Response Surface Optimization Research Articles

Heat transfer analysis for 3d ternary hybrid nanofluid flow with MHD and non-fourier flux impact over a linearly stretching surface: Response surface optimization

BackgroundCombining different-shaped nanoparticles enhances the mechanism of heat transfer. Nanoparticles can be spherical, cubic, rod, tube, helical, triangular, hexagonal, oval, or prismatic, and they are frequently combined with the base liquid. Biology and industry are two academic fields that are significantly impacted by nanotechnology. The use of hybrid nanoparticles to enhance heat transport in a working fluid has piqued the curiosity of numerous experts. Ternary hybrid nanofluids are frequently used in heat transfer applications because of have higher thermal conductivity than ordinary fluid, especially as heat exchangers. MotivationIn contemporary times, the amalgamation of liquids has assumed paramount significance in diverse domains including healthcare, production, naval academies, aerosol particle processing, instrument design, and so on. The non-Fourier flux and magnetic impact in three-dimensional flow characteristics using the linear Roseland approximation. Furthermore, ternary solid nanoparticles in a variety of densities and forms were included. Aim and objectiveThe primary goal of the research is in a three-dimensional rectangular closed domain stretching surface with Magnetic effect, linear thermal radiation and non-Fourier flux to analyze the heat and velocity transfer rate with different cases like Case-1: AA7072+SWCNT+MWCNT with PEG−water a base fluid, Case-2 Fe3O4+Diamond+TiO2 considered along as PEG−water a base fluid ternary hybrid nanofluid. Methodology: By transforming the three-dimensional model's governing PDEs into nonlinear ODEs. The ODE45 solver in MATLAB was utilized to construct the graphical representations of the numerical solution findings. Results & conclusionsIt is investigated how well different flow and temperature parameters function when changed. The analysis is also done on simulation findings for friction and heat transmission for different values. And transfer rate are higher in case-2 Fe3O4+Diamond+TiO2 than in case-1 AA7072+SWCNT+MWCNT with base fluid PEG−water. A collection of statistical and mathematical techniques for problem modelling and analysis is known as response surface methodology, or RSM. To guarantee that the response gets close to the desired maximum or minimum value, factorial variable settings are optimised using processes included in RSM. Residual R2 in Case-1 92.65%, Case-2 91.90% will represent the accuracy of the model.

Production optimization of food functional factor ergothioneine in wild-type red yeast Rhodotorula mucilaginosa DL-X01.

Ergothioneine (EGT) is a high-value food functional factor that cannot be synthesized by humans and other vertebrates, and the low yield limits its application. In this study, the optimal fermentation temperature, fermentation time, initial pH, inoculum age, and inoculation ratio on EGT biosynthesis of Rhodotorula mucilaginosa DL-X01 were optimized. In addition, the effects of three key precursor substances - histidine, methionine, and cysteine - on fungal EGT synthesis were verified. The optimal conditions were further obtained by response surface optimization. The EGT yield of R. mucilaginosa DL-X01 under optimal fermentation conditions reached 64.48 ± 2.30 mg L-1 at shake flask fermentation level. Finally, the yield was increased to 339.08 ± 3.31 mg L-1 (intracellular) by fed-batch fermentation in a 5 L bioreactor. To the best of our knowledge, this is the highest EGT yield ever reported in non-recombinant strains. The fermentation strategy described in this study will promote the efficient biosynthesis of EGT in red yeast and its sustainable production in the food industry. © 2024 Society of Chemical Industry.

Optimizing maintenance responsibility distribution in real estate management: A complexity-driven approach for sustainable efficiency

