Filtration Scheme Research Articles

RBFsim – A tool for early planning stage of riverbank filtration systems

Riverbank filtration (RBF) is increasingly being considered an effective method to support the management of water supply and the management of groundwater-river water exchange. Literature, however, provides very limited methods for the initial evaluation of the RBF system. Specifically, initial evaluations need to rely on limited data, be cost-effective, and provide sufficient useful output. The paper provides the development of a tool called RBFsim, designed for the early assessment of flow hydraulics in a riverbank filtration (RBF) scheme during site selection and optimization of well operation. The developed tool allows simplified computation (based on the Analytical Element Method or AEM) of the flow field for single and multiple wells in a 2D homogeneous and isotropic aquifer with uniform flow. The tool superimposes analytical solutions for key RBF quantities such as residence time (the time required for river water to reach the well) and the proportions of water (contributed by the river and groundwater) in the well discharge. These solutions are superimposed on the developed flow field. Additionally, the tool can be used to evaluate the impact of riverbed clogging on the operation of the RBF system. The simplified computation due to AEM and limited data requirements allows the tool to be used in handheld (smartphones) or desktop devices with or without internet connection. RBFsim results are verified by comparing them with results from MODFLOW and MODPATH simulations, which are based on entirely different (finite difference) computational schemes. The obtained results from both these models match within the error margin of less than 5%. Further, the practicality and applicability of RBFsim are illustrated using synthetic and field data. While the tool provides a matching river water contribution ratio with field data, it demonstrates the best-fit residence times primarily for higher well discharge rates. These limitations are attributed to complexities observed in the field, such as a heterogeneous aquifer and nonuniform flow. Overall, the developed tool simplifies the complex computations required, particularly for assessing the feasibility and risk of RBF schemes. The developed tool’s methods and code are open-sourced (licensed under CC-BY 4.0), which promotes personalized modifications and extensions.

Integration of surface-based and space-based atmospheric CO2 measurements for improving carbon flux estimates using a new developed 3-GAS inversion model

The ongoing necessity and developmental trajectory in atmospheric CO2 assimilation system revolve around enhancing the optimization efficacy of assimilation inversions through the synergistic integration of distinct observational datasets. In this study, we developed an new inversion system-Global Greenhouse-Gases Assimilation System (3-GAS), by coupling the global atmospheric transport model GEOS-Chem with the four-dimensional local ensemble transform Kalman filter (4D-LETKF) algorithm. We compiled an integrated dataset utilizing the widely recognized carbon observation data from ObsPack (Observation Package), GOSAT (The Greenhouse Gases Observing Satellite), and OCO-2 (Orbiting Carbon Observatory-2) to estimate global surface fluxes. The integration of multiple observational data significantly amplifies spatial coverage, enhances the variability in flux inversion, and fosters improvements in localized assimilation efficacy. The spatial distribution of the carbon flux from the combined assimilation emerges as a comprehensive outcome, born from the assimilation with individual observational data. This distribution is primarily influenced by the coverage attributes of the original observations and the meticulous selection of observations during the assimilation process. The validation with surface and aircraft observations reveals that the results of combined assimilation possess composite advantages, which are manifested in alleviating certain intrinsic errors inherent to individual assimilation. The combined assimilation improves the accuracy based on root-mean-square error reduced by 9%, 22% and 33% in comparison to surface-only, GOSAT-only and OCO-2-only assimilation. Eventually, predicated upon preliminary inversion results and regional characteristics, we endeavor to propose a more refined filtration scheme and error determination method for the integrated dataset, as the initiative for the efficient assimilation of multi-source data.

Performance evaluation of quantitative material decomposition in slow kVp switching dual-energy CT.

Slow kVp switching technique is an important approach to realize dual-energy CT (DECT) imaging, but its performance has not been thoroughly investigated yet. This study aims at comparing and evaluating the DECT imaging performance of different slow kVp switching protocols, and thus helps determining the optimal system settings. To investigate the impact of energy separation, two different beam filtration schemes are compared: the stationary beam filtration and dynamic beam filtration. Moreover, uniform tube voltage modulation and weighted tube voltage modulation are compared along with various modulation frequencies. A model-based direct decomposition algorithm is employed to generate the water and iodine material bases. Both numerical and physical experiments are conducted to verify the slow kVp switching DECT imaging performance. Numerical and experimental results demonstrate that the material decomposition is less sensitive to beam filtration, voltage modulation type and modulation frequency. As a result, robust material-specific quantitative decomposition can be achieved in slow kVp switching DECT imaging. Quantitative DECT imaging can be implemented with slow kVp switching under a variety of system settings.

