearly the full pore size spectrum (2 nm–5 μm). We develop fractal models to predict transport properties (permeability and diffusivity) based on the SANS-derived pore size distributions. The results indicate that transport phenomena in mudrocks are intrinsically pore size-dependent. Depending on hydrostatic pore pressures, transition flow develops in micropores, slip flow in meso- and macropores, and continuum flow in larger macropores. Fluid flow regimes progress towards larger pore sizes during reservoir depletion or smaller pore sizes during fluid storage, so when pressure is decreased or increased, respectively. Capturing the heterogeneity of mudrocks by considering fractal dimension and tortuosity fractal dimension for defined pore size ranges, fractal models integrate apparent permeability with slip flow, Darcy permeability with continuum flow, and gas diffusivity with diffusion flow in the matrix. This new model of pore size-dependent transport and integrated transport properties using fractal models yields a systematic approach that can also inform multiscale multi-physics models to better understand fluid flow and transport phenomena in mudrocks on the reservoir and basin scale.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of particle size and moisture on flow performance of loblolly pine anatomical fractions: Experimental findings and model predictions

The rising energy demand has highlighted biomass as a promising next-generation energy source. However, commercializing biomass-derived energy faces challenges, particularly in handling biomass feedstock. Factors like particle size, shape, moisture content, and surface roughness significantly impact biomass flowability. This study addresses a crucial knowledge gap by examining the effects of particle size and moisture content on the flow behavior and shear properties of different anatomical fractions of loblolly pine (Pinus taeda). The bulk shear behavior was examined using a Schulze ring shear tester, while flow performance was tested through gravity-driven flow experiments in a variable wedge-shape hopper. Results were incorporated into empirical and machine learning-based flow prediction models to evaluate their accuracy and limitations. The study found that samples with higher moisture content show higher unconfined yield strength. The critical arching distance increased with particle size, e.g., from approximately 13 and 33 mm for 2- and 6-mm whole chips, respectively at a 32-degree inclination angle. Conversely, the flow rate decreased for a given hopper opening as particle size increased. For instance, at a 60-mm hopper opening and a 32-degree inclination angle, the mass flow rates for 2- and 6-mm whole chips were 7.83 and 6.42 tonne/h, respectively. The empirical model consistently overpredicted the mass flow rate for all anatomical fractions, while the machine learning model more accurately predicted the central tendency of flow rate but was insensitive to varying tissue proportions. These novel findings provide comprehensive characterization of anatomical fractions, reveal significant combined effects of particle size and moisture content on biomass flow behavior, and demonstrate a better predictive accuracy of a machine learning model, all of which are useful for optimizing material handling strategies and biomass utilization technologies in the industry.

09 - BIOMASS FUELS↗
DOE OSTI2022

Three-dimensional realizations of flood flow in large-scale rivers using the neural fuzzy-based machine-learning algorithms

Machine learning methods have been extensively used to study the dynamics of complex fluid flows. One such algorithm, known as adaptive neural fuzzy inference system (ANFIS), can generate data-driven predictions for flow fields, but has not been applied to natural geophysical flows in large-scale rivers. Herein, we demonstrate the potential of ANFIS to produce three-dimensional (3D) realizations of the instantaneous flood flow field in several large-scale, virtual meandering rivers. The 3D dynamics of flood flow in large-scale rivers were obtained using large-eddy simulation (LES). The LES results, i.e., the 3D velocity components, were employed to train the learnable coefficients of an ANFIS. Further, the trained ANFIS, along with a few time-steps of LES results (precursor data) were then used to produce 3D realizations of flood flow fields in large-scale rivers with geometries other than the one the ANFIS was trained with. We also used the trained ANFIS to generate 3D realizations of river flow at a discharge other than that the ANFIS was trained with. The flow field results obtained from ANFIS were validated using separate LES runs to assess the accuracy of the 3D instantaneous realizations of the machine learning algorithm. An error analysis was conducted to quantify the discrepancies among the ANFIS and LES results for various flood flow predictions in large-scale rivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Feasibility of using thermal response methods for nonintrusive compressed air flow measurement