Efficient route management is critical for optimizing maintenance activities in real estate management. This study delves into the intricate task of allocating maintenance duties among building surveyors, a pivotal concern for property management firms. The primary goal of route planning is to enhance operational efficiency by minimizing travel time. To achieve this, the study explores three distinct algorithms: Saving, Nearest Neighbor, and an Evolutionary Algorithm (EA) customized with Dual Response Surface Optimization (DRSO). The integration of DRSO and EA enhances adaptability, allowing for dynamic responses to changes and improved allocation of maintenance tasks. Practical limitations, such as time and capacity, are considered through a case study involving a well-established building management organization. Results indicate that the Nearest Neighbor Algorithm generates 16–18 routes, the Saving Algorithm produces 18 routes, and the DRSO-driven EA also yields 18 routes. Significantly, the DRSO-driven EA consistently outperforms traditional methods, achieving a remarkable 17.7% reduction in route distance and an 18.8% reduction in journey time. In specific scenarios with 50 and 80 locations in Northeast and Central Bangkok, the DRSO-driven EA demonstrates practicality and efficacy. The algorithm's ability to address real-world challenges is underscored by these examples, showcasing its potential for broader implementation in real estate management. This study contributes significantly to the optimization of maintenance routes, presenting a clear roadmap for enhancing operational efficiency and customer satisfaction. Furthermore, it addresses the challenges posed by capitalism's growth constraints, offering insights for the adoption of sustainable economic practices in management, economics, and engineering.

Investigating the synergistic effects of carbon fiber and silica fume on concrete strength and eco-efficiency

The present study endeavors to quantitatively evaluate the performance of concrete by incorporating carbon fiber reinforcement and micro silica addition. A comprehensive experimental investigation is conducted to examine the effects of these two additives on the concrete properties. Additionally, an eco-efficiency analysis is performed to assess the environmental impact of the modified concrete. Furthermore, a response surface optimization technique is employed to optimize the concrete mix design based on desired performance criteria. The findings of this study provide valuable insights into enhancing the performance and eco-efficiency of concrete by utilizing carbon fiber reinforcement and micro silica addition. To accomplish this objective, varying percentages of CF (ranging from 0% to 0.80%) and different densities of micro silica (ranging from 0 kg/m3 to 50 kg/m3) were incorporated into the concrete mixtures. Subsequent tests were conducted to evaluate the mechanical properties, including compressive strength, split tensile strength, and flexural strength, at least 3 specimens for each mix were tested. Furthermore, the eco-strength efficiency of the concrete mixtures was assessed by determining the ratios of embodied carbon. The results demonstrate that the inclusion of 0.60% CF and 26.5 kg/m3 of micro silica in the concrete mixture yields the optimal proportion, leading to a significant enhancement in compressive strength (CS), split tensile strength (STS), and flexural strength (FS) by 54.11%, 80%, and 36.6%, respectively, compared to a control sample devoid of CF and micro silica. Through thorough experimentation, a response surface methodology (RSM) was employed to develop an optimized model. Consequently, the derived equations enable the calculation of the impact of adding carbon fiber to concrete.

Impact of tapered leading-edge micro-cylinder on the performance of wells turbine for wave energy conversion: CFD-optimization algorithms coupling study

Oscillating water column-based Wells turbine is one of the potential possibilities for wave energy conversion. The early turbine stall caused an early performance loss, limiting the power produced and the operating range. The present work intends to boost the output power and operating range of the Wells turbine by using a tapered leading-edge micro-cylinder. This design is unique in that the micro-cylinder's diameter and its distance from the leading-edge change along the blade span. A response surface optimization technique based on computational fluid dynamics (CFD) is used to determine the optimal dimensions of the new design. Utilizing the optimal new design in the upgraded Wells turbine significantly increases power output and operating range, specifically by 78.13% and 33.33%, respectively. According to comprehensive flow analysis, the novel micro-cylinder design generates a pair of vortices that successfully reduce axial flow velocities close to the suction side across a sizable portion of the blade span. This, in turn, results in the postponement of flow separation towards the trailing edge.

A Study of the Impacts of Measurement errors on Robust Parameter Design for Multi-response

Robust parameter design is a principle in quality improvement methodologies that is directed towards reducing the effects of errors which are either poised by the noise factors or the control factors. Response surface methodology is an effective approach to robust parameter design. Previous studies discussed Robust parameter design based on the response surface model by considering measurement errors in control variables for a single response variable. However, in process design, determining optimal levels of control variables is an important issue in some problems with different outputs. This study therefore investigates the impacts of measurement errors in the levels of control variables on processes with multiple quality characteristics (responses). Different variances of error were tested on the levels of control variables and the analysis of response surface modeling and optimization was performed. The result showed that as measurement errors in the levels of control variables increase, the coefficient of determinations for the multi-response and the expected quality loss deviates from what is obtainable in the initial state. It can be concluded based on the result however, that measurement errors in the levels of control variables exert impacts on robust parameter design for multi-response.

