Optimization of Temperature Rise during CO2 Absorption Process Using Response Surface Methodology

2014 ◽  
Vol 625 ◽  
pp. 42-45
Author(s):  
Tan Lian See ◽  
Mohd Shariff Azmi ◽  
Kok Keong Lau
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Temperature Rise ◽  
Pilot Scale ◽  
Experimental Results ◽  
Inlet Concentration ◽  
Absorption Process ◽  
Increase With Increase ◽  
Predicted Values ◽  
Set Up

This study aims to optimize the temperature rise during CO2 absorption process using response surface methodology (RSM). Verification experiments were performed using a pilot scale experimental set up to validate the optimization condition generated from RSM analysis. The magnitude of temperature rise was observed to increase with increase of pressure and it was especially significant with the increase of CO2 inlet concentration. However, the increase of temperature with higher CO2 inlet concentration was not very obvious after 60% of CO2 inlet concentration. The predicted values of the optimized temperature rise were generally in good agreement with the actual experimental results and this indicated that the empirical correlation generated was well suited with the experimental results.

Application of Response Surface Methodology to Investigate CO2 Absorption Column Temperature Rise

2014 ◽  
Vol 917 ◽  
pp. 257-266 ◽  
Author(s):  
Lian See Tan ◽  
Mohd Shariff Azmi ◽  
Lau Kok Keong ◽  
Mohammad Azmi Bustam
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Flow Rate ◽  
Temperature Rise ◽  
Gas Flow ◽  
Liquid Temperature ◽  
Inlet Concentration ◽  
Gas Flow Rate ◽  
Column Temperature ◽  
Column Pressure

This study aims to investigate the impact of process parameters to the column temperature rise during the absorption process using response surface methodology (RSM). The parameters studied were liquid temperature, column pressure, CO2 inlet concentration and gas flow rate. While all the factors studied had significant impact to the quadratic model for the temperature rise, the magnitude of temperature rise was more obvious with the variation of column pressure and CO2 inlet concentration. The column temperature rise was found to be high when the liquid temperature, column pressure and CO2 inlet concentration were high. Similar behavior of high column temperature rise was also observed when the gas flow rate was low.

scholarly journals Assessment of TiO2 Nanoconcentration and Twin Impingement Jet of Heat Transfer Enhancement—A Statistical Approach Using Response Surface Methodology

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 595
Author(s):  
Mahir Faris Abdullah ◽  
Rozli Zulkifli ◽  
Hazim Moria ◽  
Asmaa Soheil Najm ◽  
Zambri Harun ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Heat Transfer Rate ◽  
Transfer Rate ◽  
Tio2 Nanoparticle ◽  
Experimental Results ◽  
Improvement Rate ◽  
Design Expert ◽  
Impingement Jet

Impinging jets are considered to be a well-known technique that offers high local heat transfer rates. No correlation could be established in the literature between the significant parameters and the Nusselt number, and investigation of the interactions between the correlated factors has not been conducted before. An experimental analysis based on the twin impingement jet mechanism was achieved to study the heat transfer rate pertaining to the surface plate. In the current paper, four influential parameters were studied: the spacing between nozzles, velocity, concentration of Nano solution coating and nozzle-plate distance, which are considered to be effective parameters for the thermal conductivity and the heat transfer coefficient of TiO2 nanoparticle, an X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) analysis were done, which highlighted the structure and showed that the nanosolution coated the surface homogenously. Moreover, a comparison was done for the experimental results with that of the predicted responses generated by the Design Expert software, Version 7 User’s Guide, USA. A response surface methodology (RSM) was employed to improve a mathematical model by accounting for a D-optimal design. In addition, the analysis of variance (ANOVA) was employed for testing the significance of the models. The maximum Nu of 91.47, where H = S = 1 cm; Reynolds number of 17,000, and TiO2 nanoparticle concentration of 0.5% M. The highest improvement rate in Nusselt was about 26%, achieved with TiO2 Nanoparticle, when S = 3 cm, H = 6 cm and TiO2 nanoparticle = 0.5 M. Furthermore, based on the statistical analysis, the expected values were found to be in satisfactory agreement with that of the empirical data, which was conducted by accounting for the proposed models’ excellent predictability. Multivariate approaches are very useful for researchers, as well as for applications in industrial processes, as they lead to increased efficiency and reduced costs, so the presented results of this work could encourage the overall uses of multivariate methods in these fields. Hypotheses: A comparison was done for the predicted responses generated by the Design Expert software with the experimental results and then studied to verify the following hypotheses: ► Preparation of three concentrations of TiO2 nanosolution was done and studied. ► The heat transfer rate could be increased by surface coating with TiO2 nanoparticle. ► The heat transfer could be improved by the impingement jet technique with suitable adjustments.