Depth filtration for clarification of intensified lentiviral vector suspension cell culture.

Depth filtration significantly impacts efficiency of lentiviral (LV) vector purification process. However, it is often deprioritized in the overall scope of viral vector manufacturing process optimization. The demand for LV vectors has increased with the rise in disease indications, making it crucial to improve current manufacturing processes. Upstream bioreactor process intensification has enabled cell densities of over 107 viable cells/mL, creating challenges for harvest unit operations. The larger size of LV vectors and their physiochemical similarity to host cell-DNA (HC-DNA) and poor clarification performance causes significant challenges for the subsequent chromatography-based purifications. As a result, a robust and scalable harvest of LV process is needed, especially for LV in vivo therapeutic quality needs. In this study, we systematically evaluated the overlooked yet important issue of depth filtration systems to improve enveloped LV functional vector recovery. We found that an established depth filtration system in process A that provided 94% (n = 6) LV functional recovery could not be translated to intensified Process B cell culture. Hence, the depth filtration process became a bottleneck for the purification performance in an intensified process. We demonstrated an improvement in LV functional vector recovery from 34% to 82% via filter train optimization for an intensified suspension cell culture system (>107 cells/mL with higher titer), while still maintaining a loading throughput of ≥82 L/m2 and turbidity ≤20 NTU. It was demonstrated that the two or three-stage depth filtration scheme is scalable and more suitable for high cell density culture for large scale for LV manufacturing process.

Pore characteristics of cake by filtration based on LBM-DEM-DLVO coupling method

Slurries containing fine particles are widely dewatered by flocculation combined with filtration. Understanding the microscopic filtration process of a flocculated slurry is helpful in designing flocculation and filtration schemes; however, there is currently limited research. In this study, the Lattice Boltzmann method–Discrete Element method–DLVO coupling method (LBM–DEM–DLVO) was used to conduct numerical experiments on the pore characteristics of cake by filtration. The numerical results demonstrate that the cake formed by filtration of the flocculated slurry contains two types of pores: interfloc and intrafloc pores. The diameter of the interfloc pores, which are the dominant channels for water seepage in the cake, is relatively large. The pore properties of the cake were significantly influenced by the interaction force between the particles in the floc and the filtration pressure; the mechanism was analyzed. Engineering proposals for dewatering are also presented. A multi-stage pressure treatment process and increased Finter during flocculation are recommended.

Regression Filtration With Resetting to Provide Exponential Convergence of MRAC for Plants With Jump Change of Unknown Parameters

This paper proposes a new method to provide the exponential convergence of both the parameter and tracking errors of the composite adaptive control system without the persistent excitation (PE) requirement. Instead, the derived composite adaptive law ensures the above-mentioned properties under the strictly weaker finite excitation (FE) condition. Unlike known solutions, in addition to the PE requirement relaxation, it provides better transient response under jump change of the plant uncertainty parameters. To derive such an adaptive law, a novel scheme of uncertainty filtration with resetting is proposed, which provides the required properties of the control system. A rigorous proof of all mentioned properties of the developed adaptive law is presented. Such law is compared with the known composite ones, which also relax the PE requirement, using the wing-rock problem to conduct numerical experiments. The obtained results fully support the theoretical analysis and demonstrate the advantages of the proposed method.

METHODICAL EVALUATION OF HEALTHCARE INTELLIGENCE FOR HUMAN LIFE DISEASE DETECTION

Event intelligence for early diseases detection is highly demanded in current era and it requires reliable technology-oriented applications. Trusted emerging technologies play a vital role in modern healthcare systems for early diagnoses of different medical conditions because it helps to speed up the treatment process. Despite the enhancement of current healthcare systems, robust diagnosis of different type of diseases for intra-patients (outside of hospital settings) is still considered as a difficult task. However, the continuous evolution of trusted technologies in health sectors narrate the reboot process which could upgrades the healthcare service provision as the trusted next generation health units. In order to assist the healthcare providers to carry out early diseases’ detection for intra-patient clients, we designed this systematic review. We extracted 40 studies from the databases i.e. IEEE Xplore, Springer, Science direct and Scopus, from March 2016 and February 2021, and we formulated our research questions based on these studies. Subsequently, we rectified these studies using two filtration schemes namely, inclusion-omission policy and quality assessment, and as a result, we obtained 19 studies which successfully mapped our defined research questions .We found that these 19 studies clearly highlighted the different trusted architecture of internet of things, mobile cloud computing and machine learning, that are significantly beneficial to diagnose medical conditions for the intra-patient clients such as neurological diseases, cardiac malfunctions and other common diseases.

