Outlet Concentration Research Articles

Flexible concentration control of Newtonian and non-Newtonian fluids in a microfluidic device via AC electrothermal flow

Microfluid preparation at targeted concentration is crucial for lots of applications such as protein crystallization and drug efficacy evaluation. Herein, we report an efficient method to continuously produce Newtonian and non-Newtonian fluids at desired concentrations via AC electrothermal (ACET) flow. Two miscible fluids with different initial concentrations are first injected into the device via two separate inlets. The demanded concentrations are obtained under ACET flow, which mixes the fluids into specific states first and obtain the targeted concentrations at outlet afterwards via the voltage and fluid velocity control. To elucidate the underlying principles of fluid concentration control through the ACET effect, we have developed a three-dimensional numerical model coupling the electric, thermal, flow and concentration fields to perform analyses. Our findings indicate that fluid concentration modulation is significantly impacted by both intrinsic fluid properties and external control parameters, including the fluid's apparent viscosity, conductivity, velocity, and driving voltage. Specifically, as the fluid's apparent viscosity increases, the flow weakens, resulting in a higher driving voltage being required to achieve the targeted fluid concentration. The Joule effect and temperature gradient in fluids intensify with increased fluid conductivity, enhancing the ACET flow and correspondingly reducing the necessary driving voltage for concentration control. The duration of the ACET flow in the microchannel varies with the fluid velocity, subsequently affecting the concentration adjustment. The intensity of the ACET flow augments with an increase in the driving voltage, leading to diverse fluid mixing performances and outlet concentrations as the voltage changes. Overall, the fluid concentration control is directly influenced by fluid properties and can be flexibly adjusted through external control of fluid velocity and voltage. The simplicity of the chip design and the flexibility of concentration control offered by this approach make it highly appealing for a wide range of applications that require precise fluid concentration control.

Equilibrium loadings and adsorption isotherm model parameters estimated from multi-component breakthrough curves

Quantitative knowledge of competitive adsorption isotherms is essential for the design and optimization of adsorption based separation processes. Since the experimental determination of these thermodynamic functions is complicated and time consuming, there is a need for fast and easy to apply methods. In particular attractive are methods that evaluate measured breakthrough curves (BTC). Key features of these curves can be predicted with the equilibrium theory, which ignores kinetic effects that cause band broadening. If the adsorption equilibria can be described by the classical competitive Langmuir isotherm model, outlet concentration profiles can be calculated analytically. The paper summarizes and illustrates well-known classical results for N-component systems. The theory is applied to analyze experimentally determined BTC for a ternary mixture fed into an initially fully regenerated column under constant flowrate and under isothermal conditions. It is demonstrated that the retention times and intermediate plateau concentrations, which are observable for example in a single ternary BTC experiment, allow estimating a defined number of characteristic equilibrium loadings. These loadings can be directly used for easy estimation of the parameters of an assumed isotherm model. Various possibilities to use a reduced number of loadings and to include complementary results of standard pulse experiments are described. The isotherms generated from the ternary BTC are successfully validated by results of single component and ternary BTC experiments carried out subsequently. Options to generalize the method to determine isotherm model parameters from measured BTC to initially preloaded columns and to more complex mixtures are finally outlined.

Coupling adsorption and in-situ Fenton-like oxidation by iron-containing low-grade attapulgite clay towards organic pollutant removal: From batch experiment to continuous operation

Coupling adsorption and in-situ Fenton-like oxidation process was developed for Methylene blue (MB) using refined iron-containing low-grade attapulgite (ATP) clay, and the removal mechanism was investigated. The MB was initially adsorbed on the porous ATPs, and then the enriched MB was removed by the H2O2-assisted Fenton-like oxidation with the iron-containing ATP catalyst. Under optimal conditions, the ATP powder exhibits the maximum removal efficiency of 100% with negligible iron leaching (1.5 mg L−1) and no sludge formation. Furthermore, polysulfone/ATP (PSF/ATP) pellets were fabricated through a water-induced phase separation process to construct a fixed-bed reactor (FBR) for continuous contaminant removal. For the first cycle, the maximum adsorption capacity was 15.5 L with an outlet MB concentration of 1.973 mg L−1 (< 2 mg L−1, GB4287-2012) using the PSF/ATP pellets containing 50.0 g of ATP powders, and the maximum Fenton-like oxidation capacity was 35.5 L with the outlet concentration of 0.831 mg L−1. After five cycles, the total treated volume of the MB solution was ca. 255 L, and the efficiency remained above 99%. After 10 h of continuous treatment towards practical resin industrial wastewater, the chemical oxygen demand (COD) removal efficiency was still measured at 83.05%, costing 0.398 $ m−3. These results demonstrate the practical applicability of iron-containing low-grade ATP clay for textile water treatment.

