Response Surface Methodology For Optimization Research Articles

Omnidirectional soft pneumatic actuators: a design and optimization framework.

Soft pneumatic actuators (SPAs) play a pivotal role in soft robotics due to their unique characteristics of compliance, flexibility, and adaptability. There are plenty of approaches that examine the modeling parameters of SPAs, aiming to optimize their design and, thus, achieve the most advantageous responses. Current optimization methods applied to SPAs are usually performed individually for each design parameter without considering the simultaneous effect all parameters can have on the output performance. This modeling shortcoming is essential to be addressed since customized SPAs are used in a variety of applications, each with different output requirements. This study provides a generalized design optimization framework for modeling the SPA performance for their motion profiles, the produced strain energy while being deformed, and their stiffness characteristics. Utilizing experimentally validated finite element methods, all geometrical and material parameters of the models are investigated in response surface methodology optimization using the central composite design approach. The results showcase the entire design space of omnidirectional SPAs, along with their output performance, providing guidelines to the end user for design optimization. The offering of this modeling process for SPAs can be adapted to the demands of any potential application and ensure the best performance with respect to the required output responses.

Ultrasonic assisted removal of methyl orange and bovine serum albumin from wastewater using modified activated carbons: RSM optimization and reusability

Abstract The removal of industrial pollutants from water remains a significant challenge in water treatment processes. This study investigated the efficacy of powder-activated carbon (PAC), thermally modified PAC (TPAC), and chemically modified PAC (CPAC) for removing bovine serum albumin (BSA) and methyl orange (MO) from simulated wastewater. After undergoing treatment, the BET surface area of TPAC increased to 823 m2/g, while that of CPAC increased to 657 m2/g compared to the initial surface area of pristine PAC, which was 619 m2/g. Batch adsorption experiments assisted by ultrasonication were conducted to evaluate the impact of solution pH, initial concentration, and contact time on the adsorption capacities (qmax) of BSA and MO. TPAC demonstrated superior performance, achieving qmax values of 152 mg/g for MO and 133 mg/g for BSA, compared to PAC, which provided qmax values of 124 mg/g and 112 mg/g for BSA, respectively. Furthermore, pH levels of 3 and 5 were identified as highly effective for the removal of MO and BSA from water, respectively. The adsorption kinetics of both MO and BSA followed pseudo2nd-order (R2 > 0.99) reaction kinetics under both batch and ultrasonic conditions, confirming the removal of contaminants through chemisorption. The adsorption trends also satisfied the Langmuir isothermal model, indicating the formation of a uniform monolayer during the adsorption process of these contaminants. To understand the simultaneous effect of all the variables, response surface methodology (RSM) using central composite design (CCD) was used to predict the adsorption capacities of CPAC. After five adsorption cycles, the removal efficiencies of MO (from 98% to 80%) and BSA (from 55% to 40%) decreased in the CPAC system. The results suggested that CPAC can be effectively utilized to remove MO from wastewater.

Optimization of the removal efficiency of three biodegradable chelating agents for soil cadmium

In recent years, there has been a significant increase in the release of cadmium-containing pollutants into the environment from mining, industrial emissions, wastewater irrigation and the use of chemical fertilizers and pesticides. This leads to the degradation of soil quality and poses a threat to human health. Chemical leaching remediation technology is an effective method for controlling Cd contamination in soil. However, the leaching agent has a low removal efficiency of heavy metals. In order to find more suitable environmentally friendly new leaching agents, this study investigates the effects of three biodegradable chelating agents PMAS, EDTMPS and GLDA on the removal of heavy metal Cd in soil in the single factor soil leaching experiment. The concentration of the chelating agents, the leaching time and the pH of the leaching solution were varied to study their effects. The Box-Behnken (BBD) effect based on RSM was used to design the experimental conditions to optimize the leaching process of three biodegradable chelating agents. The optimum conditions for Cd removal by PMAS, EDTMPS and GLDA were obtained as follows: concentration 7 %, pH = 3.61, reaction time 180 min; concentration 4.94 %, pH = 3.0, reaction time 180 min; and concentration 4.96 %, pH = 3.0, reaction time 180 min. The validation test results showed that the deviation from the experimental value is less than 3 % under the theoretically optimal washing conditions, confirming the reliability and accuracy of the response surface methodology optimization process, which provides a reference for the development of efficient, environmentally friendly and low-cost leaching agents.

