Second-order Response Surface Research Articles

Multi-objective preform optimization for spherical hinge mandrel based on response surface methodology

The multi-objective optimization was studied in application of response surface method and orthogonal design for a preform design of vehicle thrust rod spherical hinge mandrel. Firstly, taking deformation uniformity and mold filling completeness as objectives, then an orthogonal experiment was designed to acquire main factors which influence total deformation quality. The effects of two main factors were precisely predicted through MATLAB and the results were discussed by optimal graphics. Secondly, on basis of optimized results, a second-order response surface model was established through equant design. The model was designed for preform re-optimization taking lower forging load and mold maximum effective stress as objectives. In application of preform optimization method, the best polytechnic parameters were selected, and qualified products were produced.

Application of RSM and ANN in Predicting Surface Roughness for Side Milling Process under Environmentally Friendly Cutting Fluid

The paper presents a potential study on prediction of surface roughness in side milling by optimization techniques approaches. Two methods, response surface methodology (RSM) and artificial neural networks (ANN) were used for optimized prediction. The model of surface roughness was expressed as the main parameter in side milling term of cutting speed, feed rate and axial depth of cut. Rotatable central composite design (RCCD) is employed in developing second-order response surface mathematical model. The ANN model using a multi-layer feed forward, back propagation and training function Levenberg-Marquardt (LM) algorithm with a single hidden layer. Vegetable oils have often been recommended as sustainable alternative cutting fluid since the ecological and health impacts in the use of mineral oil have been questioned and also the rising cost of mineral oil. The advantages of oxidative stability of coconut oil as vegetable oil were utilized in this study to investigate surface roughness of low carbon steel. The machining of ferrous alloy like steel is sometimes a difficult task. This study used uncoated tool because it is suitable when turning and milling alloy. Flood condition was selected because it has been proved effective at low cutting speed. The analysis predicted by RSM and ANN models resulted a good agreement between the experimental and predicted values. The results indicated that the ANN model predict with more accurate compared with the RSM model.

Parametric optimization of H-type finned tube with longitudinal vortex generators by response surface model and genetic algorithm

Low-low temperature electrostatic precipitator technology is one of the important ways for energy saving and emission reduction of coal-fired power plants. In order to further improve the dust removal efficiency and enhance waste heat recovery performance, a novel H-type finned elliptical tube heat exchanger with longitudinal vortex generators is proposed. To achieve the maximum heat transfer enhancement with the minimum friction factor augmentation, the response surface model and multi-objective genetic algorithm are adopted to optimize the design parameters. Firstly, combined with the finite volume method and the central composite design method, the second-order response surface model between the design parameters (the length, height, angle, and position of longitudinal vortex generators) and the objective functions (Nusselt number and friction factor) is established. Then, based on the response surface model, the Pareto optimal solution set is obtained by the multi-objective genetic algorithm. Finally, by comprehensively comparing Nusselt number, friction factor and performance evaluation criteria of Pareto optimal solutions, the optimal combination is determined. Compared with the H-type finned tube heat exchanger, the performance evaluation criteria of the optimized novel heat exchanger is improved by 48–55%, which contributes to improve the overall performance of low-low temperature electrostatic precipitator system. The findings of this paper may provide practical guidelines for researchers and designers to develop efficient heat exchangers.

Effect of design and kinematic parameters on energy requirement in inclined screw mixer

Introduction. Rational parameters and modes of an inclined batch screw mixer are validated to achieve the lowest energyintensive feed mixing under observance of the zootechnical requirements for the feed quality on uneven mixing. The establishment of functional dependences between parameters and modes enables to design power-efficient equipment for the on-farm feed production.Materials and Methods. Experimental studies of the feed mixing were implemented on an inclined screw batch feed mixer. The experimental design included variation of four independent factors: mixer shaft speed, filling ratio of the mixing chamber, mixing time, and mixing chamber angle. Mixing irregularity and energy intensity of the process were taken as optimization criteria characterizing the mixing efficiency.Research Results.The optimization criteria versus the variability level factor, which are two-dimensional sections of the second-order response surfaces, are plotted. The rational values at mixing irregularity of less than 5% were as follows: mixer shaft speed was 27.5-36.5 min-1 , filling ratio of the mixing chamber was 0.43–0.51, mixing time was 3.0–4.2 min, mixing chamber angle was 22°–25°. At such parameter values, the mixing irregularity will be minimal, and it will be 4.10– 4.18%, and the process intensity is from 2.08 to 2.16 kW • h/t.Discussion and Conclusions. The dependences obtained as a result of the experimental studies allowed establishing the domain of rational design parameters and modes of an inclined batch screw mixer. The results obtained can be used in further studies under the development of initial requirements for the creation of new technical means with a gravitation effect of intensive mixing.

