Fouling Model Research Articles

Water Treatment by Nanofiltration and Reverse Osmosis Membranes Using Hermia Fouling Models

Water Treatment by Nanofiltration and Reverse Osmosis Membranes Using Hermia Fouling Models

An Experimental and Modeling Approach to Study Tangential Flow Filtration Performance for mRNA Drug Substance Purification.

Following the recent COVID-19 pandemic, mRNA manufacturing processes are being actively developed and optimized to produce the next generation of mRNA vaccines and therapeutics. Herein, the performance of the tangential flow filtration (TFF) was evaluated for high-recovery, and high-purity separation of mRNA from unreacted nucleoside triphosphates (NTPs) from the in vitro transcription (IVT) reaction mixture.For the first time, the fouling modelwas successfully validated with TFF experimentaldata to describe the adsorption of mRNA on filtration membrane. The fouling model enables monitoring of the mRNA purification processes, designing an appropriate strategy for filter clean-up, replacing the column at the right time and reducing the process cost. Recovery greater than 70% mRNA without degradation was obtained by implementing a capacity load of ∼19g/m2, <2.5psi transmembrane pressure (TMP) and feed flux of 300 LMH.This approach also enables the purification of multiple mRNA drug substance sequences for the treatment of a wide range of different diseases.

Structure-function relationship for functional films with constructed graded channels in dye/salt separation and fouling resistance

The structural assembly of polypyrrole particle stacking, combined with polydopamine space-filling, forms composite film with a network of interconnected fluid channels. The composite films achieve high water flus, separation efficiency and ratio of organic dyes/inorganic salts (flux: >600 L m−2 h−1 bar−1; dye rejection: ~100 %; salt rejection: <5 %). Simulation using different dye fouling models show that the dye only interacts at the surface, and hardly affects internal pores of the film throughout the filtration process. Owing to the patterned surface structure as constructed by microsphere arrangement and inter-structure adaptation assembly, the functional film has excellent contamination tolerance and rinsing regeneration for macromolecular pollutants. The results of computational fluid dynamics simulations further indicate that the high shear stress above the microspheres with vortex flow in the interstitial space has a positive effect on reducing contaminant deposition. In addition to the separation property, the composite film shows good structural stability and mechanical strength in various complex water environments, benefiting their future practical applications. This work unveils the structure-function relationship for composite function films with constructed graded channels in dye/salt separation, which is important for the design and future application of these functional films.

Understanding the fouling characteristics in ultrafiltration membrane for marine algae-laden seawater pretreatment: Focus on the role of algal extracellular organic matter

The increasing frequency and extent of harmful algal blooms (HABs) due to global warming and environmental pollution pose significant challenges to the ultrafiltration (UF)-seawater reverse osmosis (SWRO) desalination process. The UF process is a dominant pretreatment method to reduce HAB fouling potential in subsequent SWRO processes. Herein, we systematically evaluate the UF membrane fouling characteristics at different growth phases of HAB algae in terms of reversible/irreversible fouling and pinpoint the fouling mechanisms on UF membranes in the real seawater matrix. We employed Prorocentrum donghaiense as a model marine HAB specie to characterize algal derivatives, including extracellular organic matter (EOM) and granule particles. LC-OCD, MFIs, 3D-EEM, and GPC were used to analyze algae-derived matters. Results from the multiple fouling model revealed that algal solution in both stationary and decline phases exhibit severe membrane fouling, characterized by rapid cake layer formation, swift flux decline, and high membrane resistance. Soluble EOM (S-EOM) was the primary contributor to membrane fouling, linked to its elevated concentrations of dissolved organic matters, polysaccharides, proteins, and humic substances, which are predominantly hydrophobic. Additionally, granule particles mitigated organic membrane fouling, as evidenced by the smaller permeate volume required for S-EOM cake layer formation (<5 mL), resulting in a faster initial flux decline. These results revealed a shift in released organic matter from protein-centric to humic substance-centric during the transition from exponential growth to the decline phase, with correlation analysis further underscoring the substantial contribution of humic substances to membrane resistance. This research highlights the distinct UF membrane fouling characteristics at different marine algal growth stages, offering theoretical support for predicting and managing HABs.

