scholarly journals A Comparison between Several Response Surface Methodology Designs and a Neural Network Model to Optimise the Oxidation Conditions of a Lignocellulosic Blend

Biomolecules ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 787
Author(s):  
Roberto López ◽  
Camino Fernández ◽  
Fernando J. Pereira ◽  
Ana Díez ◽  
Jorge Cara ◽  
...  
Keyword(s):  
Neural Network ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Molar Ratio ◽  
Good Prediction ◽  
Optimal Conditions ◽  
Total Flow ◽  
Resource Requirement ◽  
Prediction Ability ◽  
Central Composite

In this paper, response surface methodology (RSM) designs and an artificial neural network (ANN) are used to obtain the optimal conditions for the oxy-combustion of a corn–rape blend. The ignition temperature (Te) and burnout index (Df) were selected as the responses to be optimised, while the CO2/O2 molar ratio, the total flow, and the proportion of rape in the blend were chosen as the influencing factors. For the RSM designs, complete, Box–Behnken, and central composite designs were performed to assess the experimental results. By applying the RSM, it was found that the principal effects of the three factors were statistically significant to compute both responses. Only the interactions of the factors on Df were successfully described by the Box–Behnken model, while the complete design model was adequate to describe such interactions on both responses. The central composite design was found to be inadequate to describe the factor interactions. Nevertheless, the three methods predicted the optimal conditions properly, due to the cancellation of net positive and negative errors in the mathematical adjustment. The ANN presented the highest regression coefficient of all methods tested and needed only 20 experiments to reach the best predictions, compared with the 32 experiments needed by the best RSM method. Hence, the ANN was found to be the most efficient model, in terms of good prediction ability and a low resource requirement. Finally, the optimum point was found to be a CO2/O2 molar ratio of 3.3, a total flow of 108 mL/min, and 61% of rape in the biomass blend.

Comparison of different modeling methods toward predictive capability evaluation of the bonding strength of wood laminated products

2021 ◽  
pp. 095440892110530
Author(s):  
Morteza Nazerian ◽  
Seyed Ali Razavi ◽  
Ali Partovinia ◽  
Elham Vatankhah ◽  
Zahra Razmpour
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Bonding Strength ◽  
Fuzzy Inference ◽  
Molar Ratio ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Artificial Neural

The main aim of this study is usability evaluation of different approaches, including response surface methodoloy, adaptive neuro-fuzzy inference system, and artificial neural network models to predict and evaluate the bonding strength of glued laminated timber (glulam) manufactured using walnut wood layers and a natural adhesive (oxidized starch adhesive), with respect to this fact that using the modified starch can decrease the formaldehyde emission. In this survey, four variables taken as the input data include the molar ratio of formaldehyde to urea (1.12–1.52), nanocellulose content (0%–4%, based on the dry weight of the adhesive), the mass ratio of the oxidized starch adhesive to the urea formaldehyde resin (30:70–70:30), and the press time (4–8 min). In order to find the best predictive performance of each selected evaluation approach, different membership functions were used. The optimal results were obtained when the molar ratio, nanocellulose content, mass ratio of the oxidised starch, and press time were set at 1.22, 3%, 70:30, and 7 min, respectively. Based on the performance criteria including root mean square error (RMSE) and mean absolute percentage error (MAPE) obtained from the modeling of response surface methodology, adaptive neuro-fuzzy inference network, and artificial neural network, it became evident that response surface methodology could offer a better prediction of the response with the lowest level of errors. Beside, artificial neural network and adaptive neuro-fuzzy inference system support the response surface methodology approach to evaluate bonding strength response with high precision as well as to determine the optimal point in fabrication of laminated products.

scholarly journals Response surface methodology-artificial neural network based optimization and strain improvement of cellulase production by Streptomyces sp.

