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At least 325 records · Page 18

Identifying preferential flow from soil moisture time series: Review of methodologies

Abstract Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods to highlight important information for readers who want to identify PF from soil moisture data and to inform those who aim to develop new methods or improve existing ones. Core Ideas Soil moisture data can be used to identify the occurrence of preferential flow (PF) and its initiating conditions. Various data‐analysis methods to identify PF differ in susceptibility to error, bias, and subjectivity. These methods can utilize vast amounts of data from soil moisture monitoring networks to develop understanding of when, where, and under what conditions PF occurs. Newly developed methods may lead to better accuracy and reliability, and reduce the need for subjective judgments. Plain Language Summary Preferential flow through soil occurs when a large amount of water is suddenly available, as during an intense storm. This type of flow moves rapidly through the soil in distinct narrow pathways rather than moving evenly throughout the body of soil, with major consequences for groundwater resources, ecosystems, spreading of contaminants, and other vital concerns. Methods of detecting preferential flow have been developed that utilize measurements of soil water content made by sensors installed at various depths. This measurement technology has been widely implemented, many locations now having datasets years in length, and various methods have been developed for using these to identify preferential flow. The various methods are based on different features in the soil moisture records and vary in their advantages and shortcomings. In this review, we explain and evaluate these methods, highlighting important information for their implementation to identify preferential flow from soil moisture data and for efforts to develop new methods or improve existing ones.

Nimmo, John R↗

Partial spectral flow in the D1D5 CFT

The two-dimensional 𝒩 = 4 superconformal algebra has a free field realization with four bosons and four fermions. There is an automorphism of the algebra called spectral flow. Under spectral flow, the four fermions are transformed together. In this paper, we study partial spectral flow where only two of the four fermions are transformed. Partial spectral flow is applied to the D1D5 CFT where a marginal deformation moves the CFT away from the free point. The partial spectral flow is broken by the deformation. We show that this effect can be studied due to a transformation of the deformation which is well-defined under partial spectral flow. As a result in the spectrum, we demonstrate how to compute the second-order energy lift of a D1D5P state through its partial spectral flowed state. We find that D1D5P states related by partial spectral flow do not have the same lift in general.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

MRV Challenge 3: velocity and passive scalar comparison in a 3D turbulent flow

The third iteration of a magnetic resonance velocimetry (MRV) challenge comparison activity consisting of 3D flow measurements for a turbulent flow in a water channel moving past centrally positioned cubic obstacles is reported. In this challenge iteration, MRV measurements are coupled with either temperature or concentration measurements to extend the diagnostic utility. Five research teams from around the world conducted the measurements on a single shared apparatus. The water channel included partial elements along the channel sidewalls that varied in height and precluded easy optical accessibility. In addition to a turbulent mainstream flow, a secondary flow entered the channel between the second and third cubic elements from a square injector hole at the channel bottom wall. The injector jet interacts with the mainstream flow and mixes turbulently as it advects downstream. For the selected flow regime and water solutions used as working fluids, the mixing of the higher temperature or concentration through the secondary flow with the mainstream flow satisfies the same dynamics so that both temperature and concentration fields behave as passive scalars and can be directly compared. The measurements are explained in detail by each participating team, and the results are interpolated onto a common grid and compared using line profiles, contour plots, and isosurfaces.

Benson, Mike [ORNL] (ORCID:000000023210116X)↗

Free-Surface Liquid Lithium Flow Modeling and Stability Analysis for Fusion Applications

Liquid metal plasma facing components are considered an attractive design choice for fusion devices including pilot plants. Virtual prototyping of such devices includes modeling of free-surface flow of the electrically conductive liquid, which requires computational fluid dynamics (CFD) and magnetohydrodynamics (MHD) simulations. Numerical tools capable of simulating flows and heat transfer in the free-surface MHD flow were developed at PPPL based on the customized ANSYS CFX. Here, MHD is introduced using a magnetic vector potential approach. Free-surface flow capabilities are available in the code and were tested. Special stabilization procedures were derived and applied to improve convergence of the momentum equations with the source terms due to the Lorentz force and surface tension. Important characteristics of the fusion-relevant liquid metal flow is free surface smoothness and stability. Heat flux from the plasma impacts the liquid surface at a very acute angle, so any change of the free surface from axisymmetry can dramatically increase the local heat flux density and thus create excessive evaporation of liquid lithium into the plasma, which is detrimental to operations. Stability analysis of the liquid metal film flow was performed to determine applicable flow regimes. Thin film flow along horizontal wall is considered. Effects of gravity, magnetic field, and surface tension are included in the analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The role of the spatial heterogeneity and correlation length of surface wettability on two-phase flow in a CO 2 -water-rock system