Purification of crude glycerol derived from biodiesel production process using ceramic membranes: Experimental studies and modeling of flux behavior

Large-scale biodiesel production generates large quantities of glycerol with high impurities levels, and new purification processes are needed to add value to this by-product of biodiesel production. Thus, this study evaluated the application of ceramic membranes for glycerol purification from biodiesel production and the influence of the mean pore diameter of the membrane, pressure, temperature, and the addition of acidified water to the mixture to be purified. The experiments were carried out in a tangential filtration module with ceramic membranes of 5 kDa, 20 kDa, 0.05 μm, and 0.2 μm, varying the pressure by 1, 2, and 3 bar and the temperature by 25, 40, and 60 °C. The results showed that increasing the pressure, average pore diameter and temperature caused an increase in the permeate flux. Furthermore, adding acidified water increased permeate fluxes and glycerol concentrations for all membranes and pressures used. A higher glycerol content (91.13 %) was obtained with the 5 kDa membrane at 3 bar and 60 °C. The traditional fouling mechanism models failed to fit most of the experimental data. On the other hand, the proposed generalized model adequately predicted the experimental permeate flux data for the different types of fouling mechanisms observed.

Numerical study on formation characteristics of particle-crystal mixed fouling in the heat exchanger tube

A mixed fouling prediction model is developed to investigate the problem of heat exchanger fouling in cooling water systems, which considers the particle-crystal mixed fouling deposition and evolution processes. As the fouling thickness exceeds the fluid cell height, the fluid cell is converted into a porous media cell to represent the fluid flow in the fouling layer. The mixed fouling layer growth and evolution are simulated using the porous media model and a user-defined program. The fouling resistance obtained from the model agrees well with the experimental data in the literature. Additionally, the fouling thickness distribution on heat transfer surfaces is predicted. The differences between mixed fouling and single fouling are compared. Then the effect of fluid parameter variations on fouling characteristics is investigated within the heat exchange channel. The results show that fouling accumulates at the end of the pipe, exhibiting a distribution trend of being thin at the front and thick at the back. Moreover, the risk of fouling formation significantly increases with increasing inlet temperature, concentration and heat flux, while high inlet velocity leads to small fouling resistance. The asymptotic value of fouling resistance decreases by 59.1% when the inlet velocity increases from 0.25 to 0.65 m/s.

Single-use chromatographic clarification to eliminate endonuclease treatment in production of recombinant adeno-associated viral vectors

In current manufacturing processes for recombinant adeno-associated viral vectors (rAAV), endonuclease treatment is used prior to depth filtration to break down host cell DNA that is released from cells post-lysis. Without this treatment, traditional depth filters exhibit negligible clearance of host cell DNA, a key process-related impurity. In this work, we evaluate single-use chromatographic clarification using Harvest RCTM filters (3 M) to process rAAV8 and rAAV9 HEK293 cell culture lysate with and without endonuclease pretreatment. We demonstrate endonuclease-free clarification for both serotypes with yield >90 % and up to 3 log reduction of host cell DNA, from >104 ng/mL to <50 ng/mL, matching or exceeding the filtrate quality in traditional depth filtration with 100 U/mL of endonuclease added during lysis. The addition of 100 mM of salt in the harvest buffer is also shown to improve filtration throughput, prevent filter clogging, and limit rAVV binding to the filter device. Finally, a mechanistic cake-fiber fouling model is shown to be a good representation of the Harvest RCTM filtration mechanism. The endonuclease-free clarification approach enables cost savings of USD 100,000 per 500 L batch, equivalent to the cost of cGMP-grade endonuclease at this scale. The benefits of endonuclease-free clarification further include easier raw material sourcing as well as eliminating the need for a residual endonuclease assay in rAAV manufacturing processes.

Phenol Removal through Horseradish Peroxidase Immobilization on Ultrafiltration Membranes: Comparative Analysis of Immobilization Methods and Fouling Patterns

This research investigates the removal of phenol using pure peroxidase from horseradish grade I in conjunction with a dead-end ultrafiltration membrane. Various horseradish peroxidase (HRP) immobilization techniques— physical adsorption, covalent bonding, and cross-linking with glutaraldehyde—were applied to a regenerated cellulose (RC) membrane with a surface area of 44 m2 and a molecular weight cut-off of 30 kDa. The investigation examined factors influencing phenol removal, including phenol concentration, membrane fouling, and the reusability of immobilized enzymes. Results indicated that covalent bonding was the most suitable enzyme immobilization technique, achieving a remarkable 90.1% immobilization yield. Phenol removal efficiency reached 100% at 30 min under specific conditions: phenol concentration of 1 mg/L, pH 6.0, hydrogen peroxide concentration of 0.5 mM, and operating pressure set at 3 psig, with temperature maintained at 28 ± 3 °C. Membrane fouling resulted in a decrease in flux. The performance of fouling models was found to be influenced by phenol concentration, with the Cake Formation Model (CFM) proving most effective at low concentrations, while the Complete Pore Blocking Model (CBM) emerged as more suitable at higher concentrations. The immobilized enzyme exhibited reusability for five cycles, maintaining a phenol removal efficiency exceeding 50%. These findings contribute to understanding the enzymatic phenol removal process and the use of appropriate enzyme immobilization techniques for the effective and sustainable treatment of phenol-contaminated water.

