• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.275-282
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• 2006

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolernce of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or etimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte Carlo simulation and got the probabilistic sensitivity. The sensitivity of structural response with respect to in constant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• Current Research on Agriculture and Life Sciences
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• v.32 no.2
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• pp.67-73
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• 2014

Mulberry fruits were semi-dried using hot air ($60-100^{\circ}C$) or cool air ($20-40^{\circ}C$), and the effects of the drying temperature and processing time on the quality of the final dried mulberry fruits were investigated. Response surface methodology was employed to establish a statistical model and predict the conditions resulting in minimal loss of the total phenolic content (TPC) and ascorbic acid. Thus, using overlapped contour plots, the optimal conditions for producing semi-dried mulberry fruits, which reduced the moisture residue to 45% and minimized the nutrient losses of TPC and ascorbic acid, were determined for the hot-air process ($60.7^{\circ}C$ for 5.4 h) and cool-air process ($34.8^{\circ}C$ for 23.3 h). Plus, a higher drying temperature was found to lead to a faster loss of moisture and ascorbic acid, while the TPC was significantly decreased in the cool-air dried mulberry fruits due to the higher activity of polyphenol oxidase between 30 and $40^{\circ}C$.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.10
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• pp.1196-1203
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• 2011

Statistical optimum methodology of table of orthogonal array, ANOM, ANOVA and RSM are applied to formulate optimum allocation design with design variables. It can be minimized average SPL of control volume, the objective function in closed system by optimal allocated positions of absorbing material. Structural natural frequency and acoustic natural frequency of cavity are analyzed by FEM and BEM in the closed system. Using BEM, average SPL of specific control volume is calculated according to the condition before using absorbing material and after using it. It is shown that noise is reduced by $5.02dB_{RMS}$ by absorbing material located at optimal position and minimum $1.83dB_{RMS}$ and maximum $3.47dB_{RMS}$ by the table of orthogonal array.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.943-950
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• 2009

Cadmium (Cd) adsorption onto the activated carbon containing hydroxyapatite (HAP) was investigated in batch experiments and response surface methodology (RSM) using the Box-Behnken methods were applied to the experimental results. Cd adsorption with different HAP mass ratio of from 10% to 30%. With more HAP, Cd was more adsorbed. These results suggest that the higher HAP mass causes an increase of the ion exchange potential of the HAP sorbent. Equilibrium experimental results from Cd adsorption was fitted to Langmuir and Freundlich isotherm models. Cd adsorption on HAP sorbent were found to follow the Freundlich isotherm model well in the initial adsorbate concentration range. Also, Cd adsorption was a function of the HAP mass ratio ($x_1$), initial Cd concentration ($x_2$), and initial pH ($x_3$) from the application of the RSM. Statistical results showed the order of significance of the independent variables to be initial Cd concentration > HAP mass ratio > initial pH.

• Food Science and Biotechnology
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• v.18 no.6
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• pp.1342-1350
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• 2009

This paper investigates the production and optimization of $\beta$-galactosidase enzyme using synthetic medium by Kluyveromyces lactis NRRL Y-8279 in stirred tank bioreactor. Response surface methodology was used to investigate the effects of fermentation parameters on $\beta$-galactosidase enzyme production. Maximum specific enzyme activity of 4,622.7 U/g was obtained at the optimum levels of process variables (aeration rate 2.21 vvm, agitation speed 173.4 rpm, initial sugar concentration 33.8 g/L, incubation time 24.0 hr). The optimum temperature and pH of the $\beta$-galactosidase enzyme produced under optimized conditions were $37^{\circ}C$ and pH 7.0, respectively. The enzyme was stable over a pH range of 6.0-7.5 and a temperature range of $25-37^{\circ}C$. The $K_m$ and $V_{max}$ values for O-nitrophenol-$\beta$-D-galactopyranoside (ONPG) were 1.20 mM and $1,000\;{\mu}mol/min{\cdot}mg$ protein, respectively. The response surface methodology was found to be useful in optimizing and determining the interactions among process variables in $\beta$-galactosidase enzyme production. Hence, this study fulfills the lack of using mathematical and statistical techniques in optimizing the $\beta$-galactosidase enzyme production in stirred tank bioreactor.

• Food Science of Animal Resources
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• v.37 no.1
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• pp.139-146
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• 2017

Response surface methodology (RSM) is a useful set of statistical techniques for modeling and optimizing responses in research studies of food science. In the analysis of response surface data, a second-order polynomial regression model is usually used. However, sometimes we encounter situations where the fit of the second-order model is poor. If the model fitted to the data has a poor fit including a lack of fit, the modeling and optimization results might not be accurate. In such a case, using a fullest balanced model, which has no lack of fit, can fix such problem, enhancing the accuracy of the response surface modeling and optimization. This article presents how to develop and use such a model for the better modeling and optimizing of the response through an illustrative re-analysis of a dataset in Park et al. (2014) published in the Korean Journal for Food Science of Animal Resources.