Construction of artificial microbial consortia for efficient degradation of chicken feathers and optimization of degradation conditions.

Microbes within a consortium exhibit a synergistic interaction, enhancing their collective capacity to perform functions more effectively than a single species, especially in the degradation of keratin-rich substrates. To achieve a more stable and efficient breakdown of chicken feathers, a comprehensive screening of over 9,000 microbial strains was undertaken. This meticulous selection process identified strains with the capability to degrade keratin effectively. Subsequently, antagonistic tests were conducted to isolate strains of fungi and bacteria that were non-antagonistic, which were then used to form the artificial microbial consortia. The optimal fermentation conditions for the keratinophilic microbial consortia were determined through the optimization of response surface methodology. The results revealed that 11 microbial strains-comprising of 4 fungi and 7 bacteria-were particularly proficient in degrading chicken feathers. The artificially constructed microbial consortia (AMC) comprised two bacterial strains and one fungal strain. The optimal conditions for feathers degradation were identified as a 10g/L concentration of chicken feathers, a 2.6% microbial inoculation volume and a fermentation fluid pH of 9. Under these conditions, the degradation rate for chicken feathers reached a significant 74.02%, representing an 11.45% increase over the pre-optimization rate. The AMC developed in this study demonstrates the potential for efficient and economical process of livestock and poultry feathers. It provides innovative insights and a theoretical foundation for tackling the challenging degradation of keratin-rich materials. Furthermore, this research lays the groundwork for the separation and purification of keratins, as well as the development of novel proteases, which could have profound implications for a range of applications.

A column study on Cu (II) adsorption from synthetic solutions using phyto-mineral hybrid adsorbents: RSM optimization, regression modeling and isotherm studies

Abstract Herein we report a novel approach to synthesize hybrid adsorbents using moringa oleifera and zeolite. Three variants were prepared using zeolite mass fractions % of 0.25 %, 0.5 % and 0.75 % respectively. The hybrid adsorbents were investigated for Cu (II) removal from synthetic wastewater using fixed bed column. The lab-scale fixed bed column was designed for Cu (II) removal and optimized using Response Surface Methodology (RSM). The variable parameters included bed height, flow rate, metallic concentration and zeolite mass fraction %. As per results, higher zeolite mass fraction resulted in higher Cu (II) removal. Similarly, the higher bed height increased the removal % of Cu (II). On the other hand, both higher flow rate and metallic concentrations resulted in a declined removal. The highest removal of Cu (II) ions was indicated by hybrid adsorbent with zeolite mass fraction of 0.75 % with 96 % at 1 mL/min flow rate, bed height of 3 cm and metallic concentration of 5 ppm respectively. The maximum adsorption capacities (Qm) indicated by hybrid adsorbents were 19 mg/g (0.25 % Mass Fraction Z), 21.5 mg/g (0.5 % Mass Faction Z) and 24.5 mg/g (0.75 % Mass Fraction Z). The adsorption data best fitted Langmuir Isotherm with R2 value of 0.99 for all variants. When the adsorption data was analyzed using isotherms, data by all three variants best fitted Langmuir isotherm with R2 values of 0.99 for all the variants. Conclusively, higher mass fraction % of zeolite enhanced the removal capacity of Phyto-mineral hybrid adsorbents for Cu (II), whereas higher flow rates and metal concentrations resulted in a declined adsorption of the respective metal ions.

