Three-dimensional Transport Model Research Articles

Self-consistent computation of spin torques and magneto-resistance in tunnel junctions and magnetic read-heads with metallic pinhole defects

A three-dimensional self-consistent spin transport model is developed, which includes both tunnelling transport, leading to tunnelling magneto-resistance, as well as metallic transport, leading to giant magneto-resistance. An explicit solution to the drift-diffusion model is also derived, which allows analysing the effect of both the reference and free layer thickness on the spin-transfer torque polarization and field-like coefficient. It is shown the model developed here can be used to compute the signal-to-noise ratio in realistic magnetic read-heads, where spin torque-induced fluctuations and instabilities limit the maximum operating voltage. The effect of metallic pinhole defects in the insulator layer is also analysed. Increasing the area covered by pinholes results in a rapid degradation of the magneto-resistance, following an inverse dependence. Moreover, the spin torque angular dependence becomes skewed, similar to that obtained in fully metallic spin valves, and the spin-transfer torque polarization decreases. The same results are obtained when considering tunnel junctions with a single pinhole defect, but decreasing cross-sectional area, showing that even a single pinhole defect can significantly degrade the performance of tunnel junctions and magnetic read-heads below the 40 nm node.

Dosimetry data from fuel channel clips for benchmarking a new computational fluid dynamics model in neutron transport

Accurate neutron transport models for BWRs are needed to characterize neutron damage to the top guide, top guide cylinder, vessel nozzles, and to other upper internals. In the past, neutron transport calculations above top-of-active-fuel (TAF) have had large uncertainties (well in excess of ± 20%) mainly due to the fact that the steam density distribution in that region is not well known. An advanced three-dimensional (3D) neutron transport model, which incorporates computational fluid dynamics (CFD) in the code suite, has been developed. Retrospective dosimetry measurements were made to benchmark the transport results. Six fuel channel clips were removed from the top of the fuel bundles, and small disk-shaped dosimetry samples were cut from the clips. The cuts were made through the Inconel spring and through the stainless steel clip body. The clips were selected from bundles that cover regions of low, intermediate, and high steam density. The average C/M ratio for the 10 dosimeters is 1.06. It has been shown that all of the calculated dosimeter activities fall within ± 20% of the measurement. This meets the criterion set by RG 1.190 [1] for acceptability of the calculations.

Improve the Accuracy in Numerical Modeling of Suspended Sediment Concentrations in the Hangzhou Bay by Assimilating Remote Sensing Data Utilizing Combined Techniques of Adjoint Data Assimilation and the Penalty Function Method

Suspended sediment dynamics play an important role in controlling nearshore and estuarine geomorphology and the associated ecological environments. Modeling the transport of suspended sediment is a complicated and challenging research topic. The goal of this study is to improve the accuracy of modeling the suspended sediment concentrations (SSCs) with newly developed techniques. Based on a three-dimensional suspended cohesive sediment transport model, the transport of suspended sediment and SSCs are simulated by assimilating SSCs retrieved from the Geostationary Ocean Color Imager (GOCI) with the adjoint data assimilation in the Hangzhou Bay, a typical strong tidal estuary along the coast of the East China Sea. To improve the effect of the data assimilation, the penalty function method, in which the reasonable constraints of the estimated model parameters are added to the cost function as penalty terms, will be introduced for the first time into the adjoint data assimilation in the SSCs modeling. In twin experiments, the prescribed spatially varying settling velocity is estimated by assimilating the synthetic SSC observations, and the results show that the penalty function method can further improve the effect of data assimilation and parameter estimation, regardless of synthetic SSC observations being contaminated by random artificial errors. In practical experiments, the spatially varying settling velocity is firstly estimated by assimilating the actual GOCI-retrieved SSCs. The results demonstrate that the simulated results can be improved by the adjoint data assimilation, and the penalty function method can additionally reduce the mean absolute error (MAE) between the independent check observations and the corresponding simulated SSCs from 1.44 × 10−1 kg/m3 to 1.30 × 10−1 kg/m3. To pursue greater simulation accuracy, the spatially varying settling velocity, resuspension rate, critical shear stress and initial conditions are simultaneously estimated by assimilating the actual GOCI-retrieved SSCs to simulate the SSCs in the Hangzhou Bay. When the adjoint data assimilation and the penalty function method are simultaneously used, the MAE between the independent check observations and the corresponding simulated SSCs is just 9.90 × 10−2 kg/m3, which is substantially less than that when only the settling velocity is estimated. The MAE is also considerably less than that when the four model parameters are estimated to be without using the penalty function method. This study indicates that the adjoint data assimilation can effectively improve the SSC simulation accuracy, and the penalty function method can limit the variation range of the estimated model parameters to further improve the effect of data assimilation and parameter estimation.

