Particle Breakthrough Research Articles

Microscale insights into deep bed membrane filtration: Influence of internal surface roughness

Deep bed filtration is widely applied in bioprocessing, virus filtration, and water purification to remove small impurities, such as particles or virus fragments. However, more needs to be understood about the parameters that influence particle capture and deposition. Detailed simulations and microfluidic filtration experiments with straight pores have been widely investigated, yet realistic membrane porosity features such as pore gradients and roughness have not been addressed in detail. The internal membrane morphology is assumed to have a strong effect on filtration performance. Therefore, this study introduces a new microfluidic membrane mimicking device (MMD) and methodology that analyzes spatio-temporal particle collections in a deep bed filtration MMD with gradually decreasing pore size toward the retentate side. The design allows us to systematically tailor an internal filter surface roughness to investigate its influence on differently sized soft particles and the consequences for filtration performance, in particular, particle capture. Optical investigation and quantitative evaluation show enhanced particle–pillar interactions for increased roughness. This results in a reduced penetration depth and reduced particle breakthrough. The modes of capture or filtration phenomena, such as pore blocking, bridging, or dendrite formation, differ significantly between smooth and rough membrane filter structures. In the case of rough inner filter surfaces, those phenomena lead to a less distinct decrease in volumetric flow, allowing a longer filtration process. The microfluidic study offers a detailed investigation of how microscale phenomena influence the filtration process. The results provide a fundamental understanding of microscale filtration effects based on roughness and, hence, motivate a tailoring of the internal membrane filter surface according to the filtration problem at hand.

Bayesian learning of gas transport in three-dimensional fracture networks

Modeling gas flow through fractures of subsurface rock is a particularly challenging problem because of the heterogeneous nature of the material. High-fidelity simulations using discrete fracture network (DFN) models are one methodology for predicting gas particle breakthrough times at the surface but are computationally demanding. We propose a Bayesian machine learning method that serves as an efficient surrogate model, or emulator, for these three-dimensional DFN simulations. Our model trains on a small quantity of simulation data with given statistical properties and, using a graph/path-based decomposition of the fracture network, rapidly predicts quantiles of the breakthrough time distribution on DFNs with those statistical properties. The approach, based on Gaussian Process Regression (GPR), outputs predictions that are within 20%–30% of high-fidelity DFN simulation results. Unlike previously proposed methods, it also provides uncertainty quantification, outputting confidence intervals that are essential given the uncertainty inherent in subsurface modeling. Our trained model runs within a fraction of a second, considerably faster than reduced-order models yielding comparable accuracy (Hyman et al., 2017; Karra et al., 2018) and multiple orders of magnitude faster than high-fidelity simulations.

The impact of diffusiophoresis on hydrodynamic dispersion and filtration in porous media

It is known that the dispersion of colloidal particles in porous media is determined by medium structure, pore-scale flow variability and diffusion. However, much less is known about how diffusiophoresis, that is, the motion of colloidal particles along salt gradients, impacts large-scale particle dispersion in porous media. To shed light on this question, we perform detailed pore-scale simulations of fluid flow, solute transport and diffusiophoretic particle transport in a two-dimensional hyper-uniform porous medium. Particles and solute are initially uniformly distributed throughout the medium. The medium is flushed at constant flow rate, and particle breakthrough curves are recorded at the outlet to assess the macroscopic effects of diffusiophoresis. Particle breakthrough curves show non-Fickian behaviour manifested by strong tailing that is controlled by the diffusiophoretic mobility. Although diffusiophoresis is a short-time, microscopic phenomenon owing to the fast attenuation of salt gradients, it governs macroscopic colloid dispersion through the partitioning of particles into transmitting and dead-end pores. We quantify these behaviours by an upscaled analytical model that describes both the retention and release of colloids in dead-end pores and the observed long-time tailings. Our results suggest that diffusiophoresis is an efficient tool to control particle dispersion and filtration through porous media.

Combining descriptive and predictive modeling to systematically design depth filtration-based harvest processes for biologics.

