• Title/Summary/Keyword: Box-Behnken model

Search Result 89, Processing Time 0.029 seconds

Optimization of Medium for the Carotenoid Production by Rhodobacter sphaeroides PS-24 Using Response Surface Methodology (반응 표면 분석법을 사용한 Rhodobacter sphaeroides PS-24 유래 carotenoid 생산 배지 최적화)

  • Bong, Ki-Moon;Kim, Kong-Min;Seo, Min-Kyoung;Han, Ji-Hee;Park, In-Chul;Lee, Chul-Won;Kim, Pyoung-Il
    • Korean Journal of Organic Agriculture
    • /
    • v.25 no.1
    • /
    • pp.135-148
    • /
    • 2017
  • Response Surface Methodology (RSM), which is combining with Plackett-Burman design and Box-Behnken experimental design, was applied to optimize the ratios of the nutrient components for carotenoid production by Rhodobacter sphaeroides PS-24 in liquid state fermentation. Nine nutrient ingredients containing yeast extract, sodium acetate, NaCl, $K_2HPO_4$, $MgSO_4$, mono-sodium glutamate, $Na_2CO_3$, $NH_4Cl$ and $CaCl_2$ were finally selected for optimizing the medium composition based on their statistical significance and positive effects on carotenoid yield. Box-Behnken design was employed for further optimization of the selected nutrient components in order to increase carotenoid production. Based on the Box-Behnken assay data, the secondary order coefficient model was set up to investigate the relationship between the carotenoid productivity and nutrient ingredients. The important factors having influence on optimal medium constituents for carotenoid production by Rhodobacter sphaeroides PS-24 were determined as follows: yeast extract 1.23 g, sodium acetate 1 g, $NH_4Cl$ 1.75 g, NaCl 2.5 g, $K_2HPO_4$ 2 g, $MgSO_4$ 1.0 g, mono-sodium glutamate 7.5 g, $Na_2CO_3$ 3.71 g, $NH_4Cl$ 3.5g, $CaCl_2$ 0.01 g, per liter. Maximum carotenoid yield of 18.11 mg/L was measured by confirmatory experiment in liquid culture using 500 L fermenter.

Lattice-spring-based synthetic rock mass model calibration using response surface methodology

  • Mariam, Al-E'Bayat;Taghi, Sherizadeh;Dogukan, Guner;Mostafa, Asadizadeh
    • Geomechanics and Engineering
    • /
    • v.31 no.5
    • /
    • pp.529-543
    • /
    • 2022
  • The lattice-spring-based synthetic rock mass model (LS-SRM) technique has been extensively employed in large open-pit mining and underground projects in the last decade. Since the LS-SRM requires a complex and time-consuming calibration process, a robust approach was developed using the Response Surface Methodology (RSM) to optimize the calibration procedure. For this purpose, numerical models were designed using the Box-Behnken Design technique, and numerical simulations were performed under uniaxial and triaxial stress states. The model input parameters represented the models' micro-mechanical (lattice) properties and the macro-scale properties, including uniaxial compressive strength (UCS), elastic modulus, cohesion, and friction angle constitute the output parameters of the model. The results from RSM models indicate that the lattice UCS and lattice friction angle are the most influential parameters on the macro-scale UCS of the specimen. Moreover, lattice UCS and elastic modulus mainly control macro-scale cohesion. Lattice friction angle (flat joint fiction angle) and lattice elastic modulus affect the macro-scale friction angle. Model validation was performed using physical laboratory experiment results, ranging from weak to hard rock. The results indicated that the RSM model could be employed to calibrate LS-SRM numerical models without a trial-and-error process.

Adsorption Characterization of Cd by Coal Fly Ash Using Response Surface Methodology (RSM) (반응표면분석법을 이용한 석탄회에서의 Cd 흡착특성에 관한 연구)