Simulation of Helium transport in fractured rocks: Implementation of a dual continuum model in DarcyTools

The main purpose of this work is to present a new analytical solution to study the transient matrix diffusion problem in fractured rocks. The solution is based on a Dual Continuum Model (DCM) and accounts for a zero-order source term in the matrix. The new solution can therefore be applied to describe transport of naturally occurring elements in rock minerals, such as those generated by radioactive decay, i.e., Helium. Also presented in this paper, is a conceptual model to estimate the DCM parameters from properties of an equivalent continuous porous medium (ECPM), thus allowing to incorporate transport calculations within a secondary continuum, i.e., matrix, in ECPM models.For practical applications, the new analytical solution is implemented in a Fortran module that can be readily coupled to a multi-component transport solver, i.e., DarcyTools. This allows DarcyTools to apply the DCM as a subgrid model and thus carry out simultaneous matrix diffusion and transport calculations in a bedrock, with or without including the source term. Since due to the apparent difference in transport time scales in fracture and matrix, simulation results can be sensitive to the grid size and time step taken by the solver, a comparison study is carried out to evaluate the accuracy of the numerical results in a two-dimensional fracture-matrix system.Implementation of the DCM is also verified by comparing the DarcyTools predicted results with exact solutions. For this purpose, a new semi-analytical solution is also derived in the Laplace domain to calculate a solute breakthrough curve in the fracture. Excellent agreement in results is found for the two solutes considered, namely, a non-reactive tracer and Helium generated as alpha particles by radioactive decay in the matrix. Furthermore, the DCM is incorporated in a large-scale three-dimensional transport model to describe concentration distribution of the given solutes in a fractured bedrock. The results suggest that the DCM implementation can effectively capture the impact of mass exchange between fractures and rock matrix in the bedrock.

Development of a CNN+LSTM Hybrid Neural Network for Daily PM2.5 Prediction

A CNN+LSTM (Convolutional Neural Network + Long Short-Term Memory) based deep hybrid neural network was established for the citywide daily PM2.5 prediction in South Korea. The structural hyperparameters of the CNN+LSTM model were determined through comprehensive sensitivity tests. The input features were obtained from the ground observations and GFS forecast. The performance of CNN+LSTM was evaluated by comparison with PM2.5 observations and with the 3-D CTM (three-dimensional chemistry transport model)-predicted PM2.5. The newly developed hybrid model estimated more accurate ambient levels of PM2.5 compared to the 3-D CTM. For example, the error and bias of the CNN+LSTM prediction were 1.51 and 6.46 times smaller than those by 3D-CTM simulation. In addition, based on IOA (Index of Agreement), the accuracy of CNN+LSTM prediction was 1.10–1.18 times higher than the 3-D CTM-based prediction. The importance of input features was indirectly investigated by sequential perturbing input variables. The most important meteorological and atmospheric environmental features were geopotential height and previous day PM2.5. The obstacles of the current CNN+LSTM-based PM2.5 prediction were also discussed. The promising result of this study indicates that DNN-based models can be utilized as an effective tool for air quality prediction.

What chemical reaction dominates the CO2 and O2 in-situ uranium leaching? Insights from a three-dimensional multicomponent reactive transport model at the field scale