Ventilation Strategies for Highly Occupied Public Environments: A Review

In urban public transportation and highly diversified air environments, air pollutant exposure is becoming an increasing concern in terms of public health and personal safety. Herein, the scientific literature on air quality and virus transmission in densely crowded environments is reviewed to determine effective control methods. The research results are classified on the basis of different crowded environments. Much research has been conducted on pollutants in subways and buses. High particulate matter concentrations in public transportation are still a serious problem, but few studies on the spread of viruses exist. With existing types of ventilation systems, increasing local exhaust may be an efficient way to remove pollutants. Air quality sensors should be distributed in densely crowded spaces to achieve real-time display of pollutant concentration data. When pollution levels exceed the safe values, scientifically designed ventilation and filtration schemes should be implemented to reduce the pollution levels. Occupant activities are among the important factors that make pollutant transmission more complex. The analysis results herein contribute to the assessment of indoor pollutant concentrations and the protection of occupants from cross-infection.

Cleanroom air quality: combined effects of ventilation rate and filtration schemes in a laboratory cleanroom

ABSTRACT Ventilation performance and air quality in cleanrooms are affected by several interconnected parameters, and a change in one component can impact the entire system. Furthermore, occupant interactions with the physical environment can influence particle dispersion, disrupt current airflow by introducing new wakes and ultimately decrease ventilation efficacy. As a result, we set up an experimental study to measure the effects of traffic, flowrate and filtration on ventilation performance while a source of contamination was inside the room. Experiments included three types of occupant movements (i.e., NM, WO, WT) and were performed under two different airflow conditions. Three different metrics, namely relative ventilation efficiency (), decay rate (R) and exposure (γ), were introduced to statistically compare changes in ventilation performance in response to different experimental setups. Decay rates obtained for 0.3-micron particles decreased by up to 50% in the presence of occupants. Lowering cleanroom flowrate due to additional filtering can reduced ventilation effectiveness by almost 50%. Care should be exercised when changing filter efficiency because it can reduce the rate of air supply. These findings are especially intriguing in the context of cleanroom retrofit, as reducing air exchange rates was an unintended consequence of improving filter efficiency.

From drain to the garden: Household material utilization in hair dye wastewater filtration scheme

From drain to the garden: Household material utilization in hair dye wastewater filtration scheme

Complementary filter for determining the orientation of moving objects

The choice of the structure and parameters of the complementary filter for determining the orientation of moving objects in order to reduce its errors in the presence of gyroscope drift and significant linear accelerations is considered. For the analysis the complementary filter constructed according to the filtration scheme is accepted. First- and second-order filters are compared. For the second-order filter, two variants for constructing a filter are considered, depending on which disturbanceit is desirable to reduce in the first place.

Synthesis of the moving object positioning system

The choice of structure and parameters of the positioning system of a moving object based on a complementary filter using GPS-receiver and accelerometer is considered in order to reduce the effect of significant short-term interference of the GPS receiver when there is a zero offset accelerometer. For the analysis the complementary filter constructed according to the filtration scheme is accepted. Second- and third-order filters are compared. The high efficiency of the filter is shown. It is shown that by choosing a certain structure of a complementary third-order filter, it is possible to eliminate the steady-state component in the filter output signal.

Elevated manganese concentrations in groundwater wells after longtime abstraction with bank filtration: developing and testing of a sorption model for Ringerike waterworks, Norway

Groundwater abstraction wells located in aquifers hydraulically connected with rivers or lakes will induce bank filtration if the water level in the aquifer is lowered below the surface-water level. Many groundwater works utilize this induced infiltration to increase the abstraction capacity of their wells. Unfortunately, infiltration of organic-rich surface water may alter the aquifer’s redox geochemistry, and mobilize iron and/or manganese. Ringerike groundwater works in southeastern Norway operates with bank filtration. Manganese concentrations in the abstracted water began to increase 19 years after the start of operations, and stabilized at an elevated level 8 years later. The estimated manganese retardation (Rsorp = 45±18) from a simplified advection-sorption model is comparable to the observed manganese retardation range 36 < Robs < 50, assuming a groundwater residence time tgw ~200 days. The advection-sorption model is based on limited sediment composition and hydrochemical data, which introduces significant uncertainty to Rsorp. However, Rsorp and Robs in the same range, and the good fit between PHREEQC simulated and observed data, indicates that sorption is a possible explanation for the delayed breakthrough of elevated manganese concentrations in Ringerike waterworks’ production wells. Comparable bank filtration schemes are advised to establish observation well(s) between the bank filtration and production well field for early detection of sorption fronts. This would facilitate (1) longer time available for remediation measures and their evaluation, and (2) less manganese to be desorbed during the remediation stage.

