Search

Dissolved oxygen (DO) concentration in water is one of the most important water quality parameters in rivers, lakes, and reservoirs. The most effective way to increase DO concentration in water is aeration. Conduits with high aeration performance are predicted to significantly increase aeration efficiency. Based on this prediction, the physical parameters affecting the aeration efficiency (E20) of the conduit aeration system were experimentally investigated. The effect of different jet plunge angles, flow rates, hydrostatic levels, Froude numbers, and gate opening rates was investigated to optimize the system for the best ventilation efficiency. As a result, the aeration efficiency (E20) improves with increasing air intake performance at low gate openings, high Froude numbers, and hydrostatic levels. The increase in jet plunge angles and hydrostatic level directly increases the aeration efficiency. The study showed that conduit systems can be an important alternative for pond aeration due to initial investment and operating costs, low energy cost, and high aeration efficiency. [ABSTRACT FROM AUTHOR]

The study assesses the optimal aeration efficiency of a stepwise cascade aeration system through experimental trials in a lab scale model setup, aimed at determining the geometric and flow characteristics of the cascade system. Subsequently, the collected datasets are employed to evaluate the efficacy of four advanced machine learning algorithms, namely K-nearest neighbour (KNN), gradient boosting regressor (GBR), decision tree regressor (DTR), and random forest regressor (RFR), in predicting the aeration efficiency at 20 °C (E20) of the cascade aeration system. The predictive machine learning tools are compared based on different performance indices and various graphical interpretations including comparative plot, heat plot, plot of relative error, violin diagram, and Taylor diagram. For assessing the accuracy of the best-fitted predictive model, i.e. GBR, a field-scale surface-water–based water treatment plant with a multi-stage filtration unit, which was set up in an arsenic-affected rural area of West Bengal, India, was used to validate the results, and findings were used to optimize the field-scale plant. It is observed that E20 is dependent on dimensionless discharge (dc/h), squares of the number of the steps (N2), and inclination (h/l) as per dimension analysis. The analysis reveals that with an increase in inclination, E20 for a specific number of cascade steps drops to a certain point and then increases. The highest aeration efficiency (E20) of 0.913 is observed at a hydraulic loading rate of 0.167 l/m2/s, N = 10 and h/l = 0.64. Furthermore, the results demonstrate that the GBR model (with R2 test value of 0.96 and MAE test value of 0.027) emerges as the most accurate regression tool, surpassing the other models in predicting E20 values. Additionally, the findings indicated that at the flow rates of 0.075, 0.1, 0.125, and 0.15 m3/m2/h with the inclination of 0.363 and N = 10, the dissolved oxygen in water increases by more than 5 mg/l, with corresponding aeration efficiencies (E20) of 0.757, 0.675, and 0.602, respectively. Machine learning models offer the potential to optimize the design of aeration structures for accurate prediction and facilitating cost efficiency. [ABSTRACT FROM AUTHOR]

There is a growing interest in high-performance, sustainable, and efficient aeration technologies to ensure the necessary oxygen levels in ponds, wastewater treatment plants, and aquaculture areas. Multiple optimization efforts are mandatory to maximize the aeration performance and energy efficiency of high-aeration performance systems simultaneously. This study aims to optimize the aeration performance of aquaculture systems using the Taguchi-based gray relational analysis (GRA) method. Taguchi-based gray relational analysis method has been preferred due to its capability of enabling optimization with fewer experiments, analyzing interactions among independent variables, and its applicability in both linear and nonlinear systems. The use of the Taguchi-based GRA method to improve efficiency in the aeration process is a novel approach for these systems with multiple variables. In this study, the optimal parameter levels for the conduit aeration system were determined and compared with the initial levels through validation tests. Additionally, the effects of parameters on aeration performance and energy cost were analyzed. As a result, it was determined that the aeration performance of the system increased fourfold compared to the initial level, and the cost decreased sixfold. It was observed that the most effective parameter on the system is the gate opening, and the least effective parameter is the tank diameter. [ABSTRACT FROM AUTHOR]

This paper explores the ability of multivariate adaptive regression splines, decision trees, Gaussian processes, and multiple non-linear regression equation approaches to predict the aeration efficiency at various weirs and discusses their results. In total, 126 experimental observations were collected in the laboratory, of which 88 were arbitrarily selected for model training, and the rest were used for model validation. Various graphical presentations and goodness-of-fit parameters were used to assess the performance of the models. Performance evaluation results, Whisker plot, and Taylor's diagram indicated that the GP_rbf-based model was superior to other implemented models in predicting the aeration efficiency of weirs with CC (0.9961 and 0.9973), MAE (0.0079 and 0.0195), RMSE (0.0122 and 0.0251), scattering index (0.0594 and 0.1238), and Nash Sutcliffe model efficiency (0.9923 and 0.9564) values in the training and validating stages, respectively. The predicted values by GP_rbf lie within the ±30% error line in the training and validating stages, with most of it lying at/close to the line of agreement. The random forest model had better predictability than other decision tree models implied. The sensitivity analysis of parameters suggests shape factor and drop height as major influencing factors in predicting the aeration efficiency. HIGHLIGHTS Experimental study to evaluate aeration efficiency at various shapes of sharp-crested weir models.; Application of machine learning techniques to predict aeration efficiency of sharp-crested weirs.; Introduction of shape factor for different shapes of weirs as an input to ML models.; Use of graphs and goodness-of-fit parameters to assess the performance of applied ML models.; Sensitivity analysis.;

