Response Surface Methodology Methodology Research Articles

Optimization of microwave-produced coal-derived char insulation foam using response surface methodology

A new char-based insulation foam (CIF) is developed using coal-derived pyrolysis char (PC) and lignin, a paper and pulp industry byproduct. In this study, CIF is prepared by adopting the microwave method and Response Surface Methodology (RSM) is utilized to optimize predictions about the properties such as thermal conductivity, foam texture, compressive strength, and pore distribution of CIF. The three independent variables including percent char content, lignin/char ratio, and foaming agent/polyol ratio are considered in the RSM methodology. The face-centered central composite design is selected to obtain 17 test runs. Optimization of the predicted responses is performed to find the recipe considering a composite desirability function. Confirmatory test results show agreement between the predicted and observed values, with the percent error ranging from 0.00 % to 11.35 %, thereby confirming the accuracy of the prediction equations. The optimized CIF exhibits a thermal conductivity of 0.0633 W/m.K and a compressive strength of 695 kPa making it comparable to or better than traditional building insulation products such as fiber insulation, polymer composite, particle board, and ceramic glass foam. Therefore, this new CIF has the potential to be used as an energy-saving insulation material for building envelopes.

The efficient elimination of lead ions from aqueous solution using MgCuAl-Layered double hydroxides@montmorillonite composite: A kinetic, isotherm and statistical analysis

In this study, a MgCuAl-layered double hydroxide (MCA-LDH)-based montmorillonite cationic clay (MMT) composite was synthesized via a co-precipitation method and then characterized using various analytical techniques, including BET surface area, TEM, XRD, FT-IR, and SEM/EDS analysis, to confirm the successful loading of LDH onto MMT. The material was subsequently used as a novel adsorbent for Pb2+ ion removal from aqueous solution in batch mode experiments. The effects of important variables on Pb2+ adsorption were investigated, and the values of these variables were optimized using the central composite design (CCD) of the response surface methodology (RSM). The results showed that the favorable conditions for the adsorption of Pb2+ onto the MCA-LDH@MMt composite were pH 5, an initial Pb2+ concentration of 85 mg/l, and an adsorbent dose of 0.225 g/100 ml. Under these conditions, the maximum adsorption efficiency was 89.1%. Using the RSM methodology, a quadratic polynomial equation was obtained that expresses the relationship between the adsorption efficiency and the effective parameters. The results show that pH and temperature had a greater effect on the adsorption efficiency. The pseudo-second-order model kinetically well fitted the adsorption process, while external mass transfer and intra-particle diffusion controlled the adsorption mechanics. The Langmuir isotherm model fitted the isotherm to the adsorption process, yielding a capacity of 132.83 mg/g. The thermodynamic study showed that the spontaneous adsorption of Pb2+ onto MCA-LDH@MMt composites is exothermic in nature. Moreover, there was a mere 30% reduction in the removal efficiency after five consecutive regeneration cycles. In conclusion, this work demonstrated that the MCA-LDH@MMt composite could be a promising adsorbent for the treatment of aqueous solutions contaminated with heavy metals.

OPTIMIZING FOAMING PROPERTIES AND FOAM MAT DRYING PROCESS OF CRANBERRY PULP: RSM AND TOPSIS APPROACH

In this study, the impact of independent variables, including licorice root extract (LRE), xanthan gum (XG), and whipping time (WT) on foam expansion and stability of cranberry pulp foam was investigated. In this respect, the foaming properties of produced foams were optimized using Response Surface Methodology (RSM) with a Box-Behnken design (BBD). Besides, the foam produced under optimal conditions (LRE = 0.22%, XG = 0.05%, and WT = 7.84 min) was dried using foam mat drying (FMD) at different temperatures (50, 60, and 70 °C). According to the results, the drying characteristics were improved with increasing temperature, and in general, the powder properties were significantly affected by temperature changes. Therefore, the ideal drying temperature (70 °C) for FMD of cranberry foam was determined by the TOPSIS method. As a result, the foaming properties and the FMD process of cranberry pulp foam were successfully optimized by RSM and TOPSIS methodology, respectively.

An Innovative Approach to Determine Programmed Intermittent Epidural Bolus Pump Settings for Labor Analgesia: A Randomized Controlled Trial.