Photocatalytic antibiotic degradation in coated open microchannels by applying 2D and 3D flow modeling with kinetics

The accumulation of active pharmaceutical ingredients in the aqueous environment is a serious problem that will become even more concerning in the future. In this work, the photocatalytic degradation of ciprofloxacin (CIP) in aqueous solution was assessed over P25-TiO2 coated open microchannels with gravity-driven flow under UV-A irradiation. The deposition of different amounts of TiO2 in the microchannels was carried out via a facile, self-developed procedure. The degradation kinetics of ciprofloxacin was described via the Langmuir-Hinshelwood mechanism. Since the flow characteristics in the microchannel had influence on the concentration distribution of CIP in the microchannel, the coupled momentum and mass conservation law was solved numerically in MATLAB 2023a (2D case) as well as in ANYS Fluent 2023 R1 (2D and 3D cases). Although the implemented 2D model in MATLAB 2023a allowed the preliminary estimation of the selected kinetic parameters, namely adsorption equilibrium constant and specific Langmuir-Hinshelwood rate constant, the sensitivity of the model was not satisfactory which was attributed to the empirical correlations used for the estimation of the external mass transfer coefficient. The 2D and 3D models in ANSYS Fluent 2023 R1 predicted efficiently the outlet concentration of ciprofloxacin for different inlet CIP concentrations and liquid phase flow rates. Therefore, the as developed 2D and 3D models in ANSYS Fluent 2023 R1 can be used for the design of reactors containing coated microchannels with gravity-driven flow for photocatalytic degradation of active pharmaceutical ingredients.

Exploring granular filter media in sustainable drainage systems (SuDS) for stormwater pollutant adsorption: A pilot study

Granular filter media are integral to sustainable drainage systems (SuDS) for their efficiency in removing pollutants from urban runoff. This study focuses on understanding the filtration processes within these media by combining a pilot experimental study with a modeling approach. The experimental study involved characterizing the physical and hydraulic properties of various granular filter media materials, including sand, pea-gravel, gravel, and geotextile membranes. Three laboratory-scale stormwater filtration rigs were tested to evaluate the filter media's pollutant removal capacity and hydraulic performance. This work presents a phenomenological model that predicts the spatial variation in the concentrations of stormwater and urban runoff substances, specifically nitrate ions (NO3-), phosphate ions (PO43-), chemical oxygen demand (COD), and suspended solids, by studying their concentration profiles. The stormwater quality model was used to predict the concentration profiles for stormwater with an average inflow consisting of 2.9 mg/L nitrates, 3.4 mg/L phosphate ions, 225 mg/L COD, and 3.3 mg/L of suspended solids. The predicted outlet concentrations matched well with measured experimental data. The results showed that adding geotextile membranes to a granular filter significantly improves its ability to adsorb dissolved species for stormwater applications. This research highlights the importance of understanding the physical and hydraulic properties of granular filter media and their impact on stormwater pollutant removal efficiency. The developed model can assist in the design and optimization of stormwater treatment systems by predicting the performance of different filter media materials, allowing for informed decision-making and improved system functionality.

Impact of forced aeration on vertical flow treatment wetland performances for combined sewer overflow