Optimization of Manufacturing Process of Traditional Algerian Jben Cheese Using Response Surface Methodology (RSM)

2018 ◽  
Vol 8 (1) ◽  
pp. 31-42
Author(s):  
M. Amimour ◽  
T. Idoui ◽  
A. Cheriguene
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Manufacturing Process ◽  
Milk Powder ◽  
Statistical Design ◽  
Polynomial Equation ◽  
Enzymatic Extract ◽  
Traditional Cheese ◽  
Order Polynomial ◽  
Predicted Values

The Aim of this study was to develop an optimized method for manufacturing process of traditional Algerian Jben cheese, using response surface methodology (RSM). In order to develop the objective method of making this traditional cheese, several factors have been studied and a Plackett-Burman statistical design was applied. The effects of the four screened factors (enrichment with milk powder, 10 - 20 g/l; pH of milk, 5.75 - 6.75, enzymatic extract dose, 0.5 - 1.5 ml and coagulation temperature 40 - 60 °C) on the response were investigated, using a Box-Behnken statistical design. Multiple regression analysis was used so that experimental data fits to a second-order polynomial equation. This multiple analysis showed that the model explains about 90.73% of the variation. Based on statistical results, it can be noticed that enrichment with milk powder and pH of milk (Ë‚0.0001***) were highly significant factor influincing cheese yield. The optimal production parame-ters that maximized cheese product (20 g/l enrichment with milk powder, 5.75 pH of milk, 1.29 ml enzymatic extract dose and 60°C coagulation temperature) and the maximal predicted cheese yield (52.68 % ) were found out through response surface methodology. Under these conditions, a verification experiment was carried out and cheese yield was found to be 49.46 %. The overall percentage of agreement for the experimental results (more than 93 % validity) with the predicted values indicates the validation of the statistical model and the success of the optimization process.

scholarly journals Optimization of Supercritical Carbon Dioxide Extraction of Quercus infectoria Oil

2015 ◽  
Vol 74 (7) ◽  
Author(s):  
Liza Md Salleh ◽  
Stashia ELeaness Rosland Abel ◽  
Gholamreza Zahedi ◽  
Russly Abd Rahman ◽  
Hasmida Mohd Nasir ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Goodness Of Fit ◽  
Maximum Yield ◽  
Extraction Yield ◽  
Extraction Time ◽  
Extraction Temperature ◽  
Predicted Values ◽  
Artificial Neural Network Ann ◽  
Quercus Infectoria

This current study focuses on the modelling and optimization of supercritical fluid extraction of Quercus infectoria galls oil. In this case, response surface methodology (RSM) and artificial neural network (ANN) were applied for the modelling and prediction of extraction yield of galls oil. A 17-run Box-Behnken Design (BBD) was employed to statistically optimize the process parameters of SC-CO2 extraction of Quercus infectoria galls at a condition as follows: pressure (5000, 6000, 7000 Psi), temperature (40, 50, 60°C) and extraction time (30, 45, 60 min). The maximum yield of the extracted oil is1.12 % and the optimum conditions are at an extraction pressure of 5574 Psi; extraction temperature of 75°C and extraction time of 54 min. Under the optimal conditions, the experimental results agree with the predicted values obtained through analysis of variance (ANOVA). This indicates a successful response surface methodology and highly satisfactory goodness of fit of the model used. The analysis of experimental design for process optimization results demonstrates that temperature and extraction time are the main parameters that influence the oil extraction of Quercus infectoria.

scholarly journals OPTIMIZATION OF LEVOFLOXACIN REMOVAL FROM AQUEOUS SOLUTION USING ELECTROCOAGULATION PROCESS BY RESPONSE SURFACE METHODOLOGY

2021 ◽  
Vol 52 (1) ◽  
pp. 204-217
Author(s):  
Mohammed & Mohammed-Ridha
Keyword(s):  
Aqueous Solution ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Correlation Coefficient ◽  
Iron Hydroxide ◽  
Second Order ◽  
Experimental Results ◽  
Order Kinetic ◽  
Experimental Conditions ◽  
Good Agreement