Numerical Simulation of Propagation Characteristics of Hazardous Noxious Substances Spilled from Transport Ships

This study numerically investigates the propagation characteristics of hazardous noxious substances (HNSs) spilled from transport ships and suggests the metal model for predicting the HNS propagation velocity varied with the current velocity and HNS density. The commercial computational fluid dynamics (CFD) code ANSYS FLUENT (V. 17.2) was used for two-dimensional simulation based on the Reynolds-averaged Navier–Stokes (RANS) equation together with the standard k–ε model. The scalar transport equation was also solved to estimate the spatial and transient behaviors of HNS. The main parameters to analyze the near-field propagation characteristics of HNSs spilled from the ship were layer thickness, HNS concentration, and propagation velocity. It was found that advection becomes more dominant in propagating an HNS layer that becomes thinner as the current velocity increases. When the current velocity increased beyond a certain level (~0.75 m/s), the mixing effect made the HNS layer less dense but thicker. Consequently, lower-density HNS causes increased HNS concentrations at sea level. As the current velocity increased, the concentration distribution became homogeneous regardless of HNS density. In particular, the second-order response surface model provided for three variables on the basis of the numerical results for 15 cases with the use of the general least-squares regression method, showing a good fit. This model would be useful in estimating the propagation velocity of HNS spilled from a ship.

Optimal pile design of dolphin structure considering axial compressive pressure-bending moment ratio under offshore load conditions

This study proposes an optimal design of a dolphin structure under offshore load conditions such as berthing, mooring, wind, wave, and current loads. The design objective is to reduce the total weight of the pile structure by determining its diameter, thickness, and arraying direction with constraints of axial compressive pressure-bending moment ratio and total displacement. As design requirements, the stress has to be satisfied under the allowable compressive pressure-bending moment, and the total displacement of the steel piles should be less than 0.1 m on the upper deck. The structural analysis data are generated using Box–Behnken design based on the design of experiments. In the meta-model-based approximate optimization process, the pressure-bending moment ratio and total displacement are expressed using a backpropagation neural network, and the structural weight of the pile is approximated via a second-order polynomial-based response surface model. Compared with the initial design, the optimal solution of the total weight of the steel piles reduces by 27.37% under the satisfied constraint conditions. For the post-optimization study, the optimal sensitivity analysis with respect to the seabed level is conducted.

Using Window Regression to Gap-Fill Landsat ETM+ Post SLC-Off Data

The continued development of algorithms using multitemporal Landsat data creates opportunities to develop and adapt imputation algorithms to improve the quality of that data as part of preprocessing. One example is de-striping Enhanced Thematic Mapper Plus (ETM+, Landsat 7) images acquired after the Scan Line Corrector failure in 2003. In this study, we apply window regression, an algorithm that was originally designed to impute low-quality Moderate Resolution Imaging Spectroradiometer (MODIS) data, to Landsat Analysis Ready Data from 2014–2016. We mask Operational Land Imager (OLI; Landsat 8) image stacks from five study areas with corresponding ETM+ missing data layers, using these modified OLI stacks as inputs. We explored the algorithm’s parameter space, particularly window size in the spatial and temporal dimensions. Window regression yielded the best accuracy (and moderately long computation time) with a large spatial radius (a 7 × 7 pixel window) and a moderate temporal radius (here, five layers). In this case, root mean square error for deviations from the observed reflectance ranged from 3.7–7.6% over all study areas, depending on the band. Second-order response surface analysis suggested that a 15 × 15 pixel window, in conjunction with a 9-layer temporal window, may produce the best accuracy. Compared to the neighborhood similar pixel interpolator gap-filling algorithm, window regression yielded slightly better accuracy on average. Because it relies on no ancillary data, window regression may be used to conveniently preprocess stacks for other data-intensive algorithms.