Investigating the Fouling Models of the Microfiltration Mixed Matrix Membranes-Based Oxide Nanoparticles Applied for Oil-in-Water Emulsion Separation

Membrane fouling is a major problem encountered in the use of microfiltration (MF) processes to separate the emulsified oil from water. This work involves assessing the efficacy of removing oil-in-water emulsion (O/W emulsion), and evaluating fouling resistance by studying the membrane morphology before and after fouling, and after washing with different cleaning solutions via field emission scanning electron microscopy (FESEM) analysis. Also, the fundamental mechanism involved in the flux drop during crossflow MF has been assessed using models such as the Hermia blocking models and the modified model by Field. The standard and intermediate pore blocking models provided the best prediction for experimental behavior when analyzing the decay in the flux with time for the bio silicon oxide/polyvinylchloride (B-SiO2/PVC) membrane and the stannic oxide/polyvinylchloride (SnO2/PVC) membrane. This research established regression equations of the flux for both membranes in which these equations are highly correlated with R2 of 98.33% for B-SiO2/PVC and R2 of 99.52% for SnO2/PVC using the surface response methodology (RSM). The high flux recovery ratio (FRR) is indicative of the improved antifouling feature of the manufactured membranes where it was 96.8% for B-SiO2/PVC and 94.6% for SnO2/PVC. The results obtained by Hermia and Field were in good agreement with RSM analysis supporting the standard pore-blocking mechanism.

Treatment of highly iron-contaminated brackish groundwater by MF, UF, and NF membranes for potable water resource production: influence of operating parameters, comparative study, membrane fouling, and machine learning modeling

ABSTRACT The present investigation focuses on using commercially available MF, UF, and NF membranes to eliminate Fe from real groundwater. The impact of process parameters, including applied pressure, temperature, pH, time, and concentration, on flux and Fe removal% is investigated. Results of the permeation test confirm higher permeability for MF membranes (214.71 L/m2.h.bar) than that for NF (2.708 L/m2.h.bar) and UF (56.52 L/m2.h.bar) membranes. The FESEM-EDS characterization confirms the deposition of dominant foulant Fe particles over the membrane surface. At 2 bar applied pressure (temperature = 30 °C, pH = 6.13, and concentration = 6.62 ppm), MF, UF, and NF can eliminate 93.5, 90.2, and 100% Fe, respectively. However, UF and NF exhibit much lower fluxes (72.43 and 3.85 L/m2.h, respectively) compared to MF (317.13 L/m2.h) at the same process conditions. NF eliminates 100% Fe from start to end with rising pressure, while MF (62.16–100) and UF (87.09–100) show gradually improved removal rates. Above pH 6, all membranes demonstrate higher Fe rejection because the oxidation rate of ferrous iron increases at a high pH. With increasing concentration (6–500 ppm), Fe removal efficiency increases for NF (88.26–94.18%) but decreases for both MF (89.63–23.64%) and UF (27.66–14.4%). To validate experimental findings, five machine learning (ML) regression models are scrutinized using various statistical measures.

Ash fouling characteristic analysis and prediction for pillow plate heat exchanger in waste heat recovery based on attentive-feature decision algorithm

Ash fouling on heat exchanger surfaces in waste heat recovery and utilization is an inevitable result of solid fuel combustion and particle deposition, affecting the efficiency, availability and operating cost of an energy utilization system. Fouling prediction plays a critical role in reasonable design and efficient operation of heat exchangers. However, credible monitoring and accurate prognostic towards fouling condition always remain a challenge, largely due to the complex flue gas component and abominable service environment of heat exchangers. In this paper, a novel ash fouling prediction method combined with Effective Particle Size Filtering and Multistep Attentive-Feature Decision algorithm (EF-MAFD) for Pillow Plate Heat Exchanger (PPHE) is proposed. First, a numerical fouling model with Discrete Phase Model (DPM) combined particle deposition and removal model is developed. Validation work is conducted on Nusselt number, pressure drop coefficient and normal restitution coefficient with existing experimental data. The effect of geometrical configuration of PPHE and condition on the fouling characteristic is then evaluated with this model. Next, the EF-MAFD ash fouling prediction model is established, in which the initial particle size distribution is transformed into an effective diameter innovatively and two indicators evaluating the fouling state, namely critical fouling resistance and critical fouling time are defined and predicted. The results indicate that fouling mainly occurs downstream of the welding spots and shows an asymptotic growing trend over time. PPHE with smaller diameter of welding spot, channel height and pitch ratio possess anti-fouling potential. In comparison to existing methods, the newly developed EF-MAFD method has the capacity to deal effectively with the complex particle distribution and provides the most satisfying prediction ability with coefficient of determination (R2) of 0.93 and mean absolute prediction error (MAPE) of 7.8 %. The proposed method could be utilized as a reliable tool to support fouling condition-based maintenance and design for various types of heat exchangers operating in fly ash conditions.