2020 ◽  
Vol 36 (4) ◽  
Author(s):  
Ega Soujanya Lakshmi ◽  
Manda Rama Narasinga Rao ◽  
Muddada Sudhamani
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Wild Strain ◽  
Cellulase Activity ◽  
Cellulase Production ◽  
Optimal Conditions ◽  
Zone Formation ◽  
Artificial Neural

ABSTRACT Thirty seven different colonies were isolated from decomposing logs of textile industries. From among these, a thermotolerant, grampositive, filamentous soil bacteria Streptomyces durhamensis vs15 was selected and screened for cellulase production. The strain showed clear zone formation on CMC agar plate after Gram’s iodine staining.  Streptomyces durhamensis vs15 was further confirmed for cellulase production by estimating the reducing sugars through dinitrosalicylic acid (DNS) method. The activity was enhanced by sequential mutagenesis using three mutagens of ultraviolet irradiation (UV), N methyl-N’-nitro-N-nitrosoguanidine (NTG) and Ethyl methane sulphonate (EMS). After mutagenesis, the cellulase activity of GC23 (mutant) was improved to 1.86 fold compared to the wild strain (vs15). Optimal conditions for the production of cellulase by the GC 23 strain were evaluated using Response Surface Methodology (RSM) and Artificial Neural Network (ANN). Effect of pH, temperature, duration of incubation, , and substrate concentration on cellulase production were evaluated. Optimal conditions for the production of cellulase enzyme using Carboxy Methyl Cellulase as a substrate are 55 oC of temperature, pH of 5.0 and incubation for 40 h. The cellulase activity of the mutant Streptomyces durhamensis GC23 was further optimised to 2 fold of the activity of the wild type by RSM and ANN.  

Optimization of Biodiesel Ultrasound-Assisted Synthesis from Castor Oil Using Response Surface Methodology (RSM)

2015 ◽  
Vol 10 (2) ◽  
pp. 123-133 ◽  
Author(s):  
Mohammadreza Sabzimaleki ◽  
Barat Ghobadian ◽  
Mohsen Mazloom Farsibaf ◽  
Gholamhassan Najafi ◽  
Masoud Dehghani Soufi ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Reaction Time ◽  
Response Surface ◽  
Castor Oil ◽  
Molar Ratio ◽  
Reaction Yield ◽  
Ultrasound Assisted ◽  
Short Time ◽  
The Relationship ◽  
Central Composite

Abstract Production of biodiesel from castor oil (CO) using ultrasound-assisted has been investigated in this study. The objective of the present work was therefore to determine the relationship between various important parameters of the alkaline-catalyzed transesterification process to obtain a high reaction yield in a short time. The response surface methodology (RSM) was used to statistically analyze and optimize the operating parameters of the process. A central composite design (CCD) was approved to study the effects of the reaction time, the methanol to oil molar ratio, the ultrasonic cycle and the ultrasonic amplitude on reaction yield. The optimum conditions for alkaline-catalyzed transesterification of CO was found to be a reaction time of 540 s, methanol to oil molar ratio of 8.15:1,ultrasonic cycle of 0.73% and ultrasonic amplitude 64.34%. By exerting the calculated optimum condition in the process, the reaction yield reached 87.0494%. The results from the RSM analysis indicated that the reaction time has the most significant effect on the reaction yield.

scholarly journals Response surface methodology for optimizing the glycerolysis reaction of olive oil by Candida rugosa lipase

2014 ◽  
Vol 20 (1) ◽  
pp. 127-134 ◽  
Author(s):  
Kumar Singh ◽  
Mausumi Mukhopadhyay
Keyword(s):  
Response Surface Methodology ◽  
Reaction Time ◽  
Olive Oil ◽  
Water Content ◽  
Response Surface ◽  
Candida Rugosa ◽  
Candida Rugosa Lipase ◽  
Molar Ratio ◽  
Immobilized Candida Rugosa Lipase ◽  
Central Composite

In the present work, solvent free olive oil glycerolysis for the monoglycerides (MG) and diglycerides (DG) production with an immobilized Candida rugosa lipase was studied. MG and DG production were optimized using experiment design techniques and response surface methodology (RSM). RSM based on five-level, a five-variable central composite design (CCD) was used to optimize MG and DG production: reaction time, temperature, molar ratio of glycerol to oil, amount of lipase, and water content in glycerol. The reaction time, temperature, and amount of lipase were observed to be the most significant factors on the process response. The immobilized Candida rugosa lipase revealed optimum yield of MG and DG as 38.71 and 40.45 wt% respectively following a 5h reaction time with 0.025 g of lipase and 5% water content in glycerol at 40?C temperature. The yield of MG and DG production can be enhanced 1.5 fold by RSM.

scholarly journals The Brazilian Way to Consume acai: Do guarana Extract and Sugar Concentrations Influence on Acceptance?