The biological treatment process (BTP) is responsible for removing chemical oxygen demand (COD) and ammonia using microorganisms present in wastewater. The BTP consumes large quantities of energy due to the transfer of oxygen using air pumps/blowers. Energy consumption in the BTP is due to low solubility of oxygen, which results in low aeration efficiency (AE). The aim of the study was to develop an AE model that can be used to monitor the performance of the BTP. Multilayer perceptron artificial neural network (MLP ANN) algorithm was used to model AE in the BTP. The performance of the AE model was evaluated using R2, mean square error (MSE), and root mean square error (RMSE). Sensitivity analysis was performed on the AE model to determine variables that drive AE. The results of the study showed that MLP ANN algorithm was able to model AE. R2, MSE, and RMSE results were 0.939, 0.0025, and 0.05, respectively, during testing phase. Sensitivity analysis results showed that temperature (34.6%), COD (21%), airflow rate (19.1%), and OTR/KLa (15.7%) drive AE. At high temperatures, the viscosity of wastewater is low which enables oxygen to penetrate the wastewater, resulting in high AE. The AE model can be used to predict the performance of the BTP, which will assist in minimizing energy consumption. HIGHLIGHTS Aeration efficiency increases with an increase in temperature.; Aeration efficiency decreases with an increase in airflow rate.; Temperature and airflow rate are the biggest driver of energy consumption.; Temperature, COD, and airflow rate control aeration efficiency in the biological treatment process.; High temperatures and airflow rates improve volumetric mass transfer coefficient.;

The influence of aeration diffuser system design on electricity usage, effluent water quality, and life-cycle cost in biological wastewater treatment was investigated. A plant-wide model was implemented, and simulations were carried out with different process configurations and aeration systems. Model-aided design of new aeration diffuser systems could significantly decrease electricity usage and life-cycle cost while at the same time avoiding negative effects on the treatment performance. The optimum distribution of diffuser systems in tanks in series was found to be influenced by process configuration, volumetric loading rate, temperature, and the internal recirculation flow rate. Compared with a conventional design approach, increasing the number of diffusers, up to a critical point, led to higher energy efficiency and lower life-cycle cost. This was despite an increasing limitation of the minimum airflow rate, leading to dissolved oxygen levels significantly exceeding control targets. Aeration systems optimized by simulations were found to, independently of process configuration, exhibit 20% lower electricity usage and 16%–18% lower life-cycle costs compared with systems designed based on a more conventional approach typically applied in practice. [ABSTRACT FROM AUTHOR]

Due to its simplicity and accurately measuring the flow rate, the venturi system is a special kind of pipe that is widely used in various applied fluid mixtures. One of the venturi system's important applications is ejectors devices that accurately facilitate adding air to water to sustain oxygen demand target levels in many waterworks engineering systems. This study aims to improve venturi system measurement accuracy through experimental investigation and analytical analysis for the venturi system conditional configuration parameters effect on target aeration operational efficiency. In the experiment work, different runs are implemented to characterize the performance of such aerators by describing the impact of venturi characteristics and configurations, including water flow rate, air inlets orifices diameters, inlet velocities, throat lengths, inlet angles, outlets angles, and outlet diameters on aeration efficiency. Results show that the venturi air vent diameter is an important governing parameter for determining aeration performance value. Additionally, an indicated increase in aeration performance with an increasing throat length to its diameter ratio. Meanwhile, the results revealed a varying noted effect of the venturi system characteristics and configurations on aeration performance. Moreover, the equations that relate venturi system configuration and Reynolds numbers with the aeration operational performance are developed to facilitate the target accurate aeration efficiency estimation. Novelty: In this research work, analytical and experimental studies related to venturi system configuration have been implemented as well as its aeration operational performance. The overall conclusion of this study is that the aeration performance (η) is inversely proportional with Reynold's number. While it is directly related to outlet angle (θ). ‐To facilitate developing the target aeration operational performance equations, experiments results are grouped according to guidance ratios (Lt/d2 and dA/d2) and outlet angle (θ)of the tested venturi system. By applying the results of venturi system aeration performance equations, the injection of the dissolved oxygen into various waterworks can be accurately estimated for each particular situation. [ABSTRACT FROM AUTHOR]

The dissolved oxygen content in surface waters is one of the vital indicators for human water quality usage as well as the aquatic plant and animal environmental life sustainability. Parshall flumes are one of the important ejector devices that are successfully used for oxygen requirement satisfying in various irrigation, wastewater, and ecosystems. However, the present study aimed to manage and improve various waterworks aeration efficiency through integrated modeling of experimental and analytical analysis as well as their operation conditional parameters for the Parshall flumes configuration. On the basis of the experiment work data sets run results, the principal component regression (PCR), partial least squares (PLS), and ridge regression (RR) techniques are used to develop the required aeration efficiency prediction models for such aerators by interrelating the impact of Parshall flumes characteristics and configurations, as well as various water flow rates on aeration efficiency. The predictive models developed in the study were statistically compared to the experimental data. The comparison confirms a good reliability and high accuracy. Considering the proposed aeration models, the optimum design of the new Parshall flumes can be successfully facilitated. [ABSTRACT FROM AUTHOR]

• Optimal aeration placement within a 4-meter range improves efficiency and enhances water quality. • Addressing dissolved oxygen stratification with gentle water agitation promotes species well-being. • Seasonal ARIMA forecast integration enables informed decisions for energy optimization in aquaculture. Aquaculture relies significantly on effective aeration systems to ensure optimal conditions for aquatic organisms. This 96-day study investigates the dynamic relationship between Oxygen Transfer Rates (OTR) and seasonal variations, with a specific focus on the impact of seasonal dynamics and the placement of paddle wheel aerators. The study recognizes the pivotal role of Total Dissolved Solids (TDS) and Total Suspended Solids (TSS) as key water quality parameters influencing aeration efficiency. A series of water circulation experiments were conducted at regular intervals to assess mixing rates, revealing a nuanced trajectory ranging from 27.05 to 14.22 m³/kWh. The study scrutinized the influence of TDS and TSS on these rates. Additionally, water velocity variations, ranging from 0.45 to 1.67 m/s, were examined, highlighting density-dependent changes, particularly evident post four weeks of operation. Oxygen stratification analysis provided insights into deviations in Dissolved Oxygen (DO) concentrations, with particular attention to climatic aberrations. Rigorous statistical analyses, including chi-squared, Pearson correlation, Gaussian distribution checks, and student's t -tests, validated the methodological robustness and data reliability. Employing a Seasonal Auto Regressive Integrated Moving Average (SARIMA) model, the study achieved a remarkable 97 % accuracy in forecasting DO levels for the subsequent 96 days. Real-time validation, complemented by a Chi-square goodness of fit test, reaffirmed the model's reliability, establishing congruence between observed and forecasted values. This research underscores the critical roles of strategic aerator placement and seasonal considerations in optimizing pond aeration efficiency, providing substantive insights for the sustainable management of aquaculture ecosystems. [Display omitted] [ABSTRACT FROM AUTHOR]