The complex behavior of uranium in recovery is mostly driven by water-rock interactions following lixiviant injection into ore-bearing aquifers. Significant challenges exist in exploring the geochemical processes responsible for uranium release and mobilization. Herein this study provides an illustration of a ten-year field scale CO2 and O2in-situ leaching (ISL) process at a typical sandstone-hosted uranium deposit in northern China. We also conducte a three-dimensional (3-D) multicomponent reactive transport model to assess the effects of potential chemical reactions on uranium recovery, in particular, to focus on the role of sulfide mineral pyrite (FeS2). Numerical simulations are performed considering three potential ISL reaction pathways to determine the relative contributions to uranium release, and the results indicate that bicarbonate promotes the oxidative dissolution of uranium-bearing minerals and further accelerates the uranium leaching in a neutral geochemical system. Moreover, the presence of FeS2 exerts a strong competitive role in the uranium-bearing mineral dissolution by increasing oxygen consumption, favoring the formation of iron oxyhydroxide, and therefore causing an associated decrease in uranium recovery rates. The simulation model demonstrates that dissolution of carbonate neutralizes acidic water generated from pyrite oxidation and aqueous CO2 dissociation. In addition, the cation concentrations (i.e., Ca and Mg) are increasing in the pregnant solutions, showing that the recycling of lixiviants and kinetic dissolution of carbonate generates a larger number of dissolved Ca and Mg and inevitably triggers the secondary dolomite mineral precipitation. The findings improve our fundamental understanding of the geochemical processes in a long-term uranium ISL system and provide important environmental implications for the optimal design of uranium recovery, remediation, and risk exposure assessment.

Heat transfer enhancement of water-cooled triply periodic minimal surface heat exchangers

Whether triply periodic minimal surface (TPMS) heat exchangers are applicable to cooling or cold storage systems as a cooler for supercritical carbon dioxide (SCO2) is undocumented. Here the conjugated heat transfer of SCO2 in TPMS Schoen-G heat exchanger and printed circuit heat exchanger (PCHE) was predicted based on three-dimensional steady turbulent Reynolds-averaged Navier-Stokes equations, energy equation and shear stress transport model using computational fluid dynamics software ANSYS CFX when SCO2 inlet temperature and pressure vary in 65–30 ℃ and (8–9)MPa. SCO2 in two heat exchangers is cooled under counter-flow conditions by a stream of cold water with given inlet temperature and mass flow rate. It was shown that the mean heat transfer coefficient of SCO2 in TPMS Schoen-G heat exchanger is larger than PCHE. As the inlet pressure rises, the friction factor increases and Nusselt number decreases in the heat exchangers due to decreased Reynolds number and Prandtl number, respectively. The friction factor ratio, Nusselt number ratio and performance evaluation criterion vary in the range of 0.38–0.50, 1.07–1.49, and 1.45–2.04 with Reynolds number and inlet temperature when the PCHE serves as a reference heat exchanger. The streamlines in TPMS Schoen-G heat exchanger are quite smooth even though the areas with a higher velocity appear. The streamlines in PCHE exhibit a spiral flow pattern to result in extra hydraulic loss. The heat transfer enhancement of TPMS Schoen-G heat exchanger is much better TPMS Schwarz-D heat exchanger at a Reynolds number higher than 16,000. The enhancement is attributed to a larger heat transfer surface area and more topological tortuosity without flow separation than PCHE.

Evaluating the effectiveness of a geostatistical approach with groundwater flow modeling for three-dimensional estimation of a contaminant plume

When assessing the risk from an underground environment that is contaminated by radioactive nuclides and hazardous chemicals and planning for remediation, the contaminant plume distribution and the associated uncertainty from measured data should be estimated accurately. While the release history of the contaminant plume may be unknown, the extent of the plume caused by a known source and the associated uncertainty can be calculated inversely from the concentration data using a geostatistical method that accounts for the temporal correlation of its release history and groundwater flow modeling. However, the preceding geostatistical approaches have three drawbacks: (1) no applications of the three-dimensional plume estimation using concentration data from multiple depths in real situations, (2) no constraints for the estimation of the plume distribution, which can yield negative concentration and large uncertainties, and (3) few applications to actual cases with multiple contaminants. To address these problems, the non-negativity constraint using Gibbs sampling was incorporated into the geostatistical method with groundwater flow modeling for contaminant plume estimation. This method was then tested on groundwater contamination in the Gloucester landfill in Ontario, Canada, using three-dimensional contaminant transport model and concentration data from multiple depths. The method was applied to three water soluble organic contaminants: 1,4-dioxane, tetrahydrofuran, and diethyl ether. The effectiveness of the proposed method was verified by the general agreement of the calculated plume distributions of the three contaminants with concentration data from 66 points in 1982 (linear correlation coefficient of about 0.7). In particular, the reproduced peak of 1,4-dioxane corresponding to the large disposal in 1978 was more accurate than the result of preceding minimum relative entropy-based studies. The same peak also appeared in the tetrahydrofuran and diethyl ether distributions approximately within the range of the retardation factor derived from the fraction of organic carbon.

