Homogeneous Model Research Articles

The Effective Vertical Anisotropy of Layered Aquifers.

Many sedimentary aquifers consist of small layers of coarser and finer material. When groundwater flow in these aquifers is modeled, the hydraulic conductivity may be simulated as homogeneous but anisotropic throughout the aquifer. In practice, the anisotropy factor, the ratio of the horizontal divided by the vertical hydraulic conductivity, is often set to 10. Here, numerical experiments are conducted to determine the effective anisotropy of an aquifer consisting of 400 horizontal layers of which the homogeneous and isotropic hydraulic conductivity varies over two orders of magnitude. Groundwater flow is simulated to a partially penetrating canal and a partially penetrating well. Numerical experiments are conducted for 1000 random realizations of the 400 layers, by varying the sequence of the layers, not their conductivity. It is demonstrated that the effective anisotropy of the homogeneous model is a model parameter that depends on the flow field. For example, the effective anisotropy for flow to a partially penetrating canal differs from the effective anisotropy for flow to a partially penetrating well in an aquifer consisting of the exact same 400 layers. The effective anisotropy also depends on the sequence of the layers. The effective anisotropy values of the 1000 realizations range from roughly 5 to 50 for the considered situations. A factor of 10 represents a median value (a reasonable value to start model calibration for the conductivity variations considered here). The median is similar to the equivalent anisotropy, defined as the arithmetic mean of the hydraulic conductivities divided by the harmonic mean.

A Measure of Departure from Marginal Homogeneity using Continuation Odds for Square Contingency Tables with Ordered Categories

For the analysis of square contingency tables with ordinal classifications, the marginal homogeneity (MH) model is the one of important models. Some measures for analyzing the degree of departure from the MH model have been proposed. This study proposes a new measure using the continuation odds. Continuation odds may be considered as discrete time hazard. The proposed measure is expressed in the form of Cressie-Read’s power-divergence (including the Kullback-Leibler divergence) or Patil and Taillie’s diversity index (including Shannon entropy). This study derives a plug-in estimator of the proposed measure and an approximate confidence interval for the proposed measure. Through numerical examples, we evaluate the performances of them. Additionally. the usefulness of the proposed measure is demonstrated by applying it to real data that the row and column variables are the discrete survival time variables.

Estimating equivalent elastic properties of frozen clay soils using an XFEM-based computational homogenization

This study addresses the challenge of estimating the elastic properties of heterogeneous frozen clay soils by introducing a comprehensive approach that combines analytical and numerical models. The frozen clay soil is treated as a mixture composed of frozen clay-water composites and nonclay mineral inclusions. An inversion algorithm is employed to deduce the elastic properties of the matrix (clay-water composites) of two artificially frozen sandy clay samples with known temperature-dependent elastic properties. Subsequently, a two-dimensional numerical simulation using the eXtended Finite Element Method (XFEM) is conducted to carry out numerical homogenization by considering the imperfect bond among frozen clay-water composites and nonclay minerals. The numerical homogenization model offers insights into the temperature-dependent behavior of the interface stiffness parameter. The numerical homogenization results are compared with conventional numerical homogenization approaches like the FEM, which rigidly defines the bonding between inclusions and the matrix. The comparison indicates that the neglect of imperfect bonds among clay-water composites and nonclay minerals will lead to unrealistic outcomes in cases with a high fraction of inclusions. This integrated approach advances the understanding and prediction of elastic properties of frozen clay soils by considering their heterogeneous nature.

Efficient removal of Cr(VI) ions from industrial wastewater using carbon-based adsorbents functionalized with boronic acid