Combined Sewer Overflow Treatment Wetlands (CSO wetlands) are designed to remove pollutants under stochastic events with variable hydraulic loads. Upgrading them with forced aeration promises to increase the effectiveness and resilience of the treatment. We have tested two vertical CSO wetlands with forced aeration (CSOa and CSOb) to understand the effects of aeration on CSO treatment. Both filter beds have 0.95 and 0.80 m of saturated layer. CSOa uses gravel as top filtering layer, while CSOb utilizes sand and an additional transition layer. Tracer tests were conducted in both filters with and without aeration to assess the impact of aeration on hydraulic performance. CSOa operated with four different aeration conditions, with the optimal condition tested on both filters for comparison. Samples were taken for analysis of global parameters and the redox potential was monitored online. In the tracer test, CSOa allowed to observe the mixing impact of aeration, which avoids any preferential path when influent entered the filter. The addition of a sand layer at the surface (CSOb) allows for a more even distribution of water on the top, which limits preferential flows when aeration is off. In both filters, the results showed that aeration increased the residence time and mixing degree (NTIS <3). Testing different aeration strategies revealed the dependence of dissolved pollutant removal on oxygen supply. In CSOa, the median outlet concentration varied from 23 to 6.4 mg.L−1 in TSS, 153 to 32 mg.L−1 total COD (CODt), 124 to 20 mg.L−1 soluble COD (CODs) and 5 to 2.5 mg.L−1 NH4-N according to aeration strategy. The lower outlet concentrations were always under the highest aeration condition. Under the optimal condition (75 min on/15 min off), median removal of CSOa was 97% TSS, 85% CODt, 78% CODs and 75% NH4-N. Besides COD and TSS, outlet concentration and removal efficiency did not significantly differ between CSOa and CSOb. Pollutant removal demonstrated a linear correlation with organic surface load. Overall, forced aeration in CSO-TW distinctly affected filter dynamics and improved its performance.

Experimental, numerical simulation and genetic algorithm as a hybrid method for the design of hydrogen peroxide separation via non-dispersive solvent extraction

This work employed a hybrid approach combining experiments, numerical simulation, and genetic algorithm (GA) to optimize the non-dispersive solvent extraction (NDSX) process of H2O2. A numerical simulation model with high accuracy was developed. The relative error between the simulation results and experimental data was controlled within 2.2 %. The results indicated the velocity of lumen side and temperature are the key factors affecting the extraction efficiency. The non-dominated sorting GA-II algorithm coupled with the numerical simulation was used to optimize the NDSX process. The Pareto optimal design of the NDSX process can be achieved within the water outlet concentration range of 13.44 to 550.2 kg m-3. Intensification factors of NDSX versus extraction towers are evaluated to be 17.9 and 13.2. In summary, this work provides a design framework for NDSX of H2O2, which is expected to simultaneously promote the mass transfer efficiency and safety of the H2O2 separation process.

Numerical and experimental investigation of solute transports through different types of dialyzer membrane

The flow and mass transport through different membrane types from different hemodialyzers are investigated in a co-current direction to emphasize the effect of solute diffusion through the dialyzer membranes. The numerical model consists of the blood flowing in a hollow fiber surrounded by a dialysate flow, where the mass transport and fluid flow were simultaneously calculated. The high flux dialyzers considered in the present study are FINEFLUX FIX-210S eco, ELISIO-210HR, and PEPA FDY-21B, which differ mainly in characteristics of the membrane structure and surface. Urea and maltodextrin solutions are used as model solutes to consider the effect of molecular size difference. The numerically predicted outlet concentrations closely align with experimental values, where the variation between predicted and measured values remain below 10% across all dialyzer types for urea solutions, and specifically below 8% for maltodextrin solution. Among the various dialyzers tested, FINEFLUX membrane could provide the highest maltodextrin clearance (83.09 ml/min) and overall mass transfer area coefficient (KoA) (119.56 ml/min) potentially due to its fast-diffusion characteristic. In this co-current flow study, the results suggest that urea transport is primarily influenced by flow control with minimal impact from boundary layers, while maltodextrin transport is predominantly governed by diffusion control.

Exploring predictors of substance use disorder treatment engagement with machine learning: The impact of social determinants of health in the therapeutic landscape

BackgroundImproved knowledge of factors that influence treatment engagement could help treatment providers and systems better engage patients. The present study used machine learning to explore associations between individual- and neighborhood-level factors, and SUD treatment engagement. MethodsThis was a secondary analysis of the Global Appraisal of Individual Needs (GAIN) dataset and United States Census Bureau data utilizing random forest machine learning and generalized linear mixed modelling. Our sample (N = 15,873) included all people entering SUD treatment at GAIN sites from 2006 to 2012. Predictors included an array of demographic, psychosocial, treatment-specific, and clinical measures, as well as environment-level measures for the neighborhood in which patients received treatment. ResultsGreater odds of treatment engagement were predicted by adolescent age and psychiatric comorbidity, and at the neighborhood-level, by low unemployment and high population density. Lower odds of treatment engagement were predicted by Black/African American race, and at the neighborhood-level by high rate of public assistance and high income inequality. Regardless of the degree of treatment engagement, individuals receiving treatment in areas with high unemployment, alcohol sale outlet concentration, and poverty had greater substance use and related problems at baseline. Although these differences reduced with treatment and over time, disparities remained. ConclusionsNeighborhood-level factors appear to play an important role in SUD treatment engagement. Regardless of whether individuals engage with treatment, greater loading on social determinants of health such as unemployment, alcohol sale outlet density, and poverty in the therapeutic landscape are associated with worse SUD treatment outcomes.