This study was aimed to investigate the response surface methodology (RSM) to evaluate the effects of various experimental conditions on the removal of levofloxacin (LVX) from the aqueous solution by means of electrocoagulation (EC) technique with stainless steel electrodes. The EC process was achieved successfully with the efficiency of LVX removal of 90%. The results obtained from the regression analysis, showed that the data of experiential are better fitted to the polynomial model of second-order with the predicted correlation coefficient (pred. R2) of 0.723, adjusted correlation coefficient (Adj. R2) of 0.907 and correlation coefficient values (R2) of 0.952. This shows that the predicted models and experimental values are in good agreement. The results of the kinetic study showed that the second-order kinetic model was in good agreement with the experimental results and suggested that the mechanism of chemisorption controlled the LVX adsorption. The experimental results indicated that the adsorption of LVX on iron hydroxide flocs follows Sips isotherm with the value of the correlation coefficient (R2) of 0.937. Sips isotherm shows that both homogenous and heterogeneous adsorption can occur.

scholarly journals Process Parameter Optimization in Fused Deposition Modeling (FDM) Using Response Surface Methodology (RSM)

2020 ◽  
Author(s):  
Muhammad Salman Mustafa ◽  
Muhammad Qasim Zafar ◽  
Muhammad Arslan Muneer ◽  
Muhammad Arif ◽  
Farrukh Arsalan Siddiqui ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Response Surface Methodology ◽  
Impact Strength ◽  
Response Surface ◽  
Layer Thickness ◽  
Fused Deposition Modeling ◽  
Experimental Results ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Printing Parameters

Abstract Fused Deposition Modeling (FDM) is a widely adopted additive manufacturing process to produce complex 3D structures and it is typically used in the fabrication of biodegradable materials e.g. PLA/PHA for biomedical applications. However, FDM as a fabrication process for such material needs to be optimized to enhance mechanical properties. In this study, dogbone and notched samples are printed with the FDM process to determine optimum values of printing parameters for superior mechanical properties. The effect of layer thickness, infill density, and print bed temperature on mechanical properties is investigated by applying response surface methodology (RSM). Optimum printing parameters are identified for tensile and impact strength and an empirical relation has been formulated with response surface methodology (RSM). Furthermore, the analysis of variance (ANOVA) was performed on the experimental results to determine the influence of the process parameters and their interactions. ANOVA results demonstrate that 44.7% infill density, 0.44 mm layer thickness, and 20C° printing temperatures are the optimum values of printing parameters owing to improved tensile and impact strength respectively. The experimental results were found in strong agreement with the predicted theoretical results.

Optimization of a Whole-Stalk Operating System after Sugarcane Base Cutting

2019 ◽  
Vol 62 (1) ◽  
pp. 157-166
Author(s):  
Luxin Xie ◽  
Jun Wang ◽  
Shaoming Cheng ◽  
Jinbing Hu
Keyword(s):  
Operating System ◽  
Response Surface Methodology ◽  
Central Composite Design ◽  
Response Surface ◽  
Fracture Rate ◽  
Cleaning Performance ◽  
Abrasion Rate ◽  
Leaf Stripping ◽  
Predicted Values ◽  
Central Composite

Abstract. Leaf stripping and top breaking are the key procedures in whole-stalk sugarcane harvesting. In this study, a whole-stalk operating system after sugarcane base cutting was developed and tested to improve the leafy trash cleaning performance and adaptability of a whole-stalk harvester. A leaf shredding procedure was proposed before leaf stripping, and an anti-float top breaking device was developed for breaking cane tops. The rotational speeds of the leaf shredding (RL), leaf stripping (RS), and top breaking (RT) rollers were regarded as experimental factors, and the leafy trash content (including leaves, leaf sheaths, and tops in this study), top breaking rate, abrasion rate, and non-fracture rate of the middle or bottom parts were selected as indices. Central composite design combined with response surface methodology and comprehensive evaluation method were employed to conduct experiments and explore the interaction effects of factors on indices. The optimal operating parameters were nonlinearly optimized and determined to be RL of 512.9 rpm, RS of 418.8 rpm, and RT of 307.0 rpm. Under these conditions, the predicted values of leafy trash content, top breaking rate, abrasion rate, and non-fracture rate were 4.98%, 88.39%, 5.19%, and 96.21%, respectively. Verification experiments indicated that the observed values were in agreement with the predicted values. Results suggested that the leaf shredding device and anti-float top breaking device developed in this study were effective for improving the leafy trash cleaning performance and adaptability of the whole-stalk operating system, and there was a good potential for performance improvement of whole-stalk sugarcane harvesters. Keywords: Central composite design, Leaf shredding, Leaf stripping, Response surface methodology, Top breaking, Whole-stalk harvester.

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