Abstract The adsorption of potentially toxic element ions from contaminated water sources has garnered significant attention due to its critical role in environmental remediation and ensuring safe drinking water. Potentially toxic element ions can be removed from water using conventional adsorbents such as activated zeolites; however, these materials have low absorption and slow kinetics. To solve these issues, carbon-based adsorbents that exhibit easy synthesis, high porosity, designability, and stability have been proposed. In this study, a carbon-based adsorbent, named Magnetic Nitrogen-Doped Carbon (M-NC), and graphene oxide were developed for the selective removal of potentially toxic element ions. To increase the potential for HM immobilization, sulfide-modified biochar was created via a process called simultaneous carbon layer encapsulation. A theoretical physicochemical and thermodynamic investigation of the adsorption of potentially toxic elements s Zn2+, Cd2+, Ni2+, Ag2+, Pb2+ and Cu2+ on carbon-based adsorbents was performed with statistical physics fundaments. The biochar with large surface areas is used to remove potentially toxic element ions, one of the most important potentially toxic element pollutants, from aqueous solutions. The capacity of the adsorbent for removing potentially toxic element ions was studied using Langmuir adsorption isotherm under ultrasound-assisted conditions. The MNCs can be applied to the Langmuir model and pseudo-second-order kinetics. It is possible to use the Langmuir and second-order kinetic equations to accurately explain the adsorption method. Thermodynamic limitations were also envisioned because sorption is exothermic when it happens spontaneously. A homogeneous statistical physics adsorption model was used to describe and analyze the experimental potentially toxic element removal isotherms at 30 °C and pH5 utilizing adsorbents produced by pyrolysis of biomasses (broccoli stalks). The findings show the proposed adsorbent, with an efficiency of 98.7 % and even reaching 99.3 % in certain cases, making it a standout choice for potentially toxic element removal applications. This research holds significance in advancing the understanding of environmentally sustainable potentially toxic element removal processes, particularly in the context of biomass-derived adsorbents, offering potential solutions for water purification and environmental remediation.

On the comparison between phenomenological and kinetic theories of gas mixtures with applications to flocking

We study the comparison between the phenomenological and kinetic models for a mixture of gases from the viewpoint of collective dynamics. In the case in which constituents are Eulerian gases, balance equations for mass, momentum, and energy are the same in the main differential part, but production terms due to the interchanges between constituents are different. They coincide only when the thermal and mechanical diffusion are sufficiently small. In this paper, we first verify that both models satisfy the universal requirements of conservation laws of total mass, momentum, and energy, Galilean invariance and entropy principle. Following the work of Ha and Ruggeri (ARMA 2017), we consider spatially homogeneous models which correspond to the generalizations of the Cucker Smale model with thermal effect. In these circumstances, we provide analytical results for the comparison between two resulting models and also present several numerical simulations to complement analytical results.

Acoustic wave simulation in strongly heterogeneous models using a discontinuous Galerkin method

In recent years, the discontinuous Galerkin method (DGM) has been rapidly developed for the numerical simulation of seismic waves. For wavefield propagation between two adjacent elements, it is common practice to apply a numerical flux to the boundary of each element to propagate waves between adjacent elements. Several fluxes, including the center, penalty, local Lax-Friedrich (LLF), upwind, and Rankine-Hugoniot jump condition-based (RH condition) fluxes, are widely used in numerical seismic wave simulation. However, some fluxes do not account for media differences between adjacent elements. Although different fluxes have been successfully used in DGM for many velocity models, it is unclear whether they can produce sufficiently accurate or stable results for strongly heterogeneous models, such as checkerboard models commonly used in tomographic studies. We test different fluxes using the acoustic wave equation. We analyze the accuracy of the penalty, LLF, upwind, and RH-condition fluxes based on the results of the numerical simulations of the homogeneous and two-layer models. We conduct simulations using checkerboard models, and the results indicate that the LLF, penalty, and upwind fluxes may have instability problems in heterogeneous models with long-time simulations. We observe instability issues in the LLF, penalty, and upwind fluxes when the wave-impedance contrast is high at the media interface. However, the results of the RH-condition flux remain consistently stable. The series of numerical examples presented in this work provide insights into the characteristics and application of fluxes for seismic wave modeling.

Real-time simulation for multi-component biomechanical analysis using localized tissue constraint progressive transfer learning

In virtual surgical training, it is crucial to achieve real-time, high-fidelity simulation of the tissue deformation. The anisotropic and nonlinear characteristics of the organ with multi-component make accurate real-time deformation simulation difficult. A localized tissue constraint progressive transfer learning method is proposed in this paper, where the base-compensated dual-output transfer learning strategy and the localized tissue constraint progressive learning architecture are developed. The proposed strategy enriches the multi-component biomechanical dataset to fully represent complex force-displacement with minimal high-quality data. Meanwhile, the proposed architecture adopts focused and progressive model to accurately describe tissues with varied biomechanical properties rather than singular homogeneous model. We made comparison with 4 state-of-the-art (SOTA) methods in simulating multi-component biomechanical deformations of organs with 100 pairs of testing data. Results show that the accuracy of our method is 50% higher than other methods in different validation matrix. And our method can stably simulate the deformations in 0.005 s per frame, which largely improves the computing efficiency.