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.

Numerical investigation on ash accumulation characteristics of serrated spiral finned tube heat exchanger in waste heat utilization

In this study, a comprehensive loose fouling model is established to investigate the fouling characteristics of fly ash on serrated spiral finned tube heat exchangers. This model considers the energy change during particle collision, the velocity change after particle rebound and slip, and the amplification of fouling time under mixed particle sizes. The results show that the fouling position, morphology, and height obtained by the theoretical model agree well with the experiments. Besides, the serrated spiral fin is the main fouling position due to its high fin ratio and the strong disturbance effect. The 5 μm particles have the highest deposition rate, and fine particles tend to adhere to the second row of finned tubes due to the consumption of initial kinetic energy by the first row. With an increase in fin height by 6 mm, the deposition rate only increases by 1.2 %, while an increase in sawtooth height by 5 mm results in a deposition rate increase of 14.3 %. When the flue gas velocity is less than 7 m/s, finned tubes arranged in a staggered configuration provide the best combination of heat transfer, flow resistance, and anti-ash accumulation performance.

Implementation of filtration models for filter performance prediction in bioprocess dead-end membrane filtration

Mechanistic modeling is frequently applied during process development and scale-up in bioprocessing. For normal flow filtration (NFF, also called dead-end filtration) processes, such as aseptic filtration, harvest clarification, and virus removal etc., the modeling based on a theoretical fouling law has long been used to assess filter performance and filtration area requirements. This case study describes how an appropriate fouling model is selected and provides guidance for using the fouling model for bioprocess application. There is general agreement that the modeling and process simulation enables accurate filter size calculations for scale-up. Their predictions can then be used to identify optimal filter formats for each unit operation. However, because feed characteristics and conditions vary between processes, fouling models need to consider several filter fouling mechanisms for different bioprocess applications and unit operations. This study reviewed several fouling models and considered various bioprocess filter fouling scenarios, as well as the accuracy of filtration area predictions from the models. It was determined that filtration runs in small scale sizing studies should be run to at least 40 % flux decay to minimize the risk of prediction error due to extrapolation.

A review of CFD simulation in pressure driven membrane with fouling model and anti-fouling strategy

A review of CFD simulation in pressure driven membrane with fouling model and anti-fouling strategy

Experimental assessment and numerical simulations of marine fouling effect on underwater sound absorption coatings

Underwater sound absorption coatings capable of absorbing sound energy is essential to conceal underwater vehicles. While the accumulation of marine fouling on surfaces of ship hulls, platforms, and submarines can significantly alter their acoustic properties. Currently, the precise impact that different stages of marine fouling have on underwater sound absorption coatings remains unclear. In this study, a novel lab assessment method was developed to investigate the acoustic effect of marine fouling on the underwater sound absorption coatings. Four distinct stages of marine fouling were artificial fabricated and characterized, including conditioning film, microfouling, medium macrofouling, and heavy macrofouling. These effects are quantified through comprehensive tests conducted in a water-filled impedance tube. It is found that the first two stages of marine fouling have a negligible impact on the underwater sound absorption performance within the low frequency range of 500 Hz and 2000 Hz. While a limited impact is observed in the frequency range of 2000 Hz–5000 Hz, where the sound absorption coefficient remains approximately 0.6. Conversely, in the third and fourth stages of fouling, the average sound absorption coefficient drops from 0.8 to 0.2. Further, a new acoustic finite element method (FEM) model of hard fouling was developed to predict the acoustic effect, and the numerical results show the same trend with the experimental results. These findings emphasize the importance of considering antifouling strategies during the design of underwater sound absorption coatings, with a particular focus on targeting hard fouling organisms as the primary objective.