Aeration is the process of increasing the dissolved oxygen (DO) content of water, which is an important water quality parameter for the survival of aquatic life. In this process, large amounts of air bubbles develop; as a result, contact surface area increases, and hence the water-air-mass transfer accelerates. There are numerous methods for increasing DO concentration in water, including self-aeration, mechanical aeration, chemical aeration, and hydraulic structures. The hydraulic structures are an economical and efficient way of enhancing stream/river water aeration. Even though the water only comes into contact with the structure for a short while, it increases the amount of DO in a river system. In this study, an experimental investigation has been carried out to determine the aeration performance of different types of piano key weir (PKW). To this end, three different types (type-A, type-B, and type-C) of PKW laboratory-scaled models were tested. The results demonstrated that the type-A PKW created maximum oxygen transfer efficiency of the three PKW types. In addition, the results show that the aeration efficiency of all PKW models increases with drop height but decreases with increasing discharge over the weirs. HIGHLIGHTS This study is based on a comparative analysis of aeration performances of different types of piano key weir, which has not yet been published elsewhere.; Studying and comparing the aeration capacity of the different types of piano key weirs.; Studying the effects of drop height on aeration performance of piano key weirs.;

The dissolved oxygen (DO) level in water is vital for water quality and supporting aquatic life. Hydraulic jumps involve rapid flow changes from super-critical to sub-critical, visible at abrupt bed slope shifts, like at spillway bases in rivers or canals. The hydraulic jump efficiently mixes oxygen from air into water and offers a cost-effective method of aeration by entraining air bubbles in the stream to improve oxygen transfer compared to traditional systems. The objective of this experimental research is to investigate the aeration performance with hydraulic jump parameters and establish correlations crucial to measuring aeration (or transfer) efficiency. Relationships between transfer efficiency, jump height, jump length, sequent depth ratio, discharge, inlet Froude number, and channel bed slope were determined. To investigate the nature of such relationships, a series of experiments were conducted in a rectangular tilt flume to test the aeration performance of forced submerged hydraulic jumps with five different discharges and five different smooth bed slopes. The inlet Froude number before the jump varied from 2.18 to 8.23. Experimental observation confirms a positive relationship between transfer efficiency and jump control parameters. During experimentation, transfer efficiency was found to vary between 9.4 % and 34 %. This research includes estimating the optimal transfer efficiency due to hydraulic jumps, which can help hydraulic engineers in building structures that can revitalize any degraded stream. • Analyze aeration efficiency (E) in hydraulic jump (HJ) with smooth bed slope and discharge. • Identify governing parameters using dimensional analysis to correlate E and HJ. • Achieved maximum of 89% velocity drop and 90.23% energy dissipation at 35 lps and 6° slope for optimal E improvement. • E increased from 9.4 to 34 % with increasing discharge (15–35 lps) and bed slope (0–6°). • Results can help to build structures to maintain healthy oxygen levels in water. [ABSTRACT FROM AUTHOR]

The scope of the paper is to analyse the different similarities of air entrainment among the hydraulic jumps, plunging jets, and plunging breaking waves and to discuss current practices. The measured data are reexamined and scrutinised to investigate the gas exchange phenomena through an air-water interface. In particular, oxygen transfer efficiency and penetration depth by air bubbles are discussed. The calculated results highlight that the oxygen transfer efficiency is decreased with the increase of energy dissipation rate both in plunging jets and breaking waves. In contrast, it is shifted almost parallel in the case of hydraulic jumps. In addition, the aeration lengths in the hydraulic jumps and penetration depths both in plunging jets and plunging breaking waves were dependent on the jet impact velocity. HIGHLIGHTS Air bubble entrainments through hydraulic jumps, plunging jets, and plunging breaking waves are studied.; Aeration lengths in the hydraulic jump and penetration depths in the plunging jets and plunging breaking waves were determined.; Dissolved oxygen, as well as oxygen transfer efficiency, were measured and compared among the phenomena.; Scale effects were observed among the phenomena in terms of the oxygenation.;

The improvement of wastewater treatment plants is an environmental and economic priority. The highest energy consumption in wastewater treatment plants relates to aeration units with the current technologies. Microorganisms can use air micro-nanobubbles (AMNBs) for biological activity due to AMNB’s high oxygen transfer rate, high stability in the aeration reactor, and increased contact surface. This study investigated the effect of aeration with AMNB on hydraulic retention time (HRT), energy consumption, chemical oxygen demand (COD), and nitrogen removal efficiency in the biological treatment of raw municipal wastewater without pretreatment for an extended time during cold and hot seasons. Suspended growth treatment and attached growth mode were studied by installing an active bio-curtain (ABC) as an improvement solution. In the presence of AMNB and ABC, effective micro-organisms significantly increased ten times as conventional activated sludges (CAS). Micro-nanobubble aeration helped the oxygen transfer and accelerated the aerobic layer formation, which took advantage of partial nitrification and denitrification for total nitrogen removal and resulted in total nitrogen removal by 99%. In comparison, 78% and 97% of COD removal in suspended and attached growth modes were achieved in the warm seasons at the optimum HRT of 9 h. In the cold seasons, with a decrease of about 5%, the COD removal yields 73% and 90% in the identical HRT (9 h), respectively. The aeration energy consumption in this study to eliminate the definite ratio of organic loads shows a reduction of about 40% compared to CAS. Excess sludge reduction has also been achieved by up to 70%. In conclusion, this research shows the potential and possibility of practical exploitation of the AMNB aeration and ABC to treat municipal wastewater. [ABSTRACT FROM AUTHOR]