Race-ethnicity disparities in COVID-19 outcomes may be worsened by shorter- and long-term aerosol pollutants exposure

BACKGROUND AND AIM: The importance of ultrafine particles (UFP or PM₀.₁) exposure to respiratory disease has been identified. However, its effect (and that of PM₂.₅) on COVID-19 outcomes remain unknown. This study aims to identify and quantify shorter- and long-term aerosol impacts on COVID-19 in context of disparate outcomes observed for minority race-ethnicity groups in New York State (NYS). METHODS: COVID-19 outcomes included infections, hospitalizations, ICU admissions, and deaths reported by the CDC COVID-19 Case Surveillance Restricted Access Detailed Data, 2020–2022. UFP and PM₂.₅ data were simulated by a global three-dimensional model of chemical transport with state-of-the-science aerosol microphysical processes extensively validated with observations. For shorter-term (0–30 lag days) UFP and PM₂.₅ exposure, Distributed Lag Non-linear Model (DLNM) were used to examine the association at county-level, adjusting for meteorological factors. Long-term (average level of 2013–2020) associations with COVID-19 were assessed by Negative Binomial Mixed Models adjusting for county-level confounders. County-level confounders from the Census Bureau, Behavioral Survey, and Homeland Infrastructure Data were used. RESULTS: Compared to White, Hispanic/Black subgroups had greater excess risk of COVID-19 infection (+25%), hospitalization (+31%), ICU admission (+60%), and death (+5.5%). Excess risk per IQR increase for long-term UFP (PM₂.₅) exposure was significant for COVID-19 hospitalization: +40%; 95%-CI=20.5–63.6% (+22%;18.8–25.5%), ICU admission: +44%;39.1–49.2% (+24%;18.6–30.5%), and death: +40%;38.0–42.4% (+19%;8.2–30.7%). For short-term exposures, risks for all COVID-19 outcomes were elevated (RRs range from 1.0–4.6, all p < 0.05) when UFP > 2000 #·cm−3 and PM₂.₅ > 6.3 µg·m−3. CONCLUSIONS: Both shorter- and long-term exposure to aerosols increased the risk of COVID-19 infection and subsequent outcomes, with ultrafine particles (UFP) exerting larger effects than PM₂.₅, and with greater likelihood. The UFP and PM₂.₅-associated risks were disproportionately higher for race-ethnicity minorities (particularly Hispanic and Black) and for their economically vulnerable subgroups. KEYWORDS: COVID-19, ultrafine aerosol, particulate matter, environmental justice, socioeconomic status

Developing a Lagrangian sediment transport model for open channel flows

A three-dimensional stochastic Lagrangian particle tracking sediment transport model is developed to solve the discrete advection–dispersion equation using a combination of empirical dispersion equations. The performance of three widely-used longitudinal dispersion coefficient equations was examined to select one of them as the primary dispersion equation term in the developed model. Also, a conditional empirical equation was used to consider the effect of vertical dispersion term in top layers near the water surface. The performance of particle tracking model (PTM) to calculate the sediment concentration was evaluated for various sediment classes (very fine sand, fine sand, and medium sand) using available laboratory dataset. Multiple statistical measures were calculated using the Taylor diagram for each dispersion equation. Based on the result, the developed particle tracking model estimated the suspended sediment concentration in a rectangular open channel with a correlation coefficient (R) of 0.96, standard deviation (STD) of 0.262, and root mean square deviation (RMSD) of 0.06 for three different sediment classes proving the acceptable accuracy of the developed model for different range of sediment gradations. In addition, the accuracy of PTM was compared to recently developed models. Comparison between the particle tracking model and the analytical solution of the advection–dispersion equation showed that the developed model predicted the maximum concentration of suspended sediment 6% and 9.4% lower than the analytical solution result for 30 and 50 s simulation time in the straight channel, respectively. However, there was a good agreement between the longitudinal and transverse sediment concentration distribution from the model and the analytical solution approach. The result of the sensitivity analysis and validation process showed that the model could be used to simulate sediment transport in open channel flows.