Photocatalytic mineralization of diisopropanolamine (DIPA) from natural gas industry wastewater under visible light irradiation: Response surface optimization of synthesis parameters

The photocatalytic mineralization of diiospropanolamin (DIPA) in aqueous solution was investigated employing modified TiO2 under visible light. Response surface methodology based central composite design (CCD) was used to explore the effect of different synthesis parameters. The analysis showed substantial impact (p < 0.0195) of operational factors and their interactions on DIPA mineralization during photocatalytic degradation. Model predictions closely aligned with experimental outcomes (R2 = 0.9706, Adj-R2 = 0.9442). The morphology analysis revealed spherical agglomerates with well-dispersed iron on TiO2, which was corroborated by Raman spectroscopy showing similar spectra to bare TiO2 however, increased intensity and broader peaks at higher iron concentrations. Additionally, X-ray Diffraction confirmed the crystalline nature of the synthesized nanocomposite, while BET surface area analysis demonstrated an increasing trend with metal loading. Under optimal conditions, with 5% Fe loading and 300 °C calcination for 1 h, the photocatalytic efficiency significantly improved, achieving 45.78% DIPA mineralization in the first hour and complete (100%) mineralization in 2 h. This represents a promising solution for addressing natural gas industry wastewater challenges. Future goals include further optimization for enhanced efficiency.

Response surface optimization of active peptides of Rana spinosa (Quasipaa spinosa) meat process and evaluation of immunomodulatory activity

Response surface optimization of active peptides of Rana spinosa (Quasipaa spinosa) meat process and evaluation of immunomodulatory activity

Dynamic Adsorption of a Cationic Dye onto Wool Fibers as Column-Filling Media: Response Surface Optimization and Fixed-Bed Adsorption Modeling.

This study reports a simple and low-cost method for water purification using recyclable natural fibers (coarse wool fibers) as column-filling media for adsorption in the dynamic mode. As an instance of a dissolved organic pollutant, a cationic dye (basic blue 9, BB9) was assayed. According to the Langmuir isotherm (recorded at 300 K), the calculated maximum adsorption capacity of the fibrous material was found to be 24.86 mg/g for the retention of BB9. Response surface methodology (RSM) was employed for the design of experiments and the model-based optimization of the adsorption process performed in the dynamic regime (fixed-bed column). The optimal conditions provided by RSM indicated an adsorbent column height of H = 13.5 cm and a feed flow rate of Fv = 3 mL/min; these operating parameters ensured a color removal efficiency of 92.56% after 240 min of contact time. The recorded breakthrough curve under the optimal conditions was further interpolated using five quantitative mathematical models (Adams-Bohart, Thomas, Yoon-Nelson, Yan, and Clark) to assess the dynamic behaviors in the fixed-bed column. The best goodness-of-fit was achieved for the Thomas and Yoon-Nelson models. Thus, the coarse wool fibers used in a fixed bed demonstrated a relevant efficiency in the removal of cationic organic pollutants from contaminated water.

Optimization of DLTS Hinges for the Assembly of the Solar Arrays of a Communication CubeSat

This paper demonstrates the analytical and numerical investigations for the obtainment of the predefined critical parameters of double-layer tape spring (DLTS) hinges. The DLTS hinge is utilized for the coupling between the solar panels to assist the accommodation and formulation of the assumed origami-based pattern of the solar arrays. They are examined for the assurance of safety, durability, non-permanent deformation, and stability from the stowed to the deployment configuration. Von Misses stress (σv) and steady-state moment simulations are investigated by varying the critical hinge design parameters of curvature radius (R), subtended angle (θ) and layer thickness (t). Two optimization models, Taguchi and response surface methodology/RSM, are utilized by employing the computational findings to obtain and validate the modified optimal geometric parameters within this analytical experiment. For the Taguchi method, the optimization of σv and the steady-state moment is accomplished with a t of 1.75–2.25 mm, R of 1.5–2.0 mm, and θ of 1–1.2°. Furthermore, the RSM model shows that the t, R, and θ parameters are determined to be 2.90 mm, 2 mm, and 1.35°, respectively. For optimization of the hinge design, both models should be considered for improved verification and accuracy of the results.

