Application of dispersion and regression analysis to optimize the efficiency of the technological procedure of dechlorination of PCB-contaminated insulating oils
Abstract
Abstract. Modern experimental research theory includes plans for statistical multifactorial analysis. The advantage of this theory is that all factors are changed simultaneously so that a minimum number of experimental points distributed in the experimental hyperspace is obtained, which results in much lower costs and shorter time of experimental tests. The process of decontamination of polychlorinated biphenyls (PCB) from transformer oils is based on a dechlorination reaction using a reagent mixture (KPEG) consisting of potassium hydroxide (KOH) and polyethylene glycol (PEG), whereby the PCB molecule is chemically decomposed. Using 23 orthogonal plans, the influence of the mass percent of KPEG/oil, KOH/PEG molar ratio and temperature on the dechlorination reaction were investigated to optimize this process. The success of the reaction was evaluated by determining the efficiency of chemical degradation of PCBs (DRE) from transformer oil. The DRE values were from 81.81% to 99.81%. Using dispersion analysis, the significance and degree of interactivity of the examined factors on DRE were determined, and using regression analysis, a multi-linear regression model was set up.
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