LONG-RANGE ATMOSPHERIC TRANSPORT OF RADON IN EAST ASIA AND DEPOSITION OF ITS PROGENIES IN JAPAN.

A three-dimensional long-range atmospheric transport model for 222Rn and its progenies was applied to simulate 210Pb deposition in Japan and its adjacent waters. Monthly precipitation and 210Pb deposition simulated by the model for winter months were favorably compared with observational data although they were exceptionally underestimated in Aomori. The large monthly deposition along the Japan Sea coast lines during winter was successfully simulated by the model to be nearly 200Bqm-2, which was contrasted by about 10-fold smaller deposition in other regions. It was also pointed out that the heavy deposition areas formed a narrow band structure along the coastline with width of several tens of kilometers and 210Pb deposition amount positively correlated with the height of mountains located leeward of the heavy deposition areas.

Heterogeneity-Driven Hydrodynamics Conditions the Hydrochemistry of Spring Water in Volcanic Islands.

Perched aquifers represent significant unexploited groundwater reserves in volcanic islands and contain valuable freshwater resources. These water reserves provide critical resources to indigenous populations suffering water scarcity. Groundwater discharged from a perched aquifer into two adjacent (14 m) springs in the volcanic summits constituted by basaltic and pyroclastic deposits of Gran Canaria Island (Spain) was examined. Based on springs discharge data, a three-dimensional groundwater flow and solute transport model of the investigated perched aquifer was calibrated to reproduce its hydraulic regime, as well as to explain the hydrochemical and isotopic composition of its main discharge systems, the studied springs. Groundwater flow simulations effectively replicated flow paths of the two springs affected by the existing geological heterogeneities, with differential travel times of 246 and 130 years, respectively, and with a convergent flow toward them partially explaining the averaged differences in electrical conductivity, δ18 O, and tritium observed between the springs. It can be concluded that, although water quality in both springs is similar and homogenous, as they come from the same aquifer system, geological heterogeneities in the upper elevation volcanic areas is likely the cause for the differences in the residence times of the two springs, which suggests that the flow regimes for the two springs are independent. The chemistry of the two springs, however, is essentially the same, with the exception of tritium, which is used to ascertain residence time.

Real-world wintertime CO, N2O, and CO2 emissions of a central European village

Abstract. Although small rural settlements are only minor individual sources of greenhouse gases and air pollution, their high overall occurrence can significantly contribute to the total emissions of a region or country. Emissions from a rural lifestyle may be remarkably different than those of urban and industrialized regions, but nevertheless they have hardly been studied so far. Here, flux measurements at a tall-tower eddy covariance monitoring site and the footprint model FFP are used to determine the real-world wintertime CO, N2O, and CO2 emissions of a small village in western Hungary. The recorded emission densities, dominantly resulting from residential heating, are 3.5, 0.043, and 72 µg m−2 s−1 for CO, N2O, and CO2, respectively. While the measured CO and CO2 emissions are comparable to those calculated using the assumed energy consumption and applying the according emission factors, the nitrous oxide emissions exceed the expected value by a magnitude. This may indicate that the nitrous oxide emissions are significantly underestimated in the emission inventories, and modifications in the methodology of emission calculations are necessary. Using a three-dimensional forward transport model, we further show that, in contrast to the flux measurements, the concentration measurements at the regional background monitoring site are only insignificantly influenced by the emissions of the nearby village.

Mathematical modeling of snacks drying process from minced fish in a fluidized bed

A mathematical model of snacks drying process from minced fish in a fluidized bed with distributed parameters of the heat exchange process between the surface of an anisotropic body and the environment is proposed. The solution of the problem of non-stationary heat transfer by heat conduction using the Galerkin method is considered. The trial and verification functions of the method used, implemented in the PTC MathCAD engineering calculation environment, are linearly independent, represent the first elements of a complete system of polynomial functions and satisfy the boundary and initial conditions. Theoretical and experimental studies have been carried out, which allow considering the process of drying snacks from minced fish in a fluidized bed and scientifically substantiate options for its improvement. According to the results of experimental studies, the adequacy of the obtained mathematical model is shown. It is proved that with a uniform initial temperature distribution during preheating, the temperature inhomogeneity increases up to the moment of a phase transition on the surface of dried object. The importance of taking into account the preheating phase of wet material is established, since at this stage a temperature profile is formed, which is characterized by significant heterogeneity. This is especially important, since temperature heterogeneity directly affects the quality of the food product. The possibility of taking into account anisotropy in heat transfer processes using a three-dimensional mathematical model of transport with distributed parameters is confirmed. The developed technique allows significantly increasing the accuracy of an anisotropic boundary value problem solving by replacing the operation of integrating the stiffness matrix elements with a system of differential equations by algebraic formulas.