Nitric acid dissolution of germanium overlay in hard zinc slag to enhance germanium leaching and optimization of response surface methodology

With the rapid development of global digital economy and aerospace, the gap between the supply and demand of germanium is expanding, and the establishment of a new process for the deep leaching of germanium from hard zinc slag is imminent. In this paper, on the basis of analyzing the reasons for the low germanium leaching rate from hard zinc slag, a new process of germanium leaching enhanced by HNO3 dissolution of externally wrapped ZnFe2O4 is established, and response surface optimization is carried out. The PbggGe4O7 phase in hard zinc slag is externally wrapped with ZnFe2O4 phase, and the non-reaction between ZnFe2O4 and hydrochloric acid is the main reason for the low leaching rate of germanium from hard zinc slag, so it is necessary to add HNO3 to dissolve the external ZnFe2O4 in leaching, and then use hydrochloric acid to leach the PbGe4O7 containing germanium in the interior. The potential pH diagram of the Pb-Ge-Cl-H2O system was also plotted, indicating that increasing the concentration of chloride ions during hydrochloric acid leaching contributes to the generation of GeCl4 at low acidity. When the hydrochloric acid concentration was 134.65 g/L, the liquid–solid ratio was 6, the theoretical dosage of HNO3 was 0.3, and the leaching time was 236 min, the optimum leaching rate of germanium was 93.72%, which was 23.72% higher than that of germanium leaching from hard zinc slag.

Optimization of Medium for Lipid Production from <i>Lipomyces maratuensis</i> InaCC Y720 Using Statistical Experiment Design

<i>Lipomyces maratuensis</i> InaCC Y720 is a potential novel oleaginous yeast. Media-based production optimization has never been carried out using this strain. This study aims to define an optimized medium from 12 medium component factors, where the Taguchi method is used for screening significant factors of medium and the response surface methodology (RSM) is used to optimize the concentration of significant factors. According to Taguchi, glucose, yeast extract, and magnesium sulfate (MgSO<sub>4</sub>) have a significant influence on lipid accumulation, with their concentrations maintained at optimal levels through RSM optimization. Conversely, potassium dihydrogen phosphate, sodium hydrogen phosphate, and calcium chloride inhibit lipid accumulation, and copper(II) sulfate has the least influence, categorizing them as eliminated factors. The RSM-optimized medium increased lipid content by 3.6-fold compared to the initial medium. Glucose and yeast extract showed a positive correlation with lipid accumulation, suggesting potential for further optimization, while the optimum concentration for MgSO<sub>4</sub> was 0.15 g/L. This study is intended to serve as a reference for increasing lipid accumulation by <i>L</i>. <i>maratuensis</i> InaCC Y720.

Application of Response Surface Methodology for Optimization of Parameters in Metal Powder Reinforced Polyethylene Terephthalate Matrix Composite

Application of Response Surface Methodology for Optimization of Parameters in Metal Powder Reinforced Polyethylene Terephthalate Matrix Composite

Efficient adsorption of methyl red, methyl orange and bromothymol blue by polyamine resin: Role of linearity and size of carboxylate in enhanced encapsulation and molecular matching

Dyes constitute the major contribution to the environmental organic pollutants. Besides being hazardous to aquatic life, dyes are highly toxic and injurious to human health. Herein, we disclose the synthesis of a novel hyper cross-linked, dubbed as BPA-PEA, for the adsorptive removal of methyl red (MR), methyl orange (MO) and bromothymol blue (BTB). BPA-PEA displayed maximum adsorption capacities (qmax) for the adsorptive removal of these ionic dyes as 230.6 mg/g, 117.7 mg/g, and 80.42 mg/g for MR, MO and BTB, respectively. Density Functional Theory (DFT) simulations indicate a spontaneous binding process, with binding order closely aligns with the experimentally observed order (MR > MO > BTB). Moreover, the higher interaction in the resin-MR complex was believed due to the linearity and smaller size of the carboxylate group in the MR. Response Surface Methodology (RSM) optimization shows excellent suitability from their statistical parameter as well as low SSE value with the experimental values. The kinetic and isothermal data suggest that the adsorption process followed a chemisorption pathway and adsorption equilibrium was achieved within 2, 6, and 18 h for BTB, MR, and MO, respectively. A significant influence of pH was also observed in the adsorption of MO (5.5), MR (6.1), and BTB (5.3). The BPA-PEA was found to be thermally stable (Td = 348 °C) and mesoporous in nature, having a high surface area (78.3 m2 g−1). The adsorption mechanism is mainly governed by electrostatic interaction between the dyes and adsorbent, however, other adsorptive mechanism such as H-bonding interactions, hydrophobic interactions or π-π interactions were also involved. In addition, the adsorption efficiency of BPA-PEA was maintained for consecutive 5 cycles, with slightly decline (less than 5 mg/g for MR, MO, and BTB) in the adsorption capacity. Given the high adsorption capacity, short adsorption time, and reusability, BPA-PEA can serve as a promising adsorbent for the removal of anionic dyes from wastewater.

