Solute Transport Research Articles

Sequential model identification with reversible jump ensemble data assimilation method

In data assimilation (DA) schemes, the form representing the processes in the evolution models are pre-determined except some parameters to be estimated. In some applications, such as the contaminant solute transport model and the gas reservoir model, the modes in the equations within the evolution model cannot be predetermined from the outset and may change with the time. We propose a framework of sequential DA method named Reversible Jump Ensemble Filter (RJEnF) to identify the governing modes of the evolution model over time. The main idea is to introduce the Reversible Jump Markov Chain Monte Carlo (RJMCMC) method to the DA schemes to fit the situation where the modes of the evolution model are unknown and the dimension of the parameters is changing. Our framework allows us to identify the modes in the evolution model and their changes, as well as estimate the parameters and states of the dynamic system. Numerical experiments are conducted and the results show that our framework can effectively identify the underlying evolution models and increase the predictive accuracy of DA methods.

Angiotensin 1–7 restrains vascular injury of extracorporeal membrane oxygenation by inhibiting ferroptosis

BackgroundAngiotensin 1–7 (Ang1-7) is the classical end product of angiotensin II, which has the effects of dilating blood vessels, protecting endothelial cells, anti-hypertension, improving cardiac function, and inhibiting atherosclerosis. We hypothesize that Ang1-7 inhibits human umbilical vein endothelial cells (HUVEC) ferroptosis through NF-κB/P53 signal pathway, and reduces extracorporeal membrane oxygenation (ECMO) vascular injury. MethodsCultured HUVEC were seeded into 15 wells and randomly divided into five groups: the control group and four experimental groups (erastin, erastin + Ang1-7, erastin + Ang1-7 + Betulinic acid, erastin + Betulinic acid). After stimulation, cell viability, lactate dehydrogenase (LDH), malondialdehyde (MDA), and superoxide dismutase (SOD) activity were measured. The effects of Ang1-7 on HUVEC microstructure, antioxidant enzymes (ferritin heavy chain 1 (FTH1), cystine/glutamic acid reverse transport solute carrier family 7 members 11 (SLC7A11 or XCT), superoxide dismutase-2 (SOD-2) and glutathione peroxidase 4 (GPX4)), NF-κB, P-NF-κB, P53, and P-P53). ResultsErastin stimulation promoted HUVEC lipid peroxidation, decreased antioxidant enzyme expression, increased P-NF-κB, P53, and P-P53 expressions, and damaged HUVEC mitochondrial structure. Ang1-7 alleviated the effect of erastin on HUVEC, which was destroyed by Betulinic acid. ConclusionAngiotensin1-7 pretreatment inhibited vascular endothelial cells’ ferroptosis and alleviated ECMO vessel injury through NF-κB /P53 signal pathway.

Analytical Solutions for a Fully Coupled Hydraulic‐Mechanical‐Chemical Model With Nonlinear Adsorption

ABSTRACTAdsorption characteristics play a crucial role in solute transport processes, serving as a fundamental factor for evaluating the performance of clay liners. Nonlinear adsorption isotherms are commonly found with metal ions and organic compounds, which introduce challenges in obtaining analytical solutions for solute transport models. In this study, analytical solutions are proposed for a fully coupled hydraulic‐mechanical‐chemical (HMC) model that accounts for both the Freundlich and Langmuir isotherms. To mitigate the difficulties arising from the variable coefficients, the system of second‐order partial differential equations involving three variables is linearized. The method of separation of variables, theory of integration, and Fourier series are utilized to derive analytical solutions. The analytical method presented can potentially be extended to a broad spectrum of nonlinear adsorption isotherms. The results reveal a 56.5% reduction in solute breakthrough time under the Freundlich isotherm and a remarkable 2.6‐fold extension under the Langmuir isotherm when compared to the linear isotherm. The adsorption constants of the Freundlich and Langmuir isotherms exhibit a positive correlation with breakthrough time, while the exponent of the Freundlich isotherm and the maximal adsorption capacity in the Langmuir isotherm demonstrate a negative association with breakthrough time. This study enhances the precision of solute transport prediction and provides a more scientific assessment of clay liner performance.