• Nuclear Engineering and Technology
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• v.46 no.5
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• pp.619-632
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• 2014

The Best Estimate Plus Uncertainty (BEPU) method has been widely used to evaluate the uncertainty of a best-estimate thermal hydraulic system code against a figure of merit. This uncertainty is typically evaluated based on the physical model's uncertainties determined by expert judgment. This paper introduces the application of data assimilation methodology to determine the uncertainty bands of the physical models, e.g., the mean value and standard deviation of the parameters, based upon the statistical approach rather than expert judgment. Data assimilation suggests a mathematical methodology for the best estimate bias and the uncertainties of the physical models which optimize the system response following the calibration of model parameters and responses. The mathematical approaches include deterministic and probabilistic methods of data assimilation to solve both linear and nonlinear problems with the a posteriori distribution of parameters derived based on Bayes' theorem. The inverse problem was solved analytically to obtain the mean value and standard deviation of the parameters assuming Gaussian distributions for the parameters and responses, and a sampling method was utilized to illustrate the non-Gaussian a posteriori distributions of parameters. SPACE is used to demonstrate the data assimilation method by determining the bias and the uncertainty bands of the physical models employing Bennett's heated tube test data and Becker's post critical heat flux experimental data. Based on the results of the data assimilation process, the major sources of the modeling uncertainties were identified for further model development.

• Korean Journal of Agricultural Science
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• v.39 no.2
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• pp.195-202
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• 2012

This study was examined the optimization of processing conditions for taste-assurance factors of boiled Korean native chicken (KNC) through response surface methodology. The effects of two independent variables, including heating time ($X_1$) and water volume ($X_2$), were investigated using central composite design. Hypoxanthine content, lipid oxidation, texture, and sensory results were chosen as dependent variable. Results showed high reliability on hypoxanthine and texture property in leg meat (not breast meat) of boiled KNC. Statistical modeling revealed that 3.5 folds of added water (v/w) based on chicken weight and 73.5 min of cooking time was the optimum for producing characteristic taste and textural properties from the leg meat of KNC.

• Integrative Medicine Research
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• v.6 no.4
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• pp.388-394
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• 2017

Background: The present study optimized ultrasound-assisted extraction conditions to maximize extraction yields of glycyrrhizic acid from licorice. Methods: The optimal extraction temperature ($X_1$), extraction time ($X_2$), and methanol concentration ($X_3$) were identified using response surface methodology (RSM). A central composite design (CCD) was used for experimental design and analysis of the results to obtain the optimal processing parameters. Results: Statistical analyses revealed that three variables and the quadratic of $X_1$, $X_2$, and $X_3$ had significant effects on the yields and were followed by significant interaction effects between the variables of $X_2$ and $X_3$ (p<0.01). A 3D response surface plot and contour plots derived from the mathematical models were applied to determine the optimal conditions. The optimum ultrasound-assisted extraction conditions were as follows: extraction temperature, $69^{\circ}C$; extraction time, 34?min; and methanol concentration, 57%. Under these conditions, the experimental yield of glycyrrhizic acid was 3.414%, which agreed closely with the predicted value (3.406%). Conclusion: The experimental values agreed with those predicted by RSM models, thus indicating the suitability of the model employed and the success of RSM in optimizing the extraction conditions.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.1
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• pp.19-28
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• 2019

The purpose of this study is to evaluate the walking behavior analysis methodology used in the previous studies, paying attention to the demand for empirical data collecting for urban and neighborhood planning. The preceding researches are divided into (1)Recording, (2) Surveys, (3)Statistical data, (4)Global positioning system (GPS) devices, and (5)Mobile Big Data analysis. Next, we analyze the precedent research and identify the changes of the walkability research. (1)being required empirical data on the actual walking and moving patterns of people, (2)beginning to be measured micro-walking behaviors such as actual route, walking facilities, detour, walking area. In addition, according to the trend of research, it is analyzed that the use of GPS device and the mobile big data are newly emerged. Finally, we analyze pedestrian data based on mobile big data in terms of 'application' and distinguishing it from existing survey methodology. We present the possibility of mobile big data. (1)Improvement of human, temporal and spatial constraints of data collection, (2)Improvement of inaccuracy of collected data, (3)Improvement of subjective intervention in data collection and preprocessing, (4)Expandability of walking environment research.