Response Surface Methodology for Salmonella Inactivation during Extrusion Processing of Oat Flour

An increase in the number of foodborne outbreaks and recalls due to Salmonella in low-moisture foods has resulted in the need for the development and validation of process controls to ensure their microbiological safety. Furthermore, the Food Safety Modernization Act Preventive Controls for Human Food final rule requires food processors to validate their process controls to ensure food safety. The objective of this study was to develop a response surface model to predict Salmonella inactivation in oat flour, as affected by moisture, fat content, screw speed, and temperature. Oat flour was adjusted to different moisture (14 to 26% wet basis) and fat (5 to 15% [w/w]) contents and was then inoculated with a five-strain cocktail of Salmonella. Inoculated material was extruded through a single-screw extruder running at different screw speeds (75 to 225 rpm) and temperatures (65 to 85°C), without a die. Once steady-state conditions were attained, extruded samples were collected, cooled, and stored under refrigeration, and Salmonella survivors were enumerated. A split-plot central composite second-order response surface design was used, with the central point replicated six times. Temperature showed a significant ( P < 0.0005) positive effect on microbial reduction. Moisture content showed significant linear ( P = 0.0014) and quadratic ( P = 0.0005) effects, whereas higher fat content showed a significant ( P < 0.0001) protective effect on Salmonella destruction. The screw speed did not play a major role in inactivating Salmonella, but it had a significant ( P = 0.0004) interactive effect with temperature. Results indicated that a >5.5-log reduction was achieved in oat flour extruded at a temperature above 85°C at all moisture and fat contents evaluated at a screw speed of 150 rpm. The developed response surface model can be used to identify the extrusion process conditions to achieve a desired reduction of Salmonella based on the moisture and fat contents of the product.

Optimization of biodiesel production from Annona squamosa seed oil using response surface methodology and its characterization

ABSTRACTIn the present study, Annona squamosa seed oil has been evaluated as a potential feedstock for biodiesel production. The response surface methodology was used to determine the optimal conditions for the biodiesel production using a central composite design. A quadratic polynomial was developed to predict the response as a function of independent variables and their interactions and only the significant factors affecting the yield were fitted to a second-order response surface reduced 2 factor interaction (2FI) model. Four process variables were assessed at five levels. A biodiesel yield of 98.19% was obtained at optimum conditions: 7.53:1 methanol to oil molar ratio, 1.18 wt% catalyst concentration, reaction temperature of 59.55°C, and reaction time of 47.29 min.

The effect of intrinsic and extrinsic factors on moisture sorption characteristics of hard candy

This study assessed effects of intrinsic factors, composition and candy size, and extrinsic factors, storage temperature, and humidity, on moisture sorption characteristics of hard candy. Nine types of plain hard candy with various percentage of sucrose (45.0 to 65.0% wt/wt) and citric acid (0.0 to 1.0% wt/wt) were prepared. The prepared samples had surface area per weight ratio (SA/W) of 2.05 to 3.69 cm2/g. Moisture sorption isotherms of all candy formulations were built at 25 °C and 35 °C and were well-represented by Guggenheim-Anderson-de Boer (GAB) model (R2 between 0.9634 and 0.9960). Compositions and SA/W significantly affected moisture sorption characteristics of hard candies. Increasing citric acid content increased rate of moisture uptake, while increasing SA/W decreased absorption rate. Additionally, the predictive models for rate of moisture uptake of candies with different compositions and SA/W at 25 °C and 35 °C and 75% relative humidity based on second-order response surface methodology were developed and validated. Practical applications Moisture sorption isotherms built and the obtained models of moisture uptake could be used as a guideline to predict moisture sorption characteristics or to estimate shelf life of hard candies, with known compositions and/or storage conditions.

Application of Response Surface Methodology for Coffee Effluent Treatment by Ozone and Combined Ozone/UV

ABSTRACTThis paper reports a study using ozone (O3) and combined ozone/ultraviolet (O3/UV) processes for color removal and caffeine degradation from synthetic coffee wastewater using a second-order response surface methodology (RSM) with a three-level central composite face-centered (CCF) design. The effects of O3 concentration, initial pH, and reaction time were examined for both processes. The reaction time and pH were statistically significant for caffeine degradation and color removal. In the ozonation process, higher caffeine degradation and color removal were observed in alkaline pH, indicating that ozone attacks indirectly, consequently generating hydroxyl radicals. Regarding the ozone/UV process, it was observed that lower caffeine degradation and color removal occurred at neutral pH, indicating an adverse effect due to lower ozone dissolution and consequently the production of a smaller amount of free hydroxyl radicals. The achieved results showed that the techniques were efficient for color removal (85% and 99%, respectively) and caffeine degradation (88% and 98%, respectively).