Soft computing (SC) methods have increasingly been used to solve complex hydraulic engineering problems, especially those characterized by high uncertainty. SC approaches have previously proved to be an accurate tool for predicting the aeration efficiency coefficient (E20) in hydraulic structures such as weirs and flumes. In this study, the performance of the standalone support vector regression (SVR) algorithm and three of its hybrid versions, support vector regression–firefly algorithm (SVR-FA), support vector regression–grasshopper optimization algorithm (SVR-GOA), and support vector regression–artificial bee colony (SVR-ABC), is assessed for the prediction of E20 in stepped cascades. Mutual information theory is used to construct input variable combinations for prediction, including the parameters unit discharge (q), the total number of steps (N), step height (h), chute overall length (L), and chute inclination (α ). Entropy indicators, such as maximum likelihood, Jeffrey, Laplace, Schurmann–Grassberger, and minimax, are computed to quantify the epistemic uncertainty associated with the models. Four indices—correlation coefficient (R), Nash–Sutcliffe efficiency (NSE), root mean square error (RMSE), and mean absolute error (MAE)—are employed for evaluating the models' prediction performance. The models' outputs reveal that the SVR-FA model (with R = 0.947 , NSE = 0.888 , RMSE = 0.048 and MAE = 0.027 in testing phase) has the best performance among all the models considered. The input variable combination, including q, N, h, and L, provides the best predictions with the SVR, SVR-FA, and SVR-GOA models. From the uncertainty analysis, the SVR-FA model shows the closest entropy values to the observed ones (3.630 vs. 3.628 for the "classic" entropy method and 3.647 vs. 3.643 on average for the Bayesian entropy method). This study proves that SC algorithms can be highly accurate in simulating aeration efficiency in stepped cascades and provide a valid alternative to the traditional empirical equation. [ABSTRACT FROM AUTHOR]

The spray of water over a basin using a perforated disk accelerates oxygen transfer. The laboratory model, employed in the current work, consists of a vertical riser that discharges water by free fall into a basin. Four fall heights of water of 2.4, 1.8, 1.2, and 0.6 m were investigated to evaluate the performance of this system. This system was also tested at flow rates of 46.8, 93.7, 140.6, and 187.5 mL/s. This study showed that the oxygen mass transfer coefficient was directly proportional to both the fall height and flow rate of water. The maximum standard aeration efficiency (SAE) value was recorded at the maximum fall height of 2.4 m and flow rate of 187.5 mL/s, at which a maximum KLa20 = 1.82 h–1 was recorded. The multilinear regression-based model developed in this study successfully predicted mass transfer coefficient (KLa20) and standard aeration efficiency (SAE values that agree well with actual measurements under given conditions, with a scattering within ±5%. The optimum flow rate and fall height that achieve the minimum operating cost were obtained at certain KLa20 values. The cost of aeration of 1 m3 of water was calculated, ranging from 0.0076 to 0.008 USD/m3. [ABSTRACT FROM AUTHOR]

In this study, the potential of soft computing techniques, namely Random Forest (RF), M5P, Multivariate Adaptive Regression Splines (MARS), and Group Method of Data Handling (GMDH), was evaluated to predict the aeration efficiency (AE20) of Parshall and Modified Venturi flumes. Experiments were conducted for 26 various Modified Venturi flumes and one Parshall flume. A total of 99 observations were obtained from experiments. The results of soft computing models were compared with regression-based models i.e., with multiple linear regression (MLR) and multiple nonlinear regression (MNLR). Results of the analysis revealed that the MARS model outperformed other soft computing and regression-based models for predicting AE20 of Parshall and Modified Venturi flumes with Pearson's correlation coefficient (CC) = 0.9997, and 0.9992, and root mean square error (RMSE) = 0.0015, and 0.0045 during calibration and validation periods, respectively. Sensitivity analysis was also carried out by using the best executing MARS model to assess the effect of individual input variables on AE20 of both flumes. Obtained results on sensitivity examination indicate that the oxygen deficit ratio (r) was the most effective input variable in predicting the AE20 of Parshall and Modified Venturi flumes. HIGHLIGHTS Aeration efficiency of Parshall and Modified Venturi flumes was predicted by using soft computing techniques.; M5P, RF, MARS, and GMDH models were first employed to predict the aeration efficiency.; Outcomes of soft computing models were first compared against regression-based models.; Effectiveness of applied models was evaluated using performance evaluation indicators.; The MARS-based model outperformed other models.;

This work presents an experimental evaluation of a Venturi and Venturi-Vortex microbubble aeration system, taking as input variables the water-air flow ratio, water renewal time and area-volume ratio of the water tank. The aeration process response variables are defined in terms of oxygen transfer and aeration efficiency through the standard volumetric mass transfer coefficient (KLa20), standard oxygen transfer rate (SOTR), and standard aeration efficiency (SAE). Two methods of air injection were analyzed: 1. Air injection in the throat chamber of the Venturi generator; 2. air supplying in the suction side of the hydraulic pump of the aeration system. Experimental results indicate that the water renewal time variable (RT) is a statistically significant factor with respect to the KLa20, which can be maximized by decreasing RT. The effects of the variable flow ratio (FR) are greater than the effects of renewal time and area-volume ratio (AVR) concerning SOTR and SAE, indicating a maximum response with a minimum flow ratio, using the Venturi-Vortex microbubble generator. When the flow ratio decreases, the air flow increases, generating and transferring a greater amount of microbubbles (MB) into the water. It was found that increasing the air flow produced an increase in the standard oxygen transfer rate SOTR and standard aeration efficiency SAE. Results allow concluding that the injection of the air flow from the suction side of the pump promotes the generation of microbubbles (MB) for a maximum air flow allowed by the system. SOTR and SAE could be maximized whit the flow ratio factor and the Venturi-Vortex generator, supplying air flow from the suction side of the hydraulic pump.