Three settings are required on a programmed intermittent epidural bolus (PIEB) pump for labor analgesia: the PIEB next bolus (PIEBnb), PIEB interval (PIEBi), and PIEB volume (PIEBv). The ideal settings for these parameters are still unknown. We hypothesized a mathematical modeling tool, response surface methodology (RSM), could estimate 3 PIEB pump parameters while balancing 3 clinically important patient outcomes simultaneously. The study objective was to use RSM to estimate PIEB settings (PIEBnb, PIEBi, and PIEBv) while maximizing maternal satisfaction, minimizing the need for clinician-administered boluses, and optimizing the ratio of delivered/requested patient-controlled epidural analgesia (PCEA) boluses simultaneously. With institutional ethics approval, a double-blind randomized trial was completed in a tertiary care labor and delivery center. Nulliparous, English-speaking American Society of Anesthesiologists (ASA) physical status II patients aged 18 to 45 years at full term, single gestation in vertex presentation, in spontaneous labor and ≤7 cm cervical dilation were included. Patients with comorbidities, contraindications to neuraxial analgesia, using chronic analgesics, <152 cm, or body mass index (BMI) >45 kg/m2 were excluded. After informed consent, labor analgesia was initiated using 10 mL ropivacaine 0.2% with 10 µg/mL fentanyl solution and PCEA (volume 6 mL every 10 minutes). Patients were randomized to predetermined PIEB settings. RSM identified 3 pump settings that represented a stationary point that best maximized or minimized 3 outcomes simultaneously: PCEA ratio (a ratio closest to 1), clinician bolus (optimal is 0), and maternal satisfaction (visual analog scale, 0-100, ideal response is ≥90). Of 287 potential participants, 192 did not meet inclusion criteria or declined to participate, and 26 were withdrawn, leaving 69 patients for study inclusion. Using RSM, the suggested PIEB settings for all the primary study outcomes were as follows: PIEBnb = 29.4 minutes, PIEBi = 59.8 minutes, and PIEBv = 6.2 mL. These PIEB settings corresponded to the following clinical outcomes: maternal satisfaction at 93.9%, PCEA ratio at 0.77, and need for clinician bolus at 0.29. The dermatome sensory score was between T10 and T5 in 89% of the patients. The median lowest Bromage score was 4. This novel study used a mathematical model to estimate PIEB pump settings while simultaneously maximizing 3 clinical outcomes. Equally weighted clinical outcomes prevent maximal outcome optimization and may not reflect patient priorities. Future studies or quality improvement endeavors could use RSM methodology to estimate PIEB pump settings targeting optimal values for a single clinical outcome of determined importance to parturients.

Exploring waste marble dust as an additive in cementitious grouts for semi-flexible pavement applications: Analysis and optimization using RSM

This research aims to explore the potential utilization of waste marble dust (MD) within cementitious grouts for applications in semi-flexible pavements, a hybrid pavement type combining the benefits of both flexible and rigid pavements. MD was used to replace cement (ranging from 0 to 25%), combined with w/c ratios of 0.35 to 0.50, in the formulation of cementitious grouts. The assessment of grout characteristics encompassed evaluations of flowability and compressive strength (7d and 28d curing). Moreover, the microstructural characteristics of cement grouts incorporating MD were scrutinized through Scanning electron microscope-SEM and Energy dispersive X-Ray spectroscopy-EDS analyses. Additionally, response surface methodology (RSM) was used for experimental design, analysis, and the optimization of the factors (MD and w/c ratio). The significance of the model was examined through various statistical indicators. The optimal composition of cementitious grouts was determined using optimization technique within the RSM framework. Furthermore, optimal grout combinations were employed in fabricating semi-flexible mixtures and evaluated for Marshall stability, moisture susceptibility, indirect tensile stiffness modulus, dynamic modulus, compressive strength, and resistance to fuel spillage. The results indicated that an optimal combination of 15% waste marble dust and a 0.40 w/c ratio was identified through optimization techniques within the RSM methodology. Furthermore, Analysis of variance formula-ANOVA outcomes exhibiting a higher R² value (>0.80) and higher adequate precision (>4.0) underscore the significance of the proposed models, revealing a robust correlation between experimental and predicted data. The semi-flexible mixtures also showcase superior performance in terms of Marshall stability, stiffness, dynamic modulus, moisture resistance, and resistance to fuel spillage. Moreover, the integration of waste marble dust in cementitious grouts for constructing semi-flexible pavements not only addresses disposal concerns but also contributes to environmental sustainability.

