Performance analysis and modelling of circular jets aeration in an open channel using soft computing techniques.

Dissolved oxygen (DO) is an important parameter in assessing water quality. The reduction in DO concentration is the result of eutrophication, which degrades the quality of water. Aeration is the best way to enhance the DO concentration. In the current study, the aeration efficiency (E20) of various numbers of circular jets in an open channel was experimentally investigated for different channel angle of inclination (θ), discharge (Q), number of jets (Jn), Froude number (Fr), and hydraulic radius of each jet (HRJn). The statistical results show that jets from 8 to 64 significantly provide aeration in the open channel. The aeration efficiency and input parameters are modelled into a linear relationship. Additionally, utilizing WEKA software, three soft computing models for predicting aeration efficiency were created with Artificial Neural Network (ANN), M5P, and Random Forest (RF). Performance evaluation results and box plot have shown that ANN is the outperforming model with correlation coefficient (CC) = 0.9823, mean absolute error (MAE) = 0.0098, and root mean square error (RMSE) = 0.0123 during the testing stage. In order to assess the influence of different input factors on the E20 of jets, a sensitivity analysis was conducted using the most effective model, i.e., ANN. The sensitivity analysis results indicate that the angle of inclination is the most influential input variable in predicting E20, followed by discharge and the number of jets.

A review: Aeration efficiency of hydraulic structures in diffusing DO in water.

This paper contemplates the review of aeration efficiency with commonly used different aeration systems such as Venturi flumes, Weirs, Conduits, Stepped channels, In Venturi Aeration, the SAE value grows fast with the number of air holes. In Weir Aeration, it was found that among all the different labyrinth weir structure, triangular notch weirs are known for the optimum results for air entrainment. The ANN model was developed with parameters discharge (Q) and tail water depth (Tw) which showed that Q is more influential parameter than Tw. In conduits structure, it was found that circular high head gated conduits have better aeration performance than other conduits. Aeration efficiency in Stepped channels cascades may range from 30% to 70%. The sensitivity analysis with ANN model showed that discharge (Q) followed by number of steps (N) was the most influential parameter in E20. Bubble size was the important parameter to undertake when using bubble diffuser. The oxygen transfer efficiency (OTE) in jet diffusers was predicted developing an ANN model. It was found in sensitivity analysis that the input of 'velocity' is highly sensitive to OTE. According to literature, jets can provide OTE in the range of 1.91- 21.53kgO2/kW-hr.

Analytical Investigation of the Impact of Jet Geometry on Aeration Effectiveness Using Soft Computing Techniques.

Jet aeration is a commonly used technique for introducing air into water during wastewater treatment. In this investigation, the efficacy of different soft computing models, namely, Random Forest, Reduced Error Pruning Tree, Artificial Neural Network (ANN), Gaussian Process, and Support Vector Machine, was examined in predicting the aeration efficiency (E20) of circular and square jet configurations in an open channel flow. A total of 126 experimental data points were utilized to develop and validate these models. To assess the models' performance, three goodness-of-fit parameters were employed: correlation coefficient (CC), root-mean-square error (RMSE), and mean absolute error (MAE). The analysis revealed that all of the developed models exhibited predictive capabilities, with CC values surpassing 0.8. Nonetheless, when it comes to predicting E20, the ANN model outperformed other soft computing models, achieving a CC of 0.9748, MAE of 0.0164, and RMSE of 0.0211. A sensitivity analysis emphasized that the angle of inclination exerted the most significant influence on the aeration in an open channel. Furthermore, the results demonstrated that square jets delivered superior aeration compared to that of circular jets under identical operating conditions.

Decision Tree-Based Modeling of the Aeration Effectiveness of Circular Plunging Jets.

Since soft computing has gained a lot of attention in hydrological studies, this study focuses on predicting aeration efficiency (E20) using circular plunging jets employing soft computing techniques such as reduced error pruning tree (REPTree), random forest (RF), and M5P. The study undertaken required the development and validation of models, which were achieved using 63 experimental data values with input variables, such as angle of inclination of tilt channel (α), number of plunging jets (JN), discharge of each jet (Q), hydraulic radius of each jet (HR), and Froude number (Fr. No), to evaluate the aeration efficiency (E20), which served as the output variable. To evaluate the effectiveness of the developed models, three different statistical indices were used such as the coefficient of correlation (CC), root-mean-square error (RMSE), and mean absolute error (MAE), and it was found that all of the applied techniques possessed good forecasting ability since their correlation coefficient values were greater than 0.8. Upon testing, it was discovered that the M5P model outperformed other soft computing-based models in its ability to predict E20, as demonstrated by its correlation coefficient value of 0.9564 and notably low values of MAE (0.0143) and RMSE (0.0193).

Studies on olive-and silicone-oils-based Janus macroemulsions containing ginger to manage primary dysmenorrheal pain.

Ginger (GIN) powder-loaded oil-in-water (o/w) macroemulsions were prepared based on olive-and silicone-oils. The dispersed oil droplets with paired-beans structure were evident and thus the final emulsion can be termed as Janus macroemulsions. The objectives of the present study are (1) to identify the marker compound present in GIN powder via HPLC analysis, (2) to process the GIN powder via anti-solvent precipitation technique, (3) to see the solubility of GIN powder in various single oils or oil combination, (4) to optimize the GIN-loaded o/w macroemulsions using the central composite design (CCD) with respect to mean particle size of dispersed oil droplets and highest percentage drug entrapment efficiency values (DEE) and (5) to evaluate the pain reducing activity of optimized GIN-loaded macroemulsion via in vivo primary dysmenorrhea (PD) mice model. Both predicted and obtained values of percentage DEE (76.29 Vs.76.09) and mean particle size (245.99 Vs. 272.51 µm) were almost the same indicating the CCD statistical design applicability. The optimized Janus macroemulsion was stable at 4 °C for over a period of 90 days. Using the PD mice model, the counting of writhing reaction produced by the tested GIN-loaded macroemulsions at low and high doses did not reveal significant difference in comparison to the positive control (aspirin treated). Only the high dose of GIN-loaded macroemulsion was able to restore the uterine tissue's normal histomorphological structure after the H & E staining. Nevertheless, the paired beans structure should be tested for entrapping the plant-derived drugs having dissimilar physicochemical characteristics but similar therapeutic activity.