Optimal Conditions of Paint Wastewater Coagulation With Gastropod Shell Conchiolin Using Response Surface Design and Artificial Neural Network-Genetic Algorithm

The potential of gastropod shell conchiolin (GSC) (a waste product of the deprotenization stage of chitosan production) as one of the alternatives to chemical coagulants has been explored for treatment of paint industrial wastewater (PW). The accuracy of response surface design (RSD) and the precision of artificial intelligence (AI) in predicting and optimizing the process conditions were harnessed in raising experimental design matrix and response optimization, respectively for the bench scale jar test coagulation experiment. PW was characterized using American public health association (APHA) standard methods. Extraction of conchiolin was done via alkaline extraction method. PW contains 2098mg/l total suspended solid (TSS) above discharge limit (1905mg/l). Fourier transform infrared (FTIR) spectrum of GSC revealed a broad N–H wagging band at 750 – 650 cm−1 indicating the presence of secondary amine linked to the presence of protein. Turbidity removal from PW via one factor at a time (OFAT) was found to be a function of pH, GSC dosage, temperature and time. Artificial neural network (ANN) response prediction shows 92% correlation with the response surface design (RSD) experimental result. The optimal conditions obtained via genetic algorithm (GA) for the response optimization at the best pH of 4 indicate optimal turbidity removal of 98% at GSC dosage, time and temperature of 4 g, 20 min and 45oC, respectively.

Design Space by Design of Experiments

The quality of methods and products are usually influenced by several input factors. Research has recently focused on understanding the effects of multidimensional and interconnected input factors on the results of pharmaceutical products and analytical methods using Design of Experiment (DoE). Furthermore, it examines how DOE may be implemented, both for students and teachers, as well as highlighting historical perspectives on DOE. A good experimental design can help you make the most use of the available resources and make the analysis of the results easier. Collaborations between researchers and practitioners that are pushing the boundaries of experimental design are examined. It provides an overview of the principles and applications of the most common screening and response surface design, as well as creating mixtures designs.

Influence Analysis of the Controllable Factors on the Objective Functions for Optimizing the Welding of PE 100 Pipelines for Natural Gas Distribution

The paper presents a series of experimental researches performed using the design of experiments method RSD (Response Surface Design) for modeling and optimizing the welding process of PE 100 pipelines, used in natural gas distribution. In this sense, the aim was to analyze the influence of controllable factors such as pressure, temperature and time on the objective functions, aiming to obtain certain characteristics of the welded joint. By modeling the welding process, based on the results obtained, an optimal welding procedure was established and validated to meet the conditions imposed on the objective functions.

Optimization of Sodium Lignosulfonate Treatment on Nylon Fabric Using Box–Behnken Response Surface Design for UV Protection

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