Advances in upstream production of biologics-particularly intensified fed-batch processes beyond 10% cell solids-have severely strained harvest operations, especially depth filtration. Bioreactors containing high amounts of cell debris (more than 40% particles <10 µm in diameter) are increasingly common and drive the need for more robust depth filtration processes, while accelerated timelines emphasize the need for predictive tools to accelerate development. Both needs are constrained by the current limited mechanistic understanding of the harvest filter-feedstream system. Historically, process development relied on screening scale-down depth filter devices and conditions to define throughput before fouling, indicated by increasing differential pressure and/or particle breakthrough (measured via turbidity). This approach is straightforward, but resource-intensive, and its results are inherently limited by the variability of the feedstream. Semi-empirical models have been developed from first principles to describe various mechanisms of filter fouling, that is, pore constriction, pore blocking, and/or surface deposit. Fitting these models to experimental data can assist in identifying the dominant fouling mechanism. Still, this approach sees limited application to guide process development, as it is descriptive, not predictive. To address this gap, we developed a hybrid modeling approach. Leveraging historical bench scale filtration process data, we built a partial least squares regression model to predict particle breakthrough from filter and feedstream attributes, and leveraged the model to demonstrate prediction of filter performance a priori. The fouling models are used to interpret and provide physical meaning to these computational models. This hybrid approach-combining the mechanistic insights of fouling models and the predictive capability of computational models-was used to establish a robust platform strategy for depth filtration of Chinese hamster ovary cell cultures. As new data continues to teach the computational models, in silico tools will become an essential part of harvest process development by enabling prospective experimental design, reducing total experimental load, and accelerating development under strict timelines.

Повышение эффективности вихревого пылеуловителя с коаксиальным вводом вторичного потока в системах обеспыливания заводов по производству железобетонных изделий

Currently, the problem of the negative impact of the dust factor on the occupational safety of employees of enterprises producing reinforced concrete products is at the top of the agenda. The finely dispersed structure is specific to dust contaminations emitted during reinforced concrete production workflows, which simultaneously causes increased harm to health and hampers compliance with the minimum required working area dust contamination parameters. Inertial-type dust collectors traditionally used in the industry do not meet the increasing requirements for the quality of operation of dedusting systems in working areas. In order to resolve the above-mentioned issue, it is recommended to use vortex dust collectors with better performance characteristics compared to regular inertial duct collectors. To adapt vortex dust collectors for reinforced concrete production conditions, a design of secondary flow axial input combined with an ejector unit to create a vacuum in the bunker area of the device has been proposed. This technical solution enables the reduction of the value of the breakthrough coefficient of РМ10 fraction fine particles during contaminated air dedusting. To confirm the efficiency of the application of the dust collector of the proposed design, experimental laboratory studies have been conducted. Dependencies characterizing the values of dust particle breakthrough as well as the breakthrough of fine particles of РМ10 fraction when removing dust particles of reinforced concrete production from air-dust mixture have been obtained. The calculated data have been compared with the data characterizing the breakthrough in a vortex dust collector of the VZP series, currently most often used. Based on the analysis of the results of comparative tests, conclusions regarding the high efficiency of the dust collector of the proposed design and the rationality of establishment of collective protection systems for employees using these collectors as the main dust collection equipment in conditions of reinforced concrete products and structures production have been made.

Technical Solutions to Reduce the Amount of Dust Particle Breakthrough when Cleaning Emissions from the Production of Reinforced Concrete Products Using Dust Collectors with Counter Swirling Flows