Optimization investigation of parameters for spot-welding of AA2014 and AISI316 dissimilar alloys

The objective of the research was to determine the exact process parameters required for spot-welding AA2014 and AISI316 alloys. The main focus was on achieving particular welding results, including nugget diameter, hardness, and tensile shear fracture load (TSFL). The central composite rotatable design model within the framework of a Response Surface Methodology (RSM) optimization approach, the study sought to intensify key spot weld process factors. The mechanical characteristics and nugget diameter of the welded joints were analyzed by carefully examining these factors to determine their significant effects. The investigation yielded crucial insights, revealing that the highest strength of welded joints, characterized by a nugget diameter of 5.982 mm, hardness of 149.6 VHN, and TSFL of 2.355 KN, was achieved at 3.4 kgf, when accompanied by 60 W power and a 2.5s duration. Notably, power emerged as the predominant factor driving the spot-welding process. Furthermore, microhardness and TSFL displayed direct correlations with power, while nugget diameter exhibited an inverse relationship. Moreover, rigorous statistical analyses, including F-tests and ANOVA, provided robust validation, indicating that the observed values fell comfortably within a 99.5% confidence interval for hardness, nugget diameter, and TSFL. These meticulously derived conclusions represent a significant stride towards establishing more standardized and efficient spot-welding protocols, particularly beneficial for the manufacturing sectors dealing with mild steel and aluminium materials.

SAMP Rao algorithm based minimization of the roughness of milled surface of Ti-6Al-4V

In order to solve optimization problems including machining responses as objectives, this study suggests a parameter-less method called the self-adaptive multi population (SAMP) Rao algorithm that does not rely on metaphors. When machining titanium alloys, achieving a good surface quality is a difficult process. In the current study, an effort has been made to reduce surface roughness during milling Ti-6Al-4V. Response surface methodology (RSM) was used in the experiment design to create a model for surface roughness using cutting parameters as variables. The developed model was tested in additional tests in addition to the primary experiments. It was shown that cutter speed and feed rate had the biggest effects on milled roughness, whereas depth of cut had very little of an impact. The model’s quality is demonstrated by the correlation coefficient (R2) 98%, which indicates that the model can explain 98% of the data. Later, a response surface-based desirability technique was used to minimize roughness of milled surface. The outcome of the proposed algorithm is compared with RSM optimizer. It has been noted that the outcomes achieved with the SAMP approach are more advantageous than RSM approach and found 18% minimum value of roughness of milled surface. Main reason to get better result in case of SAMP Rao algorithm is that it is based on the iterative search process with random values of cutting parameters with in defined range. SAMP Rao Algorithm provides cutting settings of 133.5 m min−1, 0.13 mm/tooth feed rate, and 2.06 mm of milling depth along with a minimal roughness of milled surface of 0.37 μm.

Implementation of RSM and ANN Optimization Approach for Natural Deep Eutectic Solvents-Based Extraction of Bioactive Compounds from Orange Peel.