Process optimization of microwave-assisted aqueous extraction of tannins and saponins from Malabar Spinach (Basella alba) leaves using ANN-GA and RSM methodology

The effect of microwave-assisted aqueous extraction (MAE) conditions on the recovery and quantification of tannins and saponins from Basella alba leaves has been explored. The experiment was carried out according to the Box-Behnken experimental design of response surface methodology (RSM) with 17 runs. The independent variables of the study were microwave power (100 to 300 W), treatment time (5 to 15 min), and feed/solvent ratio (0.025 to 0.05). The effect of extraction conditions on the response variables, total condensed tannin, total hydrolyzed tannin, and total saponin content, were predicted using RSM and artificial neural network-genetic algorithm (ANN-GA) methodology. The extracted values of total condensed tannin, total hydrolyzed tannin, and total saponin content, using RSM and ANN-GA were compared and evaluated for goodness of fit. The predicted values using RSM and ANN-GA models for total condensed tannin were found to be 0.18 and 0.26 mg TAE g−1, total hydrolyzed tannin were 0.14 and 0.15 mg TAE g−1, and total saponin content were 1.66 and 1.49 mg DE g−1, respectively. When compared to RSM, ANN-GA demonstrated higher value of R2 and lower values of other statistical parameters. Additionally, the predicted value of ANN-GA was more closely aligned with the experimental value.

Correlation between composition and adhesion properties of a zinc oxide-filled, acrylate pressure sensitive adhesive: An experimental design approach

A Box-Behnken response surface methodology (RSM) was adopted to provide a systematic insight on the adhesion properties of an acrylate-based, pressure sensitive adhesive (PSA) filled with nano-zinc oxide (ZnO) particles as a function of its composition. In addition to the nano-filler morphologies (needle- or plate-like) and their content (0–10 per hundred resin, phr), concentrations of triethyl citrate (TEC, 30–50 phr) plasticizer and oxalic acid (OX, 0.5–1.5 phr) crosslinking agent were also changed with respect to the base polymer. Tack and peel strength properties were measured as adhesive performance characteristics. According to the results, ZnO content and its morphology played no significant role (P < 0.05) in adhesion performance of the compositions made. In contrast, the more plasticizer was used, the more peel strength and tack properties were achieved. OX showed an inverse effect on the tack and peel strength properties at a less statistically significant level. A removable PSA was achieved adopting the RSM methodology to develop formulations, which resulted in a removable and repositionable PSA. To understand these effects, molecular structures of the adhesive ingredients and their interactions were thoroughly discussed.

Novel fluorometric protocol for assessing myeloperoxidase activity

Neutrophil myeloperoxidase (MPO) is an essential enzyme for the innate immune system. Measuring MPO activity is vital for understanding neutrophil characteristics and functions in various diseases. MPO activity can be measured using several methods, including spectrophotometric and fluorometric protocols. This paper introduces a fluorometric method for specifically quantifying MPO activity based on the H2O2-dependent oxidation of thiamine. We optimized this new method using the robust statistical approach response surface methodology (RSM) and Box Benken Design (BBD). We extensively examined the effects of several experimental parameters using the RSM methodology and determined the best conditions for accurate and sensitive MPO activity measurement. The optimal conditions were determined using the analysis of variance (ANOVA) for second-order polynomial equations. The resulting F-value (4.86) indicated that the model was significant. However, the lack-of-fitness F-value (1.79) suggested it did not differ significantly from the corresponding p-value. The greatest MPO activity (30 ± 2 U L−1) was obtained under optimum conditions, which were 1000 µM of H2O2, 10 min incubation time, and 1000 µM of thiamine. Our results suggest that this advanced fluorometric method has significant accuracy, sensitivity, and linearity up to 60 IU. The new and standard colorimetric methods also showed a good correlation. These results indicate that the new fluorometric method can be dependable and efficient for assessing MPO activity. The new method is characterized by excellent accuracy, sensitivity, and linearity, making it a valuable protocol for researchers and clinicians interested in assessing MPO activity.