  • An, Sangwoo;Choi, Jaeyoung;Cha, Minwhan;Park, Jaewoo
    • Journal of the Korean GEO-environmental Society
    • /
    • v.11 no.1
    • /
    • pp.19-26
    • /
    • 2010
  • The batch experiments and response surface methodology (RSM) have been applied to the investigation of the cadmium (Cd) adsorption by coal fly ash (CFA). CFA having maximum Cd removal mass of 8.51 mg/g were calculated from Langmuir model. Cd removal reaction with different initial pH ranged from 4 to 9. When the initial pH was higher, Cd was removed more by adsorption and precipitation. These results suggest that the lower pH cause an increase of $H^+$ ion concentration which competed with Cd ions for exchange sites in CFA. Also, The Cd adsorption was mathematically described as a function of parameters initial Cd concentration ($X_1$), initial pH ($X_2$), and initial CFA mass ($X_3$) being modeled by use of the Box-Behnken methods. Empirical models were developed to describe relationship between the experimental variables and response. Statistical analysis indicates that tree factors ($X_1$, $X_2$, and $X_3$) on the linear term (main effects), and tree factors ($X_1X_2$, $X_1X_3$, and $X_2X_3$) on the non-linear term (Interaction effect; cross-product) had significant effects, respectively. In this case, the value of the adjusted determination coefficient (adjusted $R^2=0.9280$) was closed to 1, showing a high significance of the model. Statistical results showed the order of Cd removal at experimental factors to be initial initial pH > initial Cd concentration > initial CFA mass.

Probabilistic modeling of geopolymer concrete using response surface methodology

  • Kathirvel, Parthiban;Kaliyaperumal, Saravana Raja Mohan
    • Computers and Concrete
    • /
    • v.19 no.6
    • /
    • pp.737-744
    • /
    • 2017
  • Geopolymer Concrete is typically proportioned with activator solution leading to moderately high material cost. Such cost can be enduring in high value added applications especially when cost savings can be recognized in terms of reduction in size of the members. Proper material selection and mix proportioning can diminish the material cost. In the present investigation, a total of 27 mixes were arrived considering the mix parameters as liquid-binder ratio, slag content and sodium hydroxide concentration to study the mechanical properties of geopolymer concrete (GPC) mixes such as compressive strength, split tensile strength and flexural strength. The derived statistical Response Surface Methodology is beleaguered to develop cost effective GPC mixes. The estimated responses are not likely to contrast in linear mode with selected variables; a plan was selected to enable the model of any response in a quadratic manner. The results reveals that a fair correlation between the experimental and the predicted strengths.

Swelling Pressures of a Potential Buffer Material for High-Level Waste Repository

  • Lee, Jae-Owan;Cho, Won-Jin;Chun, Kwan-Sik
    • Nuclear Engineering and Technology
    • /
    • v.31 no.2
    • /
    • pp.139-150
    • /
    • 1999
  • The swelling pressure of a potential buffer material was measured and the effect of dry density, bentonite content and initial water content on the swelling pressure was investigated to provide the information for the selection of buffer material in a high-level waste repository. Swelling tests were carried out according to Box-Behnken's experimental design. Measured swelling pressures were in the wide range of 0.7 Kg/$\textrm{cm}^2$ to 190.2 Kg/$\textrm{cm}^2$ under given experimental conditions. Based upon the experimental data, a 3-factor polynomial swelling model was suggested to analyze the effect of dry density, bentonite content and initial water content on the swelling pressure The swelling pressure increased with an increase in the dry density and bentonite content, while it decreased with increasing the initial water content and, beyond about 12 wt.% of the initial water content, levelled off to nearly constant value.

  • PDF

Implementation of Small Sized Designs for Economic Estimation of Second-Order Models (2차 모형의 경제적 추정을 위한 소형실험계획의 활용)

  • Kim, Jeong-Suk;Byeon, Jae-Hyeon
    • Proceedings of the Korean Operations and Management Science Society Conference
    • /
    • 2006.11a
    • /
    • pp.531-534
    • /
    • 2006
  • Response surface methodology (RSM) is a useful collection of experimentation techniques for developing, improving, and optimizing products and processes. When we are to estimate second-order regression model and optimize quality characteristic by RSM, central composite designs and Box-Behnken designs are widely in use. However, in developing cutting-edge products, it is very crucial to reduce the time of experimentation as much as possible. In this paper small-sized second-order designs are introduced and their estimation abilities are compared in terms of D-optimality, A-optimality, and variance of regression coefficients, ease of experimentation, number of experiments. Then we present a guideline of using specific designs for specific experimentation circumstances. The result of this study will be beneficial to experimenters who face experiments which are expensive, difficult, or time-consuming.

  • PDF

OPTIMIZATION OF A CENTRIFUGAL COMPRESSOR IMPELLER AND DIFFUSER USING A RESPONSE SURFACE METHOD (반응면기법을 이용한 원심압축기 최적설계)

  • Kim, S.M.;Park, J.Y.;Ahn, K.Y.;Baek, J.H.
    • 한국전산유체공학회:학술대회논문집
    • /
    • 2007.10a
    • /
    • pp.92-99
    • /
    • 2007
  • In this paper, optimization of the vaned centrifugal compressor was carried out at a given mass flow rate condition. Firstly, impeller optimization was conducted using response surface method (RSM) which is one of optimization methods. After the optimization of the impeller was completed, diffuser optimization was performed with the optimized impeller. In these processes, Navier-Stokes solver was used to calculate the flow inside the centrifugal compressor. And the optimization is performed with Box-Behnken design method which is efficient for fitting second-order response surfaces to reduce the number of calculations required. As a result, compared with the reference model, the efficiency and the pressure ratio of the optimized impeller and diffuser are found to be increased. The performance at off-design conditions is presented.