Comparison Between Analytical and Numerical Solutions for Water Transport in the Membrane on a PEMFC Model

Comparison Between Analytical and Numerical Solutions for Water Transport in the Membrane on a PEMFC Model

A Hybrid RANS/LES Model for Predicting the Aerodynamics of Small City Vehicles

Electric city vehicles are vital for reducing pollution in urban areas due to their zero emissions and high energy efficiency, significantly improving air quality and reducing the carbon footprint. This study investigates the aerodynamic behavior of simplified city vehicle models using computational fluid dynamics (CFD) simulations based on Reynolds-Averaged Navier-Stokes (RANS) and Detached Eddy Simulation (DES) turbulence model. The models are tested at speeds of 10 m/s, 15 m/s, and 20 m/s, with a grid independence study to ensure reliable results. ANSYS Fluent is used for the simulations, comparing the results from RANS and hybrid RANS/LES or DDES in terms of aerodynamic forces and flow patterns around the vehicle. Results show that the drag coefficient (Cd) decreases with increasing speed for both RANS and DDES models. At 10 m/s, the drag coefficients are 0.541 for RANS and 0.524 for DDES, a 3.14% reduction. At 15 m/s, the drag coefficients are 0.539 for RANS and 0.518 for DDES, a 3.89% reduction. At 20 m/s, the drag coefficients are 0.538 for RANS and 0.514 for DDES, a 4.46% reduction. Flow visualizations show that DDES simulations capture more detailed and complex flow structures, particularly in the wake region, compared to the smoother RANS patterns. These findings are essential guidelines for optimizing vehicle design to enhance aerodynamic performance and contribute to the development of more efficient, environmentally friendly urban transportation solutions.

Approaches to substantiating the placement of industrial facilities within the sanitary protection zones of surface watercourses

Introduction. The article considers an approach to be used to delineate the source water protection area for the surface water bodies without putting manufacturing plants within the delineated areas out of action. The approach is based on the assessment of the disposals produced by plants on the water quality at the surface water intake point during the plant’s accident-free operation and both accidents within and beyond the design basis. Materials and methods. The article used the water protection area laws and regulations, the data observed of the disposal dispersion in the large rivers, and the original articles presented in databases and information systems: RSCI, CyberLeninka, Scopus, Web of Science. The solute transport analytical solutions for the dilution of the linear source in the flow serve as the methodological framework. Results. The article results have shown the local disposal into the river to form dispersion halo. Due to the specific dispersion processes, an area of a strip-like shape on the opposite shore can be formed where an anthropogenic influence is not present or negligible. This can be considered the background for the safe cooperative operation of the water intake and a manufacturing plant located within the water protection area. Limitations. The present article outlines the analytical approach for estimating the dilution of wastewater in river waters. The methodologies proposed are subject to several constraints, including the assumption of a constant river channel width and profile, steady discharge of contaminated wastewater, absence of water inflow losses or replenishment, lack of interaction with suspended particulate matter, uniform mixing across all segments of the river, and neglect of wind-induced effects on pollutant dispersion near the water surface. Failure to meet any of these assumptions necessitates recourse to more sophisticated numerical modelling techniques for accurate calculation. Conclusion. The use of the approach presented in the paper allows justifying the manufacturing plant’s operation within the source water protection area for the surface water bodies.

