Optimizing Nano Metalworking Emulsions Preparation Using Response Surface Method

2021 ◽  
Vol 39 (2A) ◽  
pp. 214-232
Author(s):  
Nuhad B. Dawood ◽  
Adnan A. AbdulRazak ◽  
Adel S. Hamadi
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Ph Value ◽  
Metalworking Fluids ◽  
Quadratic Model ◽  
Value Analysis ◽  
Surface Method ◽  
Hydrophilic Lipophilic Balance ◽  
The Stability ◽  
Nano Emulsion

Nano emulsions (NEs) have important prospective advantages for assured industrials applications especially Metalworking fluids (MWFs), due to their Nano size, stability, than other types of traditional emulsions. In this work paraffin oil, water and mixture of surfactants Span20 & Tween20 are utilized for preparation of the MWF. A quadratic model was developed by applying the response surface method (RSM) to relate the droplets size and emulsion stability as a response to five independent variables namely the speed and time of mixing, concentration of the surfactant, Hydrophilic-Lipophilic Balance (HLB) value and pH value. Analysis of variance (ANOVA) was conducted; the results confirm the high significance of the regression model. The predicted values were found to be satisfactory with that experimental value. Mixing speed exerted the highest effect on the droplet size and the stability of the emulsion. The optimum conditions were found be (the concentration = 4.75 wt.%, time of mixing = 18.12 min, speed of mixing 14998.93 rpm, pH = 10.01 and HLB = 10.87) to attained Nano emulsion with 2 nm in size and stability of 24 days. Tool wear and surface roughness were studied at different speed, the results have showed that the wear ratio of the bits for all selected speeds is as follow: using commercial fluid > MWFs. The metallurgical microscope images have showed that, in case using MWFs the surface of cracks between the metals and the tool is more smooth compare with other fluids

scholarly journals Formulation and Characterization of Oil-in-Water Emulsions Stabilized by Saponins Extracted from Hedera Helix Algeriensis Using Response Surface Method

2020 ◽  
Vol 10 (5) ◽  
pp. 6282-6292
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Viscoelastic Behavior ◽  
Surface Characteristics ◽  
Rheological Parameters ◽  
Triterpene Saponins ◽  
Hedera Helix ◽  
Surface Method ◽  
Oil In Water ◽  
The Stability

Triterpene saponins extracted from Hedera helix Algeriensis plants were evaluated in terms of surface characteristics and capacity to be utilized as surfactants for the formulation of oil-in water emulsions. Surface tension and emulsifying properties were used for the identification of the surfactant characters, while emulsions were characterized by rheological methods and their stability was estimated by the control of the creaming index. The design of emulsions was conducted by employing a response surface method (RSM). The factors affecting the rheological parameters and emulsion stability were carefully evaluated by the polynomial models. Triterpene saponins were found as effective biosurfactants; they contribute strongly to the stability of emulsions by interacting with other excipients. Emulsions exhibited a shear-thinning behavior and low apparent viscosities which depend on the amount of xanthan used. They were considered as weak gels with a viscoelastic behavior. In addition, it was found that the presence of a sufficient quantity of saponins improves the stability of emulsions.

scholarly journals L-Asparaginase-producing Rouxiella Species Isolation, Antileukemia Activity Evaluation, and Enzyme Production Optimization

2019 ◽  
Author(s):  
Farhad Gilavand ◽  
Abdolrazagh Marzban ◽  
Amirarsalan Kavyanifard
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Enzyme Production ◽  
Lymphoblastic Leukemia ◽  
Bacterial Species ◽  
Production Optimization ◽  
Quadratic Model ◽  
Cancer Drug ◽  
Isolation And Identification ◽  
Surface Method