An improved CFD particulate fouling simulation method: The local fouling method

In most of the modern and developed industries, water is used as heat transfer fluid. However, the accumulation of many precipitates and suspended solids in some locations results in particulate fouling on the surface of heat exchangers. To anticipate the particulate fouling deposition at the specific location of the heat exchanger channel, an improved CFD particulate fouling model is proposed in this study, namely, the local fouling method. The method is applied to study the heat transfer surfaces of smooth and complex channels along with their particulate fouling deposition process. The results illustrate that the modeled fouling resistance of the two channels is in good agreement with the published experimental data. The average value of local fouling resistance obtained by the local method can substitute the integral fouling resistance obtained by the integral method. In addition, the fouling resistance data obtained by the local method approach has a stronger correlation with the experimental data as compared to that obtained by the existing integral method. And the local method may be applied to obtain local fouling information for both smooth and complex channels heat transfer surfaces.

Revealing the contradiction between DLVO/XDLVO theory and membrane fouling propensity for oil-in-water emulsion separation

Oil fouling is the crucial issue for the separation of oil-in-water emulsion by membrane technology. The latest research found that the membrane fouling rate was opposite to the widely used theoretical prediction by Derjaguin-Landau-Verwey-Overbeek (DLVO) or extended DLVO (XDLVO) theory. To interpret the contradiction, the molecular dynamics was adopted to explore the molecular behavior of oil and emulsifier (Tween 80) at membrane interface with the assistance of DLVO/XDLVO theory and membrane fouling models. The decreased flux attenuation and fitting of fouling models proved that the existence of Tween 80 effectively alleviated membrane fouling. Conversely, DLVO/XDLVO theory predicted that the membrane fouling should be exacerbated with the increase of Tween 80 concentration in O/W emulsion. This contradiction originated from the different interaction energy between oil/Tween 80 molecules and polyether sulfone (PES) membrane. The favorable free energy of Tween 80 was resulted from the sulfuryl groups in PES and hydrogen bonds (O-H…O) formation further strengthened the interaction. Therefore, Tween 80 could preferentially adsorb on membrane surface and form an isolation layer by demulsification and steric hindrance and resist the aggregation of oil, which effectively alleviated membrane fouling. This study provided a new insight in the interpretation of interaction in O/W emulsion.

A mathematical model for predicting crystallization fouling in narrow rectangle channel incorporating crystal growth effect

Crystallization fouling is an ongoing concern for many heat transfer systems, and simulating fouling formation under various flow and heat transfer conditions is crucial for predicting fouling resistance and improving energy efficiency. This paper proposes a mesoscopic model for predicting crystallization fouling in narrow rectangle channels accounting for the realistic crystal growth. A hybrid lattice Boltzmann and finite difference model is established to predict the coupled process of fluid flow, heat transfer, concentration diffusion and crystallization fouling. The second-order mass deposition rate is solved and transformed to the surface-reaction boundary condition in lattice Boltzmann (LB) scheme, and the volume of pixel (VOP) method is employed to simulate the dynamic crystal growth. The scheme and the sub-models are verified systematically by the analytical solution of a linear diffusion-reaction problem, the semi-theoretical fouling models, and the experimental data. The results indicate that the present model can effectively predict the crystallization fouling controlled by either surface integration or mass transfer, and show its capability to simulate the non-uniform fouling growth process in heat transfer channels, providing insight towards full understanding and mitigation design of crystallization fouling.

Interpretable, data-driven models for predicting shaft power, fuel consumption, and speed considering the effects of hull fouling and weather conditions

In response to the global call for action to reduce CO2 emissions, operational measures such as speed, route optimization, and hull cleaning play a significant role in the maritime industry. These measures can be implemented immediately without significant investment in both newbuilding ships and existing ships. To make accurate decisions regarding operational measures, reliable and precise models of environmental conditions and effects of hull fouling are required. In this study, a data-driven approach using linear regression was applied to predict shaft power, fuel consumption, and speed after intensive data preparation and feature engineering. First, a shaft power prediction model was developed by combining three independent submodels: the RPM-power model, hull fouling model, and environmental effect model. Subsequently, fuel consumption and speed prediction models were developed based on the shaft power prediction model. Model validation was performed on a 174K LNG carrier, and the results showed good accuracy even in long-term ship operations of more than two years. The mean absolute percentage errors (MAPEs) of the prediction models were 1.60%, 1.70%, and 2.68% for the shaft power, fuel consumption, and speed, respectively. The validated models were applied to two LNG carriers, and satisfactory results were obtained. This study contributes to greenhouse gas (GHS) reduction by providing interpretable, flexible, and accurate models that can help make correct decisions regarding optimal operational measures.