Why Tata Nano Failed? From Ascent to Ashes: Unraveling the Tata Nano Saga – A Chronicle of Triumph, Tragedy, and Missteps

The Tata Nano launched in 2008 was initially marketed as the world's cheapest car, designed to provide an affordable transportation solution for the masses in India. It was a revolutionary concept that aimed to bring mobility to a wider segment of the population. Ratan Tata, the former Chairman of Tata Sons, envisioned the Nano as a symbol of innovation and social impact. Under his leadership, Tata Motors endeavored to create a compact, economical car that could transform the way people in India commuted. The global ambition of the Nano was to showcase India's engineering capabilities and demonstrate how a low-cost, frugal design approach could result in a groundbreaking product. Ratan Tata's vision extended beyond the domestic market, aiming to position the Nano as a viable option for consumers worldwide. However, despite the initial hype and anticipation surrounding the Nano, various factors contributed to its failure in the Indian market. Issues such as quality concerns, safety perceptions, marketing challenges, and changing consumer preferences played a significant role in the Nano's inability to meet sales expectations and establish a sustainable presence in the automotive industry. Ratan Tata made a roapmap to sell Minimum of 3 lacs of Tata Nano car in the first Years, but the reality is Tata Nano couldn’t cross the selling of 3 lacs units even after 8 years, before its get retired. Keywords: Anticipation, Envisioned, Groundbreaking, Innovation, Revolutionary

Carbon footprint in choosing the best sustainable mode of intercity passenger transport

The carbon footprint, which measures greenhouse gas emissions, is a good environmental indicator for choosing the best sustainable mode of transportation. The available emission factors depend heavily on the calculation methodology and are hardly comparable. The minimum and maximum scenarios are one way of making the results comparable. The best sustainable passenger transport modes between Rijeka and Split were investigated and compared by calculating the minimum and maximum available emission factors. The study aims to select the best sustainable mode of transport on the chosen route and to support the decision-making process regarding the electrification of the Lika railroad, which partially connects the two cities. In the minimum scenario, ferry transport without vehicles was the best choice when the transportation time factor was not relevant, and electric rail transport when it was. In the maximum scenario, the electric train and the ferry with vehicles were equally good choices. Road transportation between cities was not competitive at all. The comparison of the carbon footprint based on minimum and maximum scenarios gives a clear insight into the ratio of greenhouse gas emissions from vehicles in passenger transport. It supports the electrification of the Lika railroad as the best sustainable transport solution on the route studied.

Ensemble surrogate modeling of advective-dispersive transport with intraparticle diffusion model for column-leaching test

Column-leaching tests are a common approach for assessing the leaching behavior and resulting environmental risks of contaminated soils and waste materials, which are frequently reused for various construction purposes. The observed breakthrough curves of the contaminants are influenced by the complex dynamics of solute transport and kinetic inter-phase mass transfer. Disentangling these interactions necessitates numerical models. However, inverse modeling and sensitivity analysis can be time-consuming, especially when sorption kinetics are explicitly described by intraparticle diffusion, which requires discretizing the domain both in the flow direction along the column axis and inside the grains. To circumvent the need for such computationally intensive models, we have developed two different ensemble surrogate models. These models employ two separate ensemble methods: random forest stacking and inverse-distance weighted interpolation. Each method is applied to base surrogate models that cover different parts of the parameter space. The base surrogate models use the method of Extremely randomized Trees (ExtraTrees). The defined parameter range is based on the German standard for column-leaching tests. To optimize the base surrogate models, we utilized adaptive-sampling methods based on three distinct infill criteria: maximizing the expected improvement, staying within a certain Mahalanobis distance to the best estimate (both for exploitation), and maximizing the standard deviation (for exploration). The ensemble surrogate model demonstrates excellent performance in emulating the behavior of the original numerical model, with a relative root mean squared error of 0.09. We applied our proposed ensemble surrogate model to estimate the complete posterior parameter distribution using Simulation-Based Inference, specifically Neural Posterior Estimation, to determine the full parameter distribution conditioned on copper-leaching data from two different soils. Samples drawn from the posterior distribution align perfectly with the observed data for both the surrogate and original models.