Robust, low-cost nonintrusive flow meters are of interest in many industries. Particularly, a reliable nonintrusive flow measurement for the diagnosis of air leaks in compressed air systems is desirable. Measurement of the air flow due to leaks in the system ensures an accurate estimation of potential cost and energy savings. This study evaluates a novel method of using thermal responses to nonintrusively measure leakage rates in compressed air lines. The method uses heat and the resulting thermal response to calculate the flow rate inside the compressed air line. Compared to the current methods for flow measurement, this method can simplify flow measurement while decreasing the sensitivity to errors when measuring flow rates. In this study, the methodology of the proposed method is explained along with the potential advantages to the design. Two approaches are evaluated: a dynamic step response and sinusoidal frequency response. Simulated tests evaluate the feasibility of the proposed methods, followed by experiments that validate the simulation results. A clear correlation between the thermal step response and the flow rate indicate viability of the proposed method in simulation. Experimental results yielded similar results, confirming the validity of the proposed method. The results of a field test in an industrial environment demonstrate the capability of the approach to other flow rate measurement techniques.

42 ENGINEERING↗
DOE OSTI2020

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) for engineering flow measurements

Increasingly, fully 3D experimental measurements of flow in complex engineering geometries are required to validate computational fluid dynamics models that support and inform reactor design and licensing. One barrier to such measurements is the complexity of typical reactor components and subsequent lack of optical access in these systems. To overcome this, the deployment of coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) is explored for flow measurement in reactor thermal hydraulic components and model (scaled) systems. Through this methodology, fully 3D flow information (via PEPT) and detailed internal geometry (via CT) are captured in opaque systems such as pipes, rod bundles, packed beds, etc. The reconstructed flow field and geometry can then be overlain to reveal detailed flow features around internal structures within a given test section. This is enabled through the use of a combined preclinical PET/CT scanner with overlapping PET and CT fields of view. Such measurements are useful for characterizing flow inside such intricate nuclear thermal hydraulic components as core geometries and heat exchangers, among others, and providing valuable 3D validation data for CFD models. In this work, basic tests of this 3D flow/geometry mapping are presented, and the implications of such measurements are discussed. Further, preliminary measurements are made with both point sources and flow in a simple pipe flow geometry to evaluate the capabilities of this technique. PEPT and CT features are coregistered with up to 0.1 mm precision, and pipe flow mean velocity and Reynolds stresses are reconstructed with similar accuracy to previous PEPT demonstrations. The utility of PEPT/CT is shown herein, and suggestions for future measurements are made.

3D flow measurement↗
DOE OSTI2021

Mixing Cell Model: A One-Dimensional Numerical Model for Assessment of Water Flow and Contaminant Transport in the Unsaturated Zone

This report describes the Mixing Cell Model code, a one dimensional model for water flow and solute transport in the unsaturated zone under steady state or transient flow conditions. The model is based on the principles and assumptions underlying mixing-cell model formulations. The unsaturated zone is discretized into a series of independent mixing cells. Each cell may have unique hydrologic, lithologic, and sorptive properties. Ordinary differential equations describe the material (water and solute) balance within each cell. Water-flow equations are derived from the continuity equation, assuming that unit gradient conditions exist at all times in each cell. Pressure gradients are considered implicitly through model discretization. Unsaturated hydraulic conductivity and moisture contents are determined by the material specific moisture-characteristic curves. Solute-transport processes include explicit treatment of advective processes, first order chain decay, and linear sorption reactions. Dispersion is addressed through implicit and explicit dispersion. Implicit dispersion is an inherent feature of all mixing-cell models and originates from the formulation of the problem in terms of mass balance around fully mixed volume elements. Expressions are provided that relate implicit dispersion to the physical dispersion of the system. Two FORTRAN codes were developed to solve the water flow and solute-transport equations: (1) the Mixing Cell Model for Flow (MCMF) solves transient water-flow problems and (2) the Mixing Cell Model for Transport (MCMT) solves the solute-transport problem. The transient water-flow problem is typically solved first by estimating the water flux through each cell in the model domain as a function of time using the MCMF code. These data are stored in either ASCII or binary files that are later read by the solute transport code (MCMT). Code output includes solute pore water concentrations, water and solute inventories in each cell and at each specified output time, and water and solute fluxes through each cell and specified output time. Computer run times for coupled transient water flow and solute transport were typically several seconds on a 2 GHz Intel Pentium IV desktop computer. The model was benchmarked against analytical solutions and finite element approximations to the partial differential equations (PDE) describing unsaturated flow and transport. Differences between the maximum solute flux estimated by the mixing cell model and the PDE models were typically less than two percent. This revision includes an option for a fixed concentration lower boundary condition for diffusive fluxes for versions 020321 and later.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