Fe electrocoagulation technology for effective removal of molybdate from water: Main influencing factors, response surface optimization, and mechanistic analysis

Excessive molybdate (MoO42–) in drinking water poses a potential hazard to human health. Herein, for the first time, Fe electrocoagulation (EC) was proposed for the removal of Mo(VI) from water. The effects of main aquatic and electrochemical factors on Mo(VI) removal were investigated. Results showed that, among the electrolytes (NaCl, Na2SO4, and NaNO3), NaNO3 obviously inhibited the anodic dissolution and Mo(VI) removal, and caused high energy consumption. NaCl was favorable for the reduction of energy consumption whereas its high concentrations inhibited Mo(VI) removal. Via using the response surface method with Box-Behnken design, the optimal process parameters for the maximum Mo(VI) removal were obtained as follows: pHi, 5.5–7.0; CD, 3.5–4.0 A/m²; ED, 0.5–0.9 cm. The analysis of variance demonstrated that initial pH, current density, and electrode distance had highly significant impacts on Mo(VI) removal (p-value < 0.01). The quadratic polynomial model was developed using the Mo(VI) removal efficiency as the response value. The Mo(VI) adsorption experiments demonstrated the effectiveness of adsorption during the Fe EC process. Results of flocs characterization by SEM-EDS, XPS, XRD, and FTIR showed that the main crystalline phases in the flocs included lepidocrocite (γ-FeOOH) and magnetite (Fe3O4), and no reduction reactions of Mo(VI) were observed. The mechanisms of Mo(VI) removal mainly involved flocculation, adsorption (electrostatic attraction and inner-sphere complexation), and co-precipitation. Continuous flow tests (172 h) using simulated groundwater showed an average Mo(VI) removal efficiency of 83.4 %. This study indicates that Fe EC is a promising water treatment technology for Mo(VI) removal.

Purification of dredged water by magnetic coagulation: Response surface optimization and dissolved organic matter removal characteristics.

In the present study, magnetic coagulation was used to treat dredged water and the response surface method was used to optimize process parameters. The dissolved organic matter (DOM) removal characteristics were characterized by three-dimensional fluorescence spectrometry and ultra-high resolution mass spectrometry. During the magnetic coagulation process, the suspended solids (SS) removal rate increased initially and then decreased under conditions of increasing magnetic powder dosage and stirring rate. After magnetic coagulation and precipitation for 20 min, the contents of SS, ammonia nitrogen, chemical oxygen demand, and total phosphorus in the treated dredged water met the requirements of the discharge standard (GB8978-1996, China). Three-dimensional fluorescence results showed that magnetic coagulation selectively removed fulvic acids and humic acid substances. After magnetic coagulation with precipitation for 10min and 20 min, the total relative content of lignins, tannins, proteins, lipids, aminosugars, unsaturated hydrocarbons, condensed aromatic structures, and carbohydrates decreased by 26.3% and 39.4%, respectively. After magnetic coagulation, the distribution range of small molecule DOM shifted to the low H/C and high O/C regions. This study provides a novel perspective for studies on the removal of DOM in dredged water by magnetic coagulation. PRACTITIONER POINTS: SS and DOM removal were significantly enhanced by the use of magnetic coagulation. SS removal efficiency was affected by stirring rate and magnetic powder dosage. Magnetic coagulation selectively removed fulvic acids and humic acid substances. DOM molecule shifted to low H/C and high O/C regions after magnetic coagulation.

Response surface methodology and optimization of hydrolysis conditions for the in vitro calcium-chelating and hypoglycemic activities of casein protein hydrolysates prepared using microbial proteases

Response surface methodology and optimization of hydrolysis conditions for the in vitro calcium-chelating and hypoglycemic activities of casein protein hydrolysates prepared using microbial proteases

Study on performance optimization of double screw-magnetic fluid combination seal

The magnetic fluid seal (MFS) is a new type of sealing method that offers the advantages of no leakage and low wear. Hence, it is widely used in rotary seals in coal, chemical, and electric power fields. However, at high speeds, the degradation and even failure of the sealing performance severely limits the application of MFS in engineering. Therefore, this study designed a combined sealing device comprising a double screw seal and MFS and optimized the pressure resistance of the screw seal using an orthogonal test in combination with the response surface optimization method. Thus, the pressure resistance could be raised to 3.1 times that before optimization. The effect of the sealing gap on the sealing pressure of the MFS was analyzed by numerical simulation, and an optimal sealing gap value of 0.2 mm was obtained. The results of the verification test showed that the performance of the combined seal was significantly better than that of MFS alone. When sealing liquids, the pressure resistance of the combined seal reached 3.3 times that of the MFS at 3000 rpm, which indicates the application potential of MFS in high-speed working conditions.