A Novel Approach to Continuum FE Multiphysics Simulation of Batteries via Heterogeneous Homogenization

Advancements in modern technology necessitate batteries that can be safely charged and discharged at high rates with minimal aging. A promising strategy to achieve these ends is through optimization of porous microstructures of existing electrode materials to promote better electrical and ionic transport without compromising energy density, as has been shown experimentally by introducing laser ablation channels to the electrodes. The present work proposes a microstructure up-scaling methodology that efficiently accounts for material heterogeneity by assigning a porosity field to a continuum scale finite element mesh, effectively homogenizing materials while maintaining the heterogeneous porosity distribution inherent to the original microstructure. Constitutive relationships relating solid electric conductivity and pore tortuosity to local porosity are directly computed from fully resolved anode, cathode, and separator microstructure 3D models and assigned in the continuum as material properties of a finite element mesh. This allows for utilization of the computationally efficient, homogenized Newman model while maintaining dependency on the heterogeneous local porosity. Then, coupled electrochemical-thermal-mechanical-pore pressure finite element simulations are performed on the battery cell model with this heterogeneous porosity field, and associated local variations on transport properties are prescribed as material properties by the precomputed constitutive relationships. Performance metrics and lithium plating potential are compared to the results of simulations of the fully homogenized cell with the same constitutive relationships and to the base case of a fully homogenous cell with typical modelling assumptions applied to porosity dependent constitutive relationships. These comparisons are made both as a means of validating the methodology and to demonstrate the vast differences that arise when simplifying assumptions are used instead of the constitutive relationships of the actual material microstructure. Finally, the methodology is used in its intended optimization application to compare the performance of a typical battery microstructure to a similar porous microstructure with micro holes added via laser ablation. The results indicate that differences in the microstructure of materials with identical average porosities and similar constitutive relationships can have significant differences in both cell performance and aging that would typically be impossible to detect using fully homogeneous continuum modeling. Figure 1

Integration of inter-ply electrical percolation phenomena in the multiphysics modelling of laminated composite materials

PurposeThis study aims to introduce a predictive homogenization model incorporating electrical percolation considerations to forecast the electrical characteristics of unidirectional carbon-epoxy laminate composites.Design/methodology/approachThis study presents a method for calculating the electrical conductivity tensor for various ply arrangement patterns to elucidate phenomena occurring around the interfaces between plies. These interface models are then integrated into a three-dimensional (3D) magneto-thermal model using the finite element method. A comparative study is conducted between different approaches, emphasizing the advantages of the new model through experimental measurements.FindingsThis research facilitates the innovative integration of electrical percolation considerations, resulting in substantial improvement in the prediction of electrical properties of composites. The validity of this improvement is established through comprehensive validation against existing approaches and experimentation.Research limitations/implicationsThe study primarily focuses on unidirectional carbon-epoxy laminate composites. Further research is needed to extend the model's applicability to other composite materials and configurations.Originality/valueThe proposed model offers a significant improvement in predicting the electrical properties of composite materials by incorporating electrical percolation considerations at inter-ply interfaces, which have not been addressed in previous studies. This research provides valuable information to improve the accuracy of predictions of the electrical properties of composites and offers a methodology for accounting for these properties in 3D magneto-thermal simulations.

Multiple Clues for Dayside Aerosols and Temperature Gradients in WASP-69 b from a Panchromatic JWST Emission Spectrum

WASP-69 b is a hot, inflated, Saturn-mass planet (0.26 M Jup) with a zero-albedo equilibrium temperature of 963 K. Here, we report the JWST 2–12 μm emission spectrum of the planet consisting of two eclipses observed with NIRCam grism time series and one eclipse observed with the MIRI low-resolution spectrometer (LRS). The emission spectrum shows absorption features of water vapor, carbon dioxide, and carbon monoxide, but no strong evidence for methane. WASP-69 b’s emission spectrum is poorly fit by cloud-free homogeneous models. We find three possible model scenarios for the planet: (1) a scattering model that raises the brightness at short wavelengths with a free geometric albedo parameter; (2) a cloud-layer model that includes high-altitude silicate aerosols to moderate long-wavelength emission; and (3) a two-region model that includes significant dayside inhomogeneity and cloud opacity with two different temperature–pressure profiles. In all cases, aerosols are needed to fit the spectrum of the planet. The scattering model requires an unexpectedly high geometric albedo of 0.64. Our atmospheric retrievals indicate inefficient redistribution of heat and an inhomogeneous dayside distribution, which is tentatively supported by MIRI LRS broadband eclipse maps that show a central concentration of brightness. Our more plausible models (2 and 3) retrieve chemical abundances enriched in heavy elements relative to solar composition by 6× to 14× solar and a C/O ratio of 0.65–0.94, whereas the less plausible highly reflective scenario (1) retrieves a slightly lower metallicity and lower C/O ratio.

