Investigating the efficiency of electrocoagulation using similar/dissimilar electrodes for the detoxification of Coralene Rubine dye: a cost effective approach.

Efficient treatment of textile dyeing wastewater can be achieved through electrocoagulation (EC) with minimal sludge production; however, the selection of the appropriate electrode is essential in lowering overall costs. Also, the reuse of the treated aqueous azo dye solution from this process has not been explored in detail. With these objectives, this study aims to treat synthetic azo dye solutions and achieve high colour removal efficiency (CRE%) using similar (Ti-Ti) and dissimilar (Ti-Cu) metal electrodes through EC with an attempt to reduce the cost.

Electrocoagulation using Ti/Ti for the remediation and reuse of aqueous Dispersive Blue-79.

The entire ecology is contaminated by the synthetic dyes that are widely utilised in the textile industries. They can be handled using a variety of technologies, but an eco-friendly method called electrocoagulation has been used to prevent additional contamination. Textile wastewater containing disperse dyes are successfully treated in Electrocoagulation (EC) utilizing Al, Fe, and Stainless Steel (SS), but it is not cost effective, also the treated water contains certain mg/L of the metals used, along with dye components, which obstructs the reuse of the same.

Electrochemical treatment of textile wastewater using copper electrodes.

The conventional electrode aluminum used in electrocoagulation (EC) for the textile wastewater undergoes pitting type of corrosion, so dissolution of the same is very high during electrolysis. This research focuses on the treatment of real-time textile effluent with copper electrodes that corrode uniformly during electrolysis, with optimizing operating parameters for high color removal efficiency (CRE%). The sludge acquired was analyzed by XPS and XRD to study the mechanism of dye removal.

Simulation of anaerobic digestion processes using stochastic algorithm.

Background: The Anaerobic Digestion (AD) processes involve numerous complex biological and chemical reactions occurring simultaneously. Appropriate and efficient models are to be developed for simulation of anaerobic digestion systems. Although several models have been developed, mostly they suffer from lack of knowledge on constants, complexity and weak generalization.

ANN application for prediction of atmospheric nitrogen deposition to aquatic ecosystems.

The occurrences of increased atmospheric nitrogen deposition (ADN) in Southeast Asia during smoke haze episodes have undesired consequences on receiving aquatic ecosystems. A successful prediction of episodic ADN will allow a quantitative understanding of its possible impacts. In this study, an artificial neural network (ANN) model is used to estimate atmospheric deposition of total nitrogen (TN) and organic nitrogen (ON) concentrations to coastal aquatic ecosystems.

Simulation of ammonium and chromium transport in porous media using coupling scheme of a numerical algorithm and a stochastic algorithm.

The migration of the species of chromium and ammonium in groundwater and their effective remediation depend on the various hydro-geological characteristics of the system. The computational modeling of the reactive transport problems is one of the most preferred tools for field engineers in groundwater studies to make decision in pollution abatement. The analytical models are less modular in nature with low computational demand where the modification is difficult during the formulation of different reactive systems.

A probabilistic cellular automaton for two dimensional contaminant transport simulation in ground water.

In recent years evolutionary computing algorithms have been proposed to solve many engineering problems. Genetic algorithms, Neural Networks, and Cellular Automata are the branches of evolutionary computing techniques. In this study, it is proposed to simulate the contaminant transport in porous media using a Cellular Automaton.