Introduction. The production of reinforced concrete products, being the basis of modern industrial construction, is a very significant source of dust emissions. Traditional cleaning methods are often unable to ensure the compliance with air quality requirements, and replacing them with more modern ones requires significant capital and operational costs. One of the most promising ways to solve the problem is the use of a new class of inertial dust collectors with counter swirling flows, combining constructive simplicity and low operating costs with sufficiently high work efficiency. The aim of the work was to analyze the factors influencing the magnitude of the breakthrough coefficient of fine dust particles, as well as the development of constructive solutions aimed at reducing it. Materials and Methods. An analytical review of technical solutions aimed at reducing the breakthrough magnitude was carried out, on the basis of which the designs of the lower input of dust collectors with counter swirling flows were developed. Methods of computational experiment and field measurements were used to confirm the effectiveness of the developed structures. Results. By means of numerical experiments, the information about the aerodynamic flow pattern in the separation chamber of the CSF dust collector was obtained, and the breakthrough magnitude of dust particles was estimated. The solutions were developed for the design of the lower coaxial input of the swirling flow of dust collectors on the counter swirling flows, taking into account the features of dust pollution generated during the operation of technological equipment of reinforced concrete production. Discussion and Conclusion. The presence of a displacement of the axis of the secondary swirling flow from the axis of symmetry of the separation chamber was established. The consequence of this was the non-coaxiality of the primary and secondary flows, which led to a decrease in the intensity of the twist, the formation of parasitic vortices, and, as a consequence, an increase in the value of the breakthrough coefficient. This effect was especially pronounced with a large proportion of fine dust particles, characteristic of dust pollution formed during the production of reinforced concrete products. The proposed design of the coaxial input of the secondary swirling flow reduced the magnitude of this eccentricity, which made it possible to achieve a significant reduction in the breakthrough magnitude of fine particles characteristic of dust emissions of reinforced concrete industries. The results obtained can be effectively used both in the production of reinforced concrete products and in other branches of construction production, which is characterized by intensive formation of fine dust emissions.

Multiphase flow model coupled with fine particle migration for applications in offshore gas hydrate extraction

Sand production, which causes clogging of pore space and reduces the gas hydrate production efficiency, is a crucial problem that prevents the successful extraction of offshore gas hydrate. The key physical processes behind sand production, including the detachment, migration and settling down of fine particles in pore space, were not well characterized and coupled in current mathematical models. In this work, a mathematical model is developed to characterize the fine particles migration and clogging for multiphase flow in the gas hydrate reservoir. Each fine particle considers the Stokes drag force, frictional force and buoyancy force in saturated pore space. The capillary force is further considered as an extra hydrodynamic force for fine particles migration in unsaturated pore space. The impacts of gas hydrate phase transition on pore space saturation and capillary pressure are quantified, and then the stress equilibrium analysis on each fine particle is re-evaluated. Fine particles can be either in static, rolling or suffusion status in the simulation. Based on this mathematical model, the impacts of fluid flow rate, fine particle concentration and bulk skeleton grain size on fine particle breakthrough curve and permeability reduction are investigated in this work. To capture fine particles migration and clogging processes in gas hydrate reservoir, the critical pore clogging ratio of 6 is quantified in this work. At last, the proposed model is applied to an in-situ gas hydrate test at Nankai Trough, and both calibration and the long-term production prediction are made.

Impact of horizontal spatial clustering in two-dimensional fracture networks on solute transport

This study explores the prevalence of fracture clustering in natural networks and its influence on fluid flow and advective transport. Fracture networks from a compilation of previously published maps that encompass igneous, metamorphic and sedimentary rock types, various geological and tectonic settings, and a broad distribution of length scales are analyzed using a two-point correlation technique to characterize the spatial scaling between fracture barycenters. The correlation dimension (Dc) ranges from 1.47 to 1.89 with a median of 1.8. These results suggest that fracture networks often exhibit spatial clustering and are rarely Poissonian as commonly assumed. Synthetic Discrete Fracture Networks (DFNs) with constant and variable transmissivity applied to all fractures are generated for three clustering (Dc = 1.6, Dc = 1.8, and Poissonian) and power law length exponent (α = 1.4, α = 1.8, and α = 2.2) scenarios. Median particle breakthrough times are shown to increase by 10–70% as spatial clustering transitions from Poissonian to highly clustered (Dc = 1.6). Median particle breakthrough times also increase, by a factor of 1.2–3.4 (20–240%), when the power law length exponent increases from α = 1.4 to α = 2.2. As clustering increases (i.e., Dc reduces), breakthrough curves become highly variable and exhibit features indicative of enhanced solute retention. The increase in median breakthrough times with clustering persists with different network size and transmissivity distribution. These results indicate that spatial clustering and length exponent both significantly influence transport. The use of power-law length distributions in generating fracture networks is relatively common, whereas the spatial organization of fractures is rarely included in transport studies of fractured rock. Structural heterogeneity introduced by spatially clustered organization of fractures leads to substantial complexity in flow paths which is not captured by Poissonian DFNs.