For maintaining healthy streams and rivers, a high concentration of oxygen is desired and hydraulic structures act as natural aerators where oxygen transfer occurs by creating turbulence in the water. Aeration studies of conventional weirs are carried out widely in the past but at the same time, labyrinth weirs, where the weir crest is cranked thereby enhancing their crest length, have got a little notice. The test records were obtained through 180 laboratory observations on nine physical models to estimate aeration efficiency (E20) at labyrinth weirs (LWs). The E20 increases with the number of key as well as drop height and it is found to be highest for rectangular shape in comparison of the triangular and trapezoidal LWs, however, E20 decreases with the increase of discharge. Further, this work unravels the novel idea and potential of the M5P model tree (M5P), support vector regression machine (SVM), and Random Forest (RF) methods for estimation of aeration efficiency (E20) at LWs. The results depicted that the RF model performs best in determining the E20 at LWs. The results of sensitivity analysis further illustrated that drop height is the parameter that affects the prediction of E20 at the LWs most.

This study compares several advanced machine learning models to obtain the most accurate method for predicting the aeration efficiency (E20) through the Parshall flume. The required dataset is obtained from the laboratory tests using different flumes fabricated in National Institute Technology Kurukshetra, India. Besides, the potential of K Nearest Neighbor (KNN), Random Forest Regression (RFR), and Decision Tree Regression (DTR) models are evaluated to predict the aeration efficiency. In this way, several input combinations (e.g. M1-M15) are provided using the laboratory parameters (e.g. W/L, S/L, Fr, and Re). Different predictive models are obtained based on those input combinations and machine learning models proposed in the present study. The predictive models are assessed based on several performance metrics and visual indicators. Results show that the KNN-M11 model ( $ RMS{E_{testing}} = 0.002, R_{testing}^2 = 0.929 $ ), which includes W/L, S/L, and Fr as predictive variables outperforms the other predictive models. Furthermore, an enhancement is observed in KNN model estimation accuracy compared to the previously developed empirical models. In general, the predictive model dominated in the present study provides adequate performance in predicting the aeration efficiency in the Parshall flume.

A Parshall flume is a versatile device due to its diverse applications in irrigation canals, mine discharge, dam seepage, sewage treatment plants and many more. It is an economical due to its construction and installation and an accurate in discharge measurement in open channel and non-full pipe. Exchange of oxygen between water and air is termed as aeration. In the study, advance soft computing models; Multivariate Adaptive Regression Splines (MARS) and Generalized Structure- Group Method of Data Handling (GS-GMDH) have used to predict aeration efficiency (E20) values at Parshall flumes and its modified forms and also compared with existing conventional models. The performance of the models was assessed using four evaluating metrics; coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE) and Nash Sutcliffe model efficacy. Agreement plot of GS-GMDH and MARS models showed that the MARS model has the maximum exactness in predicting E20 values at Parshall flumes and its modified forms with the lowest RMSE = 0.0020, MAE = 0.0015. MARS model with input combination of ratio of throat width to throat length (W/L), ratio of sill height to throat length (S/L) and Froude number is performing better than that of all other input combinations used for models and found to be more suitable for predicting the E20. Overall comparison among conventional and advance soft computing models suggests that advance soft computing models perform better than conventional models. [ABSTRACT FROM AUTHOR]

The growing intensive aquaculture system around the world maintains a high stocking density, wherein it is essential to increase and sustain the optimum dissolved oxygen concentration (DO) through the provision of artificial aeration systems. The selection of an aerator is a crucial aspect of aquaculture operations. The selected aerator must be economically efficient and should be able to fulfill the requirement of oxygen supply in the pond water. The present study provides an extensive literature review on the importance of artificial aeration in aquaculture, the standard method of test for performance evaluation of an aerator, various aeration systems and their mechanisms, method to determine the numbers of aerator requirement, comparative studies of different type of aerators, and economic consideration in selection of aerators. In addition, a thorough analysis has been done to suggest the type of aerator that is economically viable and efficient for different pond volumes based on the performance data reported in the reviews. Therefore, this study may help the end-users (fish farmers) to select the best aerator based on their requirements. [ABSTRACT FROM AUTHOR]

This work is an experimental study on the oxygen transfer capability and efficiency in a pilot‐scale decelerated oxidation ditch equipped with fine bubble diffusers and impellers (inducing horizontal liquid flows). Aqueous solutions of carboxymethyl cellulose (CMC) exhibiting shear‐thinning rheological properties are selected to simulate activated sludge in the oxidation ditch process. The effect of air flow rate and horizontal liquid velocity along the loop channel on oxygen transfer capability and aeration efficiency is examined in tap water and CMC aqueous solutions. The standard volumetric mass transfer coefficient KLa20, standard oxygen transfer efficiency (SOTE), and standard aeration efficiency (SAE) are introduced to study the oxygen mass transfer performance and energy consumption efficiency in the oxidation ditch. The results show that KLa20, SOTE, and SAE in CMC aqueous solutions follow similar trends observed in tap water. Due to the effect of shear‐thinning rheological properties, KLa20, SOTE, and SAE in CMC aqueous solutions are smaller than those in tap water. Two dimensionless numbers, Froude number and Ohnesorge number are introduced to study the oxygen transfer efficiency through the consideration of the combined influence of aeration, crossflow, gas bubble size, and physical properties of the liquid phase. [ABSTRACT FROM AUTHOR]

