28 research outputs found
Potential of distillery effluents for safe water through vermifiltration
Vermifiltration of wastewater using waste eater earthworms is a newly conceived novel technology. The present study evaluated BOD, COD and TS showing significant variation in decrease by 95%, 90% and 80% respectively through vermifiltration of distillery effluents. The nutrient contents (TN, TP, TK, TCa and TMg) in the vermicasts had increase (1.82 % in TN, 0.24% in TP, 2.15% in TK, 2.07% in TCa and 2.86 % in TMg) in the range of fold than the control level. The morphology of the control and experimental vermicast samples were analyzed with SEM and the image showed significant variation. The FT-IR spectrum analysis showed reduction of aliphatic/aromatic (C=C and OH) compounds in the vermicompost. Thus, the present study significantly highlights the vermifiltration technology in treating distillery effluent
Modelling the Forming Limit Diagram for Aluminium Alloy Sheets using ANN and ANFIS
In this work, it is planned to model the formability of various grades of aluminium sheet metals using ANN and optimization is done using ANFIS. Formability test is performed on aluminium sheet metals Al5052, Al6061 and Al8011 with thickness 0.8 mm, 1 mm and 1.2 mm. Forming limit diagrams are constructed using strain values obtained from the test. Tensile tests are conducted on the sheet samples and the important mechanical properties which affect the formability are measured and calculated. Using the forming limit strains at different states namely tension-tension, plane strain and tension-compression, modeling is done using ANN and optimization is performed using ANFIS. The architecture 7–14-14–9 is found to be the optimum and it is used in ANN modeling. Using the strain values predicted by ANN, FLD curves are constructed. The predicted strain values are compared with experimental strain values. Further optimized strain values are predicted using ANFIS. This work reveals that experimental FLD, ANN predicted FLD and ANFIS predicted FLD are in good agreement
Photocatalytic efficiency of brilliant green dye on ZnO loaded on cotton stalk activated carbon
In this study, ZnO loaded on cotton stalk activated carbon (ZnO/CSAC) has been successfully synthesized by the chemical precipitation method. XRD patterns showed that ZnO/CSAC have two phases are hexagonal wurtizite and amorphous structures. The average particle size is reduced (12.4 nm) upon loading CSAC than the ZnO NPs. The band gap value is decreased (2.50 eV) upon loading on CSAC compared to ZnO NPs. The functional groups identify using by FT-IR spectrum. FE-SEM images a pure ZnO revealed a 15–40 nm spherical structure and 10–35 nm large agglomerations spherical structure for ZnO/CSAC and then, EDAX spectrum affirmed the formation of ZnO/CSAC. BET surface area and pore volume of the 22.18 m ^2 g ^−1 and 0.210 cm ^3 g ^−1 for the ZnO NPs and make it increased surface area and pore volume due to the adding CSAC to 263.18 m ^2 g ^−1 and 0.306 cm ^3 g ^−1 . The photocatalytic degradation efficiency of brilliant green (BG) dye and results shows that ZnO/CSAC sample improves photocatalytic activity than the ZnO NPs. Amidst all; ZnO/CSAC showed the maximum degradation the efficiency (90.26%) than the ZnO. These results show that the ZnO/CSAC sample is due to the synergistic effect between ZnO (photocatalysts) and CSAC (adsorption), its also possible mechanism and pseudo-first-order model are used to analysis the kinetics
Mass Transfer Studies in Three-phase Fluidized Bed Using Response Surface Method
Mass transfer characteristics of co-current three-phase fluidization were determined in terms of mass transfer coefficient and Sherwood number using Box-Behnken method. The experiment was carried out in a 5.4 cm I.D, 6 cm O.D and 160 cm high vertical Perspex column. Gypsum particles of diameter 0.0842 cm, 0.1676 cm and 0.2818 cm,
water, and air were used as solid, liquid and gaseous phase respectively. Initially, the superficial liquid velocity was maintained constant and superficial gas velocities varied. After attaining steady state, at a particular gas velocity, the fluidized bed height and manometer readings were recorded for pressure drop estimation. The above-mentioned procedure was repeated for four different liquid velocities in a fluidized bed. The effect of individual phase holdup and mass transfer coefficient for various particle sizes with the
specific liquid flow rates and gas flow rates were studied. It was observed that the mass transfer coefficient and Sherwood number increased with increase in superficial gas velocity and particle size in cocurrent three-phase fluidized bed. A quadratic model for bed
porosity, gas holdup, Sherwood number and mass transfer coefficient were developed using response surface method (RSM)
Performance Analysis of Data Processing Using High Performance Distributed Computer Clusters
Information technology of accounting the impact of data reduction methods on the results of classification of plant leaves
COVID-19: Impact analysis and recommendations for power sector operation
The demand of electricity has been reduced significantly due to the recent COVID-19 pandemic. Governments around the world were compelled to reduce the business activity in response to minimize the threat of coronavirus. This on-going situation due to COVID-19 has changed the lifestyle globally as people are mostly staying home and working from home if possible. Hence, there is a significant increase in residential load demand while there is a substantial decrease in commercial and industrial loads. This devastating situation creates new challenges in the technical and financial activities of the power sector and hence most of the utilities around the world initiated a disaster management plan to tackle this ongoing challenges/threats. Therefore, this study aims to investigate the global scenarios of power systems during COVID-19 along with the socio-economic and technical issues faced by the utilities. Then this study further scrutinized the Indian power system as a case study and explored scenarios, issues and challenges currently being faced to manage the consumer load demand, including the actions taken by the utilities/power sector for the smooth operation of the power system. Finally, a set of recommendations are presented that will not only help government/policymakers/utilities around the world to overcome the current crisis but also helps to overcome future unforeseeable pandemic alike scenarios
Harmonics Minimisation in Non-Linear Grid System Using an Intelligent Hysteresis Current Controller Operated from a Solar Powered ZETA Converter
Due to the non-linear load characteristics in the domestic three-phase grid system, the quality of power transmission is a challenge for researchers. In this paper, the harmonics injected in a three-phase grid system due to the non-linear loads and a solution for harmonics minimisation using the hysteresis current controller (HCC) is presented. The proposed work consists of switched dc loads such as personal computers, SMPS, etc., connected to the three-phase grid system through the rectifier unit. These loads connected with other AC loads inject harmonics in the power lines. The total harmonic distortion (THD) at the power line is therefore increased. A ZETA embedded three-phase inverter using an artificial neural network-based HCC (ANN-HCC) is used to minimise the voltage and the current THDs. To ease the power consumption, a solar photovoltaic system (SPV) is used to power the ZETA embedded three-phase inverter. The output of the SPV is regulated using the ZETA dc/dc converter. However, the hysteresis bands (Uupper and Ulower) are selected using the ANN with respect to the actual value compared with the calculated current error. The vector shifts to the next based on the previous vector applied, and thereby the process repeats following the same pattern. The back propagation (BP)-based neural network is trained using the currents’ non-linear and differential functions to generate the current error. The neural structure ends when the value hits the hysteresis band. Simultaneously, the PWM control waveform is tracked by the neural network output. The proposed system is mathematically modelled using MATLAB/Simulink. An experimental setup of a similar prototype model is designed. The voltage and the current harmonics are measured using a Yokogawa CW240 power quality meter and the results are discussed