Effects and interactions of gallic acid, eugenol and temperature on thermal inactivation of Salmonella spp. in ground chicken

The combined effects of heating temperature (55 to 65°C), gallic acid (0 to 2.0%), and eugenol (0 to 2.0%) on thermal inactivation of Salmonella in ground chicken were assessed. Thermal death times were determined in bags submerged in a heated water bath maintained at various set temperatures, following a central composite design. The recovery medium was tryptic soy agar supplemented with 0.6% yeast extract and 1% sodium pyruvate. D-values were analyzed by second-order response surface regression for temperature, gallic acid, and eugenol. The observed D-values for chicken with no gallic acid or eugenol at 55, 57.5, 60, 62.5, and 65°C were 21.85, 5.43, 2.83, 0.58, and 0.26min, respectively. A second-order polynomial model developed to inactivate Salmonella was found to be significant (p<0.0001) with a R2=0.95 and a no significant lack of fit (p>0.1073). Efficacy of the additives in increasing the sensitivity of the pathogen to heat was concentration dependent. The model developed in this study can be used by processors to design appropriate thermal process to inactivate Salmonella in chicken products used in the study and thereby, ensuring an adequate degree of protection against risks associated with the pathogen.

Application of response surface method and multi-objective genetic algorithm to configuration optimization of Shell-and-tube heat exchanger with fold helical baffles

A kind of shell-and-tube heat exchangers with fold baffles was proposed to eliminate the triangular leakage zones between adjacent baffles. An effective algorithm combing second-order polynomial response surface method and multi-objective genetic algorithm was adopted to study the effect of fold baffle configuration parameters on the performance of flow and heat transfer. The helical angle, overlapped degree and shell-side inlet velocity were chosen as design parameters, and the Nusselt number and shell-side pressure drop were considered as objective functions. The results show that both the Nusselt number and shell-side pressure drop increase with the decrease of helical angle and shell-side inlet velocity, and increase with the increasing overlapped degree. A set of Pareto-optimal points were obtained, and the optimization results illustrate a good agreement with CFD simulation data with the relative deviation less than ±3%. And the empirical correlations of Nusselt number and friction coefficient were obtained based on response surface method, the helical angle and overlapped degree were fitted into empirical correlations as correction factors for the first time. It is found that the adjusted coefficient of determination of the Nusselt number and friction coefficient is 0.943 and 0.999, respectively, which illustrate the fitting is correct and reliable.

Wafter design for totally enclosed electric machines

A computational fluid dynamics (CFD) model representing the effect of wafters in a totally enclosed electric machine is presented, introducing the most relevant theoretical assumptions and simplifications. The validation of the model is conducted through experimental measurements. From the CFD simulation data, a second-order response surface is developed using statistical tools, from which the wafters’ influence on the convective heat transfer from the stator end windings is predicted. Wafter design criteria are obtained from the response surface information. Finally, a specific case is analysed, showing through CFD simulations that temperatures in the machine are reduced by including wafters in the design.

Multi-Fidelity Modeling-Based Structural Reliability Analysis with the Boundary Element Method

In this work, a method for the application of multi-fidelity modeling to the reliability analysis of 2D elastostatic structures using the boundary element method (BEM) is proposed. Reliability analyses were carried out on a rectangular plate with a center circular hole subjected to uniaxial tension using Monte Carlo simulations (MCS), the first-order reliability method (FORM), and the second-order reliability method (SORM). Two BEM models were investigated, a low-fidelity model (LFM) of 20 elements and a high-fidelity model (HFM) of 100 elements. The response of these models at several design points was used to create multi-fidelity models (MFMs) utilizing second-order polynomial response surfaces and their reliability, alongside that of the LFM and the HFM, was evaluated. Results show that the MFMs that directly called the LFM were significantly superior in terms of accuracy to the LFM, achieving very similar levels of accuracy to the HFM, while also being of similar computational cost to the LFM. These direct MFMs were found to provide good substitutes for the HFM for MCS, FORM, and SORM.

Prediction and Optimization of Phase Transformation Region After Spot Continual Induction Hardening Process Using Response Surface Method

The spot continual induction hardening (SCIH) process, which is a modified induction hardening, can be assembled to a five-axis cooperating computer numerical control machine tool to strengthen more than one small area or relatively large area on complicated component surface. In this study, a response surface method was presented to optimize phase transformation region after the SCIH process. The effects of five process parameters including feed velocity, input power, gap, curvature and flow rate on temperature, microstructure, microhardness and phase transformation geometry were investigated. Central composition design, a second-order response surface design, was employed to systematically estimate the empirical models of temperature and phase transformation geometry. The analysis results indicated that feed velocity has a dominant effect on the uniformity of microstructure and microhardness, domain size, oxidized track width, phase transformation width and height in the SCIH process while curvature has the largest effect on center temperature in the design space. The optimum operating conditions with 0.817, 0.845 and 0.773 of desirability values are expected to be able to minimize ratio (tempering region) and maximize phase transformation width for concave, flat and convex surface workpieces, respectively. The verification result indicated that the process parameters obtained by the model were reliable.