A newly developed bio‐reactor design for municipal sewage treatment was evaluated on a pilot scale (150 m3/d). The reactor system included both anaerobic/anoxic and aerobic treatment stages with external/internal airlift circulation loops integrated with a central sedimentation chamber. The design was conceived to enhance the removal of organic compounds and nutrients (phosphorus and nitrogen) within a smaller footprint than existing treatment processes. The downcomer of the internal circulation loop is integrated with the sedimentation tank facilitating high efficiency solid‐liquid separation in a compact configuration. The external/internal airlift circulation stages increase the potential for bio‐reactivity, while reducing energy consumption for process flows. Overall, the integrated configuration reduces the footprint required compared to conventional systems with equivalent hydraulic loads, ie, hydraulic retention time of ~12.8 hours with a hydraulic loading area of 10.3 m3/d/m2. The trial run data indicated removal efficiencies for COD, phosphorous, ammonia, and total nitrogen of 94.5%, 94.5%, 96.8%, and 78.6% respectively. Moreover, the treatment system also demonstrated a robust capacity to handle a wide range of COD influent concentrations (ie, ~ 120‐860 mg/L). [ABSTRACT FROM AUTHOR]

• Optimal aeration placement within a 4-meter range improves efficiency and enhances water quality. • Addressing dissolved oxygen stratification with gentle water agitation promotes species well-being. • Seasonal ARIMA forecast integration enables informed decisions for energy optimization in aquaculture. Aquaculture relies significantly on effective aeration systems to ensure optimal conditions for aquatic organisms. This 96-day study investigates the dynamic relationship between Oxygen Transfer Rates (OTR) and seasonal variations, with a specific focus on the impact of seasonal dynamics and the placement of paddle wheel aerators. The study recognizes the pivotal role of Total Dissolved Solids (TDS) and Total Suspended Solids (TSS) as key water quality parameters influencing aeration efficiency. A series of water circulation experiments were conducted at regular intervals to assess mixing rates, revealing a nuanced trajectory ranging from 27.05 to 14.22 m³/kWh. The study scrutinized the influence of TDS and TSS on these rates. Additionally, water velocity variations, ranging from 0.45 to 1.67 m/s, were examined, highlighting density-dependent changes, particularly evident post four weeks of operation. Oxygen stratification analysis provided insights into deviations in Dissolved Oxygen (DO) concentrations, with particular attention to climatic aberrations. Rigorous statistical analyses, including chi-squared, Pearson correlation, Gaussian distribution checks, and student's t -tests, validated the methodological robustness and data reliability. Employing a Seasonal Auto Regressive Integrated Moving Average (SARIMA) model, the study achieved a remarkable 97 % accuracy in forecasting DO levels for the subsequent 96 days. Real-time validation, complemented by a Chi-square goodness of fit test, reaffirmed the model's reliability, establishing congruence between observed and forecasted values. This research underscores the critical roles of strategic aerator placement and seasonal considerations in optimizing pond aeration efficiency, providing substantive insights for the sustainable management of aquaculture ecosystems. [Display omitted] [ABSTRACT FROM AUTHOR]

We studied new micro-perforated diffuser concepts for the aeration process in wastewater treatment plants and evaluated their aeration efficiency. These are micro-perforated plate diffusers with orifice diameters of 30 µm, 50 µm and 70 µm and a micro-perforated tube diffuser with an orifice diameter of 50 µm. The oxygen transfer of the diffuser concepts is tested in clean water, and it is compared with commercial aerators from the literature. The micro-perforated tube diffuser and micro-perforated plate diffusers outperform the commercial membrane diffusers by up to 44% and 20%, respectively, with regard to the oxygen transfer efficiency. The most relevant reason for the improved oxygen transfer is the fine bubble aeration with bubble sizes as small as 1.8 mm. Furthermore, the more homogenous cross-sectional bubble distribution of the micro-perforated tube diffuser has a beneficial effect on the gas mass transfer due to less bubble coalescence. However, the pressure drop of micro-perforated diffusers seems to be the limiting factor for their standard aeration efficiencies due to the size and the number of orifices. Nevertheless, this study shows the potential for better aeration efficiency through the studied conceptual micro-perforated diffusers.

This paper presents a comparative experimental study of different configurations of mechanical surface aerators used in wastewater treatment plants. A laboratory scale tank equipped with different configurations for aeration process was installed to compare the standard aeration efficiency and power consumption of curved blade impellers with 3, 6, 9, and 12 blades. Different parameters thought to have significant effects on standard aeration efficiency (SAE) and power consumption, such as submergence depth and rotating speed were studied. Results show that an optimum configuration (9 blades) has the highest aeration efficiency (2.60 Kg. O 2 /KW.hr) at 500 rpm. Also, a submersion depth ratio of 0.35 was optimum, giving the highest standard aeration efficiency, as increasing submergence depth ratio above this value causes drop in standard aeration efficiency as a result of inevitable increase in input power consumption in this case. [ABSTRACT FROM AUTHOR]

The efficiency of active aeration (AE) of constructed wetlands expressed as the ratio between implied oxygen consumption and oxygen delivered to the system is comprehensively reviewed in this paper. The aeration efficiency appears to be rather low with a mean value of 1.73% and median value of 0.48% of oxygen used in the systems for situations with only partial aerobic degradation of the pollutants. For full aerobic degradation, the mean value of AE is 3.74% but median value is much lower 1.08%. For both cases, the standard deviation is higher than the mean value (4.95% and 10.87% respectively), so there is a lot of variability in the data. For systems with the Forced Bed Aeration the results are more uniform and are close to the literature values given for this system, which is an implication that the proposed methodology might be potentially used for rough estimate of the aeration efficiency. [ABSTRACT FROM AUTHOR]