Speech enhancement with noise estimation and filtration using deep learning models

Speech enhancement helps in eliminating the environmental noises from the communication signals. The main intention of the augmentation system is to develop the perceptual quality of communication or speech. For this purpose, various filtering schemes, spectral restoration models and speech models were implemented. In order to improve the odds of reducing noise and restoring the original signal, artificial intelligence (AI) and machine learning algorithms (MLA) were included into every sector. Deep transfer learning was used in this work to remove noise from the data and restore the original signals. This proposed approach includes a filtration scheme instead of using a convolution layer in the RESNET-50 architecture. The filters tested for speech enhanced deep learning models are modified Kalman filter and enhanced wiener filter. The performance metrics were calculated between various algorithms and proposed models to identify which approaches to follow the better way result obtained. The performance metrics compared PESQ, LSD and segSNR for different low signal to noise ratio conditions.

Interactions between H2O2 and dissolved organic matter during granular activated carbon-based residual H2O2 quenching from the upstream UV/H2O2 process

Granular activated carbon (GAC) filtration can be employed to synchronously quench residual H2O2 from the upstream UV/H2O2 process and further degrade dissolved organic matter (DOM). In this study, rapid small-scale column tests (RSSCTs) were performed to clarify the mechanisms underlying the interactions between H2O2 and DOM during the GAC-based H2O2 quenching process. It was observed that GAC can catalytically decompose H2O2, with a long-lasting high efficiency (>80% for approximately 50,000 empty-bed volumes). DOM inhibited GAC-based H2O2 quenching via a pore-blocking effect, especially at high concentrations (10 mg/L), with the adsorbed DOM molecules being oxidized by the continuously generated ·OH; this further deteriorated the H2O2 quenching efficiency. In batch experiments, H2O2 could enhance DOM adsorption by GAC; however, in RSSCTs, it deteriorated DOM removal. This observation could be attributed to the different ·OH exposure in these two systems. It was also observed that aging with H2O2 and DOM altered the morphology, specific surface area, pore volume, and the surface functional groups of GAC, owing to the oxidation effect of H2O2 and ·OH on the GAC surface as well as the effect of DOM. Additionally, the changes in the content of persistent free radicals in the GAC samples were insignificant following different aging processes. This work contributes to enhancing understanding regarding the UV/H2O2-GAC filtration scheme, and promoting the application in drinking water treatment.

Tracing sources and transformations of ammonium during river bank filtration by means of column experiments

Ammonium is an undesirable substance in the abstracted water of riverbank filtration (RBF) schemes, due mainly to the complications it causes during post-treatment (e. g. during chlorination). During RBF, ammonium can be formed in the riverbed by mineralization of organic nitrogen. Column experiments with riverbed sediments and river water from the Elbe were performed to evaluate the controls on ammonium concentrations during riverbed infiltration. Concentrations of ammonium went from <0.1 mgN/l in the feed water up to 1 mgN/l in the columns effluent. Higher temperatures and lower infiltration rates led to increased ammonium concentrations in the effluent. This shows higher susceptibility to ammonium increases of RBF settings in warmer climates and points to potential threats of climate change to water quality at RBF sites. In the later phases of the experiments, after the columns have been flushed their pore volumes several times, ammonium concentrations continually decreased. This behavior was attributed to the partial consumption of easily degradable organic material in the sediments, leading to lesser reducing conditions and lower mineralization rates. Based on operation with varied nitrate concentrations (0–11 mgN/l) and 15N isotopic measurements, dissimilatory nitrate reduction to ammonium (DNRA) was not shown to be relevant in the formation of ammonium. Anaerobic ammonium oxidation (anammox), however, was hypothesized to be an important sink of ammonium inside the columns, which indicates that rivers with high nitrate concentrations, such as the Elbe, may have a buffer of protection against ammonium formation during RBF.