2013 ◽  
Vol 3 (1) ◽  
pp. 39
Author(s):  
Gabriela Montenegro ◽  
Karen S. Pereira ◽  
Lauro Melo
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Critical Value ◽  
Consumer Acceptance ◽  
Central Composite Rotatable Design ◽  
Optimal Conditions ◽  
F Test ◽  
Sensory Acceptance ◽  
Amazon Estuary ◽  
Central Composite

<p class="Normal1"><em>A</em><em>c</em><em>a</em><em>i</em> is a palm widely distributed in the Amazon estuary floodplains. The edible pulp of acai fruits is commonly macerated with water to produce a thick, purple beverage of creamy texture, oily appearance, and characteristic flavor. Depending on the Brazilian region, the acai based-product is prepared adding sugar and <em>guaran</em><em>a</em> extract, but their ideal proportions have never been determined in order to optimize consumers’ sensory acceptance. This research investigated these concentrations using response surface methodology (RSM) based on a five-level, two variable central composite rotatable design (CCRD). Dependent variable was consumer acceptance (flavor, texture and overall liking) and results were analyzed by multivariate regressions. Analyses of Variance (ANOVAs) showed significant models – F-test values (29.3 for flavor, for texture 37.8 and 30.4 for overall liking) higher than the critical value of 4.35 (d.f. = 3; p &lt; 0.05; R<sup>2</sup> of 0.926 for flavor, 0.942 for texture and 0.929 for overall liking). Acceptance models are presented (significant parameters). Results showed that guarana extract has a stronger influence (negative) on acceptance compared to sugar (positive), both not on optimal conditions yet. Therefore, more studies are needed in order to optimize acai acceptance.</p>

scholarly journals Optimization of Reducing Ffa Content of Waste Cooking Oil by Using Response Surface Methodology

2020 ◽  
Author(s):  
Sri Rizki Putri Primandari ◽  
Andril Arafat ◽  
Arwizet Karudin
Keyword(s):  
Response Surface Methodology ◽  
Optimum Condition ◽  
Response Surface ◽  
Irradiation Time ◽  
Waste Cooking Oil ◽  
Biodiesel Production ◽  
Molar Ratio ◽  
Important Process ◽  
Acid Esterification ◽  
Central Composite

Abstract Waste cooking oil has high free fatty acid (FFA). It impact to low yield of biodiesel production. Thus, reducing FFA is one of important process as feedstock of biodiesel. This study aims to investigate the optimum condition of three important process variables which are acid concentration, molar ratio of methanol and oil, and irradiation time with the 45oC of irradiation temperature for reducing FFA. The synthesis is assisted by ultrasonic irradiation. It conducted by acid esterification with H2SO4 and methanol. Optimization is conducted by Response Surface Methodology (RSM) with central composite design (CCD). The optimum condition of response for reducing FFA less than 1% were found to be 7.22:1 of methanol to oil molar ratio, 0.92% wt of H2SO4, and 26.04 minutes of irradiation time. It has been observed that ultrasonic system reduces FFA content significantly compared to conventional method.

scholarly journals Phytoremediation of Soil Contaminated with Nickel by Lepidium sativum; Optimization by Response Surface methodology

2013 ◽  
Vol 15 (1) ◽  
pp. 69-75 ◽  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Soil Samples ◽  
Lepidium Sativum ◽  
Nickel Concentration ◽  
Optimal Conditions ◽  
Polluted Soils ◽  
Independent Variables ◽  
Central Composite ◽  
Accumulator Plant

Phytoremediation is an alternative to traditional chemical and ways of treating polluted soils. The current study was carried out to investigate the phytoremediation of soil contaminated with nickel (Ni) by Lepidium sativum. Soil samples from 0 to 10 cm depth were collected. Lepidium sativum was transplanted in pots containing 5 kg of the collected soils. Central composite design and response surface methodology were employed in order to illustrate the nature of the response surface in the experimental design and explain the optimal conditions of the independent variables. Different concentrations for Ni (1 to 20 mg kg-1) and times for collecting samples (10 to 40 days) were used. The results showed the amount of Ni removed was ranged from 8.62 mg kg-1 (Ni concentration of 20 mg kg-1 and time for taking samples of 10 days) to 7.066 mg kg-1 (Ni concentration of 10.50 mg kg-1 and time for taking samples of 40days). Additionally, the findings explained that the Lepidium sativum is an effective accumulator plant for phytoremediation of Ni polluted soils. Optimum conditions for nickel concentration and time for taking samples were 19.66 mg kg-1 and 39.28 days, respectively. For the optimum condition, the amount of Ni removed was 10.8095 mg kg-1.