In the last years, the upgrading of wastewater treatment plants (WWTPs) could be required in order to comply with the more stringent regulation requirements. Nevertheless, the main issue is related to the surface availability. A proper solution could be represented by the attached biomass processes, in particular the moving bed biofilm reactors (MBBR), that have a significant footprint reduction with respect to conventional activated sludge (CAS). However, MBBR showed an important disadvantage: the poor aeration energy efficiency due to the use of coarse bubble diffusers, which guarantee high reliability and low maintenance costs with respect to fine bubble ones. Moreover, the presence of carriers inside the reactor emphasizes this aspect. The aim of this work is to verify the benefits achievable by installing a fine bubble aeration system inside a MBBR system. The comparison, in terms of oxygen transfer efficiency, between a medium bubble aeration system and a fine ceramic bubble diffuser was studied and the effect of biofilm growth on oxygen transfer was assessed. Several tests were carried out in order to test the operation of a coarse and a fine bubble side aeration at different air flow rates, both in clean water conditions, in order to evaluate the influence of carriers (Chip M type) on the aeration efficiency, both in wastewater conditions with the aim to assess the effect of bacteria growth on the carriers. The main results are the following: (i) the fine bubble system placed off-center ensured good mixing even without using the mixer; (ii) the fine bubble side aeration system compared to the coarse ones did not show significant advantages in terms of oxygen transfer efficiency; (iii) the increase in specific air flow rate negatively influenced the aeration efficiency; (iv) the presence of biomass had a positive effect on the oxygen transfer yield. [ABSTRACT FROM AUTHOR]

Abstract Stepped weir is a commonly used hydraulic structure in water treatment plants to enhance the air-water transfer of oxygen or nitrogen and volatile organic components. The flow regimes on stepped weir are classified into nappe, transition and skimming flow. This study presents the novel application of artificial intelligence methods to evaluate the aeration efficiency over stepped weir for the three flow regimes. Two methods were adopted in this study, namely, the evolutionary polynomial regression (EPR) and the M5 model tree (M5 MT). A total of 151 laboratory experimental data sets were collected from the literature to train and test the artificial intelligence models. The Mallow's coefficient C P was used to determine the effective variables affecting aeration efficiency. It was found that weir steps number, slope, the flow Reynolds number, and the ratio of the critical flow depth to the step height are the most important variables providing the lowest C p. Both the EPR and M5 MT methods provided satisfactory predictions for the aeration efficiency. The two methods have high values of correlation coefficient R > 0.93 and low values for the root mean square error RMSE< 0.052 and relative mean absolute error RMAE< 0.065. However, the EPR method has an advantage over the M5 MT method that it provides one equation for each regime, while the M5 MT method provides a number of equations for each regime. This will make the equations of the EPR method more attractive to the practitioners compared to the equations of the M5 MT method. It was found that the equations obtained from artificial intelligence methods in this study perform better than the currently existing equations in the litrature obtained from regressive methods. Highlights • A new empirical equation for the prediction of the aeration efficiency of stepped weir is developed. • Experimental data covering a broad range of hydraulic conditions are collected. • Sensitivity of the developed models for various predictors is quantified. [ABSTRACT FROM AUTHOR]

This study investigated the impact of five different carrier media on oxygen transfer efficiency and flow mixing in a 2 m 3 moving attached growth system pilot-plant. The five media studied varied in shape (cylindrical and spherical), size, voidage and protected surface area (112–610 m 2 /m 3 ). In clean water tests, the media enhanced the overall oxygen transfer efficiency by 23–45% and hydraulic efficiency (HE) by 41–53%, compared with operation with no media. When using spherical media (Media 1, 2 and 3), the presence of biofilm increased the HE to 89, 93 and 100%, respectively. Conversely, Media 4 and 5 with biofilm contributed to a reduction in HE to 74 and 63%, respectively. The media protected surface area, the parameter traditionally selected to design biofilm processes, did not correlate with HE or with oxygen transfer efficiency in clean water tests. This study provides clear evidence that other media physical properties play a role in the mixing and oxygen transfer in moving attached growth systems. A correlation (R 2 ) of 0.89 and 0.90 was obtained between the media dimensionality times voidage (Di × Voi) and HE, with and without biofilm development, respectively. The combination of parameters (Di × Voi/HE) also correlated well with oxygen transfer efficiency in clean water (R 2 of 0.92 without biofilm and R 2 of 0.88 with biofilm). Dimensionality and voidage should be utilised to design and optimise media size and shape, to enhance mixing and oxygen transfer, ultimately contributing to energy savings and higher removal efficiencies. [ABSTRACT FROM AUTHOR]

The performance of a pilot-scale superoxygenation system was evaluated in clean water and mixed liquor. A mass balance was applied over the pilot-scale system to determine the overall oxygen mass transfer rate coefficient (K L a, h −1 ), the standard oxygen transfer rate (SOTR, kg O 2 d −1 ), and the standard oxygen transfer efficiency (SOTE, %). Additionally, the alpha factor (α) was determined at a mixed liquor suspend solids (MLSS) concentration of approximately 5 g L −1 . SOTEs of nearly 100% were obtained in clean water and mixed liquor. The results showed that at higher oxygen flowrates, higher transfer rates could be achieved; this however, at expenses of the transfer efficiency. As expected, lower transfer efficiencies were observed in mixed liquor compared to clean water. Alpha factors varied between 0.6 and 1.0. However, values of approximately 1.0 can be obtained in all cases by fine tuning the oxygen flowrate delivered to the system. [ABSTRACT FROM AUTHOR]

