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In this study, electrochemical oxidation of combed fabric dyeing wastewater was investigated using graphite electrodes. The response surface methodology (RSM) was used to design the experiments via the central composite design (CCD). The planned experiments were done to track color changes and chemical oxygen demand (COD) removal. The experimental results were used to develop optimization models using RSM and the artificial neural network (ANN) and they were compared. The developed models by the two methods were in good agreement with the experimental results. The optimum conditions were found at 150 A/m2, pH 5, and 120 min. The removal efficiencies for color and COD reached 96.6% and 77.69%, respectively. The operating cost at the optimum conditions was also estimated. The energy and the cost of 1 m3 of wastewater required 34.9 kWh and 2.58 US$, respectively. The graphite electrodes can be successfully utilized for treatment of combed fabric dyeing wastewater with reasonable cost.

Titanium alloy is widely applied in aerospace, medical, shipping and other fields due to its high specific strength and low density. The purpose of this study was to analyze the formability of Ti6Al4V alloys at elevated temperatures. An accurate constitutive model is the basic condition for accurately simulating the plastic forming of materials, and it is an important basis for optimizing the parameters of the hot forging forming process. In this study, the optimization algorithm was used to accurately identify the high-temperature constitutive model parameters of Ti6Al4V titanium alloy, and the hot working diagram was established to optimize the hot forming process parameters. The optimal forming conditions of Ti6Al4V titanium alloy are given. Ti6Al4V alloy was subjected to high-temperature compression tests at 800–1000 °C and at strain rates of 0.01–5 s−1 on a Gleeble-1500D thermal/mechanical simulation machine. Each parameter of the Hansel–Spittel constitutive model was taken as an independent variable, and the accumulated error between the stress calculated by the constitutive model and the stress obtained by experimentation was used as an objective function. Based on response surface methodology, an inverse optimization method for identifying the parameters of the high-temperature constitutive model of Ti6Al4V alloy is proposed in this paper. An orthogonal test design was adopted to obtain sample point data, and a third-order response surface approximate model was established. The genetic algorithm (GA) was applied to reversely optimize the parameters of the constitutive model. To verify the accuracy of the optimized constitutive model, the average absolute relative error (AARE) and correlation coefficient (R) were used to evaluate the reliability of optimized constitutive model. The R value of the model was 0.999, and the AARE value was 0.048, respectively, indicating that the established high-temperature constitutive model for Ti6Al4V alloy has good calculation accuracy. The flow stress behavior of the material could be accurately delineated. Meanwhile, in order to study the formability of Ti6Al4V alloy, the hot processing map of the alloy, based on a dynamic material model, was established in this paper. The optimum hot working domains of the Ti6Al4V alloy were determined within 840–920 °C/0.01–0.049 s−1 and 940–980 °C/0.11–1.65 s−1; the hot processing map was verified in combination with the microstructure, and the fine and equiaxed grains and a large amount of β phase could be found at 850 °C/0.01 s−1.

In this paper, a reliability-based topology optimization (RBTO) for 3-D structures was performed using bi-directional evolutionary structural optimization (BESO) and the standard response surface method (SRSM). In order to get a stable optimal topology, the most recently-developed filter scheme was implemented with BESO, and SRSM was used to generate an approximate limit state function. These results were compared with the recently announced results of RBTO for 2-D structures, and the differences between the results for the 3-D and 2-D structures were examined. A cantilever beam and an MBB beam were selected as the numerical examples. The comparison showed that the optimal topologies of deterministic topology optimization (DTO) and RBTO for the 2-D and 3-D MBB beams, respectively, are very different. Specifically, the two-support member on the left hand side comes into being along the width for the 3-D case, but not for the 2-D case. This shows that RBTO for 3-D structures should be performed as part of the design process.

The pressure drop and conveying stability caused by the bend significantly affect the pneumatic conveying process of stiff shotcrete, which is the key to solving the problem of long-distance transportation. In this paper, the effects of different air velocities (32 m/s, 36 m/s, 40 m/s), water-cement ratios (0.1, 0.2, and 0.3), and bending-diameter ratios (4, 12, and 20) on the pressure drop of the elbow R1 and conveying stability R2 are studied using the response surface method. The conveying stability is characterized by the pressure variation coefficient (C.V). The response surface graph aids in the intuitive analysis of the effects of these variables. The results show that the impact of air velocity on R1 and R2 is exceptionally significant, and the interaction of each factor on the response value is analyzed. The response value and the quadratic polynomial regression equation between the various factors are obtained in addition to the flow characteristics of stiff shotcrete under different working conditions. The relationship established by the statistical processing of the experimental results can provide some reference for specifying the pressure loss model of stiff shotcrete.

Turbulent boundary-layer profiles on an aircraft surface were measured during flight by pitot rakes in an experiment at subsonic speeds. Because separate flights have different flight sequences in terms of time, it is not easy to compare boundary-layer profiles measured on different flights with the corresponding premised conditions directly. Using one flight as a reference, this paper proposes a method to find the closest flight condition for each time instance from data from other flights by calculating a residual norm in combinations of flight variables. The results show that the proposed method successfully finds the best matches of the time instances from the second flight with those of the first flight. In addition, applying the interpolation method using response surface methodology further improves the accuracy of evaluation in the flight range of Mach 0.4 to Mach 0.8. The total uncertainty level of the proposed interpolation method was found to be 5.7%. Although this level of uncertainty is expected to be reduced, the effectiveness of the proposed interpolation method was presented in conjunction with an evaluation of its applicability to determine the riblet effect in reducing skin-friction drag qualitatively.