Schistosomiasis mathematical model in a spatially heterogeneous environment

Schistosomiasis is classified by WHO as a neglected tropical disease. Recent research works have shown that large-scale development projects involving massive population displacement and water irrigation, such as the construction of dams, lakes, and the development of agricultural areas, favour the proliferation of bilharzia. These observations motivate us to propose a reaction–diffusion model to assess the role of the displacements of humans, snails, cercaria, miracidia in the transmission dynamics of Schistosomiasis. The model incorporates a general non-linear contact functions and density-dependent parameters. The aim is to better understanding the role of spatial interactions on the spread of Schistosomiasis, in order to propose appropriate recommendations for the control of that silent threat. We characterize the basic reproduction number R0 of the model. The uniform persistence theory, the maximum principle are used to conduct an in-depth analysis of both the homogeneous and heterogeneous models. Theoretical results are illustrated through numerical simulations.

Computer vision for enhanced quantification of FEA of ballistic impact

In finite element (FE) modelling, the visual assessment of images of contour plots is widely used for qualitative comparison and analysis. However, this approach has limitations in conducting in-depth and comprehensive analysis, which is rigorously made based on objective, massive, and quantitative data. To tackle the problems, we propose a methodology based on computer vision with k-means clustering algorithms, providing an effective quantitative strategy to improve the efficiency and accuracy of the analysis. To demonstrate the application of this methodology, three levels of FE models on impact, viz. macro (homogenous UD laminate model), meso (yarn-level fabric model), and micro (fibre-level yarn model), are developed, where the images with both simple and complex morphologies and backgrounds are all be considered. The contour plots of stress and transverse deformation are clustered into k categories based on the RGB values of the pixels in the images. Notably, the quantification of one image using the proposed methodology is completed in seconds, and the efficiency is enhanced by approximately 40 times compared with that using the manual method, without the accuracy sacrificed. This methodology enables the researchers to efficiently and precisely understand the ballistic behaviours of the textile materials from the perspectives of fibres, yarn, fabrics, etc., and has great potential to apply in other research fields, where computational simulation is widely used.

A Markov method for a mechanical system reliability assessment using discrete degradation data

Abstract A homogenous continuous-time Markov model (HCTMM) has the advantage of high accuracy and is usually used in reliability analysis. However, the transition intensities (rates) between any two states cannot be accurately obtained due to the discrete data obtained from a mechanical system and little expert knowledge. This paper proposes a method in which the transition intensity matrix of an HCTMM can be obtained indirectly using the actual discrete degradation data of a mechanical system. Firstly, the one-step transition probability matrix can be calculated by a hidden Markov model using the discrete degradation data. Secondly, the unit-time transition intensity matrix can be calculated from the one-step transition probability matrix. At last, an HCTMM is established to assess the reliability of a mechanical system based on the unit-time transition intensity matrix. Moreover, considering the maintenance activities cannot restore a mechanical system as a fire-new one, the random transition of a mechanical system after maintenance is expressed by a quasi-renewal process in this paper. Finally, three cases are studied to validate the proposed method.

Interfacial Electrochemistry of Catalyst-Coordinated Graphene Nanoribbons.

The immobilization of molecular electrocatalysts on conductive electrodes is an appealing strategy for enhancing their overall activity relative to those of analogous molecular compounds. In this study, we report on the interfacial electrochemistry of self-assembled two-dimensional nanosheets of graphene nanoribbons (GNR-2DNS) and analogs containing a Rh-based hydrogen evolution reaction (HER) catalyst (RhGNR-2DNS) immobilized on conductive electrodes. Proton-coupled electron transfer (PCET) taking place at N-centers of the nanoribbons was utilized as an indirect reporter of the interfacial electric fields experienced by the monolayer nanosheet located within the electric double layer. The experimental Pourbaix diagrams were compared with a theoretical model, which derives the experimental Pourbaix slopes as a function of parameter f, a fraction of the interfacial potential drop experienced by the redox-active group. Interestingly, our study revealed that GNR-2DNS was strongly coupled to glassy carbon electrodes (f = 1), while RhGNR-2DNS was not (f = 0.15). We further investigated the HER mechanism by RhGNR-2DNS using electrochemical and X-ray absorption spectroelectrochemical methods and compared it to homogeneous molecular model compounds. RhGNR-2DNS was found to be an active HER electrocatalyst over a broader set of aqueous pH conditions than its molecular analogs. We find that the improved HER performance in the immobilized catalyst arises due to two factors. First, redox-active bipyrimidine-based ligands were shown to dramatically alter the activity of Rh sites by increasing the electron density at the active Rh center and providing RhGNR-2DNS with improved catalysis. Second, catalyst immobilization was found to prevent catalyst aggregation that was found to occur for the molecular analog in the basic pH. Overall, this study provides valuable insights into the mechanism by which catalyst immobilization can affect the overall electrocatalytic performance.