Optimization of ultrasound-assisted aqueous 2-phase extraction system of carotenoid-allelochemicals from sweet potato roots by response surface methodologymethodology

Optimization of ultrasound-assisted aqueous 2-phase extraction system of carotenoid-allelochemicals from sweet potato roots by response surface methodologymethodology

Use Of Tannin Mimosa Based Natural Coagulants For Wastewater Treatment: Optimization and modeling using RSM Methodology

Industrial waters are discharges classified as hazardous because of their quantity, concentration or the physical and chemical properties of their constituents (turbidity, heavy metals, organic or phosphorus compounds) that threaten human health and the environment. Among the hazardous industrial waters, we distinguish industrial wastewater. These industrial discharges contain various products in insoluble or soluble form of mineral and/or organic origin, more or less biodegradable and sometimes toxic even in very low concentrations.&#x0D; In this work, the coagulation-flocculation process was used as a new technology approach for the treatment of this type of rejection. In this study, the jar test was used to determine the optimal conditions of the coagulation-flocculation process using mimosa tannins as natural coagulant by applying a response surface methodology (RSM) based on the bencken box design (BBD) of three levels with three factors (PH, coagulant dosage and setting time) . The BBD is successfully demonstrated to effectively determine the optimized parameters, where 97% of the water turbidity was removed with an initial value of 201 NTU for the optimal conditions of pH (5), coagulant dosage (10 mL/L), settling time (60 min). To evaluate the performance of optimization and modeling of coagulation flocculation process, the coefficients of determinations R2 and R2 adjusted were used, the results obtained clearly show that the R2 (97.20%) and R2 adjusted (92.16%) obtained confirm the validity of this mathematical model.

Experimental approach and optimization of hot air drying tomato waste using response surface methodology

ABSTRACT In the present work, an experimental investigation and mathematical modeling of tomato waste hot air drying (HAD) were conducted for drying temperatures of 50 and 60°C, and air velocities of 1 and 2 m s−1. Kinetics, mathematical modeling, and optimization of biological properties using response surface methodology (RSM) were investigated. Increasing the drying temperature from 50 to 60°C shortened the drying time by 5 and 20 min, respectively, for 1 and 2 m s−1 air velocities. The proposed mathematical model with the highest correlation coefficient of 0.9997 well described the moisture variation of tomato waste. Significantly high diffusivity was observed with values of 1.24 × 10−6 and 1.67 × 10−6 m2 s−1. Obtained analysis showed an increase in polyphenol (PPT) and flavonoids (TFC) and a decrease in lycopene content (LYC) and ascorbic acid (AA). Phenomenological modeling and RSM methodology indicated that both drying temperature and air velocity affected the content of TFC, LYC, and AA, whereas, for PPT, the temperature has a positive effect in contrast with negative of air velocity. Optimum drying time, PPT, TFC, LYC, and AA are 44.6 min, 227 mg GAE/g, 32.2 mg GAE/g, 517.92 mg/100 g, and 1.91 mg AAE/100 g, respectively. Optimal drying temperature and velocity were, respectively, 56.7°C and 1 m s−1.

Polyethylenimine-functionalized halloysite nanotube as an adsorbent for CO2 capture: RSM and ANN methodology

In this study, artificial neural networks (ANN) and response surface methodology (RSM) were used for the modeling and optimization of CO2 adsorption in polyethylenimine (PEI)-functionalized halloysite adsorbents. Five-level four-factor central composite design (CCD) using RSM was used to optimize adsorption operational conditions, namely temperature of 20–50 °C and pressure of 1–9 bar, and PEI concentration of 10–40 wt%. The optimum temperature, pressure, and PEI wt% values are 20 °C, 9.00 bar, 29.49 wt% for the input variables, and the adsorption capacity value of 8 mmol/g for the response parameter, respectively. The Bayesian Regularization algorithm optimization technique was used as a learning algorithm. The accuracy of the optimized model was calculated using the mean squared error (MSE) and R2. The MLP and RBF models best MSE validation performances at 100 and 30 epochs, respectively, were 0.00011 and 0.00055. After using the experimental data as training data with the ANNs and RSM approach, the resulting model can yield satisfactory results by considering the effects of independent variables and their interactions on the objective function. The correlation coefficient (R2) and the adjusted R-squared (Adj-R2) are 0.9868 and 0.9846, respectively. Additionally, the CO2 adsorption performances are modeled using ANN for the optimization purpose. Due to the appropriateness of the adequate precision or ratio values of more than 4, the model presented for the system is valid. The SBET and the total pore volume of IMSiNTs/PEI nanocomposites (IMP-30) were 33.62 m2/g and 0.312 cm3/g, respectively. The mass flux, diffusion coefficient, and mass transfer coefficient for carbon dioxide gas in the single system have measured 4.44⨯10−24 mol/m2.s, 3.93⨯10−20 m2/s, and 2.58⨯10−16 m/s in 14 min, respectively.