The breakthrough of large particles in small devices of counter-swirling flows with top strikers

The work considers the breakthrough effect of large particles in a small diameter device on counter-swirling flows. The dependences of particle breakthrough on different diameter devices were built. An experiment was carried out on a device of 100, 200, 300 and 400 mm with top paddle strikers installed at the axial outlet. A comparative analysis is made with the calculated and experimental data of the researchers in this area. The results of devices with small diameter are obtained and presented in the visual graphs and conclusions.

The effectiveness of the dust particles of the flask in the apparatus of counter-swirling flows

In this research was studied gathering efficiency and breakthrough of flask dust particles in industrial plants. The experiments were carried out on devices with counter swirling flows with various modifications and diameters of 150, 400, 600, and 800 mm. Analyzed and graphically presented the dependences of particle breakthrough on tghe devices size. The breakthrough effect in small inertial VZP devices was investigated, also the construction of VZP device was designed and experimentaly tested under operating conditions in terms of productivity and energy losses close to standard devices, but excluding the breakthrough effect of larger particles. Recommendations are given for the device usage on counter swirling flows with the best characteristics for capturing flask dust particles.

Numerical simulation of polydisperse dense particles transport in a random-orientated fracture with spatially variable apertures

Numerical experiments are conducted to quantify the transport behaviour of polydisperse dense particles through a randomly orientated fracture with spatially variable apertures. To be specific, fracture apertures are created by implementing the geostatistical algorithm of random field generation, while, based on the classical Local Cubic Law (LCL), pressure distribution and velocity field across the fracture are determined under given boundary conditions. Subsequently, the existing constant-spatial-step particle-tracking equations are modified by incorporating both particle settling gravity and fracture orientation to simulate particle transport behaviour. Using literature data, the simulation model in this study has been well validated. By simulating a set of well-designed scenarios, effects of fracture orientations, particle size-distribution, and aperture field heterogeneity and anisotropy on particle transport are systematically examined, while sensitivity analysis of the transport behaviour has been evaluated and compared. Compared to particle number breakthrough, mass breakthrough efficiency of particle plume is found to be usually much lower only except for the vertical orientation of a fracture. An increased inclination either parallel or perpendicular to the overall flow direction leads to an earlier particle breakthrough with a shorter tail on the breakthrough curves. A more heterogeneous fracture results in an enhanced longitudinal spreading of particle plume with distinct non-uniform fore- and back-end distribution. For a larger deviated particle size-distribution, particle plume during transport is evolved with more particles at its two-ends. In addition, it is observed from a vertical fracture that aperture anisotropy orientated parallel to the flow direction significantly enhances particle transport and spreading than that perpendicular to the flow direction. Fracture inclinations parallel and perpendicular to the flow direction yield a similar sensitivity on particle transport, while, compared to the heterogeneity of particle size-distribution, the aperture field heterogeneity affects particle transport more significantly. Comparing the aperture field consisting of a larger transverse correlation length with that of a larger longitudinal correlation length, the former is found with a more sensitive dependence of particle transport behaviour on aperture field anisotropy.

Influence of the presence of open three-dimensional fiber structures on solid liquid cake filtration of limestone

Solid particles in a suspension can be separated effectively through cake filtration where the filter medium is decisive particularly during the initial stage when particle breakthrough can be high. To improve the filtrate quality and throughput, filtration aid additives are used, which are known to alter filter cake structure and thus reduce flow resistance but, in forming clusters, also stabilize fine particles that would otherwise pass through the filter (cake) easily. However, filter aids are costly, increase the complexity of the system and may have adverse effects for subsequent mechanical drying and washing. Instead of supplying additives, four alternative filter media were tested exhibiting an open, three-dimensional structure that reached deeply into the depth of the forming filter cake. An aqueous limestone suspension was investigated in a conventional laboratory test unit. Composite filter medium set-up delivered up to 15% faster filtration. The results indicate that the fiber structures give better performance that reach far into the cake and are oriented not only axially but also radially. In contrary to the initial hypothesis that an axial fiber structure would produce additional drainage channels along the surface of these fibers and thus support but deliquoring, the actual deliquoring performance with air blowing appeared to be slightly less efficient. Although not investigated yet, cake discharge with a 3-D filter layer present poses an additional challenge, rendering the concept of composite filters unpractical.