Optimization of Fermentation Process for New Anti-Inflammatory Glycosylceramide Metabolite from Aspergillus sp.

A novel ceramide compound, named Aspercerebroside A (AcA), was successfully isolated from the ethyl acetate layer of the marine symbiotic fungus Aspergillus sp. AcA exhibited notable anti-inflammatory activity by effectively inhibiting the production of nitric oxide (NO) in RAW 264.7 cells at concentrations of 30 μg/mL and 40 μg/mL, offering a promising avenue for the treatment of inflammatory diseases. To optimize the yield of glycosylceramide (AcA), a series of techniques, including single-factor experiments, orthogonal experiments, and response surface optimization, were systematically employed to fine-tune the composition of the fermentation medium. Initially, the optimal carbon source (sucrose), nitrogen source (yeast extract powder), and the most suitable medium salinity (14 ppt) were identified through single-factor experiments. Subsequently, orthogonal experiments, employing an orthogonal table for planning and analyzing multifactor experiments, were conducted. Finally, a mathematical model, established using a Box-Behnken design, comprehensively analyzed the interactions between the various factors to determine the optimal composition of the fermentation medium. According to the model's prediction, when the sucrose concentration was set at 37.47 g/L, yeast extract powder concentration at 19.66 g/L, and medium salinity at 13.31 ppt, the predicted concentration of glycosylceramide was 171.084 μg/mL. The experimental results confirmed the model's accuracy, with the actual average concentration of glycosylceramide under these conditions measured at 171.670 μg/mL, aligning closely with the predicted value.

Deep eutectic solvent-based ferrofluid for highly efficient preconcentration and determination of metronidazole by vortex-assisted liquid-phase microextraction under experimental design optimization

To determine metronidazole in water samples, we developed an environmentally friendly, efficient, and straightforward ferrofluid-based liquid-liquid microextraction sample pretreatment technique. It is coupled with a high-performance liquid chromatography-ultraviolet analytical technique known for its sensitivity, speed, and precision. The magnetic separation of metronidazole-containing ferrofluid from the matrix was effortlessly achieved through the application of an external magnetic field, eliminating the need for centrifugation. Response surface optimization was employed to systematically determine the key experimental parameters influencing extraction efficiency, including pH, NaCl concentration, ferrofluid volume, and vortex duration. With a low detection limit (0.116 ng mL−1), a broad linear range between 0.5 and 700 ng mL−1 was achieved at optimal conditions. Additionally, acceptable spiking recoveries (94.3–97.3 %) and RSD values (≤3.7 %) for intra- and inter-day precision were attained in water samples. In conclusion, the effectiveness of the vortex and ferrofluid combination, along with the convenience of collection and elimination of the need for centrifugation, bestows a highly valuable technique for determining metronidazole in water samples.

Design optimization of three‐dimensional geometry of a micro horizontal axis wind turbine blade using the response surface method

AbstractThis study presents an aerodynamic design optimization of a micro micro‐horizontal‐axis wind turbine (HAWT). To obtain an optimal design, it is essential to understand the design parameters and select the responsible factors that affect the blade efficiency. The aim of this work is to redesign a 3D micro‐HAWT to improve aerodynamic performance, through improving the distribution of chord length and twist angle along the blade. Performance analysis and flow visualization of the initial design and the optimal design were carried out using CFD analyzer. In the blade optimization design, eight significant input parameters were selected, five to characterize the chord length distribution and three to represent the twist angle along the blade. To maximize the efficiency, design points that are created by Design of Experiment (DoE) are evaluated through (Multi‐Objective‐Genetic Algorithm) MOGA method. The results showed a reduction on the separation effect area on the optimal blade surface compared to the initial one. The use of response surface optimization (RSO), when combined with CFD simulation, has proven beneficial in selecting the optimal HAWT design. Finally, the open source software (Qblade) was used to investigate and to compare the performance of the initial and optimum design. An efficiency enhancement of approximately 3.6% is achieved at tip speed ration TSR = 3.4.