Microvalves can play an essential role in transport and control of fluids for biomedical applications. These valves may face reliability issues as they can fail due to deterioration of the moving parts exposed to prolonged and repeated movements or handling fluids that contain particles of several microns in diameter. An alternative to valves with moving parts are microdiodes such as micro vortex diode, which offers high resistance to flow in one direction and much smaller resistance in the opposite direction. The present study is focused on developing a two-step computationally-based approach for design and optimization of micro vortex diodes. A numerical design optimization based on the Design of Experiment and Response Surface Method is employed to improve the efficiency of a micro vortex diode using geometrical parameters. The results of the optimization study suggest an optimal design with about 69% improvement in efficiency compared to the reference design.

This study pertains to the design optimization of a four-blade ceiling fan to enhance air circulation and energy efficiency. The sweep angle of the blade profile is nonlinear. The design of experiment (DOE) computational fluid dynamics (CFD) and response surface method (RSM) methods were used in parallel to find the optimal design solution. The design variables considered were inboard angle of attack, outboard angle of attack, blade sweep, and tip-chord length. Numerical simulations were conducted using steady state Reynolds-averaged Navier–Stokes (RANS) equations and the Spalart–Allmaras turbulence model. The baseline results were validated through experimental data. Subsequently, the DOE method was employed to generate the blade design which reduce the number of simulations without losing the influence of different geometric parameter interactions. The response variables studied were volume flow rate, mass flow rate, torque, and energy efficiency. The simulations exhibited that flow pattern has a distinct feature and is further classified into three groups. In the end, the optimal blade design was identified using response surface methodology (RSM).

Artificial streams were set up to test the relationship between near-bed water velocity and periphyton growth. Periphyton community samples collected from a Japanese stream were incubated for 44 days under a light intensity of 252 ± 72 μmol·photons/m2·s, a temperature of 20–25 °C, and three near-bed water velocity classes: low (<17.9 cm/s), moderate (17.9–32.8 cm/s), and high (>32.8 cm/s). A logistic model was applied to estimate the maximum net growth rate (μmax) and carrying capacity (Bmax). A response surface method was also applied to estimate chlorophyll a (Chl-a) and ash-free dry mass (AFDM) with respect to the independent variables (i.e., time and water velocity). We detected both the highest μmax (1.99 d−1) and highest Bmax (7.01 mg/m2) for Chl-a at the moderate water velocity. For AFDM, we observed the highest μmax (0.57 d−1) and Bmax (1.47 g/m2) at the low and moderate velocity classes, respectively. The total algae density in the region of moderate velocity at the end of the experiment was 6.47 × 103 cells/cm2, corresponding to levels 1.7 and 1.3 times higher than those at lower and higher velocities, respectively. Our findings indicated that the moderate near-bed water velocity provided favorable conditions for algal growth and corresponding biomass accumulation.

In this paper, for the first time, the role of manufacturing parameters of fused deposition modeling (FDM) on the shape memory effect (SME) is investigated by design of experiments. PLA-TPU blend with a weight composition of 30:70% is processed by melt mixing and then extruded into 1.75 mm filaments for 3D printing via FDM. SEM images reveal that TPU droplets are distributed in the PLA matrix, and the immiscible matrix-droplet morphology is evident. Box-Behnken design (BBD), as an experimental design of the response surface method (RSM), is implemented to fit the model between variables and responses. The shell, infill density, and nozzle temperature are selected as variables, and their effects on loading stress, recovery stress, shape fixity, and shape recovery ratio are studied in detail. An analysis of variance (ANOVA) is applied to estimate the importance of each printing parameter on the output response and assess the fitness of the presented model. The ANOVA results reveal the high accuracy of the model and the importance of the parameters. Infill density and nozzle temperature had the greatest and least roles on shape memory properties, respectively. Also, the values of shape fixity and shape recovery were obtained in the ranges of 58–100% and 53–91%, respectively. Despite many researches on 4D printing of PLA, low ductility at room temperature and high stress relaxation rate are its weakness, which are covered by adding TPU in this research. Due to the lack of similar outcomes in the specialized literature, this paper is likely to fill the gap in the state-of-the-art problem and supply pertinent data that are instrumental for FDM 3D printing of functional shape memory polymers with less material consumption.

Tobacco stem represents an underutilized agricultural by-product rich in bioactive secondary metabolites such as phenolics, flavonoids, alkaloids, terpenoids, and saponins. Efficient recovery of these compounds depends on appropriate extraction conditions. The aim of this study was to determine the optimal solvent volume and extraction temperature for maximizing the flavonoid content, phenolic concentration, and antioxidant activity of tobacco stem extract using RSM. A Central Composite Design was applied to evaluate the influence of solvent volume and heating temperature on total flavonoid content, total phenolic content, and antioxidant activity of the ethanol extract. The developed linear regression models demonstrated good predictive accuracy and non-significant lack-of-fit values, indicating model suitability. The optimization analysis predicted the optimal extraction condition at a solvent volume of 80 mL and a heating temperature of 65°C. This prediction was validated experimentally, yielding a total flavonoid content of 2.178 mg QE/mL, total phenolic content of 18.355 mg GAE/mL, and antioxidant activity of 71.159% inhibition. These results confirm that response surface optimization effectively enhances the extraction efficiency of bioactive compounds from tobacco stem, supporting its potential valorization as a natural antioxidant source.