Urban Odyssey: “Pioneering multimodal routes for Tomorrow's smart cities”

Getting around in modern cities has become a daily puzzle for both residents and travelers. As cities increasingly evolve into complex hubs of innovation and development, the demand for efficient transportation solutions has never been higher. In the multifaceted field of urban transportation, cost-effective and efficient mobility remains a high priority. This paper looks at how cities are planning better ways for people to travel and move within the growing scope of multimodal transportation, a paradigm shift beyond traditional single-mode transit systems. Our approach to improving urban transport revolves around a few key principles: integration, innovation, and collaboration. Integration means bringing together different modes of transportation – like buses, trains, bikes, and even new technologies like ride-sharing services to make it easier for people to switch between them. This transformative approach not only aims to reduce congestion and reduce environmental footprints but also prioritizes user experience while ensuring a harmonious blend of convenience, sustainability, and accessibility. We use new technology and ideas to ensure that travel is easy, quick, and good for the environment. Looking at new trends and examples from around the world, this overview shows how cities are shaping a better future for everyone's daily commute. In this paper, we use Lingo software to solve a numerical example related to multi-modal transportation, demonstrating practical solutions for real-world implementation. Through innovation, we can find creative solutions to urban transportation challenges. Additionally, public transportation enhancements, such as the introduction of synchronized bus routes and electric vehicle charging stations, underline the commitment to sustainability and inclusivity. In the dynamic urban transportation landscape, cities will revolutionize our approach to providing cost-effective and efficient mobility solutions.

Transcriptional responses of durum wheat to chronic chromium exposure reveal candidate proteins involved in metal detoxification and compartmentalization

Chromium phytotoxicity results in relevant alterations to plant physiology, gene expression, and genomic DNA methylation at a transgenerational level. Herein, transcriptional responses of durum wheat (Triticum turgidum L.) to chronic chromium exposure were explored in roots and leaves by RNA-seq approach. Plants grown all the time in a hydroponic system supplemented with 2.5 and 10 µM hexavalent chromium were compared to unstressful control plants, assessing biomass and seed yield analyses after senescence. Then, transcriptomic analysis was performed with these plants kept under 10 µM chromium 50 days after the onset of exposure. The chromium concentrations used were considered the lowest dose sufficient to alter gene expression without impeding plant development, while the sampling time reflected the effects in the pre-harvest phase and long-lasting defense mechanisms. Root and leaf samples from plants kept under 10 µM chromium stress and from unstressful control plants were analyzed, generating 12 RNA-seq libraries. In total, 965 and 810 transcripts were found to be differentially expressed, respectively, in roots and leaves in response to 10 µM chromium stress. In roots, transcriptional changes were noted in the primary and secondary metabolism, redox homeostasis, protein modification, solute transport, nutrient uptake, and external stimuli responses. Meanwhile, the transcriptional changes in leaves were primarily found in the secondary metabolism, hormone-related pathways, chromatin modifications, cell division, protein modification and homeostasis, solute transport, and nutrient uptake. In particular, the metal uptake and translocation pathways were studied with greater emphasis to identify key proteins involved in chromium transport and compartmentalization. Furthermore, several genes involved in the biosynthesis of malate-derived organic acids, trace metal transport/detoxification/chelation, and vacuolar compartmentalization were linked to primary defense responses, and some of them were also associated with two putative gene clusters. Therefore, these genes and gene clusters are suggested as valuable biotechnological targets for future proof-of-concept studies aimed at genetic engineering of durum wheat to improve plant tolerance to chromium exposure.