Up to now, tremendous efforts have been devoted to modelling the oxygen transfer coefficient (kLa) for diffused aeration systems, while not considering the corresponding energy consumption. Enhancing kLa is favorable for an exemplary oxygenation process, but may come at the cost of greater energy withdrawal, an unwelcome tradeoff. Assessing the aeration efficiency (the rate of oxygen delivered per unit energy) reflects the overall effectiveness of an aeration process and guarantees a superior system performance. Presented here is a lab-scale study that investigates the effect of the orifice diameter, the airflow rate and the water column on the aeration efficiency. Various combinations of the studied parameters were tested using a cylindrical tank with a single orifice for air injection. An optimal performance of the aeration efficiency was observed at an orifice diameter of 0.3 mm when tested under 0.91 m water column and an airflow rate of 0.05 SLPM. Furthermore, a new empirical formula of aeration efficiency was established with a high correlation index ( R2 = 0.97) to allow preliminary prediction of aeration efficiency. [ABSTRACT FROM AUTHOR]

The paper deals with the evaluation of the effect of on/off switching of diffuser membranes, in the intermittent aeration process of the urban wastewater treatments. Accelerated tests were done using two types of commercial EPDM diffusers, which were submitted to several consecutive cycles up to the simulation of more than 8 years of real working conditions. The effect of this switching on the mechanical characteristics of the membranes was evaluated in terms of pressure increment of the air operating at different flow rates (2, 3.5 and 6 m 3 /h/diff): during accelerated tests, such increment ranged from 2% to 18%. The intermittent phases emphasized the loss both of the original mechanical proprieties of the diffusers and of the initial pore shapes. The main cause of pressure increment was attributed to the fouling of the internal channels of the pores. Further analyses performed by scanning electron microscopy and by mechanical tests on EPDM membrane, using a traditional tensile test and a non destructive optical method, from which the Young's Modulus was obtained, supported previous conclusions. Any changes in terms of oxygen transfer parameters (KLa and SOTE%) were specifically founded by causing to the repeated on/off switching. [ABSTRACT FROM AUTHOR]

The present study investigates the accuracy of five different data-driven techniques in estimating oxygen transfer efficiency in baffled chutes: feedforward neural network (FFNN), radial basis neural network (RBNN), generalized regression neural network (GRNN), adaptive neuro fuzzy inference system with subtractive clustering (ANFIS-SC), and adaptive neuro fuzzy inference system with fuzzy c-means clustering (ANFIS-FCM). Baffled apron chutes or drops are used on channel structures to dissipate the energy in the flow. A baffled chute design is effective both in energy dissipation and in aerating the flow and reducing nitrogen supersaturation. There is a close relationship between energy dissipation and oxygen transfer efficiency. This study aims to determine the aeration efficiency of baffled chutes with stepped (S), wedge (W), trapezoidal (T), and T-shaped (T-S) baffle blocks. The performances of the FFNN, RBNN, GRNN, ANFIS-SC, and ANFISFCM models are compared with those of multilinear and nonlinear regression models. Based on the comparisons, it was observed that all data-driven models could be successfully employed in modeling the aeration efficiency of S, W, and T-S baffle blocks from the available experimental data. Among data-driven models, the FFNN model was found to be the best. [ABSTRACT FROM AUTHOR]

This research systematically studied the behavior of aeration diffuser efficiency over time, and its relation to the energy usage per diffuser. Twelve diffusers were selected for a one year fouling study. Comprehensive aeration efficiency projections were carried out in two WRRFs with different influent rates, and the influence of operating conditions on aeration diffusers' performance was demonstrated. This study showed that the initial energy use, during the first year of operation, of those aeration diffusers located in high rate systems (with solids retention time - SRT-less than 2 days) increased more than 20% in comparison to the conventional systems (2 > SRT). Diffusers operating for three years in conventional systems presented the same fouling characteristics as those deployed in high rate processes for less than 15 months. A new procedure was developed to accurately project energy consumption on aeration diffusers; including the impacts of operation conditions, such SRT and organic loading rate, on specific aeration diffusers materials (i.e. silicone, polyurethane, EPDM, ceramic). Furthermore, it considers the microbial colonization dynamics, which successfully correlated with the increase of energy consumption (r 2 :0.82 ± 7). The presented energy model projected the energy costs and the potential savings for the diffusers after three years in operation in different operating conditions. Whereas the most efficient diffusers provided potential costs spanning from 4900 USD/Month for a small plant (20 MGD, or 74,500 m 3 /d) up to 24,500 USD/Month for a large plant (100 MGD, or 375,000 m 3 /d), other diffusers presenting less efficiency provided spans from 18,000USD/Month for a small plant to 90,000 USD/Month for large plants. The aim of this methodology is to help utilities gain more insight into process mechanisms and design better energy efficiency strategies at existing facilities to reduce energy consumption. [ABSTRACT FROM AUTHOR]

The efficiency of aeration systems should be monitored to guarantee suitable biological processes. Among the available tools for evaluating the aeration efficiency, the off-gas method is one of the most useful. Increasing interest towards reducing greenhouse gas (GHG) emissions from biological processes has resulted in researchers using this method to quantify N2O and CO2concentrations in the off-gas. Experimental measurements of direct GHG emissions from aerobic digesters (AeDs) are not available in literature yet. In this study, the floating hood technique was used for the first time to monitor AeDs. The floating hood technique was used to evaluate oxygen transfer rates in an activated sludge (AS) tank of a medium-sized municipal wastewater treatment plant located in Italy. Very low values of oxygen transfer efficiency were found, confirming that small-to-medium-sized plants are often scarcely monitored and wrongly managed. Average CO2and N2O emissions from the AS tank were 0.14 kgCO2/kgbCODand 0.007 kgCO2,eq/kgbCOD, respectively. For an AeD, 3 × 10−10 kgCO2/kgbCODdirect CO2emissions were measured, while CO2,eqemissions from N2O were 4 × 10−9 kgCO2,eq/kgbCOD. The results for the AS tank and the AeD were used to estimate the net carbon and energy footprint of the entire plant. [ABSTRACT FROM AUTHOR]