Towards the Configuration of a Photoelectrocatalytic Reactor: Part 2-Selecting Photoreactor Flow Configuration and Operating Variables by a Numerical Approach.

This work aims to select a photoreactor flow configuration and operational conditions that maximize the Photocatalytic Space-time Yield in a photoelectrocatalytic reactor to degrade Reactive Red 239 textile dye. A numerical study by Computational Fluid Dynamics (CFD) was carried out to model the phenomena of momentum and species transport and surface reaction kinetics. The photoreactor flow configuration was selected between axial (AF) and tangential (TF) inlet and outlet flow, and it was found that the TF configuration generated a higher Space-time Yield (STY) than the AF geometry in both laminar and turbulent regimes due to the formation of a helical movement of the fluid, which generates velocity in the circumferential and axial directions.

Towards the Configuration of a Photoelectrocatalytic Reactor: Part 1-Determination of Photoelectrode Geometry and Optical Thickness by a Numerical Approach.

Photoelectrocatalysis has been highlighted as a tertiary wastewater treatment in the textile industry due to its high dye mineralisation capacity. However, design improvements are necessary to overcome photo-reactors limitations. The present work proposes a preliminary configuration of a photoelectrocatalytic reactor to degrade Reactive Red 239 (RR239) textile dye, using computational fluid dynamics (CFD) to analyse the mass transfer rate, radiation intensity loss (RIL), and its effect on kinetics degradation, over a photoelectrode based on a TiO2 nanotube.

Performance Analysis and Architecture of a Clustering Hybrid Algorithm Called FA+GA-DBSCAN Using Artificial Datasets.

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a widely used algorithm for exploratory clustering applications. Despite the DBSCAN algorithm being considered an unsupervised pattern recognition method, it has two parameters that must be tuned prior to the clustering process in order to reduce uncertainties, the minimum number of points in a clustering segmentation MinPts, and the radii around selected points from a specific dataset Eps. This article presents the performance of a clustering hybrid algorithm for automatically grouping datasets into a two-dimensional space using the well-known algorithm DBSCAN.