Global and local breakthrough curves: A concept for filtration design through analysis of internal concentration distribution using CFD

Evaluating the filtration performance of a filter design traditionally relies on a global breakthrough curve, which represents changes in outlet concentration over time. This curve does not account for adsorption phenomena inside the filter, often necessitating trial-and-error experimentation for optimizing filter shape. To address this issue, we introduce an innovative approach that employs computational fluid dynamics (CFD) to define local breakthrough curves. These curves represent concentration changes over time at specific points within the filter. By comparing these local breakthrough curves with the conventional global breakthrough curve, we aim to enhance the precision of filter designs. This optimization strategy seeks to achieve shapes that meet predetermined performance targets or improve the efficiency of existing filters. Utilizing CFD-generated local breakthrough curves in the optimization process enables the prediction of essential filter elements required to meet specified performance criteria, such as height and thickness. Moreover, this method identifies underperforming areas in existing filters and suggests strategic avenues for improvement. Our results underscore the utility of CFD-informed local breakthrough curves as invaluable tools for streamlining the filter design optimization process.

#1094 Hemodiafiltration improves solute clearance without increasing water consumption: an educational bench model for the dialysis ward

Abstract Background and Aims Recently, the positive results of the CONVICE trial have raised the question whether the improved outcome of postdilution high volume HDF (oHDF-p) compared to high flux HD (hfHD) requires increased water consumption. From mathematical modelling it can be shown that oHDF-p always leads to higher low molecular clearance than hfHD at equal total dialysate consumption Qd_tot = Qd_dial + Qs (Qd_dial: dialysate flow through the dialyzer, Qs: substitution flow). This has also been shown in a clinical trial (Mesic et al, HDI 15, p. 522-529). However, mathematical modelling might not be intuitive for everyone, and clinical trials are always influenced by multiple confounders. To add a more intuitive way of reasoning, a simple educational bench model was designed based only on equipment easily available in a standard dialysis clinic which allows to compare dialysis efficiencies based on the urea concentrations as surrogate parameter. Since the fundamental task of dialysis is to cleanse blood from uremic solutes, the treatment modality which at equal resource utilization reduces solute concentration most is the more efficient one! Method Dialysis treatments were simulated in single pass setup using a Fresenius 5008S machine (Fig. 1). Blood inlet was simulated as a fixed urea concentration of 170 mg/dL in dialysate from a 110 L reservoir “cbi”. Treatment parameters were set such that they correspond to effective values in in-vivo treatments: As the mass transfer coefficient is always much higher in vitro with water than in vivo with blood, a small high-flux dialyzer (Fresenius FX40) was used. Blood flow Qb was set to 300 mL/min, corresponding to the in vivo blood water flow for Qb_set ∼ 350 mL/min. Alternating experiments in oHDF-p and hfHD were carried out in triplicate with Qd_tot=400 mL/min and 300 mL/min. This resulted in the settings HDF400, HD400, HDF300 and HD300 (cf. Fig. 1). Qs was set to 100 ml/min in oHDF-p. In each setting the fluid from blood and dialysate outlet were collected (recipients “cbo” and “cdo”, resp.) for 8 min. To be independent of the machine accuracy of set flow rates, sample volumes were measured by weighing, and effective flow rates of blood Qb_eff and total dialysate Qd_tot_eff were calculated. Samples were taken into monovettes from “cbi”, “cbo” and “cdo”. Urea concentrations cbi, cbo and cdo were determined by sending the samples to two commercial clinical labs who delivered consistent results. Blood and dialysate side urea clearances were calculated as KUB= Qb_eff*(cbi-cbo)/cbi and KUD=Qd_tot_eff*cdo/cbi. Results The table in Fig. 1 includes the measure values of Qb_eff and Qd_tot_eff for each setting. Blood and dialysate outlet concentrations (cbo and cdo, resp.) and calculated blood and dialysate side clearances are shown in Fig. 2. Lab results in repeated settings were highly reproducible with a SD &amp;lt; 2 mg/dL. Switching from hfHD to oHDF-p at equal Qd_tot always decreased cbo, corresponding to a higher clearance in oHDF-p. Reducing total dialysate flow from 400 to 300 ml/min caused a slight decrease in clearance in both modalities. KUB and KUD were in good agreement, showing that urea mass balance was well controlled in the experiment. Conclusion The educational bench model demonstrates the superior low molecular clearance of oHDF-p compared to hfHD at equal Qd_tot, reflected by lower urea cbo values in oHDF-p. Although the clinical outcome advantage of oHDF-p is rather related to middle molecular clearance, the model shows that the improved treatment quality of oHDF-p can be provided with no extra resource utilization compared to hfHD, and that dialysis adequacy as measured by urea clearance is even increased despite of the fact that a part of Qd_tot is deviated as substitution fluid. As moderately reducing Qd_tot in many cases only results in acceptable clearance reductions, the automated adjustment of both dialysate and substitution flow rates for oHDF-p could improve patient outcome at even reduced resource utilization.

