فهرس المقالات RSM

• حرية الوصول المقاله
  • صفحة الملخص
  • نص كامل
  
  1 - Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach
  Salila Ranjan Dixit Sudhansu Ranjan Das Debabrata Dhupal
  Nowadays in highly competitive precision industries, the micromachining of advanced engineering materials is extremely demand as it has extensive application in the fields of automobile, electronic, biomedical and aerospace engineering. The present work addresses the mo أکثر

  Nowadays in highly competitive precision industries, the micromachining of advanced engineering materials is extremely demand as it has extensive application in the fields of automobile, electronic, biomedical and aerospace engineering. The present work addresses the modeling and optimization study on dimensional deviations of square-shaped microgroove in laser micromachining of aluminum oxide (Al2O3) ceramic material with pulsed Nd:YAG laser by considering the air pressure, lamp current, pulse frequency, pulse width and cutting speed as process parameters. Thirty-two sets of laser microgrooving trials based on central composite design (CCD) design of experiments (DOEs) are performed, and response surface method (RSM), artificial neural network (ANN) and genetic algorithm (GA) are subsequently applied for mathematical modeling and multi-response optimization. The performance of the predictive ANN model based on 5-8-8-3 architecture gave the minimum error (MSE = 0.000099) and presented highly promising to confidence with percentage error less than 3% in comparison with experimental result data set. The ANN model combined with GA leads to minimum deviation of upper width, lower width and depth value of − 0.0278mm, 0.0102mm and − 0.0308mm, respectively, corresponding to optimum laser microgrooving process parameters such as 1.2 kgf/cm2of air pressure, 19.5 Amp of lamp current, 4kHz of pulse frequency, 6% of pulse width and 24mm/s of cutting speed. Finally, the results have been verified by performing a confirmatory test. تفاصيل المقالة
• حرية الوصول المقاله
  • صفحة الملخص
  • نص كامل
  
  2 - Response Surface Modeling and Optimization of Effective Parameters for Zn(II) Removal From Aqueous Solution Using Gracilaria Corticata
  Farah Assadian Ali Niazi Majid Ramezani
  10.22034/jchr.2020.578267.0
  Biosorption of Zn(II) from aqueous solution by biomass marine alga, namely Gracilaria corticata was investigated in this paper. Four independent variables, including initial zinc concentration (50-150 mg L-1), initial solution pH (3-7), contact time (10-50 min), and bio أکثر

  Biosorption of Zn(II) from aqueous solution by biomass marine alga, namely Gracilaria corticata was investigated in this paper. Four independent variables, including initial zinc concentration (50-150 mg L-1), initial solution pH (3-7), contact time (10-50 min), and biomass amount (1-2 g/100mL) were studied in the biosorption process. Optimization of the process conditions for maximizing Zn(II) removal from aqueous solutions by Gracilaria corticata was carried out using Box-Behnken design, including response surface methodology (RSM) based on 27 different experimental data. The optimal operating conditions for 95.0% removal of Zn(II) were as follows: initial zinc concentration of 100 mg L-1, initial solution pH of 5, contact time of 30.5 min, and biomass amount of 2 g/100 mL. In addition, the equilibrium isotherms were described by investigation of Langmuir and Freundlich isotherms. The Freundlich adsorption isotherm model well matched the experimental data (R2 = 0.981). The kinetic data fitted pseudo-second order model with a correlation coefficient of 0.9953. Gracilaria corticata was found to be well applicable for zinc removal based on the experimental results. تفاصيل المقالة