The damping factor improved the algorithm in semi-airborne transient electromagnetic modelling based on accelerated FDTD

3D modelling plays a crucial role in analysing semi-airborne transient electromagnetic fields, how to accurately and efficiently calculate electromagnetic response has become a significant issue. In this paper, a damping factor improved algorithm of the accelerated finite difference time domain (AFDTD) is proposed for semi-airborne transient electromagnetic modelling. Differing from the previous research, we introduce a novel function to redefine the damping factor, allowing for adaptive adjustment and enhancing calculation accuracy within the finite difference time domain (FDTD) iterative process. To verify the effectiveness of our approach, we conduct tests using homogeneous half-space models, which demonstrate that the improved damping factor significantly enhances calculation accuracy without a notable reduction in efficiency. Furthermore, we apply our improvement to typical conductivity models and polarisable conductivity models, and the results indicate that our approach achieves high accuracy in accelerated semi-airborne transient electromagnetic modelling.

Posttraumatic growth and psychopathological symptoms as predictors in the integration of North Korean adolescent refugees: Latent profile analysis.

This study is to explore identifiable psychological differences and predictors for the subgroup of refugees who at a very early age moved from a totalitarian country to a westernized democracy, ultimately to improve policies and reduce the maladaptation of refugees to a new society. More specifically, it is to fill in significant gaps in understanding and predicting refugee tendencies toward depression, social withdrawal, aggression, and posttraumatic growth. Latent class analysis was conducted to identify subgroups based on symptom profiles within a sample of 201 North Korean adolescent refugees residing in South Korea. Four subgroups were identified: (a) High growth, (b) Low trauma with high adaptive aggression, (c) Low trauma with high social withdrawal/depression, and (d) High trauma with high comorbidity. Predictors were physical health, self-esteem, peer support, teacher support, and school adjustment. Current refugee policies in South Korea would benefit from refining services to allow customization to the specific needs and characteristics of each adolescent rather than continue the current model of homogeneity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Unravelling the relation between free volume gradient and shear band deflection induced extra plasticity in metallic glasses

Previous experiments have revealed that the controllable introduction of structural gradients in metallic glasses (MGs) can endow the materials with extra plasticity due to the gradient-induced deflection of shear bands. However, the relation between the spatial structural gradient and the initiation of shear band deflection remains unclear. The current study has been focused on investigating the relationship between the improved mechanical properties of MGs and structural gradients specified by the distribution of the intrinsic free volume. Molecular dynamics (MD) simulations are firstly performed on homogeneous MG models containing various initial free volume values, showing that the shear band angle increases with decreasing free volume under uniaxial compression, whereas higher shear band angle is observed under uniaxial tension with increasing free volume. Based on the asymmetric behaviors of MGs under compression and tension, a theoretical model is developed to quantitatively characterize the influence of free volume on the mechanical response of MGs, which incorporates a failure criterion based on free volume generation during external loadings. The model can be further utilized to interpret and predict the fracture strain, shear band angle, maximum stress, and fracture surface morphology of gradient structured MGs in both simulations and experiments. The relationship between free volume gradient and shear band deflection induced extra plasticity established in this study provides valuable guidance for the structural design of MGs with enhanced mechanical properties.