Desalinated brackish water with improved mineral composition using monovalent-selective nanofiltration followed by reverse osmosis

Typical product water from desalination plants is depleted of salts and important minerals that are essential for its final consumption as well as its conveyance in the distribution system. In this study, we propose a hybrid nanofiltration (NF)-reverse osmosis (RO) filtration scheme that can produce desalinated brackish water with improved mineral composition. Here, the monovalent-divalent ion selectivity of NF membranes is used in a preliminary step to remove and “store” divalent minerals in the NF retentate stream, which are later dosed back to the mineral-free RO permeate to replenish the product water. We combine experimental data from pilot-scale NF with RO simulation to demonstrate the feasibility and economic viability of the proposed treatment scheme. In particular, we show the potential to operate the hybrid filtration scheme at high recovery ratios (>85%) and minimum saturation indices of potential scaling solids. A cost assessment further supports the applicability of the proposed treatment scheme, estimating the total capital and operating cost at $0.24/m3 product, which is on par with existing brackish-water desalination costs.

Detection and localization of multiple small damages in beam

Localizing small damages often requires sensors be mounted in the proximity of damage to obtain high Signal-to-Noise Ratio in system frequency response to input excitation. The proximity requirement limits the applicability of existing schemes for low-severity damage detection as an estimate of damage location may not be known a priori. In this work it is shown that spatial locality is not a fundamental impediment; multiple small damages can still be detected with high accuracy provided that the frequency range beyond the first five natural frequencies is utilized in the Frequency response functions (FRF) curvature method. The proposed method presented in this paper applies sensitivity analysis to systematically unearth frequency ranges capable of elevating damage index peak at correct damage locations. It is a baseline-free method that employs a smoothing polynomial to emulate reference curvatures for the undamaged structure. Numerical simulation of steel-beam shows that small multiple damages of severity as low as 5% can be reliably detected by including frequency range covering 5–10th natural frequencies. The efficacy of the scheme is also experimentally validated for the same beam. It is also found that a simple noise filtration scheme such as a Gaussian moving average filter can adequately remove false peaks from the damage index profile.

Importance of the Induced Recharge Term in Riverbank Filtration: Hydrodynamics, Hydrochemical, and Numerical Modelling Investigations

While ensuring adequate drinking water supply is increasingly being a worldwide challenging need, managed aquifer recharge (MAR) schemes may provide reliable solutions in order to guarantee safe and continuous supply of water. This is particularly true in riverbank filtration (RBF) schemes. Several studies aimed at addressing the treatment capabilities of such schemes, but induced aquifer recharge hydrodynamics from surface water bodies caused by pumping wells is seldom analysed and quantified. In this study, after presenting a detailed description of the Serchio River RBF site, we used a multidisciplinary approach entailing hydrodynamics, hydrochemical, and numerical modelling methods in order to evaluate the change in recharge from the Serchio river to the aquifer due to the building of the RBF infrastructures along the Serchio river (Lucca, Italy). In this way, we estimated the increase in aquifer recharge and the ratio of bank filtrate to ambient groundwater abstracted at such RBF scheme. Results highlight that in present conditions the main source of the RBF pumping wells is the Serchio River water and that the groundwater at the Sant’Alessio plain is mainly characterized by mixing between precipitation occurring in the higher part of the plain and the River water. Based on chemical mixing, a precautionary amount of abstracted Serchio River water is estimated to be on average 13.6 Mm3/year, which is 85% of the total amount of water abstracted in a year (~16 Mm3). RBF is a worldwide recognized MAR technique for supplying good quality and reliable amount of water. As in several cases and countries the induced recharge component is not duly acknowledged, the authors suggest including the term “induced” in the definition of this type of MAR technique (to become then IRBF). Thus, clear reference may be made to the fact that the bank filtration is not completely due to natural recharge, as in many cases of surface water/groundwater interactions, but it may be partly/almost all human-made.

Modeling and performance evaluation of underwater wireless optical communication system in the presence of different sized air bubbles

In this article, a statistical channel model is proposed to characterize the Underwater Wireless Optical Communication (UWOC) system in the presence of different air bubbles population considering freshwater scenario. The irradiance fluctuations of the received optical signal are characterized by Gaussian Mixture Model based upon the experimental data. The behavior of the UWOC channel is modeled in the form of an analytical expression. The goodness of fit test shows excellent fit of analytical expression with the experimental measured data under given channel conditions. In order to test the impact of channel characteristics of the practical application, an image is transmitted through UWOC channel in the presence of imperfections due to presence of bubbles. The performance is evaluated in terms of Structure Similarity Index attributed to image quality. A comparative performance analysis of different filtration schemes is also performed in order to improve the performance deterioration due to imperfect channel conditions. A significant improvement of UWOC system using median filter is observed under given channel conditions compared to other cases.