Multi-objective optimization of a Stairmand cyclone separator using response surface methodology and computational fluid dynamics

The performance of a cyclone is generally assessed using the pressure drop and the collection efficiency of the cyclone. In the present paper, a multi-objective optimization of a classic Stairmand cyclone separator is executed using the response surface methodology (RSM), combined with computational fluid dynamics (CFD) techniques for minimizing the pressure drop and maximizing the collection efficiency. Ten cyclone geometrical factors are considered in this work. Three of them are studied using the RSM according to the results of the preceding screening experiments. The second-order response surface models for each response are successfully carried out using the central composite design (CCD) in the RSM. The desirability function approach is used to optimize the geometrical factors of the cyclone. In comparison to the reference model, the optimal cyclone model decreases the pressure drop by 20.70% and the cut-off size by 75.38%. The accuracies of the response surface models are confirmed and the correctness of the optimal cyclone model is also validated using CFD; the results indicate excellent performance and reliability of the response surface model and the RSM optimization result. According to the analyses of the obtained flow fields, there are several reasons why decreases in the cut-off size with a lower pressure drop are found in the optimal model. The primary reasons for improvements are optimized values of relevant geometrical factors, the production of a distinct, undisturbed downward flow, an increase in the tangential velocity at the near wall region, and a decrease in the peak tangential velocity.

Optimization of high pressure processing parameters of Indian white prawn (Fenneropenaeus indicus)

ABSTRACTThe effect of pressure (150, 250 and 350 MPa), ramp rate (200, 400 and 600 MPa/min) and holding time (3, 6 and 9 min) on the quality indices (dependent variable) of Indian white prawn (Fenneropenaeus indicus) was optimized using response surface methodology. Box–Behnken response surface design was used with 15 runs. Second-order response surface model was fitted to the experimental data and the model adequacy was measured by R2 value. The linear and quadratic effect of pressure, ramp rate and holding time was significant for tri-methylamine, total volatile base nitrogen and total plate count. Based on the ridge analysis and response surface plots, the optimum combination obtained was 250 MPa pressure, 400 MPa/min ramp rate and 6 min holding time for high pressure (HP) processing of Indian white prawn. Validation of the experiment indicated that the developed model was appropriate to predict quality indices in Indian white prawn processed by HP processing.

Configuration optimization of shell-and-tube heat exchangers with helical baffles using multi-objective genetic algorithm based on fluid-structure interaction

The configuration parameters of helical angle and overlapped degree of shell-and-tube heat exchangers with helical baffles have been discussed for the thermal-structural comprehensive performance. Based on fluid-structure interaction theory, a method on configuration optimization of shell-and-tube heat exchangers with helical baffles is introduced using second-order polynomial regression response surface combined with Multi-objective Genetic Algorithm. The results show that the heat transfer coefficient per unit pressure drop of shell-and-tube heat exchangers with helical baffles increases firstly and then decreases with the increase of helical angle, and decreases with the increase of overlapped degree under certain shell-inlet velocity. And the performance of flow and heat transfer is more sensitive to helical angle compared with overlapped degree. The maximum shear stress increases with helical angle, but it is almost unaffected by overlapped degree for mechanical properties of helical baffles. The objectives of optimization are the heat transfer coefficient per unit pressure drop maximizing and maximum shear stress minimizing with scope of allowable stress, and three optimal structures are obtained. The optimal results indicate that the heat transfer coefficient per unit pressure drop increases averagely by 14.1%, the maximum shear stress decreases averagely by 4.1%, which provides theoretical guidance for industrial design of shell-and-tube heat exchangers with helical baffles.

Effective Surface Preparation Technique for Cementitious Samples in Nanoindentation Testing

The nanomechanical properties of cementitious materials determined by nanoindentation largely depend on the surface roughness and intrinsic material porosity of the samples. Studies have shown that high surface roughness causes an overall reduction in the measured indentation modulus and hardness. Therefore, it is important to reduce the surface roughness to a desirable value by means of polishing. However, polishing causes damage to the cement matrix. Thus, the most challenging task is to obtain a reasonable surface roughness with minimum disturbance to the microstructure of the samples. This paper discusses an effective surface preparation technique that would meet the roughness criteria for nanoindentation. With the application of Taguchi method, the optimum parameter combinations and relative contributions of various controlling factors such as force, speed, and time of polishing were determined. A second-order response surface model was developed based on signal to noise ratio to establish the relationship between the controlling factors and surface roughness. Finally, the predicted surface roughness values from both Taguchi method and response surface model were compared with the experimental values of the optimized confirmation runs and a good agreement was achieved.