The present investigation has focused on developing an eco-friendly method to extract bioactive compounds from orange peel using natural deep eutectic solvents (NADES). NADES-II composed of choline chloride (ChCl) and ethylene glycol (1:2) and 50% water shows the maximal extraction yield with higher antioxidant activity in terms of DPPH and ABTS scavenging activity with a high total phenolic content (TPC) and total flavonoid content (TFC). The microwave-assisted extraction (MAE) process was optimized using response surface methodology (RSM) and an artificial neural network (ANN). ANN showed a higher value of R 2 and lower values of other statistical parameters when compared to RSM. The ideal extraction conditions were optimized as a 13 min rising time, 52 °C temperature, a 21 min holding time, and a 20 mL/g liquid-to-solid ratio. MAE was compared with the conventional heating-stirring extraction (HSE) method using the NADES-II solvent under optimum conditions. The results show that higher extraction yield and antioxidant capacities (DPPH and ABTS), TPC, and TFC can be obtained from orange peel using the MAE process compared to the HSE process. Overall, this study shows an optimiztic approach for the extraction of bioactive compounds from an orange peel using eco-friendly solvents and microwave technology. It also highlights the potential of this approach for valorizing orange peel waste.

Study of factors affecting the magnetic sensing capability of shape memory alloys for non-destructive evaluation of cracks in concrete: Using response surface methodology (RSM) and artificial neural network (ANN) approaches

Currently, the field of structural health monitoring (SHM) is focused on investigating non-destructive evaluation techniques for the identification of damages in concrete structures. Magnetic sensing has particularly gained attention among the innovative non-destructive evaluation techniques. Recently, the embedded magnetic shape memory alloy (MSMA) wire has been introduced for the evaluation of cracks in concrete components through magnetic sensing techniques while providing reinforcement as well. However, the available research in this regard is very scarce. This study has focused on the analyses of parameters affecting the magnetic sensing capability of embedded MSMA wire for crack detection in concrete beams. The response surface methodology (RSM) and artificial neural network (ANN) models have been used to analyse the magnetic sensing parameters for the first time. The models were trained using the experimental data obtained through literature. The models aimed to predict the alteration in magnetic flux created by a concrete beam that has a 1 mm wide embedded MSMA wire after experiencing a fracture or crack. The results showed that the change in magnetic flux was affected by the position of the wire and the position of the crack with respect to the position of the magnet in the concrete beam. RSM optimisation results showed that maximum change in magnetic flux was obtained when the wire was placed at a depth of 17.5 mm from the top surface of the concrete beam, and a crack was present at an axial distance of 8.50 mm from the permanent magnet. The change in magnetic flux was 9.50 % considering the aforementioned parameters. However, the ANN prediction results showed that the optimal wire and crack position were 10 mm and 1.1 mm, respectively. The results suggested that a larger beam requires a larger diameter of MSMA wire or multiple sensors and magnets for crack detection in concrete beams.

Functionalized xanthohumol nanoemulsion: fabrication, characterization and bioavailability enhancement of bioactive compounds.

Xanthohumol is an isopentadienyl flavonoid in hops, which have several pharmacological effects. However, due to the poor bioavailability of xanthohumol, it cannot be widely used. In this study, solvent extraction combined with preparative liquid chromatography was used to separate and purify xanthohumol in hop residue. And the purity, yield and recovery of xanthohumol was 983.0 ± 2.1 g kg-1, 921.61 ± 5.65 g kg-1, and 5.41 ± 0.07 g kg-1, respectively. Response surface methodology optimization revealed that 216.75 g kg-1 ethyl oleate, 574.1 g kg-1 polyoxyl-35 castor oil (EL35) and 209.15 g kg-1 polyethylene glycol 200 (PEG200) produced the xanthohumol nanoemulsion with a loading capacity of 85.40 ± 0.33 g kg-1, mean droplet diameter of 42.35 ± 0.06 nm, and zeta potential of -21.78 ± 0.18 mV. Xanthohumol nanoemulsion has better relative stability. The relative oral bioavailability of xanthohumol nanoemulsion was increased by 1.76 times. These results provide a theoretical basis for the application of nanoemulsion containing xanthohumol in food and pharmaceutical industry. © 2024 Society of Chemical Industry.