Characterizing the Influence of Fracture Density on Network Scale Transport

AbstractThe topology of natural fracture networks is inherently linked to the structure of the fluid velocity field and transport therein. Here we study the impact of network density on flow and transport behaviors. We stochastically generate fracture networks of varying density and simulate flow and transport with a discrete fracture network model, which fully resolves network topology at the fracture scale. We study conservative solute trajectories with Lagrangian particle tracking and find that as fracture density decreases, solute channelization to large local fractures increases, thereby reducing plume spreading. Furthermore, in sparse networks mean particle travel distance increases and local network features, such as velocity zones where flow is counter to the primary pressure gradient, become increasingly important for transport. As the network density increases, network statistics homogenize and such local features have a reduced impact. We quantify local topological influence on transport behavior with an effective tortuosity parameter, which measures the ratio of total advective distance to linear distance at the fracture scale; large tortuosity values are correlated to slow‐velocity regions. These large tortuosity, slow‐velocity regions delay downstream transport and enhance tailing on particle breakthrough curves. Finally, we predict transport with an upscaled, Bernoulli spatial Markov random walk model and parameterize local topological influences with a novel tortuosity parameter. Bernoulli model predictions improve when sampling from a tortuosity distribution, as opposed to a fixed value as has previously been done, suggesting that local network topological features must be carefully considered in upscaled modeling efforts of fracture network systems.

The fate of silver nanoparticles in riverbank filtration systems — The role of biological components and flow velocity

Riverbank filtration is a natural process that may ensure the cleaning of surface water for producing drinking water. For silver nanoparticles (AgNP), physico-chemical interaction with sediment surfaces is one major retention mechanism. However, the effect of flow velocity and the importance of biological retention, such as AgNP attachment to biomass, are not well understood, yet.We investigated AgNP (c = 0.6 mg L−1) transport at different spatial and temporal scales in pristine and previously pond water-aged sediment columns. Transport of AgNP under near-natural conditions was studied in a long-term riverbank filtration experiment over the course of one month with changing flow scenarios (i.e. transport at 0.7 m d−1, stagnation, and remobilization at 1.7 m d−1). To elucidate retention processes, we conducted small-scale lab column experiments at low (0.2 m d−1) and high (0.7 m d−1) flow rate using pristine and aged sediments.Overall, AgNP accumulated in the upper centimeters of the sediment both in lab and outdoor experiments. In the lab study, retention of AgNP by attachment to biological components was very effective under high and low flow rate with nearly complete NP accumulation in the upper 2 mm. When organic material was absent, abiotic filtration mechanisms led to NP retention in the upper 5 to 7 cm of the column. In the long-term study, AgNP were transported up to a depth of 25 cm. For the pristine sediment in the lab study and the outdoor experiments only erratic particle breakthrough was detected in a depth of 15 cm.We conclude that physico-chemical interactions of AgNP with sediment surfaces are efficient in retaining AgNP. The presence of organic material provides additional retention sites which increase the filtration capacity of the system. Nevertheless, erratic breakthrough events might transport NP into deeper sediment layers.