scholarly journals OPTIMIZATION OF TRANSESTERIFICATION OF TRA FAT WITH KOH/y Al2O3 CATALYST USING RESPONSE SURFACE METHODOLOGY

2009 ◽  
Vol 12 (13) ◽  
pp. 69-76
Author(s):  
Huong Thi Thanh Le ◽  
Tan Viet Le ◽  
Tan Minh Phan ◽  
Hoa Thi Viet Tran
Keyword(s):  
Response Surface Methodology ◽  
Reaction Time ◽  
Response Surface ◽  
Reaction Temperature ◽  
Catalyst Concentration ◽  
Molar Ratio ◽  
Result Show ◽  
Heterogenous Catalyst ◽  
Central Composite ◽  
Al2o3 Catalyst

In this study, biodiesel was produced from fat of tra catfish by methanolysis reaction with KOH/y-A12O3 heterogenous catalyst. This research was carried out using response surface methodology (RSM) based on four-variable central composite design (CCD) with a = 1,54671. The transesterification process variables and their investigated ranges were methanol/fat molar ratio (X1: 7/1 - 9/1), catalyst concentration (X2: 5%-7%), reaction time (X3: 60 min - 120 min), and reaction temperature (X4: 55 °C - 65 °C). The result show the biodiesel yield could be reach up to 92,8 % using the following optimized reaction condition: molar ratio of methanol/fat at 8,26/1, catalyst concentration of 5,79 %, reaction time of 96 min, and reaction temperature at 59,6 °C.

scholarly journals Statistical Optimization of the Induction of Phytase Production by Arabinose in a recombinant E. coli using Response Surface Methodology

2017 ◽  
Vol 26 (1) ◽  
pp. 57-64
Author(s):  
Abd-El Aziem Farouk ◽  
Anis Shobirin Meor Hussin ◽  
Ralf Greiner ◽  
Shareef Mohideen Ismail ◽  
Hamadah Mohd Nur Lubis
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Incubation Temperature ◽  
Expression System ◽  
Optimal Conditions ◽  
Phytase Production ◽  
E Coli ◽  
Central Composite Experimental Design ◽  
Full Factorial ◽  
Central Composite

The production of phytase in a recombinant E.coli using the pBAD expression  system was optimized using response surface methodology with full-factorial faced centered central composite design. The ampicilin and arabinose concentration in the cultivation media and the incubation temperature were optimized in order to maximize phytase production using 2 3  central composite experimental design. With this design the number of actual experiment performed could be reduced while allowing eludidation of possible interactions among these factors. The most significant parameter was shown to be the linear and quadratic effect of the incubation temperature.  Optimal conditions for phytase production were determined to be 100 µg/ml ampicilin, 0.2 % arabinose and an incubation temperature of 37ºC. The production of phytase in the recombinant E. coli was scaled up to 100 ml and 1000 ml.   

scholarly journals FOUR-FACTOR RESPONSE SURFACE OPTIMIZATION OF THE ENZYMATIC SYNTHESIS OF WAX ESTER FROM PALM KERNEL OIL

2010 ◽  
Vol 8 (1) ◽  
pp. 83-90 ◽  
Author(s):  
Erin Ryantin Gunawan ◽  
Dedy Suhendra
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Palm Kernel ◽  
Molar Ratio ◽  
Wax Ester ◽  
Central Composite Rotatable Design ◽  
Palm Kernel Oil ◽  
Kernel Oil ◽  
Substrate Molar Ratio ◽  
Central Composite

The synthesis of wax ester using refined, bleached and deodorized (RBD) palm kernel oil (PKO) and oley alcohol catalyzed by Lipozyme IM was carried out. Response surface methodology (RSM) based on a five-level, four-factor central composite rotatable design (CCRD) was used to evaluate the interactive effects of synthesis, of reaction time (5-20 h), temperature (20-50 oC), amount of enzyme (0.1-0.2 g) and substrate molar ratio (palm kernel oil to oleyl alcohol, 1:1-1:5) on the percentage yield of wax esters. The optimum condition conditions derived via RSM were reaction time 8.46 h, temperature 44.4 oC, amount of enzyme 0.182 g, substrate molar ratio 1 to 3.7. The actual experimental yield was 92.9 % under optimum condition, which good accordance to the maximum predicted value of 92.4 %.   Keywords: response surface methodology, central composite rotatable design, palm kernel oil, lipozyme, alcoholysis, wax ester

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