Showing papers by "Messias Borges Silva published in 2007"
TL;DR: In this article, a neural model of the acid brown 75, acid orange 52, acid Orange 10 and Direct Red 28 dyes decoloration process was obtained. And the neural model was evaluated in function of the absorbance reading in each dye maximum absorbance wavelength.
Abstract: The purpose of this work is to obtain a neural model of the Acid Brown 75, Acid Orange 52, Acid Orange 10 and Direct Red 28 dyes decoloration process. Dyes aqueous solutions were individually treated in plug-flow reactor, with ultraviolet radiation and hydrogen peroxide. The decoloration process was evaluated in function of the absorbance reading in each dye maximum absorbance wavelength. The input variables corresponding to the input neurons of the neural feedforward backpropagation model used in the work were comprised by structural parameters characteristic of each dye (number of azo bonds and sulphonate groups) and also by process operational variables (temperature, initial pH, hydrogen peroxide volume, reactor operation time and dyes concentration). The combination of structural and operational parameters provided a hybrid character in relation to the input variable nature. The correlation coefficients (approximately 0.96 for the data total, validation and test sets) showed the good model prediction capacity. The neural model obtained also provided, via Garson Partition Method, the determination of the influence of the decoloration process input variables.
12 citations
TL;DR: In this paper, the authors proposed the use of neural networks in the prediction of residual concentrations of hydrogen peroxide from the treatment of effluents through Advanced Oxidative Processes (AOPs), in particular, the photo-Fenton process.
Abstract: This communication proposes the use of neural networks in the prediction of residual concentrations of hydrogen peroxide from the treatment of effluents through Advanced Oxidative Processes (AOP’s), in particular, the photo-Fenton process. To verify the efficiency of the oxidative process, the Chemical Oxygen Demand (COD) parameter, the values of which may be modified by the presence of oxidizing agents such as residual hydrogen peroxide, is frequently taken in account. The analysis of the H2O2 interference was performed by spectrophotometry at 450 nm wavelength, via the monitoring of the reaction of ammonia with metavanadate. The results of the hydrogen peroxide residual concentration were modeled via a feedforward neural network, with the correlation coefficients between actual and predictedvaluesabove0.96,indicatinggoodpredictioncapacity.
5 citations
TL;DR: In this paper, a two level experiment design matrix was defined and the experiments have been conducted and the most important variables have been identified based on these variables a model to see the occurrence of the defect was proposed.
Abstract: Associated to the foundry process to produce steel castings parts, there are a lot of defects which can be related separately to a process stage, casting design, raw material and other molding material, steel, pouring, solidification, heat treatment and cleaning, or related to some process stages that together can cause a specific defect. Among the main defects identified in a casting, it can be listed the scab or expansion scab. Searching for a solution in order to identify the actual causes of occurrence of the defect, the use of an Experiment Design was proposed. The main variables in the process that could be influencing the occurrence of the defect were defined. Subsequently, a two level experiment design matrix was defined and the experiments have been conducted. After the experiments have been made the most important variables have been identified. Based on these variables a model to see the occurrence of the defect was proposed. The application of the model has shown to be effective in solving the problem.
2 citations