Background: L-Asparaginase (L-Asp) is used as an efficient anti-cancer drug, especially for acute lymphoblastic leukemia (ALL). Currently, two bacterial asparaginase isoenzymes are used for cancer treatment. Therefore, this research focused on isolating native bacteria with the ability to produce L-Asp. Materials and Methods: L-Asp producing bacteria were isolated from soil samples on 9K medium supplemented with L-Asp as nitrogen source. Detection of L-Asp activity was performed by observing color change of the agar medium from yellow to orange due to the release of ammonia around the colonies. After the isolation and identification of the bacterium, L-Asp production was first optimized by the one factor-at-the-time (OFAT) technique followed by the response surface method. Next, the enzyme was extracted, purified, and assessed for antileukemia activity on U937 and MRC-5 cell lines. Results: The results revealed that L-Asp produced by Rouxiella sp. AF1 significantly inhibited the growth of U937 cells at a dose of up to 0.04 IU/ml, while MRC-5 was not affected at any enzyme doses. The final purification of the enzyme was achieved by column chromatography (Sephadex G-100) at approximately 0.31 mg/ml, and its specific activity was determined to be 0.51 IU/mg. The OFAT optimization experiments were performed primarily to determine optimal enzyme conditions, which were found to be neutral pH (pH7), 30 ∘C temperature, and 3 % NaCl, 1 % peptone, and 1% glucose concentrations. Statistical optimization was based on five factors obtained from OFAT, and response surface method (RSM) analysis introduced a quadratic model for enzyme production at the optimal range of these variables. This model provided an equation for measuring the effect of physiochemical conditions on final enzyme production. Conclusion: We showed that native bacteria may be novel candidates for isolating new metabolites such as L-Asp. Because many bacteria grow in unknown environments with unique ecological properties, the probability of discovering novel bacterial species producing bioactive compounds is high.

A Proposal of PSO with Presumption Function of the Solution Landscape by Response Surface Method

2014 ◽  
Vol 134 (9) ◽  
pp. 1293-1298
Author(s):  
Toshiya Kaihara ◽  
Nobutada Fuji ◽  
Tomomi Nonaka ◽  
Yuma Tomoi
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Surface Method

scholarly journals Creep-Based Reliability Evaluation of Turbine Blade-Tip Clearance with Novel Neural Network Regression

Materials ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 3552 ◽  
Author(s):  
Chun-Yi Zhang ◽  
Jing-Shan Wei ◽  
Ze Wang ◽  
Zhe-Shan Yuan ◽  
Cheng-Wei Fei ◽  
...  
Keyword(s):  
Neural Network ◽  
High Pressure ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Tip Clearance ◽  
Strong Nonlinearity ◽  
Surface Method ◽  
Blade Tip ◽  
Blade Tip Clearance

To reveal the effect of high-temperature creep on the blade-tip radial running clearance of aeroengine high-pressure turbines, a distributed collaborative generalized regression extremum neural network is proposed by absorbing the heuristic thoughts of distributed collaborative response surface method and the generalized extremum neural network, in order to improve the reliability analysis of blade-tip clearance with creep behavior in terms of modeling precision and simulation efficiency. In this method, the generalized extremum neural network was used to handle the transients by simplifying the response process as one extremum and to address the strong nonlinearity by means of its nonlinear mapping ability. The distributed collaborative response surface method was applied to handle multi-object multi-discipline analysis, by decomposing one “big” model with hyperparameters and high nonlinearity into a series of “small” sub-models with few parameters and low nonlinearity. Based on the developed method, the blade-tip clearance reliability analysis of an aeroengine high-pressure turbine was performed subject to the creep behaviors of structural materials, by considering the randomness of influencing parameters such as gas temperature, rotational speed, material parameters, convective heat transfer coefficient, and so forth. It was found that the reliability degree of the clearance is 0.9909 when the allowable value is 2.2 mm, and the creep deformation of the clearance presents a normal distribution with a mean of 1.9829 mm and a standard deviation of 0.07539 mm. Based on a comparison of the methods, it is demonstrated that the proposed method requires a computing time of 1.201 s and has a computational accuracy of 99.929% over 104 simulations, which are improvements of 70.5% and 1.23%, respectively, relative to the distributed collaborative response surface method. Meanwhile, the high efficiency and high precision of the presented approach become more obvious with the increasing simulations. The efforts of this study provide a promising approach to improve the dynamic reliability analysis of complex structures.

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