Computation of SWCNT/MWCNT-doped thermo-magnetic nano-blood boundary layer flow with non-Darcy, chemical reaction, viscous heating and Joule dissipation effects

CNTs have been shown to exhibit exceptional electrical and thermal conductivities, chemical and mechanical stability and physiochemical reliability in wide-ranging applications covering biomedicine, energy and aerospace. Motivated by emerging applications in nano-drug delivery in medicine and radiative ablation therapy, a steady-state mathematical model is established for magnetohydrodynamic boundary-layer transport of chemically reactive carbon nanotubes (CNTs)-doped electrically conducting blood along a porous stretching wall of a blood vessel. Multiple and single walls CNTs are considered using the model developed by Xue (2005). Heat generation, radiative flux, wall mass (concentration) slip, viscous heating and Joule magnetic dissipation are incorporated. Chemical reaction effects are addressed utilizing homogenous first-order model. The Darcy-Forchheimer drag force model is utilized for bulk matrix and inertial drag effects in the porous medium. Radiative heat-transport is studied considering Rosseland's diffusion model. The governing partial differential conservation equations for mass, momentum, energy and species are formulated in a two-dimensional Cartesian coordinate system with allied wall and free-stream boundary conditions. Via scaling transformations, a nonlinear boundary value problem is derived. Numerical computations are achieved through bvp4c scheme. The impact of selected parameters on dimensionless quantities (velocity, temperature, concentration, skin friction, local Nusselt and Sherwood numbers) are computed and elaborated through tables and graphs. A good correlation of the numerical solutions with earlier simpler models from the literature is included. The simulations show that with augmentation in Hartmann magnetic number and Forchheimer inertial drag number, significant damping in the nano-doped blood flow is produced for both SWCNTs and MWCNTs. Temperature is elevated with increment in dissipation effect i. e. Eckert number. Higher values of mass (solutal) slip parameter induce a depletion in the concentration. Nusselt number i. e. heat transfer rate to the blood vessel wall is improved with greater values of solid volume fraction for both CNTs. The present model is relevant to radiative ablation therapy combined with nano-medical treatments in blood vessels wherein constant mechanical loading via blood pressure and flow can elevate internal stresses (circumferential wall stress and endothelial shear stress) and induce morphological alterations in blood vessel wall (stretching) and endothelium in conjunction with biochemical reactions.

Genome-wide discovery for biomarkers using quantile regression at biobank scale

Genome-wide association studies (GWAS) for biomarkers important for clinical phenotypes can lead to clinically relevant discoveries. Conventional GWAS for quantitative traits are based on simplified regression models modeling the conditional mean of a phenotype as a linear function of genotype. We draw attention here to an alternative, lesser known approach, namely quantile regression that naturally extends linear regression to the analysis of the entire conditional distribution of a phenotype of interest. Quantile regression can be applied efficiently at biobank scale, while having some unique advantages such as (1) identifying variants with heterogeneous effects across quantiles of the phenotype distribution; (2) accommodating a wide range of phenotype distributions including non-normal distributions, with invariance of results to trait transformations; and (3) providing more detailed information about genotype-phenotype associations even for those associations identified by conventional GWAS. We show in simulations that quantile regression is powerful across both homogeneous and various heterogeneous models. Applications to 39 quantitative traits in the UK Biobank demonstrate that quantile regression can be a helpful complement to linear regression in GWAS and can identify variants with larger effects on high-risk subgroups of individuals but with lower or no contribution overall.

Stability of Saltwater‐Freshwater Mixing Zones in Beach Aquifers With Geologic Heterogeneity

AbstractSaltwater‐freshwater mixing zones in beach aquifers support biogeochemical reactions that moderate chemical loads in fresh groundwater discharging to marine ecosystems. Existing laboratory and numerical modeling studies have demonstrated that fluid density gradients in the mixing zone can lead to free convection and the formation of density instabilities, or salt fingers, under a range of hydrologic, morphologic, and hydrogeologic conditions. However, salt fingers have rarely been observed in real‐world beach aquifers despite a growing body of field studies investigating intertidal mixing zones. In this study, we used geostatistical methods to generate randomly distributed assemblages of fine and medium sand and incorporated those geologic realizations into variable‐density variably‐saturated flow and salt transport simulations to explore the influence of geologic structure on mixing zone stability in tidally‐influenced beaches. Ensemble‐averaged model results show that geologic heterogeneity inhibits salt finger formation and promotes a stable intertidal mixing zone due to enhanced dispersion. This effect is highest for high degrees of heterogeneity and for more laterally connected geologic architecture. Compared to hydraulically equivalent homogeneous models, sediments with moderate to high heterogeneity produce mixing zones that are on average 19%–29% smaller and 3–10 times more stable due to the absence of the downward convection and seaward movement of salt fingers. The models indicate that geologic heterogeneity may explain the lack of field observations of salt fingers in real‐world intertidal mixing zones. The findings have implications for predicting the onset of free convection in beaches and for understanding intertidal pore water biogeochemistry and chemical fluxes to the ocean.