How Does Flow Alteration Propagate Across a Large, Highly Regulated Basin? Dam Attributes, Network Context, and Implications for Biodiversity

Abstract Large dams are a leading cause of river ecosystem degradation. Although dams have cumulative effects as water flows downstream in a river network, most flow alteration research has focused on local impacts of single dams. Here we examined the highly regulated Colorado River Basin (CRB) to understand how flow alteration propagates in river networks, as influenced by the location and characteristics of dams as well as the structure of the river network—including the presence of tributaries. We used a spatial Markov network model informed by 117 upstream‐downstream pairs of monthly flow series (2003–2017) to estimate flow alteration from 84 intermediate‐to‐large dams representing >83% of the total storage in the CRB. Using Least Absolute Shrinkage and Selection Operator regression, we then investigated how flow alteration was influenced by local dam properties (e.g., purpose, storage capacity) and network‐level attributes (e.g., position, upstream cumulative storage). Flow alteration was highly variable across the network, but tended to accumulate downstream and remained high in the main stem. Dam impacts were explained by network‐level attributes (63%) more than by local dam properties (37%), underscoring the need to consider network context when assessing dam impacts. High‐impact dams were often located in sub‐watersheds with high levels of native fish biodiversity, fish imperilment, or species requiring seasonal flows that are no longer present. These three biodiversity dimensions, as well as the amount of dam‐free downstream habitat, indicate potential to restore river ecosystems via controlled flow releases. Our methods are transferrable and could guide screening for dam reoperation in other highly regulated basins.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impact of the Out‐Of‐Plane Flow Shear on Magnetic Reconnection at the Flanks of Earth's Magnetopause

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.

Liang, Haoming↗
DOE OSTI2026

Dominant Controls on Preferential Flow and Their Implications for Future Soil Water Fluxes

