Experimental investigation on a combination of soil electrokinetic consolidation and remediation of drained water using composite nanofiber-based electrodes.

A novel electrokinetic geosynthetic (EKG) can be efficient in achieving multiple objectives. In this study, a new EKG as an electrode and a drainage channel in the electro-osmotic consolidation was fabricated by electrospun nanofibers containing graphene nanoparticles (GNs) attached to a carbon fiber substrate. To investigate the effectiveness of the fabricated electrodes in electro-osmotic consolidation and remediation of water drained from the system, an experimental apparatus was constructed while considering loading capability in expanded ranges and applying the electric field, and was filled with copper (Cu)-contaminated kaolinite. Experiments were divided into control (CT) and EKG groups, and three categories, C-EK, ES1-EK, and ES2-EK (using carbon fiber, electrospun nanofibers containing 1 wt% GNs, and electrospun nanofibers consisting of 2 wt% GNs, respectively). All the experiments were conducted with the same conditions, loading, drainage condition, and duration. However, EKG experiments were performed by employing the electric field under the vertical pressure in the range of 7-113 kPa, while the CT was conducted without the electric field. According to experimental results, 18 wt% polymethyl methacrylate in the dimethylformamide solvent containing 1 and 2 wt% GNs was selected for making a nanofibrous layer on the carbon fiber. The average diameters of the fibers were 404 ± 36 and 690 ± 62 nm and yielded at 1 and 2 wt% GNs, respectively. The results revealed that using the EKG accelerated kaolinite consolidation. The average degree of consolidation was 68 and 85% in the CT and EKG experiments, respectively. Furthermore, the fabricated electrodes were highly effective as a drainage channel for remediating water drained from the system. Moreover, the highest Cu removal efficiency was obtained in ES2-EK (97%) and ES1-EK (92%), respectively. Conversely, the lowest Cu removal efficiency was observed in the C-EK group (85%).

Insights into enhanced electrokinetic remediation of copper-contaminated soil using a novel conductive membrane based on nanoparticles.

Electrokinetic remediation is a process in which a direct electric current is applied across a section of contaminated soil to remove metals. To improve the electrokinetic remediation in this study, a conductive membrane was fabricated via in situ chemical polymerization employing pyrrole and copper oxide nanoparticles. The fabricated membrane was placed in an electric field as part of the electrode structure. A physical model was constructed and filled with copper-contaminated kaolinite in the concentration of 200 mg/kg. To control the pH, 0.1 M citric acid and 0.01 M potassium chloride were used as the electrolyte solutions. Experimental parameters such as voltage, current, pH, EC, drained flow, and copper concentration were measured. The results showed that the minimum surface resistivity of the fabricated membrane under a maximum pressure of 8.2 kPa was 2.55 kΩ/m2. The experimental results demonstrated that the use of citric acid as an electrolyte was more useful to desorb the copper due to the formation of the copper-citrate complex. When employing the fabricated membrane, the copper removal increased from 13% (in CT-2) to 63% (in GM-2), while the removal of copper using potassium chloride electrolyte increased from 42% (in CT-1) to 52% (in GM-1). The highest power consumption was obtained in experiments using citric acid. Due to the higher removal efficiency of copper in GM-2, the energy utilization efficiency (ß) increased and reached 29.9 near ß value of GM-1 with the lowest power consumption.

An alternative approach to control saltwater intrusion in coastal aquifers using a freshwater surface recharge canal.

Aquifers are a major source of freshwater in many parts of the world. Saltwater intrusion from the sea or saline lakes into freshwater aquifers degrades the potable quality of these resources. Various methods have been introduced to mitigate saltwater intrusion, such as recharge wells and physical subsurface barriers. This paper presents an alternative approach to control saltwater intrusion in coastal aquifers using a surface water recharge canal. In this paper, the effectiveness of a recharge canal at mitigating saltwater intrusion is evaluated numerically using SEAWAT. The results indicate that the recharge canal leads to a reduction in the extent of the saltwater intrusion. Under a fixed hydraulic gradient, the extent of this reduction is dependent on the location of the recharge canal relative to the saltwater source. As the hydraulic gradient increases, with the optimum location of the recharge canal approaches the saltwater source location. The results also indicate that more effective saltwater repulsion is achieved when the recharge canal is located near the toe of the saltwater wedge. The results of a field scale case study indicate that a recharge canal with relatively small dimensions could have a significant effect on reduction in the extent of the saltwater intrusion.

Evaluating the potential of artificial neural network and neuro-fuzzy techniques for estimating antioxidant activity and anthocyanin content of sweet cherry during ripening by using image processing.

BACKGROUND: This paper presents a versatile way for estimating antioxidant activity and anthocyanin content at different ripening stages of sweet cherry by combining image processing and two artificial intelligence (AI) techniques. In comparison with common time-consuming laboratory methods for determining these important attributes, this new way is economical and much faster. The accuracy of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models was studied to estimate the outputs. Sensitivity analysis and principal component analysis were used with ANN and ANFIS respectively to specify the most effective attributes on outputs. RESULTS: Among the designed ANNs, two hidden layer networks with 11-14-9-1 and 11-6-20-1 architectures had the highest correlation coefficients and lowest error values for modeling antioxidant activity (R = 0.93) and anthocyanin content (R = 0.98) respectively. ANFIS models with triangular and two-term Gaussian membership functions gave the best results for antioxidant activity (R = 0.87) and anthocyanin content (R = 0.90) respectively. CONCLUSION: Comparison of the models showed that ANN outperformed ANFIS for this case. By considering the advantages of the applied system and the accuracy obtained in somewhat similar studies, it can be concluded that both techniques presented here have good potential to be used as estimators of proposed attributes.