Application of dielectric barrier discharge(DBD) plasma packed with glass and ceramic pellets for SO_2 removal at ambient temperature: optimization and modeling using response surface methodology

Air pollution is a major health problem in developing countries and has adverse effects on human health and the environment. Non-thermal plasma is an effective air pollution treatment technology. In this research, the performance of a dielectric barrier discharge(DBD) plasma reactor packed with glass and ceramic pellets was evaluated in the removal of SO_2 as a major air pollutant from air in ambient temperature. The response surface methodology was used to evaluate the effect of three key parameters(concentration of gas, gas flow rate, and voltage) as well as their simultaneous effects and interactions on the SO2 removal process. Reduced cubic models were derived to predict the SO_2 removal efficiency(RE) and energy yield(EY). Analysis of variance results showed that the packed-bed reactors(PBRs) studied were more energy efficient and had a high SO2 RE which was at least four times more than that of the non-packed reactor. Moreover, the results showed that the performance of ceramic pellets was better than that of glass pellets in PBRs. This may be due to the porous surface of ceramic pellets which allows the formation of microdischarges in the fine cavities of a porous surface when placed in a plasma discharge zone. The maximum SO_2 RE and EY were obtained at 94% and 0.81 g kWh^(-1),respectively under the optimal conditions of a concentration of gas of 750 ppm, a gas flow rate of 2lmin^(-1), and a voltage of 18 kV, which were achieved by the DBD plasma packed with ceramic pellets. Finally, the results of the model's predictions and the experiments showed good agreement.

Improving the Sound Absorption Properties of Flexible Polyurethane (PU) Foam using Nanofibers and Nanoparticles

Polyurethane foam as the most well-known absorbent materials has a suitable absorption coefficient only within a limited frequency range.The aim of this study was to improve the sound absorption coefficient of flexible polyurethane(PU)foam within the range of various frequencies using clay nanoparticles,polyacrylonitrile nanofibers,and polyvinylidene fluoride nanofibers.The response surface method was used to determine the effect of addition of nanofibers of PAN and PVDF,addition of clay nanoparticles,absorbent thickness,and air gap on the sound absorption coefficient of flexible polyurethane foam(PU)across different frequency ranges.The absorption coefficient of the samples was measured using Impedance Tubes device.Nano clay at low thicknesses as well as polyacrylonitrile nanofibers and polyvinyl fluoride nanofibers at higher thicknesses had a greater positive effect on absorption coefficient.The mean sound absorption coefficient in the composite with the highest absorption coefficient at middle and high frequencies was 0.798 and 0.75,respectively.In comparison with pure polyurethane foam with the same thickness and air gap,these values were 2.22 times at the middle frequencies and 1.47 times at high frequencies,respectively.Surface porosity rose with increasing nano clay,but decreased with increasing polyacrylonitrile nanofibers and polyvinyl fluoride nanofibers.The results indicated that the absorption coefficient was elevated with increasing the thickness and air gap.This study suggests that the use of a combination of nanoparticles and nanofibers can enhance the acoustic properties of flexible polyurethane foam.

Improving the Cellular Characteristics of Aluminum Foam for Maximum Sound Absorption Coefficient Using Genetic Algorithm

Fabricating of metal foams with desired morphological parameters including pore size,porosity and pore opening is possible now using sintering technology.Thus,if it is possible to determine the morphology of metal foam to absorb sound at a given frequency,and then fabricate it through sintering,it is expected to have optimized metal foams for the best sound absorption.Theoretical sound absorption models such as Lu model describe the relationship between morphological parameters and the sound absorption coefficient.In this study,the Lu model was used to optimize the morphological parameters of aluminum metal foam for the best sound absorption coefficient.For this purpose,the Lu model was numerically solved using written codes in MATLAB software.After validating the proposed codes with benchmark data,the genetic algorithm(GA)was applied to optimize the affecting morphological parameters on the sound absorption coefficient.The optimization was carried out for the thicknesses of 5 mm to 40 mm at the sound frequency range of 250 Hz–8000 Hz.The optimized parameters ranged from 50%to 95%for porosity,0.1 mm to 4.5 mm for pore size,and 0.07 mm to 0.6 mm for pore opening size.The result of this study was applied to fabricate the desired aluminum metal foams for the best sound absorption.The novel approach applied in this study,is expected to be successfully applied in for best sound absorption in desired frequencies.