Numerical case studies on long-term effectiveness of metallic iron based permeable reactive barriers: Importance of porosity heterogeneity of the barrier

This paper presents a three-dimensional (3-D) numerical groundwater flow and transport model of a metallic iron based permeable reactive barrier (Fe0-PRB) to assess how porosity heterogeneity of the barrier medium may affect groundwater flow over time and influence the long-term effectiveness of a Fe0-PRB. A 3-D high resolution aquifer outcrop analogue was utilized to implement aquifer heterogeneity. To evaluate the treatment performance of the PRB, the contaminant plume migration and groundwater residence time were investigated. The findings demonstrate that heterogeneity of porosity reduction of the barrier medium is an important factor in estimating the long-term performance of a continuous-wall Fe0-PRB. Ignoring the porosity heterogeneity of the barrier medium leads to an underestimation of the by-passing flow by 30%-41% in ten-years simulation, and of contaminant plume spread over time. Groundwater residence time simulations shows no evident residence time reduction during the operation of the Fe0-PRB. Installation of a pea gravel equalization zone can effectively reduce the heterogeneity of the barrier medium, and minimize the by-passing flow.

Numerical simulation of temperature variation in water layer induced by thermal jet in weak stratified environment

In order to explore the rising and diffusing path of an underwater thermal jet and the temperature variation of each water layer in the typical ocean thermohaline stratified environment, a three-dimensional mass-heat transport model of the thermal jet in a weak stratified environment was built by using the Detached-Eddy Simulation method and Volume of Fluid model to simulate the whole life evolution process of the thermal jet in different depths, temperature difference, and flow rate. A series of characteristic parameters were constructed to quantitatively evaluate the temperature change of the water layer caused by the thermal jet. The results show that the disturbance of the thermal jet on the environmental water body will lead to a change in the distribution of the isothermal layer. Under the combined influence of thermal conduction, thermal convection, and entrainment, thermal signals, cold–thermal mixing signals, or cold signals may appear in different water layers, and the boundary distribution and range of the water layer are decided by the jet parameters and the relative position between the jet and water surface.

Determination of the Activity Inventory in the Structural Components of the Dalat Nuclear Research Reactor for Its Decommissioning Planning

This report presents the methods and calculated results of the activity inventory in the structural components of the Dalat Nuclear Research Reactor (DNRR). These components include the shielding concrete, the reactor tank, and its inside irradiated facilities; the thermal and thermalizing columns; and the horizontal channels. The MCNP5 code with a three-dimensional neutron transport model was used to calculate the neutron flux distribution, neutron energy spectrum at different locations, and activation cross sections of long-lived radioactive nuclides in activated major materials, including heavy concrete, reflection graphite, and aluminum of the reactor. The calculated results of the energy spectrum and activation cross sections of MCNP5 were used in the ORIGEN2.1 point depletion code to calculate the neutron-induced activity of activated materials at different time points by modeling the irradiation history and radioactive decay. Radioactivity of long-lived key activation products such as 41Ca, 60Co, 55Fe, 63Ni, and 152Eu was modeled, and volumes of radioactive waste mainly of ordinary concrete, graphite, and aluminum in the structural components of the reactor were estimated. Experimental results of neutron flux and specific activities of some typical nuclides such as 60Co, 152Eu, 55Fe, and 63Ni in activated aluminum samples showed good agreement with the calculated results. As part of the national regulation requirements, the obtained data have been used to develop the decommissioning plan for the operational DNRR, with an estimation of about 10 years before its permanent shutdown.

