• Advances in environmental research
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• 제2권4호
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• pp.291-308
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• 2013

In the present study, an experimental design methodology was used to optimize the adsorptive removal of Basic Yellow 13 (BY13) using Turkish coal powder. A central composite design (CCD) consisting of 31 experiments was employed to evaluate the simple and combined effects of the four independent variables, initial dye concentration (mg/L), adsorbent dosage (g/L), temperature ($^{\circ}C$) and contact time (min) on the color removal (CR) efficiency (%) and optimizing the process response. Analysis of variance (ANOVA) showed a high coefficient of determination value ($R^2=0.947$) and satisfactory prediction of the polynomial regression model was derived. Results indicated that the CR efficiency was not significantly affected by temperature in the range of $12-60^{\circ}C$. While all other variables significantly influenced response. The highest CR (95.14%), estimated by multivariate experimental design, was found at the optimal experimental conditions of initial dye concentration 30 mg/L, adsorbent dosage 1.5 g/L, temperature $25^{\circ}C$ and contact time 10 min.

• Journal of Pharmaceutical Investigation
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• 제20권2호
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• pp.55-64
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• 1990

Soybean fatty acid, the largest byproduct in the production of soybean oil, was formulated for hand cream, oil in water emulsion base, to improve the suppleness and elasticity of skin. The stability of emulsion observed by a macroscopic method was used as a characteristic index for deciding an optimum formula of hand creams. The optimum formula of the most stable hand cream was obtained from polynomial regression equation, contour graphs and partial derivative graphs. The values of soybean fatty acid and stearyl alcohol in the obtained optimum formula were 9.75 and 14.75 w/w%, respectively, and sodium lauryl sulfate was not needed. Experimental value for the stability of hand cream prepared according to the optimum formula was 76,14 days, and the prediction value by computation method was 73.25 days. From the results of accelerated tests by elevated temperature, the stability of hand cream by optimum formula was 1.7 year at room temperature $(25^{\circ}C)$. The hand cream containing soybean fatty acid was found to be free of primary irritant substance to the skin by Draize technique.

• Journal of the Korean Wood Science and Technology
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• 제45권2호
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• pp.182-194
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• 2017

The optimum alkali pretreatment parameters (reaction time, reaction temperature and potassium hydroxide concentration) for facilitate the conversion into fermentable sugar (glucose) from steam exploded (severity log Ro 2.45) barley husk were determined using Response Surface Methodology (RSM) based on a factorial Central Composite Design (CCD). The prediction of the response was carried out by a second-order polynomial model and regression analysis revealed that more than 88% of the variation can be explained by the models. The optimum conditions for maximum cellulose content were determined to be 201 min reaction time, $124^{\circ}C$ reaction temperature and 0.9% potassium hydroxide concentration. This data shows that the actual value obtained was similar to the predicted value calculated from the model. The pretreated barley husk using acid hydrolysis resulted in a glucose conversion of 94.6%. This research of steam explosion and alkali pretreatment was a promising method to improve cellulose-rich residue for lignocellulosic biomass.

• 한국식품영양과학회지
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• 제19권3호
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• pp.234-238
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• 1990

The effects of salt concentration immersion time in a salt solution prior to air dehydration and heating of air temperature during dehydration upon the browning reaction and pyruvic acid content of air dried garlics to a 6.5% moisture content(wet basis) were analyzed by a response surface methodology(RSM), Those values were also predicted by using a second degree polynomial regression model. Heating of air temperature was the most significant factor affecting the both browning reaction and pyruvic acid content. Salt concentration had more influence to browning reaction than immersion time whereas immersion time was more impor-tant factor than salt concentration on a retention of pyruvic acid sugested different processing conditions. While the processing conditions to minimize the browning reaction(O.D=0.009) were 0.3% of salt solution 9 min of immersion time and 5$0^{\circ}C$ of air temperature compared to control(O.D=0.022) of air dehydration at 5$0^{\circ}C$ Pyruvic acid contents were maximized(174 $\mu$mole/g garlic solid) at the 0.1% of salt solution 3 min of immersion time and 5$0^{\circ}C$ of air temperature compared to control(147 $\mu$mole/g garlic solid) of air dehydration at 5$0^{\circ}C$

• Membrane and Water Treatment
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• 제6권4호
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• pp.293-308
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• 2015