This study characterized and modeled heterogeneous surface wettability in sandstone and investigated the role of spatial heterogeneity and correlation length of surface wettability on relative permeability in a supercritical CO 2 (scCO 2 )-brine-rock system. Understanding the role of wettability heterogeneity on relative permeability is essential to geological CO 2 sequestration, oil and gas recovery, and contaminated groundwater remediation. Although numerous studies have attempted to understand the influences of surface wettability, capillary number (Ca), and viscosity ratio, the role of the spatial variation and correlation length of surface wettability on two-phase flow in three-dimensional (3D) porous media has not been unraveled due to the challenges in the measurement and representation of realistic rock surface wettability. In this work, we conducted in-situ measurements of surface contact angle (CA) in a Bentheimer sandstone after CO 2 flooding using micro-computed tomography (micro-CT), and found that the pore-scale CA distribution on rock surfaces followed a log-normal distribution associated with a spatial correlation length. Based on the statistical information from CT scanning, a Gaussian random field was used to model CA distributions that had desired standard deviations and spatial correlation lengths, which were then adjusted within a certain range of values for sensitivity analyses to study their combined effects on the two-phase flow in the porous medium using the lattice Boltzmann (LB) method. The LB two-phase flow simulation was accelerated using hybrid, multicore parallel computing to overcome the challenges in simulating multiphase flow in a large 3D domain having 800 × 800 × 600 nodes. The simulation results showed that the surface wettability heterogeneity (i.e., standard deviation of CA) had a lesser effect on the relative permeability of the wetting fluid (water) but a more significant impact on the relative permeability of the non-wetting fluid (scCO 2 ). The Corey model was used to fit the LB-simulated relative permeability curves of water and scCO 2 and showed that the variations in the relative permeability curves for both water and scCO 2 increased as the standard deviation and spatial correlation length of CA increased. This study illustrated that the assumption of homogeneous surface wettability may cause errors in multiphase flow simulations. Furthermore, the impacts of both the standard deviation and spatial correlation length of CAs should be accounted for. This is the first study that explored the spatial correlation lengths associated with CA distributions on sandstone surfaces and comprehensively investigated the roles of both spatial variation and correlation length of CA on two-phase flow properties in 3D porous media. The optimized LB multiphase flow model was proved a powerful tool to study the interplays and combined effects of these statistical parameters, which had critical applications in numerous natural and engineering processes that involved multiphase flow in porous media.

58 GEOSCIENCES↗

Flow reduction of hydrocarbon liquid in silica nanochannel: Insight from many-body dissipative particle dynamics simulations

A modified many-body dissipative particle dynamics (mDPD) model recently developed for realistic mesoscale multiphase flow simulations is rigorously parameterized, calibrated, and applied for elucidating the flow mechanisms of hydrocarbon liquids (i.e., heptane in this work) in amorphous silica cylindrical nanochannels with inner diameters ranging from 4.5 to 22.5 nm. The simulation results suggest the presence of a strong threshold of pressure gradient under which heptane cannot be driven to flow. The threshold for the 4.5 nm diameter pore is 10 to 100 times as high as for the 9–22.5 nm diameter pore, highlighting a remarkable nanoconfinement effect. Fluid viscosity is found to exhibit a shear-thinning phenomenon with intensity to weaken with increasing channel diameter — a phenomenon not observed in nanochannel flow of liquid water and gas in literature. Most remarkably, the radial profiles of average longitudinal flow velocity fitted by the modified Hagen-Poiseuille equation showed a negative slip length (–2.5% to –0.5% relative to the diameter) and a reduction of apparent permeability by 16% to 23%. Furthermore, this finding suggests silica nanochannels tend to deter hydrocarbon flow, a phenomenon that is opposed to the flow enhancement reported in most of the prior nanochannel flow studies in literature.