OPTIMIZATION OF DIFFERENT CHEMICAL PROCESSES USING RESPONSE SURFACE METHODOLOGY- A REVIEW

Several chemical and biological processes have been investigated and predicted using Response Surface Methodology (RSM) models. Response Surfaces Methodology is a useful instrument for designing laboratory-scale experiments that optimize and support the research outcomes with statistical analysis. It is a powerful statistical technique for complex variable study systems. The standard optimization (one component at a time) strategy is well-studied. However, it has significant drawbacks, such as requiring more experimental runs and time and failing to reveal the synergistic impact of processing parameters. It is a valuable instrument for process improvement. Recent research has shown, for instance, that RSM successfully optimizes biodiesel in fats and oils generated from diverse feedstocks. According to this study, Response Surface Methodology is the best cost-effective technique for maximizing environmentally friendly and sustainable methods applied to different experimental procedures. The current review reported RSM's application, theory, methodology, advantages, and limitations for different processes using different oil sources.

Optimized Protocol for Microalgae DNA Staining with SYTO9/SYBR Green I, Based on Flow Cytometry and RSM Methodology: Experimental Design, Impacts and Validation.

Multiple fluorochromes are extensively used to investigate different microalgal aspects, such as viability and physiology. Some of them can be used to stain nucleic acids (DNA). Well-known examples are SYBR Green I and SYTO 9, the latter of which offers several advantages, especially when combined with flow cytometry (FCM)—a powerful method for studying microalgal population heterogeneity and analyzing their cell cycles. However, the effects of these dyes on the microalgae cell physiology have not been fully elucidated yet. A statistical experimental design, using response surface methodology (RSM) with FCM was applied in this study to optimize the DNA staining of a non-conventional microalgae, Chromochloris zofingiensis, with SYBR Green I and SYTO 9, and to optimize the variables affecting staining efficiency, i.e., the dye concentration, incubation time and staining temperature. We found that none of these factors affects the staining efficiency, which was not less than 99.65%. However, for both dyes, the dye concentration was shown to be the most significant factor causing cell damage (p-values: 0.0003; <0.0001) for SYBR Green I and SYTO 9, respectively. The staining temperature was only significant for SYTO 9 (p-value: 0.0082), and no significant effect was observed regarding the incubation time for both dyes. The values of the optimized parameters (0.5 µM, 05 min and 25 °C) for SYTO 9 and (0.5 X, 5 min and 25 °C) for SYBR Green I resulted in the maximum staining efficiency (99.8%; 99.6%), and the minimum damaging effects (12.86%; 13.75%) for SYTO 9 and SYBR Green I, respectively. These results offer new perspectives for improving the use of DNA staining fluorochromes and provides insights into their possible side effects on microalgae.

Mineralization of diazinon by low-cost CuO-Kaolin nanocomposite under visible light based RSM methodology: Kinetics, cost analysis, reaction pathway and bioassay