Acidic proteomes are linked to microbial alkaline preference in African lakes

Microbial amino acid composition (AA) reflects adaptive strategies of cellular and molecular regulations such as a high proportion of acidic AAs, including glutamic and aspartic acids in alkaliphiles. It remains understudied how microbial AA content is linked to their pH adaptation especially in natural environments. Here we examined prokaryotic communities and their AA composition of genes with metagenomics for 39 water and sediments of East African lakes along a gradient of pH spanning from 7.2 to 10.1. We found that Shannon diversity declined with the increasing pH and that species abundance were either positively or negatively associated with pH, indicating their distinct habitat preference in lakes. Microbial communities showed higher acidic proteomes in alkaline than neutral lakes. Species acidic proteomes were also positively correlated with their pH preference, which was consistent across major bacterial lineages. These results suggest selective pressure associated with high pH likely shape microbial amino acid composition both at the species and community levels. Comparative genome analyses further revealed that alkaliphilic microbes contained more functional genes with higher acidic AAs when compared to those in neutral conditions. These traits included genes encoding diverse classes of cation transmembrane transporters, antiporters, and compatible solute transporters, which are involved in cytoplasmic pH homeostasis and osmotic stress defense under high pH conditions. Our results provide the field evidence for the strong relationship between prokaryotic AA composition and their habitat preference and highlight amino acid optimization as strategies for environmental adaptation.

The Effect Of Incentive, Technology Readiness, And Charging Infrastructure On Electric Vehicle Adoption Mediated By Perceived Behavior Control (Empirical Study: Intention To Adopt Electric Vehicles In Jakarta And Its Surroundings)

Today, the world faces crucial challenges such as the energy crisis, air pollution, and greenhouse gas emissions. The transportation sector is considered a major contributor to these problems, which is driving climate change in various cities. To achieve the goal of zero emissions, electric vehicles are positioned as the transportation solution of the future and need to be widely adopted around the world. This researche focuses on analyzing the factors that affect the intention to adopt electric vehicles, with variables such as Incentive, Charging Infrastructure, Technology Readiness, Perceived Behavior Control, and intention to adopt. The goal is to understand how these factors contribute to shaping people's decisions to use electric vehicles. This study uses a quantitative approach with a sample of at least 150 respondents. Data collection was carried out through an online questionnaire, and data analysis was carried out using the structural equation modeling (SEM) method with Smart-PLS (Partial Least Squares Structural Equations Modeling) software version 3.0 Testing of validity, reliability, and goodness of fit was carried out to ensure the quality of the model.

Deciphering the transfer mechanisms for CO2 absorption into binary blended solutions

A thorough understanding of the mechanisms involved in CO2 chemical absorption is crucial for the development of efficient CO2 capture technologies. Due to the insufficient insight into the interaction mechanism of different components in blended solutions, CO2 absorption reactions were often categorized as unidirectional transfer between absorption products. In this study, the CO2 absorption performance of binary blended solutions, including piperazine (PZ)/n-methyldiethanolamine (MDEA), ethanolamine (MEA)/MDEA, ammonia (NH3)/MDEA, PZ/potassium carbonate (K2CO3), and NH3/K2CO3, was investigated using a combination of experimental and computational methods. The CO2 absorption mechanisms of “competitive reaction”, “transfer reaction” and “parallel reaction” in the binary blended solution system were proposed. Kinetic experiments revealed that different blended solutions had varying impacts on the process of CO2 absorption. Among them, PZ/MDEA and MEA/MDEA solutions reduced the absorption rates by an average of 8% and 25%, respectively, compared to PZ or MEA component solutions. NH3/MDEA and PZ/K2CO3 solutions had absorption rates similar to those of single NH3/PZ component solutions. NH3/K2CO3 solutions, on the other hand, exhibited an average increase of 17% in absorption rates compared to NH3 solutions. Quantum mechanical (QM) methods were employed to evaluate of the absorption products and key processes in terms of kinetics and thermodynamics. Quantitative 13C NMR analyses were conducted to further investigate the interactions between components and the pathways of mass transport in blended solutions, which demonstrated proton transfer and CO2/-COO transfer between adsorption products. This study highlights an accurate description of the transfer mechanisms of various blended systems for the enhanced CO2 capture.