74 ATOMIC AND MOLECULAR PHYSICS↗

In-situ thermophysical measurement of flowing molten chloride salt using modulated photothermal radiometry

Molten salts are leading candidates for high-temperature heat transfer fluids (HTFs) for thermal energy storage and conversion systems in concentrated solar power (CSP) and nuclear energy power plants. The ability to probe molten salt thermal transport properties in both stationary and flowing status is important for the evaluation of their heat transfer performance under realistic operational conditions, including the temperature range and potential degradation due to corrosion and contamination. However, accurate thermal transport properties are usually challenging to obtain even for stagnant molten salts due to different sources of errors from convection, radiation, and corrosion, let alone at flowing status. To the best of authors’ knowledge, there is no available in-situ technique for measuring flowing molten salt thermal conductivity. Here, we report the first in-situ flowing molten salt thermal conductivity measurement using modulated photothermal radiometry (MPR). We could successfully perform the first in-situ thermal conductivity measurement of flowing molten NaCl-KCl-MgCl 2 in the typical operating temperature (520 and 580 °C) with flow velocities ranging from around 0.3 to 1.0 m s -1 . The relative change of the molten salt thermal conductivity was measured. Gnielinski’s correlation was also used to estimate the heat transfer coefficient h of the flowing NaCl-KCl-MgCl 2 in the given experimental condition. Furthermore, the work showed the potential of the MPR technique serving as an in-situ diagnostics tool to evaluate the heat transfer performance of flowing molten salts and other high-temperature HTFs.

14 SOLAR ENERGY↗

Tensor-based flow reconstruction from optimally located sensor measurements

Reconstructing high-resolution flow fields from sparse measurements is a major challenge in fluid dynamics. Existing methods often vectorize the flow by stacking different spatial directions on top of each other, hence confounding the information encoded in different dimensions. Here, we introduce a tensor-based sensor placement and flow reconstruction method which retains and exploits the inherent multidimensionality of the flow. We derive estimates for the flow reconstruction error, storage requirements and computational cost of our method. We show, with examples, that our tensor-based method is significantly more accurate than similar vectorized methods. Furthermore, the variance of the error is smaller when using our tensor-based method. While the computational cost of our method is comparable to similar vectorized methods, it reduces the storage cost by several orders of magnitude. The reduced storage cost becomes even more pronounced as the dimension of the flow increases. We demonstrate the efficacy of our method on three examples: a chaotic Kolmogorov flow, in situ and satellite measurements of the global sea surface temperature and three-dimensional unsteady simulated flow around a marine research vessel.

Mechanics↗

Deep learning closure models for large-eddy simulation of flows around bluff bodies

Near-wall flow simulation remains a central challenge in aerodynamics modelling: Reynolds-averaged Navier–Stokes predictions of separated flows are often inaccurate, and large-eddy simulation (LES) can require prohibitively small near-wall mesh sizes. A deep learning (DL) closure model for LES is developed by introducing untrained neural networks into the governing equations and training in situ for incompressible flows around rectangular prisms at moderate Reynolds numbers. The DL-LES models are trained using adjoint partial differential equation (PDE) optimization methods to match, as closely as possible, direct numerical simulation (DNS) data. They are then evaluated out-of-sample – for aspect ratios, Reynolds numbers and bluff-body geometries not included in the training data – and compared with standard LES models. The DL-LES models outperform these models and are able to achieve accurate LES predictions on a relatively coarse mesh (downsampled from the DNS mesh by factors of four or eight in each Cartesian direction). We study the accuracy of the DL-LES model for predicting the drag coefficient, near-wall and far-field mean flow, and resolved Reynolds stress. A crucial challenge is that the LES quantities of interest are the steady-state flow statistics; for example, a time-averaged velocity component $\langle {u}_i\rangle (x) = \lim _{t \rightarrow \infty } ({1}/{t}) \int _0^t u_i(s,x)\, {\rm d}s$ . Calculating the steady-state flow statistics therefore requires simulating the DL-LES equations over a large number of flow times through the domain. It is a non-trivial question whether an unsteady PDE model with a functional form defined by a deep neural network can remain stable and accurate on $t \in [0, \infty )$ , especially when trained over comparatively short time intervals. Our results demonstrate that the DL-LES models are accurate and stable over long time horizons, which enables the estimation of the steady-state mean velocity, fluctuations and drag coefficient of turbulent flows around bluff bodies relevant to aerodynamics applications.