A convenient and low-cost co-precipitation method was utilized for stabilization of CuO nanoparticles on Kaolin. The prepared CuO-Kaolin was characterized by XRD, FT-IR, SEM, EDX and pHPZC techniques. In this empirical study, response surface methodology (RSM) based central composite design (CCD) was applied for optimization of operational factors in the photocatalytic removal of Diazinon (DZ). Under optimum conditions, i.e. initial pH=7, initial DZ concentration=30 mg L-1, photocatalyst amount=0.4g L-1 and in the presence of oxalic acid, folic acid and sodium carbonate=5 mg L-1, about 87.23 % DZ removal was achieved by CuO-Kaolin after 180 min of reaction. The ANOVA results of the polynomial model prove that the model is quite meaningful (F-value> 0.001 and P-value< 0.0001). Further, estimated electrical energy per order consumption (EEO) for visible light (VIS)/CuO-Kaolin system was calculated as 213.66 kWh m−3 with operational cost (OC) utilization of 52.053 USD kg−1 that was revealed this process is highly feasible and economic comparing with other photocatalytic processes (VIS/CuO, VIS/Kaolin and VIS). Ten cycle experiments confirmed that the CuO-Kaolin propounded a satisfied stability and recycling potency. By applying the OFAT technique, 96.05 % of DZ degradation and 79.19 % of DZ mineralization could be achieved after 180 min. The five main compounds produced during the VIS/CuO-Kaolin embracing 2-isopropyl-6-methyl-4-pyrimidinol (IMP), diethyl phosphonate, diazoxon, hydroxydiazinon, and diazinon methyl ketone are formed in the path of DZ degradation. The results of toxicity in the photocatalytic removal of DZ by D. magna showed LC50 and TU 48 h equal to 18.79 and 5.32 vol percent.

Tribological study and parameters optimisation of CNT added glass fibre reinforced polymer composite sliding under inert environment

ABSTRACTThe primary goal of this research is to examine the effect of loads, sliding velocity, and sliding distance on CNT added glass fibre reinforced polymer composite sliding in the inert gas condition. The wear performance of the CNT added GFRP composite sliding towards the steel alloy wheel was analysed by important tribological parameters. The results clearly show the subjective influences of the wear parameters and their impact on the rate of wear and the coefficient of friction (COF). The Response Surface Methodology (RSM) confirms the potential spectrum of responses. Also, it defines the optimum value of process factors like applied load, sliding distance, and sliding velocity, which results in a decreased response over the long life of the composite applied. The optimum solution for wear rate and COF, predicted using the design of experiment (DOE) technique in conjunction with the RSM methodology, allows users to choose the appropriate wear rate and COF combination. The asperities on the disc and the pin are well separated under inert gas conditions. Furthermore, because asperity contacts provide the least frictional heat, the development of wear debris is significantly delayed. As a result, the COF and wear rate are both at their lowest.

An Investigation of Performance and Emissions of Diesel Engine Using Heterogeneous Catalyst Jatropha Biodiesel: A Sustainable Model Using Taguchi and Response Surface Methodology

Abstract Excessive consumption of fossil fuels has exacerbated global warming and led to an increase in air pollution levels in the environment. The increasing oil demand prompted recent research to explore the future application of alternative, eco-friendly fuels for diesel engines. Jatropha biodiesel has been produced from JCO, using heterogeneous catalyst (CaO) through transesterification process. In this study, the performance and emission characteristics of an engine powered by a Jatropha biodiesel blends have been investigated. The application of response surface methodology (RSM) coupled with Taguchi method for optimization of engine input parameters is promising approach to derive the most accurate optimized models for output responses. Input parameters such as biodiesel blend, load, CR, and FIP were selected, experiments were designed as per L18 orthogonal array in Taguchi, and CCFCD L20 design matrix for RSM methodology. Injection timing is an essential engine characteristic, which has a considerable effect on the ordering emissions. If injection is done early, the starting air temperature and pressure are lower, which means the ignition delay will rise. The ignition delay may begin at any time after the injection begins, resulting in somewhat increased temperature and pressure initially but which then rapidly declines as the ignition delay progresses. The optimal setting of engine input parameters is recorded at 270 bar fuel injection pressure, compression ratio of 18, 7.61 kg load, and 25% blend of Jatropha biodiesel with diesel for optimum BTHE, BMEP, BSFC, Pmax, CO, and NOx emissions. Experimental results are compared with optimum output responses and deviations are found within the accepted range of errors.