Response surface methodology optimization of sodium diclofenac adsorption using activated carbon derived from falcata tree sawdust

The presence of sodium diclofenac in water is a significant problem due to its adverse effects on terrestrial and aquatic organisms. Thus, this study investigated the Falcata tree sawdust as the precursor of activated carbon for the adsorption of diclofenac in an aqueous solution. The characterization of falcata tree sawdust-activated carbon (FTSAC) was evaluated by SEM and FTIR analysis. The activated falcata sawdust converted to activated carbon has a 30 % yield. The optimal values for the operating parameters, FTSAC dosage, initial sodium diclofenac concentration, reaction time and pH, were determined using the central composite design (CCD) of the response surface methodology (RSM). The optimal removal efficiency suggested by CCD is 93.98 % with the optimum conditions of parameters of 0.80 g FTSAC dosage, 200 ppm initial sodium diclofenac concentration, 20 min reaction time, and pH 4. These optimal values of parameters were validated by an actual experiment, and the result (average removal efficiency: 92.08 %) is within a 95 % confidence interval. On the other hand, the pseudo-second-order (R2 = 0.9991) kinetic model depicts the rate of absorption of FTSAC adsorbing SD. Moreover, the Langmuir-Freundlich isotherm or Sips isotherm model (R2 = 0.9904) is the best-fit model that describes the heterogeneous adsorption dynamics of FTSAC surfaces. This study indicates that falcata sawdust can serve as a promising and viable alternative raw material to produce activated carbon.

Ultrasonic-Assisted Biphasic Aqueous Extraction of Polyphenols from Vaccinium Dunalianum Leaves: Optimization, Antioxidant, and Tyrosinase Inhibition Activities.

To optimize the ultrasonic-assisted biphasic aqueous extraction conditions for polyphenolic compounds from Vaccinium dunalianum Wight leaves and investigate their antioxidant and tyrosinase inhibition activities, single-factor experiments were conducted to investigate the effects of ethanol volume fraction (%), ammonium sulfate mass fraction (%), solid-liquid ratio (g/mL), ultrasonic temperature (°C), and ultrasonic time (min) on polyphenolic content during extraction. Based on these experiments, three key factors influencing extraction were selected for response surface methodology (RSM) optimization. The results indicated that under conditions of 26 % ethanol, 20 % ammonium sulfate, a solid-liquid ratio of 1 : 30, and extraction for 35 minutes at 50 °C, the polyphenol content reached 61.62 mg/g. The relative contents of 6'-O-caffeoylarbutin, β-arbutin, and chlorogenic acid were 34.45 %, 4.56 %, and 31.06 %, respectively. The DPPH⋅ and ABTS+⋅ scavenging rates were above 95 % and 96 %, respectively, and the ferric reducing ability exhibited a significant dose-effect relationship. The inhibition rates of monophenolase and diphenolase activities of tyrosinase were 43.84 % and 35.73 %, respectively. The optimized process for ultrasonic-assisted biphasic aqueous extraction of polyphenols from Vaccinium dunalianum Wight leaves demonstrated significant antioxidant and tyrosinase inhibition activities.

Development and evaluation of mechanistic model for standard SCR, fast SCR, and NO2 SCR of NH3-SCR over Cu-ZSM-5

Selective catalytic reduction (SCR) systems are an effective way of treating NOx emissions to meet increasingly stringent international emission standards. However, the difference of reaction temperature and catalyst location will restrict the reaction of SCR to some extent. Therefore, considering the different reaction conditions, it is necessary to analyze the relationship between them for the study of SCR reaction. In this paper, Cu-ZSM-5 is selected as the catalyst in the SCR reaction, and the effects of different temperatures and catalyst locations on NH3 molar concentration and NOx conversion under three different SCR are investigated. Firstly, a dynamic model of NH3-SCR is established and verified by the experimental data of fast SCR, standard SCR, and NO2-SCR in steady state. Then, the RSM (Response Surface Methodology) is used to further optimize NOx conversion rate. The optimal reaction conditions under the three SCR reactions were obtained by RSM optimization. The results indicate that both reaction temperature and catalyst location exert significant effects on NOx conversion under the three SCR reactions. Finally, the performance of NH3-SCR over Cu zeolite catalyst is predicted and further evaluated to provide combinations and frameworks for improved performance.