Фильтровальные характеристики пористых перегородок из проволочных сеток

The article presents the results of experimental studies of the uneven distribution of the distances between the wires of the warp and weft in woven wire meshes with square cells used to clean gases and liquids from mechanical impurities in various branches of technology. On the basis of experimental data using the methods of probability theory, the regularity of the size distribution of the cells of these grids is determined. The length of its minimum side is chosen as the determining size of a square cell. The results of the conducted studies were used to estimate the fractional coefficient of the leakage of spherical particles through the mesh in the sieve mechanism of separation of these particles from the fluid flow. The probability of particle breakthrough through the grid is assumed to be equal to the fraction of the fluid flow passing through the cells, which determines the size of which is larger than the particle diameter. For experimental verification of the calculated values of the leakage coefficient for the sieve filtering mechanism, a preliminary analysis of the influence of the parameters of the hydrodynamic mode of fluid flow through the grid and the level of fluid contamination on the filtering mechanism was carried out. The results of experimental studies of the fractional leakage coefficient values obtained by the sieve filtering mechanism are compared with the calculated data.

Influence of flow alterations on bacteria retention during microfiltration

Microfiltration membranes retain bacteria predominantly by size-exclusion. However, some empirical data points towards the fact, that alterations in flow rate as well as changes in the quality of adhesive interactions between the membrane surface and the bacteria can affect their retention. For parvo virus retaining normal flow virus-filters, systematic investigations have been undertaken to characterize the impact of flow alterations as well as modulations of particle-membrane interactions on virus particle retention. For depth filters used, e.g., for the clarification of fermentation broths, it is well known that alterations in flow rate typically lead to elevated levels of turbidity. This work adopts the acquired knowledge from virus- and depth-filters and investigates their applicability for bacteria retention by microfiltration membranes. It presents particle retention data for mycoplasma and Gram-negative and Gram-positive bacteria. Single layer flat sheet PES model microfiltration membranes with maximum pore sizes varying from 0.3 to 1.5 µm and an overall low retention were used in order to easily detect and differentiate their retention properties for the different particle species. The event of particle breakthrough is elucidated depending on the adsorptive character of the membrane surface, the pore size, and changes in flow rate including the interruption of flow. Moreover, this work investigates how the chemical and physical solution properties influence bacterial retention. These properties include the temperature of the fluid, the presence of a surfactant, the salt concentration and the pH. Flow interruptions using B. diminuta were also applied to commercially available PES sterilizing-grade microfiltration membranes showing no bacterial breakthrough.

Dependency of flow and transport properties on aperture distributions and compression states

ABSTRACTFluid conductivity and elastic properties in fractures depend on the aperture geometry – in particular, the roughness of fracture surfaces. In this study, we have characterized the surface roughness with a log‐normal distribution and investigated the transport and flow behaviour of the fractures with varying roughness characteristics. Numerical flow and transport simulations have been performed on a single two‐dimensional fracture surface, whose aperture geometry changes with different variances and correlation lengths in each realization. We have found that conventional measurement of hydraulic conductivity alone is insufficient to determine these two parameters. Transient transport measurements, such as the particle breakthrough time, provide additional constraints to the aperture distribution. Nonetheless, a unique solution to the fracture aperture distribution is still under‐determined with both hydraulic conductivity and transport measurements. From numerical simulations at different compression states, we have found that the flow and transport measurements exhibit different rates of changes with respect to changes in compression. Therefore, the fracture aperture distribution could be further constrained by considering the flow and transport properties under various compression states.

Modelling particle mass and particle number emissions during the active regeneration of diesel particulate filters

A new model has been developed to describe the size-dependent effects that are responsible for transient particle mass (PM) and particle number (PN) emissions observed during experiments of the active regeneration of Diesel Particulate Filters (DPFs). The model uses a population balance approach to describe the size of the particles entering and leaving the DPF, and accumulated within it. The population balance is coupled to a unit collector model that describes the filtration of the particles in the porous walls of the DPF and a reactor network model that is used to describe the geometry of the DPF. Two versions of the unit collector model were investigated. The original version, based on current literature, and an extended version, developed in this work that includes terms to describe both the non-uniform regeneration of the cake and thermal expansion of the pores in the DPF. Simulations using the original unit collector model were able to provide a good description of the pressure drop and PM filtration efficiency during the loading of the DPF, but were unable to adequately describe the change in filtration efficiency during regeneration of the DPF. The introduction of the extended unit collector description enabled the model to describe both the timing of particle breakthrough and the final steady filtration efficiency of the hot regenerated DPF. Further work is required to understand better the transient behaviour of the system. In particular, we stress the importance that future experiments fully characterise the particle size distribution at both the inlet and outlet of the DPF.