  • PDF

Comparison of Small Sized Designs for Second-Order Modelling (2차 모형을 위한 소형 실험계획의 비교)

  • Kim Jeong-Suk;Byun Jai-Hyun
    • Proceedings of the Korean Operations and Management Science Society Conference
    • /
    • 2006.05a
    • /
    • pp.1085-1092
    • /
    • 2006
  • Response surface methodology(RSM) is a useful collection of experimentation techniques for developing, improving, and optimizing products and processes. When we are to estimate second-order regression model and optimize quality characteristic by RSM, central composite designs and Box-Behnken designs are widely in use. However, in developing cutting-edge products, it is very crucial to reduce the time of experimentation as much as possible. In this paper small-sized second-order designs are introduced and their estimation abilities are compared in terms of D-optimality, A-optimality, and variance of regression coefficients. The result of this study will be beneficial to experimenters who face experiments which are expensive, difficult, or time-consuming.

  • PDF

Optimization of the Conditions of Flavonoid Extraction From Tartary Buckwheat Sprout Using Response Surface Methodology (반응표면분석법을 이용한 타타리메밀싹에서 플라보노이드 추출 최적화)

  • Shin, Jiyoung;Choi, Iseul;Hwang, Jinwoo;Yang, Junho;Lee, Yoonhyeong;Kim, So-i;Cha, Eunji;Yang, Ji-Young
    • Journal of Life Science
    • /
    • v.30 no.12
    • /
    • pp.1101-1108
    • /
    • 2020
  • Tartary buckwheat is a grain with many flavonoids, such as rutin, quercetin, kaempferol, and myricetin. This study aimed to optimize extraction conditions to maximize the rutin, quercetin, and myricetin contents of tartary buckwheat sprout extracts using response surface methodology. A BoxBehnken design containing 15 experiments was employed to evaluate the effects of extraction conditions, such as temperature (X1, 50~70℃), extraction time (X2, 5~9 hr), and ethanol concentration (X3, 60~90%). The coefficients of determination (R2) for all the dependent variables (extraction temperature, extraction time, and extraction ethanol concentration) were determined to be over 0.95, indicating significance. The p-value of the model in lack of fit was over 0.1 than means, indicating that the model was well predicted. The optimal extraction conditions for rutin, quercetin, and myricetin contents were obtained at X1 = 51.03, X2 = 6.62, and X3 = 69.16, respectively. Under these optimal conditions, the predicted rutin, quercetin, and myricetin contents were 808.467 ㎍/ml, 193.296 ㎍/ml, and 37.360 ㎍/ml, respectively. For the validation of the model, ten experiments were performed and the experimental rutin and quercetin contents were measured at 802.84±8.49 ㎍/ml, 193.76±2.80 ㎍/ml, and 34.84±0.43 ㎍/ml, respectively. The experimental rutin and quercetin contents were similar to the predicted contents, but the experimental myricetin content was lower than predicted.

Modeling of PECVD Oxide Film Properties Using Neural Networks (신경회로망을 이용한 PECVD 산화막의 특성 모형화)

  • Lee, Eun-Jin;Kim, Tae-Seon
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
    • /
    • v.23 no.11
    • /
    • pp.831-836
    • /
    • 2010
  • In this paper, Plasma Enhanced Chemical Vapor Deposition (PECVD) $SiO_2$ film properties are modeled using statistical analysis and neural networks. For systemic analysis, Box-Behnken's 3 factor design of experiments (DOE) with response surface method are used. For characterization, deposited film thickness and film stress are considered as film properties and three process input factors including plasma RF power, flow rate of $N_2O$ gas, and flow rate of 5% $SiH_4$ gas contained at $N_2$ gas are considered for modeling. For film thickness characterization, regression based model showed only 0.71% of root mean squared (RMS) error. Also, for film stress model case, both regression model and neural prediction model showed acceptable RMS error. For sensitivity analysis, compare to conventional fixed mid point based analysis, proposed sensitivity analysis for entire range of interest support more process information to optimize process recipes to satisfy specific film characteristic requirements.