Multiscale modeling of reactive flow in heterogeneous porous microstructures

This paper presents a multiscale reactive flow model to simulate in-situ leaching of copper in heterogeneous porous microstructures. The introduced workflow combines fluid flow simulation with advection-diffusion-reaction simulation, both required to model reactive flow. The proposed workflow can include the fluid flow in resolved and unresolved pore structures and utilizes required parameters from molecular simulation (ionic diffusivity) and reaction databases (reaction rate parameters). The modeling approach is validated by comparing results to other open-source codes for a model calcite dissolution on acid injection. This model is applied to copper mining by leaching to analyze the reactive flow through a fractured digital rock model of a subsurface sample. Results are analyzed by tracking the concentration distribution along the pore space structure and calculating the outlet concentration of copper to conform the leaching path. Several sensitivity studies are performed to show the robustness of the modeling framework as well as to investigate the importance of each of these parameters on copper production. The complexity of the model is systematically increased from a single scale surface reaction model, to consider the influence of competitive bulk solution reactions, and finally to include flow through porous media to model multiscale reactive flow. This study shows that a multi-scale flow model with homogeneous bulk and heterogeneous surface reactions is required to accurately model copper leaching.

Numerical simulation of the co-firing of pulverized coal and eucalyptus wood in a 1000MWth opposed wall-fired boiler

Currently, coal-fired coupled biomass power generation is widely regarded as a primary method for reducing carbon emissions in coal-fired power plants. This research investigates the co-firing of biomass in an opposed wall-fired boiler and the implementation of air-staged combustion technology using numerical simulation approaches. The study examines the impact of various air methods of distribution and blending ratios on combustion properties and NOx emissions. The findings demonstrate that the abrasive wear of fuel particles on the platen superheater is decreased by the addition of biomass to the fuel mix. Furthermore, a drop in the furnace chamber's overall temperature is the outcome of raising the blending ratio. Different blending ratios have their own adapted air distribution methods. At blending ratios of 10% and 30%, the W-type air distribution exhibits the lowest NOx outlet concentrations of 231.84 mg/Nm3 and 220.6 mg/Nm3, respectively. Moreover, the W-type air distribution shows the highest burnup rates of 98.74% and 98.43% at these blending ratios. This suggests that it is feasible to change the burner monolayer air distribution and combine it with co-firing of biomass technology to achieve low NOx and efficient operation of a hedge-fired boiler.

Dynamic Model Validation and Simulation of Acetone-Toluene and Benzene-Toluene Systems for Industrial Volatile Organic Compound (VOC) Abatement.

Environmental impact mitigation is one of the grand challenges for industries globally. Volatile organic compounds (VOCs) are solvents whose emissions are potentially toxic to human health and ecosystems yet indispensable for the manufacturing of life-saving medicine. Adsorption with activated carbon columns is an established countermeasure for end-of-pipe emission control, whose efficiency, however, is impeded by irregular bed saturation due to the complex nature of its inputs. This work presents the application of a validated nonisothermal adsorption model to examine multicomponent trace mixtures of acetone-toluene and benzene-toluene on activated carbon. Our results indicate preferential adsorption of toluene over both acetone and benzene for all concentrations examined, which is in agreement with experimental data. Moreover, moderate temperature variations and pressure drops are revealed. Finally, Glueckauf's hodograph theory is employed for maximum outlet concentration prediction and compared with simulation results and experimental data, thus providing valuable insights into nonisothermal VOC abatement, which paves the way for industrial operation optimization.