Comparison of clogging induced by organic and inorganic suspended particles in a porous medium: implications for choosing physical clogging indicators

Water from different sources generally contains different kinds of suspended particles, which introduces the challenge of how to control physical clogging during managed aquifer recharge (MAR). Suspended solid concentration (SS) and turbidity (NTU) are widely recognized as indicators of physical clogging potential. The aims of this study were to examine the degree of physical clogging caused by organic and inorganic suspended particles and elaborate the different mechanisms that controlled clogging under specific SS and NTU conditions. Column experiments were performed by continuous suspended particle injection through a saturated porous medium under stable physicochemical and hydrodynamic conditions. Three sets of transport tests were carried out. One test was conducted with chlorinated-secondary wastewater (CSW), which SS was 17.59 ± 0.44 mg L−1 corresponding to 3.09 ± 0.05 NTU. The other two tests were silica-particle wastewater (SPW) with the same SS (1.73 ± 0.03 NTU) and the same NTU (29.21 ± 0.57 mg L−1 SS) as the CSW, abbreviated to SPW-SS and SPW-NTU, respectively. The particle breakthrough curves (BTCs), spatial deposition profiles, and variations in hydraulic conductivity were measured. The transport model, DLVO theory, and O’Melia and Ali clogging model were applied to explain the mechanisms of physical clogging in different systems. The retention of inorganic particles was greater than that of organic particles; 56.02% of organic particles were retained in CSW, while 87.62 and 86.36% of inorganic particles were retained in SPW-SS and SPW-NTU, respectively. The distribution of organic particles was less uniform than that of inorganic particles. However, the variation of the relative hydraulic conductivity (K/K0) was more significant for organic particles than for inorganic particles, with decreased by just 1.80 ± 0.64% in SPW-SS and 4.03 ± 1.64% in SPW-NTU, but decreased by 85.86 ± 1.22% in CSW. This study explained the results with the support of classical models and the DLVO theory. The physicochemical characteristics of suspended particles determined whether and how physical clogging occurred. Suspended particles with different properties follow different transport-deposition processes and have different tendencies to cause physical clogging. Especially for organic particles, clogging degree is quite noticeable. Our results imply that the same SS and NTU threshold values cannot be applied to different types of source water during recharge to prevent physical clogging, even in the same controlled environmental conditions. Physicochemical characteristics of suspended particles need to be considered when developing physical clogging indicators.

Combined time-lapse magnetic resonance imaging and modeling to investigate colloid deposition and transport in porous media

Colloidal particles can act as vectors of adsorbed pollutants in the subsurface, or be themselves pollutants. They can reach the aquifer and impair groundwater quality. The mechanisms of colloid transport and deposition are often studied in columns filled with saturated porous media. Time-lapse profiles of colloid concentration inside the columns have occasionally been derived from magnetic resonance imaging (MRI) data recorded in transport experiments. These profiles are valuable, in addition to particle breakthrough curves (BTCs), for testing and improving colloid transport models. We show that concentrations could not be simply computed from MRI data when both deposited and suspended colloids contributed to the signal. We propose a generic method whereby these data can still be used to quantitatively appraise colloid transport models. It uses the modeled suspended and deposited particle concentrations to compute modeled MRI data that are compared to the experimental data. We tested this method by performing transport experiments with sorbing colloids in sand, and assessed for the first time the capacity of the model calibrated from BTCs to reproduce the MRI data. Interestingly, the dispersion coefficient and deposition rate calibrated from the BTC were respectively overestimated and underestimated compared with those calibrated from the MRI data, suggesting that these quantities, when determined from BTCs, need to be interpreted with care. In a broader perspective, we consider that combining MRI and modeling offers great potential for the quantitative analysis of complex MRI data recorded during transport experiments in complex environmentally relevant porous media, and can help improve our understanding of the fate of colloids and solutes, first in these media, and later in soils.