The conversion of plastic waste into fuel by pyrolysis has been recognized as a potential strategy for commercialization. The amount of plastic waste is basically different for each country which normally refers to non-recycled plastics data; consequently, the production target will also be different. This study attempted to build a model to predict fuel production from different non-recycled plastics data. The predictive model was developed via Levenberg-Marquardt approach in feed-forward neural networks model. The optimal number of hidden neurons was selected based on the lowest total of the mean square error. The proposed model was evaluated using the statistical analysis and graphical presentation for its accuracy and reliability. The results showed that the model was capable to predict product yields from pyrolysis of non-recycled plastics with high accuracy and the output values were strongly correlated with the values in literature.
In recent years, there has been considerable interest in the use of natural fibers as potential reinforcing fillers in polymer composites despite their hydrophilicity, which limits their widespread commercial application. The present study explored the fabrication of nanocomposites by melt mixing, using an internal mixer followed by a compression molding technique, and incorporating rice husk (RH) as a renewable natural filler, montmorillonite (MMT) nanoclay as water-resistant reinforcing nanoparticles, and polypropylene-grafted maleic anhydride (PP-g-MAH) as a compatibilizing agent. To correlate the effect of MMT delamination and MMT/RH dispersion in the composites, the mechanical and thermal properties of the composites were studied. XRD analysis revealed delamination of MMT platelets due to an increase in their interlayer spacing, and SEM micrographs indicated improved dispersion of the filler(s) from the use of compatibilizers. The mechanical properties were improved by the incorporation of MMT into the PP/RH system and the reinforcing effect was remarkable as a result of the use of compatibilizing agent. Prolonged water exposure of the prepared samples decreased their tensile and flexural properties. Interestingly, the maximum decrease was observed for PP/RH composites and the minimum was for MMT-reinforced and PP-g-MAH-compatibilized PP/RH composites. DSC results revealed an increase in crystallinity with the addition of filler(s), while the melting and crystallization temperatures remained unaltered. TGA revealed that MMT addition and its delamination in the composite systems improved the thermal stability of the developed nanocomposites. Overall, we conclude that MMT nanoclay is an effective water-resistant reinforcing nanoparticle that enhances the durability, mechanical properties, and thermal stability of composites.
Three-phase induction motors (TIMs) are widely used for machines in industrial operations. As an accurate and robust controller, fuzzy logic controller (FLC) is crucial in designing TIMs control systems. The performance of FLC highly depends on the membership function (MF) variables, which are evaluated by heuristic approaches, leading to a high processing time. To address these issues, optimisation algorithms for TIMs have received increasing interest among researchers and industrialists. Here, we present an advanced and efficient quantum-inspired lightning search algorithm (QLSA) to avoid exhaustive conventional heuristic procedures when obtaining MFs. The accuracy of the QLSA based FLC (QLSAF) speed control is superior to other controllers in terms of transient response, damping capability and minimisation of statistical errors under diverse speeds and loads. The performance of the proposed QLSAF speed controller is validated through experiments. Test results under different conditions show consistent speed responses and stator currents with the simulation results.
Integrated fixed-film activated sludge (IFAS) process is considered as one of the leading-edge processes that provides a sustainable solution for wastewater treatment. IFAS was introduced as an advancement of the moving bed biofilm reactor by integrating the attached and the suspended growth systems. IFAS offers advantages over the conventional activated sludge process such as reduced footprint, enhanced nutrient removal, complete nitrification, longer solids retention time and better removal of anthropogenic composites. IFAS has been recognized as an attractive option as stated from the results of many pilot and full scales studies. Generally, IFAS achieves >90% removals for combined chemical oxygen demand and ammonia, improves sludge settling properties and enhances operational stability. Recently developed IFAS reactors incorporate frameworks for either methane production, energy generation through algae, or microbial fuel cells. This review details the recent development in IFAS with the focus on the pilot and full-scale applications. The microbial community analyses of IFAS biofilm and floc are underlined along with the special emphasis on organics and nitrogen removals, as well as the future research perspectives.