Cryptococcus albidus D24'ten Lipaz Üretimi Üzerindeki En Etkili Besin Maddelerinin Öneminin Belirlenmesi

In this study, the optimization of the medium components used for the production of lipase enzyme from Cryptococcus albidus D24 was performed using the Plackett-Burman statistical design method (PBD), and the most important nutrients affecting the production of lipase enzyme from D24 strain were determined as the first step. According to PBD, the highest lipase activity (19.34 U/ml/min) was obtained with medium including Tween 80 (X2) 2.5% (v/v), and (g/L) Peptone (X4) 8.0, Yeast Extract (X6) 7.5, Beef Extract (X7) 7.5, Malt Extract (X8) 7.5, NH4Cl (X9) 6.0, NaNO3 (X10) 1.5, (NH4)NO3 (X12) 6.0, (NH4)HCO3(X13) 6.0, MgSO4.7H2O (X15) 1.0, and KH2PO4 (X16) 2.0 at the end of 144 h cultivation. Regarding the concentration effect (CE) values obtained from PBD, NH4Cl (CE=7.1587), olive oil (CE=3.5544), (NH4)HCO3 (CE=3.0747), and tryptone (CE=2.1427) were evaluated as the more effective nutrients among the sixteen compounds studied. After that, the optimum concentrations of these effective compounds were experimented with Response Surface Methodology (RSM). Experimental results showed that the medium containing olive oil (X3) 1.5% (v/v), and (g/L) tryptone (X5) 3.0, NH4Cl (X9) 7.5, and (NH4)HCO3 (X13) yielded maximum lipase activity (12.03 U/ml/min) compared to other studied compounds. Although the maximum lipase activity obtained with RSM methodology was lower than that obtained by PBD, the cost of the nutrients used to produce one-unit enzyme is 0.104 Euro in the PBD, while only 0.0277 Euro is spent in RSM. In other words, the production of lipase using compounds coded X3, X5, X9, and X13 provides a cost-effective process.

Investigation of a spherical pendulum electromagnetic generator for harvesting energy from environmental vibrations and optimization using response surface methodology

A fundamental step towards the industrial application of an energy harvester device is the optimization of the output electrical power according to environmental conditions. In the present work, designing a pendulum spherical electromagnetic generator (S-EMG) is considered for harvesting energy from environmental vibrations with frequencies less than 12 Hz. Low frequencies pose significant challenges for vibration energy harvesters. The spherical structure creates a uniform and radial magnetic field, so the outputs will not depend on the direction of motion. Performance of S-EMG is evaluated considering different conditions, including the frequency, the load resistance, and the pendulum cord density. The output power density is optimized using the response surface methodology (RSM) based on the central composite design and the desirability function. In addition, the quadratic response surface regression model was used to predict the results. The optimized parameters were found as 5.966 Hz, 93.138 Ω, and 1154.070 kg/m3, for frequency, load, and density, respectively. The predicted power density was 4.357 µW/cm3, which is significant despite of the light weight and small size of the device. The results were also validated by re-testing inside and outside the design ranges. Furthermore, the importance of input parameters on system performance was evaluated using analysis of variance, which shows that frequency and density have the most effect (30.93 % and 30.66 %, respectively) on output power density. The RSM methodology is found to be helpful in determining the appropriate specifications for the energy harvesting device versus different environments.

Enhancing EDM performance characteristics of Inconel 625 superalloy using response surface methodology and ANFIS integrated approach

The objective of the present work is to find out the optimal level as well as the influence of the electrical discharge machining (EDM) process on material removal rate (MRR), surface roughness (SR), and tool wear rate (TWR). The machining is carried out on Inconel 625 superalloy by using a copper tool electrode in a kerosene submerged medium. The optimum level of input parameters such as current, pulse on time (Ton), pulse off time (Toff), and gap voltage are calculated to achieve maximum MRR and minimum SR and TWR. L27 orthogonal design is used to perform the experiments and optimum levels of MRR, SR and TWR have been obtained by the response surface methodology (RSM) and adaptive network-based fuzzy inference system (ANFIS) approach. Analysis of variance (ANOVA) is used to identify the significant and non-significant parameters. For implementing, RSM methodology, the Design Expert 13 software was used for the optimization and modelling of the experimental data. MATLAB R20b software was utilized for developing the ANFIS model. It is found that the pulse on time (Ton) and pulse off time (Toff) are the significant parameters for MRR and SR and more wire wear increases as the value of pulse on time (Ton) increases. The obtained quadratic RSM model is found significant for MRR, SR, and TWR. Similarly, ANFIS proved to be accurate for the optimization of output responses with model accuracy percentages noted as 95.55% for MRR, 90.35% for TWR, and 97.82% for SR. The obtained results show that the predicted values and experimental values are very well suited for the proposed objective. The obtained data can be utilized for the EDM industry during the machining of Inconel alloy.