Estimating the parameters of competitive Langmuir adsorption isotherms from measured responses to rectangular pulse injections exploiting equilibrium theory

Knowledge of adsorption isotherms is essential for the design and optimization of chromatographic separation processes. Since the experimental determination of these thermodynamic functions is a complicated and time consuming task, there is a need to develop methods which are fast and easy to apply. An attractive group of methods is based on neglecting in the analysis of measured dynamic elution profiles all kinetic effects. These methods assume the validity of an isotherm model equation and exploit the possibility to solve analytically the column mass balance equations of the equilibrium model. If just the dispersive part of an elution profile is, the method is known as “elution by characteristic point” (ECP). The ECP method has been applied successfully to analyse column effluent profiles of single component dissolved in a mobile phase. This work extends the ECP method to analyse just the shapes of elution profiles recorded after injecting samples that contain two key components to be separated. The extended ECP method requires recording only one overloaded elution profile for the two-component mixture and offers a fast and efficient way to estimate isotherm model parameters. The method is in particular attractive if there is limited access to the pure components, as for example in cases of enantiomers. The underlying theory is presented and applied for the case that the adsorption equilibria can be described satisfactorily by the classical competitive Langmuir model. Core of the theory are the available analytical equations describing the outlet concentration profiles of the two solutes for the equilibrium controlled case the. Considering a case study, it is shown that the extended ECP method can be applied successfully for columns characterized by 2500 or more theoretical plates. However, the method can be useful also for columns with lower efficiency. It provides then a rough estimation regarding the isotherm courses.

Improving incomplete mixing modeling for junctions of water distribution networks

AbstractMost of the existing water quality models for water distribution networks assume complete mixing at junctions. Albeit few models offer the possibility to consider incomplete mixing (IM) at junctions, most of them were developed under laboratory conditions and for equal pipe size junctions. In real-world distribution networks, however, cross junctions of 150 × 100 × 150 × 100 mm or 100 × 150 × 150 × 150 mm are common, yet no model has been developed for these configurations. This paper presents a new equation to compute concentrations in cross junction outlets while considering IM for six cross junction configurations, including unequal pipe sizes and 150 mm pipes. For each cross junction configuration, mixing was studied under 25 flow scenarios in the laboratory and 40 simulated flow scenarios using OpenFOAM software. Two new flow rate ratios were selected as independent variables to compute different outlet concentrations. For two specific cross junctions with equal pipe sizes, the root-mean-squared error between the observed and simulated concentrations of the newly developed model was 0.02, while it was 0.05 and 0.07, respectively, for the AZRED IM model and the Shao et al. IM model.

Simple model for water wash performance in amine scrubbing for CO2 capture

In amine-based capture systems, a water wash is necessary to remove gaseous amine to minimize atmospheric emissions and maximize amine recovery. Water wash simulation requires rigorous thermodynamic and kinetic models like those for absorption and stripping systems. An offline water wash model has been developed based on simplified thermodynamic and mass transfer assumptions to simulate a single-stage water wash for flue gas from gas-fired turbines with little or no aerosol, and to expedite simulations without needing to utilize process modeling software. Calculation of activity coefficients using both Pitzer–Debye–Hückel and Debye–Hückel theory suggest that the liquid phase in a typical water wash will be ideal due to the dilute concentration of molecular and ionic species.Vapor phase piperazine (PZ) is predicted with a driving force based on the volatility of the free amine that has not reacted with other species or dissociated into its ionic form, and the predicted outlet concentration is nearly identical to that predicted by rigorous Aspen PlusⓇ simulations. The predicted UT FEED outlet concentration is 220 ppb compared to 260 ppb predicted by Aspen PlusⓇ.Single-stage water washes are predicted to have single ppm concentration of MEA leaving the wash outlet flue gas. Amino-methyl-propanol (AMP) is predicted to be reduced to 10–30 ppm by a single-stage wash, and is predicted to be a difficult-to-capture amine without further washing steps. This prediction correlates with published TCM data from an ALIGN-CCUS campaign. Amine compounds at a similar or lower volatility to that of PZ are predicted to be reduced to ppb levels via a single-stage wash.