Electrical conductivity fluctuations as a tracer to determine time-dependent transport characteristics in hyporheic sediments

Assessing solute transport in riverbed sediments is important for quantifying the effective reactivity of hyporheic sediments and the magnitude of exchange flows between rivers and their river beds. A typical approach of estimating transport in riverbed sediments is by measuring natural tracers such as fluctuations of temperature or electrical conductivity (EC) and fitting models to them that assume time-independent travel time distributions, implying steady-state flow. Here, we use a transport parameterization that is based on the advection–dispersion equation (ADE) with coefficients that continuously vary in time. The ADE is solved numerically and its solution is fitted to measured EC time series using Bayesian parameter inference. A continuous function of model parameters is constructed by smoothly interpolating between point values with different temporal resolution, and Tikhonov regularization is used to avoid spurious parameter fluctuations. The approach is tested using EC time series synchronously measured in river water and hyporheic porewater of two urban rivers in Germany and one urban river in South Australia. For all datasets the goodness of fit was improved by introducing a time-dependent EC offset. Estimated porewater velocities were highly transient in three out of the four datasets with values increasing by up to a factor of six over the course of a day. Flux transients were likely related to both variations of hydraulic gradients along and spatial shifting of flow paths. Comparison to stationary, non-parametric deconvolution indicated that transient flow may induce multimodality in stationary travel time distributions. Given the high temporal dynamics of transport in the streambed sediments of the three investigated urban rivers, we envision that the presented model is also a valuable tool to improve the assessment of reactive transport in riverbed sediments.

Mechanistic definition and prediction of the mass exchange coefficient between rivers and hyporheic zones: The [formula omitted] of two [formula omitted]s

Solute transport in interconnected rivers and hyporheic zones is typically modeled through dual-domain models where first-order solute mass transfer between the two domains, ΩR and ΩHZ, is represented by a coefficient α. The transient storage model (TSM) is an example of such an approach. In practice, α is determined by fitting the tails of solute tracer breakthrough curves using a TSM. This approach has led to ambiguity regarding α’s physical meaning and transferability. Here, we investigated the physical basis for α and tested it with virtual experiments through the fully coupled multiphysics model hyporheicFoam for the ΩR−ΩHZ system. hyporheicFoam explicitly simulated coupled flow and solute transport over a kilometer with centimeter-scale resolution. Model results were analyzed to calculate α following its theoretical definition directly. Using the determined α within a TSM enables accurate reproduction of solute transport, underscoring α’s physical relevance and precision.

Dispersion of a non-uniform solute slug in pulsatile viscoelastic fluid flow

Solute transport in pulsatile viscoelastic fluid flow is relevant in nutrient transport and drug delivery in blood flow. Previous studies have extensively analyzed the effect of the shear-thinning nature of the blood but neglected the elastic property. The present study aims to fill this lacuna by analyzing the role of blood viscoelasticity on solute transport. To accomplish this, we study solute transport for a non-uniformly distributed solute slug in the pulsatile flow of an Oldroyd-B fluid through a tube in the presence of wall absorption. We employ Gill's procedure and Aris' method of moments to compute the transport coefficients Km(t) (m≤4). We also numerically solve the species transport equation using a finite difference scheme to directly determine local solute concentration C(t,z,r). Consistent results for a non-viscoelastic fluid predict a negative convection coefficient K1 and a positive effective diffusivity K2 for realistic values of the parameters. However, the present analysis predicts positive K1 and negative K2 for small tubes due to flow reversal caused by the fluid elasticity. For high Λ1, the amplitude of oscillation for K1 and K2 exhibits scaling K1∼Λ11.5 and K2∼Λ12 indicating an enhancement in the dispersion due to fluid elasticity, where Λ1 is the dimensionless relaxation time. The analysis of the skewness and (excess) kurtosis coefficients reveals inconsistency in previous studies on Newtonian fluids. Thus, we present consistent results not only for a viscoelastic fluid but also for a Newtonian fluid subjected to a pulsatile pressure gradient. In addition, the solute dispersion is significantly influenced by the non-uniformity of a solute slug. As the radius of a slug increases, solute dispersion reduces in short and moderate times; however, at large times, it is independent of the radius of a slug.