Mechanics↗

Suppression of the collisionless tearing mode by flow shear: implications for reconnection onset in the Alfvénic solar wind

We analyse the collisionless tearing mode instability of a current sheet with a strong shear flow across the layer. The growth rate decreases with increasing shear flow, and is completely stabilised as the shear flow becomes Alfvénic. We also show that, in the presence of strong flow shear, the tearing mode growth rate decreases with increasing background ion-to-electron temperature ratio, the opposite behaviour to the tearing mode without flow shear. We find that even a relatively small flow shear is enough to dramatically alter the scaling behaviour of the mode, because the growth rate is small compared with the shear flow across the ion scales (but large compared with shear flow across the electron scales). Our results may explain the relative absence of reconnection events in the near-Sun Alfvénic solar wind observed recently by NASA’s Parker Solar Probe.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

SPH Modeling of Biomass Granular Flow: Engineering Application in Hoppers and Augers

Numerical modeling of granular biomass material flow in handling operations is indispensable to decipher flow upsets, commonly manifested as clogging and jamming in hoppers and augers. With a computational tool developed based on smoothed particle hydrodynamics (SPH), we simulated the hopper flow and auger feeding of six granular biomass materials. The good agreement between the experimental and numerical flow rates demonstrated the capability of the developed SPH solver in modeling the complicated flow of granular biomass materials. Further, the impact of physical and numerical parameters is investigated, and the major results show that the hopper flow pattern is controlled by shear band evolution; hopper clogging is collectively influenced by the opening size, wall friction, and material packing, and the impact of material compressibility on the auger feed rate is minimal. These parametric studies validate the solver’s robustness in simulating biomass flow in handling equipment and demonstrate that the SPH computational tool can provide insights about granular flow mechanics to facilitate handling equipment design and optimize handling operations.

09 BIOMASS FUELS↗

Flow resistance of phloem sieve plates revisited using an experimental model

Sieve plate resistance has been identified as the key to understanding the efficiency of phloem transport of carbohydrates in trees. These plates with small holes connecting sieve tubes are responsible for the largest resistance to flow in the phloem. Their structure determines how fast sugars can be transported through the phloem with certain pressure differences and what the limits for phloem transport in different plants are. Because experiments with the phloem are very challenging, our understanding of sieve plate resistance is mostly based on anatomical studies and hydrodynamic modeling of flow through sieve plates. These models calculate the resistance of the entire sieve tube–sieve plate system using the Hagen–Poiseuille flow resistance for the sieve cell lumen and a combination of the Hagen–Poiseuille resistance and Sampson flow resistance through the sieve pores. The resistance of the entire sieve plate is calculated by summing the Hagen–Poiseuille and Sampson flow resistances of each pore. To test the validity of this model formulation, an experimental model with aspect parameters similar to phloem sieve tubes was built using polyvinyl chloride (PVC) piping and plastic straws of different diameters and lengths. This system was used to measure flow rates and calculate flow resistance at Reynolds numbers 0.5–300. The results suggest that the current models may significantly overestimate the flow resistance caused by sieve plates and that the resistance might be better described by formulations used for perforated plates.

54 ENVIRONMENTAL SCIENCES↗

Limit cycle oscillations in the zonal-flow-catalyzed interactions of ion-temperature-gradient turbulence

Limit-cycle oscillations are studied for ion temperature gradient turbulence, which, in the absence of large diamagnetic (mean) shear flows, saturates through energy transfer from unstable modes to large-scale stable modes via zonal-flow intermediary modes. Oscillations of zonal flow and turbulence levels are strongly constrained by the reactive, largely non-dissipative character of the zonal flows. Since existing predator–prey models for observed oscillations in experiments do not include energy transfer through zonal flows to stable modes, low-order fluid models with this physics are constructed and investigated. A simple three-wave truncation produces low-amplitude zonal flows that slowly oscillate around a zero mean, with turbulence oscillations between coupled wavenumbers that exceed linear frequencies by orders of magnitude. This inconsistency with experimental observations is caused by the weak non-linear drive of zonal flows in three-wave systems and the lack of multiple-wavenumber turbulent interactions. A more comprehensive model that preserves multiple wavenumber interactions within the context of conservative zonal-flow-mediated energy transfer to stable modes accurately reflects observed dynamics when the phase between stable and unstable modes is occasionally randomized.