Palm oil mill effluent (POME) was produced in huge amounts in Malaysia, and if it discharged into the environment, it causes a serious problem regarding its high content of nutrients and high levels of COD and BOD concentrations. This study was devoted on POME treatment and purification using an integrated process consisting of microalgae treatment followed by membrane filtration. The main objective was to find the optimum conditions as retention time and pH in the biological treatment of POME. Since after the optimum conditions there is a diverse effect of time and the process become costly. According to our knowledge, there is no existing study optimized the retention time and percentage removal of nutrients for microalgae treatment of POME wastewater. In order to achieve with optimization, a second order polynomial model regression coefficients and goodness of fit results in removal percentages of ammonia nitrogen ($NH_3-N$), orthophosphorous ($PO_4{^{-3}}$), COD, TSS, and turbidity were estimated. WinQSB technique was used to optimize the objective function of the developed model, and the optimum conditions were found. Also, ultrafiltration membrane is useful for purification of POME samples as verified by experiments.

• International Journal of Air-Conditioning and Refrigeration
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• 제16권1호
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• pp.1-8
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• 2008

Numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm(NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis is presented in this work. Reynolds-averaged Navier-Stokes(RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.

• 대한조선학회논문집
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• 제42권5호
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• pp.534-541
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• 2005

Until now, Korean shipyards have accumulated a great amount of data. But they do not have appropriate tools to utilize the data in practical works. Engineering data contains experts' experience and know-how in its own. It is very useful to extract knowledge or information from the accumulated existing data by using data mining technique This paper treats an evolutionary computation based on genetic programming (GP), which can be one of the components to realize data mining. The paper deals with linear models of GP for the regression or approximation problem when given learning samples are not sufficient. The linear model, which is a function of unknown parameters, is built through extracting all possible base functions from the standard GP tree by utilizing the symbolic processing algorithm. In addition to a standard linear model consisting of mathematic functions, one variant form of a linear model, which can be built using low order Taylor series and can be converted into the standard form of a polynomial, is considered in this paper. The suggested model can be utilized as a designing tool to predict design parameters with small accumulated data.

• 한국군사과학기술학회지
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• 제22권1호
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• pp.27-34
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• 2019

This paper presents a chamber pressure model development of K2 rifle by applying Gaussian mixture model. In order to materialize a real recoil force of a virtual reality shooting rifle in military combat training, the chamber pressure which is one of major components of the recoil force needs to be investigated and modeled. Over 200,000 data of the chamber pressure were collected by implementing live fire experiments with both K100 and M193 of 5.56 mm bullets. Gaussian mixture method was also applied to create a mathematical model that satisfies nonlinear, asymmetry, and deviations of the chamber pressure which is caused by irregular characteristics of propellant combustion. In addition, Polynomial and Fourier Regression were used for comparison of results, and the sum of squared errors, the coefficient of determination and root-mean-square errors were analyzed for performance measurement.

• Steel and Composite Structures
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• 제32권4호
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• pp.455-466
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• 2019

Despite the rapid advancement in computing resources, many real-life design and optimization problems in structural engineering involve huge computation costs. To counter such challenges, approximate models are often used as surrogates for the highly accurate but time intensive finite element models. In this paper, surrogates for first-order shear deformation based finite element models are built using a polynomial regression approach. Using statistical techniques like Box-Cox transformation and ANOVA, the effectiveness of the surrogates is enhanced. The accuracy of the surrogate models is evaluated using statistical metrics like $R^2$, $R^2{_{adj}}$, $R^2{_{pred}}$ and $Q^2{_{F3}}$. By combining these surrogates with nature-inspired multi-criteria decision-making algorithms, namely multi-objective genetic algorithm (MOGA) and multi-objective particle swarm optimization (MOPSO), the optimal combination of various design variables to simultaneously maximize fundamental frequency and frequency separation is predicted. It is seen that the proposed approach is simple, effective and good at inexpensively producing a host of optimal solutions.

• 한국가시화정보학회지
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• 제17권2호
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• pp.48-57
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• 2019

A straightforward strategy for particle image velocimetry (PIV) interrogation and post-processing has been proposed, aiming at reducing errors and clarifying vortex structures. The interrogation window size should be kept small to reduce bias error and improve spatial resolution. A spatial filter is then applied to the velocity field to reduce random error and clarify flow structure. The performance of three popular spatial filters were assessed: box filter, median filter, and local quadratic polynomial regression filter. In order to quantify random uncertainty, the image matching (IM) method is applied to an experimental dataset of homogeneous and isotropic turbulence (HIT) obtained by 2D-PIV. We statistically analyze the uncertainty propagation through the spatial filters, and verify the reduction in random uncertainty. Moreover, we illustrate that the spatial filters help clarify vortex structures using vortex identification criteria. As a result, PIV random uncertainty was reduced and the vortex structures became clearer by spatial filtering.