Numerical experiments with real data for estimating greenhouse gas fluxes in a region

This work is devoted to the problem of obtaining an estimate of methane emissions using satellite data and the results of mathematical modeling. To implement the algorithm, a variant of the local Kalman ensemble filter (LETKF) is used, which represents an optimal estimate of the desired parameter based on observational data and a forecast based on a metematic model in a given time interval. This algorithm has properties that allow it to be used locally, i.e., to assimilate data by subdomains. The paper presents the implementation of the algorithm for real observational data and the results of mathematical modeling (calculation of the forecast of the state of the system). The results of the three-dimensional model of transport and diffusion (MOZART-4) are taken as the results of mathematical modeling, and satellite observations (AIRS data) are used as observational data. As a result of the algorithm, an average estimate of methane fluxes in the subdomain was obtained at specified time intervals.

Open-source modelling of aerosol dynamics and computational fluid dynamics: Bipolar and unipolar diffusion charging and photoelectric charging

Electric charging is one of the essential aerosol dynamic mechanisms and is harnessed for detection, capture and control of ultrafine aerosol particles in a range of devices. For simplicity, charging and transport mechanisms are commonly modelled with zero spatial dimensions (0-D) and averaged properties such as mean charge or mean particle diameter. These models often neglect localised effects of the flow distribution, diffusion, discrete charge states, and particle polydispersity, often proving inadequate to explain experimental data. This work aims to provide an open-source three-dimensional (3-D) aerosol charging and transport model including bipolar and unipolar diffusion charging, and photoelectric charging algorithms for use in detailed design and analyses of aerosol systems. The computational model consists of more than 200 particle transport equations for discrete charge states and polydisperse sizes coupled with ion conservation equations in the framework of OpenFOAM, an open-source computational fluid dynamics platform. Three test cases are introduced to verify implementation of three charging models by comparison with published literature: bipolar and unipolar diffusion charging, and photoelectric charging. Tutorial cases, which model three distinct aerosol sensors, are described and demonstrate the capabilities of the 3-D aerosol charging and transport models within the predetermined flow field. The aerosolChargingFoam code is available at https://openaerosol.sourceforge.io for widespread use and can be further modified under the GNU general public licence. Program summaryProgram title: aerosolChargingFoamCPC Library link to program files:https://doi.org/10.17632/4pf4n2vg9f.1Developer's repository link:https://openaerosol.sourceforge.io/Licensing provisions: GNU General Public License 3Programming language: C++Nature of problem: aerosolChargingFoam solves generalised aerosol electrical charging and transport equations coupled with computational fluid dynamics using the open-source computational platform, OpenFOAM [1]. The electric charging algorithm including unipolar diffusion charging, bipolar diffusion charging, and photoelectric charging is verified with zero-dimensional test cases [2-4] and generalized to three-dimensional monodisperse or polydisperse particle distributions for more than 50 particle charge states. aerosolChargingFoam can be straightforwardly coupled with other existing solvers, which enables computations of complex multi-physics aerosol charging processes in practical conditions.Solution method: aerosolChargingFoam employs an explicit time-stepping for the time-dependent source terms for generalised aerosol charging. The solution methods and schemes provided by OpenFOAM 9 are used for solving the spatial and time derivatives in the transport equations.

Identification of Groundwater Contamination using MODFLOW: A Case study of Chhatral Area, Gandhinagar

Abstract: In India, groundwater is a primary source of freshwater and used mainly for agriculture and irrigation purposes. Approximately 80% of the population is dependent on groundwater for household and agricultural purposes in India. The pace of urbanization in Gandhinagar has been accelerated since the capital of Gujarat state was formed; hence a study is carried out to identify the status of groundwater quality in the Chhatral area of Gandhinagar city. In this study, MODFLOW and MT3DMS software are used to identify contaminated groundwater status in particular study areas. MODFLOW software helped in simulating ground water quality under various hydro-geological conditions. After the initial simulation, the area was assigned to MT3DMS, a three-dimensional multi-species solute transport model where arsenic and fluoride concentrated chemicals are figured out above the permissible limit authorized by WHO and BIS for drinking purposes. The results of this study demonstrated that there is need to take necessary steps to control ground water quality in the study area. Groundwater quality modelling will help the stakeholders, government organizations & users to get the exact groundwater quality status for future use. Keywords: Groundwater contamination, Arsenic, Fluoride, MODFLOW, and MT3DMS