A process capability function approach to multiple response surface optimization based on a posterior procedure

Multiple response surface optimization (MRSO) aims to determine a setting of input variables that simultaneously optimizes multiple responses. The process capability function (PCF) approach is an attractive alternative to MRSO because it considers both the mean and variance of the responses systematically through the process capability index. In MRSO, the responses are often in conflict. Thus, the preference information of a decision maker (DM) on the tradeoffs among the responses should be considered. However, the existing PCF methods are based on an unrealistic assumption that all DM preference information is given in advance. In this article, a posterior preference articulation procedure based on the PCF approach, called P-PCF, is proposed. P-PCF first generates nondominated solutions using the ε-constraint method and then allows the DM to select his/her preferred cluster or final solution using the K-means clustering method. The proposed method is illustrated using a well-known MRSO problem.

Design Optimization of a Hybrid-Driven Soft Surgical Robot with Biomimetic Constraints.

The current study investigated the geometry optimization of a hybrid-driven (based on the combination of air pressure and tendon tension) soft robot for use in robot-assisted intra-bronchial intervention. Soft robots, made from compliant materials, have gained popularity for use in surgical interventions due to their dexterity and safety. The current study aimed to design a catheter-like soft robot with an improved performance by minimizing radial expansion during inflation and increasing the force exerted on targeted tissues through geometry optimization. To do so, a finite element analysis (FEA) was employed to optimize the soft robot's geometry, considering a multi-objective goal function that incorporated factors such as chamber pressures, tendon tensions, and the cross-sectional area. To accomplish this, a cylindrical soft robot with three air chambers, three tendons, and a central working channel was considered. Then, the dimensions of the soft robot, including the length of the air chambers, the diameter of the air chambers, and the offsets of the air chambers and tendon routes, were optimized to minimize the goal function in an in-plane bending scenario. To accurately simulate the behavior of the soft robot, Ecoflex 00-50 samples were tested based on ISO 7743, and a hyperplastic model was fitted on the compression test data. The FEA simulations were performed using the response surface optimization (RSO) module in ANSYS software, which iteratively explored the design space based on defined objectives and constraints. Using RSO, 45 points of experiments were generated based on the geometrical and loading constraints. During the simulations, tendon force was applied to the tip of the soft robot, while simultaneously, air pressure was applied inside the chamber. Following the optimization of the geometry, a prototype of the soft robot with the optimized values was fabricated and tested in a phantom model, mimicking simulated surgical conditions. The decreased actuation effort and radial expansion of the soft robot resulting from the optimization process have the potential to increase the performance of the manipulator. This advancement led to improved control over the soft robot while additionally minimizing unnecessary cross-sectional expansion. The study demonstrates the effectiveness of the optimization methodology for refining the soft robot's design and highlights its potential for enhancing surgical interventions.

Effect and mechanism of iron-carbon micro-electrolysis pretreatment of organic peroxide production wastewater.

The wastewater from organic peroxide production has high chemical oxygen demand (COD) concentration and poor biodegradability, so it is necessary to find a cost-effective treatment method. The iron-carbon microelectrolysis (IC-ME) technology was used to pretreat the organic peroxide production wastewater, and the influence of reaction conditions on the removal effect of pollutants and the degradation mechanism were studied. The effects of initial pH, iron filings, iron-carbon ratio, and reaction time on the wastewater treatment were investigated by single-factor and response surface optimization experiments, and the degradation mechanism was analyzed by three-dimensional fluorescence spectroscopy, UV-Vis, and gas chromatography mass spectrometry (GC-MS). The experimental results showed that the COD removal efficiency was 35.67% and the biodegradability of wastewater was increased from 0.113 to 0.173 under the conditions of initial pH of 3.1, the dosage of iron filings of 30.5g/L, the ratio of iron-carbon of 1.01, and the reaction time of 122.8min, and the process of IC-ME for degrading COD of wastewater from the production of organic peroxide was consistent with the secondary reaction. The IC-ME process could decompose macromolecular organic compounds such as tyrosine proteins and aromatic proteins, and improve the biodegradability of wastewater. It provides a theoretical reference for the practical application of IC-ME to treat this type of wastewater.