Li, P. -Y. (ORCID:0000000295254171)↗

Experimental, numerical and analytical evaluation of j × B -thrust for fast-liquid-metal-flow divertor systems of nuclear fusion devices

Abstract Divertor systems of fusion devices are exposed to intense heat loads from plasmas, which degrade solid plasma-facing components. Fast liquid metal (LM) flow divertors may be more advantageous for this purpose but have risk of piling due to intense magnetohydrodynamic (MHD) drag. However, severe deceleration of the flow could be countered with the injection of currents that are transverse to external magnetic fields, allowing to thrust the flow with j × B (Lorentz) forces. Given that the injection of currents as an approach to propel LM-divertor flows has remained experimentally understudied, this article focuses on the evaluation of j × B -thrust and finding its drawbacks. j × B -thrust was experimentally tested with free-surface-LM flows, a vertical magnetic field and an externally applied current. Experiments were reviewed with a theoretical model, showing agreement in the trends of theory and experiments. Full 3D-MHD-free-surface-flow simulations were also performed with FreeMHD and confirmed the sensitivity to unstable flow behavior in LM systems when applying external currents. Furthermore, excessive power requirements are expected for the implementation of j × B -thrust at the reactor scale, making these systems inefficient for commercial devices. This paper evidences that the simple operation of a LM-flow divertor with j × B -thrust, without any of the instabilities caused from reactor plasmas or parasitic currents, already presents intrinsic challenges.

Magnetohydrodynamics↗

Saturation of fishbone instability through zonal flows driven by energetic particle transport in tokamak plasmas

Gyrokinetic and kinetic-MHD simulations are performed for the fishbone instability in the DIII-D discharge #178631, chosen for validation of first-principles simulations to predict the energetic particle (EP) transport in an ITER prefusion baseline scenario. Fishbone modes are found to generate zonal flows, which dominate the fishbone saturation. The underlying mechanisms of the two-way fishbone-zonal flows nonlinear interplay are discussed in details. Numerical and analytical analyses identify the fishbone-induced EP redistribution as the dominant generation mechanism for zonal flows. The zonal flows modify the nonlinear dynamics of phase space zonal structures, which reduces the amount of EPs able to resonate with the mode, leading to an early fishbone saturation. Simulation results including zonal flows agree quantitatively with DIII-D experimental measurements of the fishbone saturation amplitude and EP transport, supporting this novel saturation mechanism by self- generated zonal flows. Moreover, the wave-particle mode-locking mechanism is shown to determine quantitatively the fishbone frequency down-chirping, as evident in GTC simulation results in agreement with predictions from analytical theory. Finally, the
fishbone-induced zonal flows are possibly responsible for the formation of an ion-ITB in the DIII-D discharge. Based on the low EP transport and the large zonal flow shearing rates associated with the fishbone instability in gyrokinetic simulations of the ITER scenario, it is conjectured that high performance scenarios could be designed in ITER burning plasmas through fishbone-induced ITBs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Disentangling the Influences of Storm-Relative Flow and Horizontal Streamwise Vorticity on Low-Level Mesocyclones in Supercells

Sufficient low-level storm-relative flow is a necessary ingredient for sustained supercell thunderstorms and is connected to supercell updraft width. Assuming a supercell exists, the role of low-level storm-relative flow in regulating supercells’ low-level mesocyclone intensity is less clear. One possibility considered in this article is that storm-relative flow controls mesocyclone and tornado width via its modulation of overall updraft extent. This hypothesis relies on a previously postulated positive correspondence between updraft width, mesocyclone width, and tornado width. An alternative hypothesis is that mesocyclone characteristics are primarily regulated by horizontal streamwise vorticity irrespective of storm-relative flow. A matrix of supercell simulations was analyzed to address the aforementioned hypotheses, wherein horizontal streamwise vorticity and storm-relative flow were independently varied. Among these simulations, mesocyclone width and intensity were strongly correlated with horizontal streamwise vorticity, and comparatively weakly correlated with storm-relative flow, supporting the second hypothesis. Accompanying theory and trajectory analysis offers the physical explanation that, when storm-relative flow is large and updrafts are wide, vertically tilted streamwise vorticity is projected over a wider area but with a lesser average magnitude than when these parameters are small. These factors partially offset one another, degrading the correspondence of storm-relative flow with updraft circulation and rotational velocity, which are the mesocyclone attributes most closely tied to tornadoes. In conclusion, these results refute the previously purported connections between updraft width, mesocyclone width, and tornado width, and emphasize horizontal streamwise vorticity as the primary control on low-level mesocyclones in sustained supercells.