The modelling error in multi-dimensional time-dependent solute transport models

Starting from full-dimensional models of solute transport, we derive and analyze multi-dimensional models of time-dependent convection, diffusion, and exchange in and around pulsating vascular and perivascular networks. These models are widely applicable for modelling transport in vascularized tissue, brain perivascular spaces, vascular plants and similar environments. We show the existence and uniqueness of solutions to both the full- and the multi-dimensional equations under suitable assumptions on the domain velocity. Moreover, we quantify the associated modelling errors by establishing a-priori estimates in evolving Bochner spaces. In particular, we show that the modelling error decreases with the characteristic vessel diameter and thus vanishes for infinitely slender vessels. Numerical tests in idealized geometries corroborate and extend upon our theoretical findings.

Thermodynamics-based unsaturated hydro-mechanical-chemical coupling model for wellbore stability analysis in chemically active gas formations

A thermodynamics-based unsaturated hydro-mechanical-chemical (HMC) coupling model is developed to analyze the coupled response and stability of boreholes in chemically active gas formations. The newly coupled constitutive relations are formulated by incorporating the chemical effect into the solid-gas-liquid unsaturated framework to account for the interactions between rock deformation, gas-liquid two-phase flow, and chemical potential difference. Compared with previous models, the present model shows significant prediction differences in field variables and wellbore stability evolution. The maximum absolute difference of pore pressure, effective radial stress, effective tangential stress, and collapse pressure can reach 8.98 MPa, 7.64 MPa, 7.29 MPa, 7.65 MPa, respectively. It is more conservative to select a long-term wellbore collapse pressure rather than a short-term one to guide drilling operations. The two-phase flow behavior, jointly controlled by wellbore pressure, capillary pressure, and chemical osmosis effect, provides a more realistic observation of the mud intrusion process. Compared with low salinity muds, high salinity muds can effectively impede the mud intrusion into the formation, which is more conducive to preventing wellbore collapse, but at the same time increases the risk of wellbore fracture. Sensitivity analysis shows that solute diffusion and reflection coefficients affect early wellbore stability through pore pressure and solute transport, while the chemical swelling coefficient has a long-term effect through chemically induced deformation. The results can provide theoretical guidance for quantitative optimization of mud parameters and prevention of wellbore instability when drilling in chemically active gas formations.

Dispersion in a slit with crossflow filtration through a porous wall

Crossflow filtration is a separation technique where fluid flows tangentially across a membrane or porous media, reducing clogging by sweeping away retained particles and allowing continuous filtration. Dispersion of solute matter in crossflow filtration plays an essential role in the separation performance of many industrial processes. The current work aims to generalize the Taylor dispersion theory and study the solute transport in a slit–porous medium system with a crossflow. The solute is depleted by the porous medium at the slit top porous wall or the interface between the slit and the porous medium, where the continuity of the solute concentration and mass flux is applied. The solute is simultaneously transported axially by the main flow along the slit and vertically by the crossflow perpendicular to the slit. Using the Reynolds decomposition and cross-sectional averaging techniques, the generalized reduced-order model for the advection-dispersion solute transport in the slit–porous medium system with the presence of a crossflow is established, where the effective velocity of the main flow and the effective dispersion coefficient are obtained. The analysis of the results reveals that the nondimensional Taylor dispersion coefficient scales with the Peclet numbers for the crossflow and the main flow, respectively, as DT∼Pev−5/3 (when Pev≥20) and DT∼Peu2. The proposed theoretical model, along with the findings of this study, paves the way for the fundamental study of dispersion in more complex systems.