Optimizing the hydraulic performance of a baffled horizontal subsurface flow constructed wetland through computational fluid dynamics modelling

Baffled constructed wetlands (CWs) offer a promising solution to address low hydraulic efficiency in traditional CWs. However, there is a research gap in the field regarding the optimal length and quantity of baffles, and their comprehensive effects on hydraulic efficiency. This study is the first CFD-based assessment to comprehensively investigate the combined influence of baffle length and the number of baffles on the hydraulic efficiency of CWs. Using OpenFOAM simulations at a laboratory scale, various baffle configurations were examined with lengths ranging from 0.4 m to 0.58 m and baffle numbers varying from 0 to 11. Experimental tracer tests were conducted to validate the simulations. The high correlation coefficient (R2) between the tracer test results and simulations (ranging between 0.84 and 0.93) further underscores the reliability of the findings. Residence time distributions (RTDs) were derived from the temporal evolution of the outlet concentration of a tracer. The results indicate that augmenting the number of baffles under a fixed baffle length has a greater impact on the RTD curves, causing a backward displacement of the peak time. However, when the number of baffles is three or fewer, extending the baffle length does not significantly affect the RTD. When the baffle length is held constant at 0.58 m, there is a 58% enhancement in hydraulic efficiency as the number of baffles increases from 0 to 5. However, when maintaining a constant number of 11 baffles, increasing the baffle length from 0.4 to 0.5 m results in only a 5.5% improvement in hydraulic efficiency. Moreover, a generalized predictive equation for hydraulic efficiency was derived based on the CFD results and dimensional analysis. The study enhances the optimization of constructed wetland design by providing greater understanding of hydrodynamic behavior, leading to improved performance and applicability in practical environmental engineering.

Simulation of the Impurity Absorption from a Laminar Flow in a System of Hollow-Fiber Membranes

The external stationary flow of a viscous incompressible fluid and the convective-diffusion mass transfer of a solute in an ordered system of parallel hollow fiber membranes arranged normally to the flow direction are calculated in the ranges of Reynolds numbers \(\operatorname{Re} \) = 0.01–100 and Schmidt numbers \({\text{Sc}}\) = 1–1000. The Navier–Stokes equations and the equation of convective diffusion were solved using the methods of computational fluid dynamics with a no-slip boundary condition and with a constant solute concentration condition on the outer surface of the streamlined fiber. The calculations were performed for a row of fibers and for a multi-fiber system consisting of four and sixteen rows of fibers. The outlet concentrations and the fiber solute retention efficiencies \(\eta \) were calculated depending on the packing density of the fibers and the \(\operatorname{Re} \) and \({\text{Sc}}\) numbers. It is shown that it is possible to use the fiber solute retention efficiency \(\eta \) defined for a single row of fibers to predict the retention efficiency of an extended multi-row fibrous bed.

Mixing performance of an expansive mixer on viscoelastic solutions under alternating current electric field

Development of effective technologies for mixing viscoelastic solutions with reagents is still a challenge, which plays an important role in the fields of disease diagnosis, water desalination, and immunoassay. The purpose of this paper is to numerically study the mixing performance of an expansive mixer on the viscoelastic solution under the impact of an alternating current (AC) electric field through the analyzation of mixing efficiency, the concentration distribution, and average outlet velocity. A poly acrylic acid (PAA) water solution with different concentrations characterized by the Oldroyd-B constitutive model is used as a mixed medium, and an open-source toolbox called rheoTool based on finite volume algorithm is applied to solve the governing equations. We quantitatively determine the mixing efficiency for different PAA concentrations, AC electric field strengths, and frequencies and compare the mixing efficiency created by AC and direct current (DC) electric fields. Our investigation indicates that the mixing efficiency of the mixer diminishes with the PAA concentrations but enhances with the AC electric field strengths for a relatively high polymer concentration, and AC electric fields with different frequencies lead to a larger mixing efficiency than DC electric fields for a low polymer concentration. Additionally, the influence of the model parameters on the average outlet velocity and concentration distribution is discussed at length. Our numerical simulation results show that the mixer has an excellent mixing performance for both Newtonian and viscoelastic solutions, with a mixing efficiency of more than 99% at a low polymer concentration and a stable outflow velocity.