54 ENVIRONMENTAL SCIENCES↗

One-dimensional temperature measurement of supersonic jet flow by resonantly ionized photoemission thermometry of molecular nitrogen

As the field of fluid dynamics progresses, the demand for sophisticated diagnostic methods to accurately assess flow conditions rises. In this work, resonantly ionized photoemission thermometry (RIPT) has been used to directly target and ionize diatomic nitrogen (N 2 ) to measure one-dimensional (1D) temperature profiles in a supersonic jet flow. This technique can be considered non-intrusive as the premise uses resonantly enhanced multiphoton ionization (REMPI) to target molecular nitrogen. This resonance excites N 2 into absorption bands of the P, Q, and R rotational branches of N 2 ( b 1 Π u ). The ideal (3 + 1) REMPI scheme excites from the ground state and ionizes N 2 ( b 1 Π u ← X 1 Σ g + ) where de-excitation results in photoemission from the first negative band of ionized N 2 + ( B 2 Σ u + → X 2 Σ g + ) as nitrogen returns to the ground state. The resulting emission can be observed using an intensified camera, thus permitting inference of the rotational temperature of ground-state molecular nitrogen. A linearly regressive Boltzmann distribution is applied based on previous calibration data for this technique to quantify the temperature along the ionized line. This work applies this technique to a pure N 2 supersonic jet in cross-flow and counter-flow orientations to demonstrate N 2 RIPT’s applications in a supersonic flow. Temperature variations are observed at different locations downstream of the exit in cross-flow, and axisymmetric in counter-flow, to generate profiles characterizing the flow dynamics. Due to the collisional effects resulting from the number density of N 2 at higher pressures, a (3 + 2) REMPI scheme is observed throughout this text.

Clark, Aleksander (ORCID:0009000855600042)↗

Discrete Fracture Network Modeling to Estimate Upscaled Parameters for the Topopah Spring, Lava Flow, and Tiva Canyon Aquifers at Pahute Mesa, Nevada National Security Site

This report describes the results of Discrete Fracture Network (DFN) simulations for the Topopah Spring Aquifer (TSA), Lava Flow Aquifer, and Tiva Canyon Aquifer (TCA), at Pahute Mesa on the Nevada National Security Site (NNSS), formerly the Nevada Test Site. The research focuses on calculating upscaled groundwater flow and contaminant transport parameters using DFNs generated according to fracture characteristics observed in the TSA, LFA and TCA at Pahute Mesa. The highly fractured and heterogeneous nature of these aquifers makes them candidates for stochastic DFN modeling of radionuclide transport on a small scale with subsequent upscaling. One hundred independent DFN realizations are generated for each aquifer, and the upscaled parameters for continuum simulations of subsurface flow and transport in fractured media at Pahute Mesa are calculated. Our goal is to implement a modeling approach that can translate parameters to larger-scale models that account for local-scale flow and transport processes, such as channelization of flow and transport along a few well connected, large fractures. Additionally, to simulate advective and advective-diffusive transport through the fracture networks, the Time Domain Random Walk (TDRW) approach is applied to account for matrix diffusion into a finite half-space. Moreover, a novel approach to calculate dynamic (active) fracture surface area to reflect flow channeling is implemented. This work will improve the representation of radionuclide transport processes in largescale, regulatory-focused models by providing estimates of hard-to-measure flow and contaminant transport parameters at large scales. In this report, we (1) show recent results of flow and transport simulations on multiple DFN realizations of the TSA, LFA, TCA; (2) discuss the resulting distributions of estimated upscaled parameters; (3) describe the estimation of upscaled parameters for an equivalent parallel-plate continuum model and (4) present a comparison between simulated transport from the equivalent continuum model and an actual DFN.

54 ENVIRONMENTAL SCIENCES↗