Abstract Soil water flow, particularly preferential flow (PF), is a critical control on hydrological and biogeochemical processes, including groundwater recharge, contaminant transport, and carbon cycling. However, it remains challenging to predict PF occurrence across large environmental gradients. Here, we developed a deep learning (DL) model to estimate event‐scale soil water flow velocity and the probability of PF occurrence using high‐frequency soil moisture and precipitation data from 33 sites across the National Ecological Observatory Network. The model demonstrated high skill in predicting the binary occurrence of PF (91% F1‐score; 85% accuracy) but the performance was limited in predicting soil water velocity ( R 2 = 0.31). We found that precipitation characteristics (duration, volume, and intensity) were the most important predictors for soil water velocity. Among the non‐precipitation event variables, sand content showed relatively high predictive skill, though differences among non‐event climate variables were generally modest. Lower sand content was associated with increased predicted soil water velocity, a finding that highlights the role of soil structure in producing more non‐uniform flow, which contrasts with traditional uniform flow models. Projecting a reduced DL model under both moderate and high‐emissions future climate scenarios (2060–2099 Representative Concentration Pathways 4.5 and 8.5), we found ∼7.3% increase under RCP4.5 and ∼15% under RCP8.5 of soil water velocities compared to the historical simulation, while modeled likelihood of PF changed little. These findings suggest climate change is not making PF more frequent, but it is making existing PF pathways more efficient with important consequences for associated nutrient and contaminant transport under climate change. Plain Language Summary Water movement in soil is critical for water quality. While often modeled as a uniform flow process, in reality water moves rapidly through cracks and burrows in what is called “preferential flow” (PF), which limits natural filtration and can transport pollutants. We developed a deep learning model, trained on data from 33 U.S. sites, to predict when and how fast this PF occurs based on precipitation, soil, and climate data. The model showed that precipitation characteristics (duration, intensity, volume) were the most important predictors of PF. Lower soil sand content/higher clay content was associated with faster water flow, likely due to clay soils forming aggregates and cracks that water moves through rather than infiltrating uniformly. Further analyses based on climate projections suggest that the speed at which PF occurs will become more rapid under future climate scenarios compared to historical simulation. This highlights the need to represent PF in soil water models when assessing future water quality. Key Points The effect of precipitation peak intensity on soil water velocities declined with increasing precipitation intensity Antecedent soil moisture failed to predict preferential flow (PF), contrasting the high predictive power of sand content Climate predictions suggest that soil water velocities through PF paths will increase ∼15% by 2099

Li, Bonan↗
DOE OSTI2021

Flow of long chain hydrocarbons through carbon nanotubes (CNTs)

The pressure-driven flow of long-chain hydrocarbons in nanosized pores is important in energy, environmental, biological, and pharmaceutical applications. This paper examines the flow of hexane, heptane, and decane in carbon nanotubes (CNTs) of pore diameters 1–8 nm using molecular dynamic simulations. Enhancement of water flow in CNTs in comparison to rates predicted by continuum models has been well established in the literature. Our work was intended to observe if molecular dynamic simulations of hydrocarbon flow in CNTs produced similar enhancements. We used the OPLS-AA force field to simulate the hydrocarbons and the CNTs. Our simulations predicted the bulk densities of the hydrocarbons to be within 3% of the literature values. Molecular sizes and shapes of the hydrocarbon molecules compared to the pore size create interesting density patterns for smaller sized CNTs. We observed moderate flow enhancements for all the hydrocarbons (1–100) flowing through small-sized CNTs. For very small CNTs the larger hydrocarbons were forced to flow in a cork-screw fashion. As a result of this flow orientation, the larger molecules flowed as effectively (similar enhancements) as the smaller hydrocarbons.

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

The effect of entrance flow development on vortex formation and wall shear stress in a curved artery model

In this work, we numerically investigate the effect of entrance condition on the spatial and temporal evolution of multiple three-dimensional vortex pairs and the wall shear stress distribution in a curved artery model. We perform this study using a Newtonian blood-analog fluid subjected to a pulsatile flow with two inflow conditions. The first flow condition is fully developed while the second condition is undeveloped (i.e., uniform). We discuss the connection along the axial direction between regions of organized vorticity observed at various cross sections of the model and compare results between the different entrance conditions. We model a human artery with a simple, rigid 180° curved pipe with a circular cross section and constant curvature, neglecting the effects of taper, torsion, and elasticity. Numerical results are computed from a discontinuous high-order spectral element flow solver. The flow rate used in this study is physiological. We observe differences in secondary flow patterns, especially during the deceleration phase of the physiological waveform where multiple vortical structures of both Dean-type and Lyne-type coexist. The results indicate that decreased axial velocities under an undeveloped condition produce smaller secondary flows that ultimately inhibit growth of any interior flow vortices. We highlight the effect of the entrance condition on the formation of these structures and subsequent appearance of abnormal inner wall shear stresses, which suggest there may be a lower prevalence of cardiovascular disease in curved arteries where the flow is rather undeveloped—a potentially physiologically significant result to help understand the influence of blood flow development on disease.

60 APPLIED LIFE SCIENCES↗