Electrochemical treatment of azo dye wastewater by dynamic flow diaphragm system: Response surface methodology optimization and energy consumption analysis

In this experiment, the degradation process of azo dye wastewater was studied based on the diaphragm double chamber electrochemical reactor, taking the mono azo dye amaranth as an example. Through the circulation flow of appropriate volume of wastewater in the cathode and anode chamber, the simultaneous action of cathode and anode was realized, and the degradation and decolorization efficiency of azo wastewater was improved while reducing energy waste. The optimal reaction conditions optimized by response surface methodology were as follows: the voltage was 20.74 V, the plate spacing was 4.89 cm, and the cycle speed was 60.66 rad / min. The optimal decolorization rate was 99.66 %. The energy consumption analysis of the dynamic flow diaphragm system electrochemical method and the static flow diaphragm system electrochemical method for the treatment of azo dye wastewater was compared and analyzed. In addition, the possible degradation process of azo dye wastewater by dynamic flow electrochemistry was inferred by ultraviolet spectroscopy and mechanism prediction analysis. The experimental results show the great potential of the dynamic flow membrane system process in the treatment of azo dyes.

Effect of seawater salinity, pH, and temperature on external corrosion behavior and microhardness of offshore oil and gas pipeline: RSM modelling and optimization

This research aims to investigate the effects of seawater parameters like salinity, pH, and temperature on the external corrosion behaviour and microhardness of offshore oil and gas carbon steel pipes. The immersion tests were performed for 28 days following ASTM G-1 standards, simulating controlled artificial marine environments with varying pH levels, salinities, and temperatures. Besides, Field emission scanning electron microscopy (FESEM) analysis is performed to study the corrosion morphology. Additionally, a Vickers microhardness tester was used for microhardness analysis. The results revealed that an increase in salinity from 33.18 to 61.10 ppt can reduce the corrosion rate by 28%. In contrast, variations in seawater pH have a significant effect on corrosion rate, with a pH decrease from 8.50 to 7 causing a 42.54% increase in corrosion rate. However, the temperature of seawater was found to be the most prominent parameter, resulting in a 76.13% increase in corrosion rate and a 10.99% reduction in the microhardness of offshore pipelines. Moreover, the response surface methodology (RSM) modelling is used to determine the optimal seawater parameters for carbon steel pipes. Furthermore, the desirability factor for these parameters was 0.999, and the experimental validation displays a good agreement with predicted model values, with around 4.65% error for corrosion rate and 1.36% error for microhardness.

Response Surface Methodology Optimization of Wear Rate Parameters in Metallic Alloys

The optimization of wear rate parameters in metallic alloys using Response Surface Methodology (RSM) has been experimentally performed. The wear rate, a critical factor affecting the durability and performance of metallic components, served as the response parameter, while track diameter, sliding speed, and mass difference were considered as independent variables. The Central Composite Design (CCD) experimental method systematically explored the response surface and optimizes the wear rate. A mathematical model was developed, revealing a significant p-value of 0.043 in the ANOVA table, indicating the collective influence of the independent variables on wear rate at a significance level of 0.05. Furthermore, the model demonstrates a substantial explanatory power, with R-squared of 69.45% and adjusted R-squared of 51.95%. The p-value calculated to be 0.60 for the statistical Lack of fit indicated a satisfactory model. These findings highlight the effectiveness of RSM in optimizing the experimental input values and offer valuable insights for enhancing the durability and performance of metallic alloys in various industrial applications. The obtained result addresses the problem of uncertainty inherent in optimal levels of input parameters wear experimentation.