scholarly journals Bioremediation of hexavalent chromium by an indigenous bacterium Bacillus cereus S10C1: optimization study using two level full factorial experimental design

2021 ◽  
Vol 24 (S1) ◽  
pp. 1-14
Author(s):  
Amina Nacer ◽  
Souheyla Boudjema ◽  
Mahmoud Bouhaous ◽  
Nacer Boudouaia ◽  
Zohra Bengharez
Keyword(s):  
Experimental Design ◽  
Bacillus Cereus ◽  
Hexavalent Chromium ◽  
Factorial Experimental Design ◽  
Indigenous Bacterium ◽  
Optimization Study ◽  
Full Factorial Experimental Design ◽  
Bacterium Bacillus ◽  
Full Factorial

scholarly journals The Design and Implementation of Adsorptive Removal of Cu(II) from Leachate Using ANFIS

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Nurdan Gamze Turan ◽  
Okan Ozgonenel
Keyword(s):  
Experimental Design ◽  
Contact Time ◽  
Fixed Bed ◽  
Experimental System ◽  
Factorial Experimental Design ◽  
Adsorbent Dosage ◽  
Initial Ph ◽  
Full Factorial Experimental Design ◽  
Full Factorial ◽  
Aqueous Leachate

Clinoptilolite was investigated for the removal of Cu(II) ions from industrial leachate. Adaptive neural fuzzy interface system (ANFIS) was used for modeling the batch experimental system and predicting the optimal input values, that is, initial pH, adsorbent dosage, and contact time. Experiments were studied under laboratory batch and fixed bed conditions. The outcomes of suggested ANFIS modeling were then compared to a full factorial experimental design (23), which was utilized to assess the effect of three factors on the adsorption of Cu(II) ions in aqueous leachate of industrial waste. It was observed that the optimized parameters are almost close to each other. The highest removal efficiency was found as about 93.65% at pH 6, adsorbent dosage 11.4 g/L, and contact time 33 min for batch conditions of 23experimental design and about 90.43% at pH 5, adsorbent dosage 15 g/L and contact time 35 min for batch conditions of ANFIS. The results show that clinoptilolite is an efficient sorbent and ANFIS, which is easy to implement and is able to model the batch experimental system.

Analysis of the effects of fabric reinforcement parameters on the mechanical properties of textile-based hybrid composites by full factorial experimental design method

2017 ◽  
Vol 48 (3) ◽  
pp. 580-598 ◽  
Author(s):  
Hande Sezgin ◽  
Omer B Berkalp
Keyword(s):  
Experimental Design ◽  
Hybrid Composites ◽  
Design Method ◽  
High Strength ◽  
Factorial Experimental Design ◽  
Fabric Reinforcement ◽  
Experimental Design Method ◽  
Glass Carbon ◽  
Full Factorial Experimental Design ◽  
Full Factorial

In this study, the effect of some fabric reinforcement parameters (fabric direction, yarn type and stacking sequence) on the mechanical properties of textile based hybrid composites are analysed by using full factorial experimental design method. The analysis of the results is achieved by using Minitab 17 software program. One factor (fabric reinforcement direction) with two levels (warp direction and weft direction) and two factors (yarn type and stacking sequence) with three levels (jute/glass, jute/carbon, glass/carbon and consecutive, low strength inside, high strength inside) are selected as the reinforcement design. Full factorial experimental design analysis results indicate that, the highest tensile and impact strength values among the experimental design are realised when samples are taken from the warp direction and E-glass/carbon combination is chosen as the yarn (material) type. Moreover, it is verified that while higher tensile strength is achieved by placing higher strength fabrics to the inner layers, higher impact strength is achieved by placing high strength fabrics to the outer layers of hybrid composite structures. Analysis of variance tables also show that at 95% confidence level, the effects of the factors are statistically significant ( p < 0.05).

Sign in / Sign up

Export Citation Format

Share Document