• Title/Summary/Keyword: Box-Behnken technique

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Optimization of Color Sorting Process of Shredded ELV Bumper using Reaction Surface Method (반응표면법을 이용한 폐자동차 범퍼 파쇄물의 색채선별공정 최적화 연구)

  • Lee, Hoon
    • Resources Recycling
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    • v.28 no.2
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    • pp.23-30
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    • 2019
  • An color sorting technique was introduced to recycle End-of-life automobile shredded bumpers. The color sorting is a innovate method of separating the differences in the color of materials which are difficult to separate in gravity and size classification by using a camera and an image process technique. Experiments were planned and optimal conditions were derived by applying BBD (Box-Behnken Design) in the reaction surface method. The effects of color sensitivity, feed rate and sample size were analyzed, and a second-order reaction model was obtained based on the analysis of regression and statistical methods and $R^2$ and p-value were 99.56% and < 0.001. Optimum recovery was 94.1% under the conditions of color sensitivity, feed rate and particle size of 32%, 200 kg/h, and 33 mm respectively. The recovery of actual experiment was 93.8%. The experimental data agreed well with the predicted value and confirmed that the model was appropriate.

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
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    • v.31 no.5
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    • pp.529-543
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    • 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.

Statistical Optimization for Biodegradation of 2,4-Dichlorophenoxyacetic Acid by Soil Isolated Bacterium (토양 분리 박테리아에 의한 2,4-Dichlorophenoxyacetic산의 분해 최적화)

  • Kim, Byunghoon;Myunghee Han;Sungyong Cho;Sungjin Ahn;Lim, Sung-Paal;Sunkyun Yoo
    • Microbiology and Biotechnology Letters
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    • v.31 no.1
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    • pp.83-89
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    • 2003
  • 2,4-Dichlorophenoxyacetic acid (2,4-D) as a widely used herbicide has caused serious environmental problems because of its difficult decomposition in nature. We isolated the strain capable of metabolizing 2,4-D as sole carbon and energy source by an enrichment culture technique from the 2,4-D contaminated soil collected at orchard in Gwangju, Korea. This strain was identified tentatively as Aeromonas sp. NOH2. With this strain, we established the response surface methodology (Box-Behnken Design) to optimize the principle parameters for maximizing biodegradation of 2,4-D such as culture pH, temperature, and nutrient concentration in liquid batch culture. The ranges of parameters were obtained from preliminary works done at our laboratory and chosen as 5.5, 6.5, and 7.5 for pH, 25, 30, and $35^{\circ}C$ for temperature, and 5, 20, and 35 g/1 nutrient concentration. Initial concentration of 2,4-D was 500 ppm and nutrient source was tryptic soy broth. The experimental data were significantly fitted to a second order polynomial equation using multiple regression. The most important parameter influencing 2,4-D degradation and biomass production was nutrient concentration. For 2,4-D degradation, the optimum values of pH and temperature, and nutrient concentration were obtained at pH (6.5), temperature (31.8 to $32.1^{\circ}C$), and nutrient concentration (29.6 to 30.1.0 g/1).

Laser micro-drilling of CNT reinforced polymer nanocomposite: A parametric study using RSM and APSO

  • Lipsamayee Mishra;Trupti Ranjan Mahapatra;Debadutta Mishra;Akshaya Kumar Rout
    • Advances in materials Research
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    • v.13 no.1
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    • pp.1-18
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    • 2024
  • The present experimental investigation focuses on finding optimal parametric data-set of laser micro-drilling operation with minimum taper and Heat-affected zone during laser micro-drilling of Carbon Nanotube/Epoxy-based composite materials. Experiments have been conducted as per Box-Behnken design (BBD) techniques considering cutting speed, lamp current, pulse frequency and air pressure as input process parameters. Then, the relationship between control parameters and output responses is developed using second-order nonlinear regression models. The analysis of variance test has also been performed to check the adequacy of the developed mathematical model. Using the Response Surface Methodology (RSM) and an Accelerated particle swarm optimization (APSO) technique, optimum process parameters are evaluated and compared. Moreover, confirmation tests are conducted with the optimal parameter settings obtained from RSM and APSO and improvement in performance parameter is noticed in each case. The optimal process parameter setting obtained from predictive RSM based APSO techniques are speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), Air pressure (1 kg/cm2) for Taper and speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), air pressure (3 kg/cm2) for HAZ. From the confirmatory experimental result, it is observed that the APSO metaheuristic algorithm performs efficiently for optimizing the responses during laser micro-drilling process of nanocomposites both in individual and multi-objective optimization.

Assessment of statistical sampling methods and approximation models applied to aeroacoustic and vibroacoustic problems

  • Biedermann, Till M.;Reich, Marius;Kameier, Frank;Adam, Mario;Paschereit, C.O.
    • Advances in aircraft and spacecraft science
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    • v.6 no.6
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    • pp.529-550
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    • 2019
  • The effect of multiple process parameters on a set of continuous response variables is, especially in experimental designs, difficult and intricate to determine. Due to the complexity in aeroacoustic and vibroacoustic studies, the often-performed simple one-factor-at-a-time method turns out to be the least effective approach. In contrast, the statistical Design of Experiments is a technique used with the objective to maximize the obtained information while keeping the experimental effort at a minimum. The presented work aims at giving insights on Design of Experiments applied to aeroacoustic and vibroacoustic problems while comparing different experimental designs and approximation models. For this purpose, an experimental rig of a ducted low-pressure fan is developed that allows gathering data of both, aerodynamic and aeroacoustic nature while analysing three independent process parameters. The experimental designs used to sample the design space are a Central Composite design and a Box-Behnken design, both used to model a response surface regression, and Latin Hypercube sampling to model an Artificial Neural network. The results indicate that Latin Hypercube sampling extracts information that is more diverse and, in combination with an Artificial Neural network, outperforms the quadratic response surface regressions. It is shown that the Latin Hypercube sampling, initially developed for computer-aided experiments, can also be used as an experimental design. To further increase the benefit of the presented approach, spectral information of every experimental test point is extracted and Artificial Neural networks are chosen for modelling the spectral information since they show to be the most universal approximators.

A study on the Degradation and By-products Formation of NDMA by the Photolysis with UV: Setup of Reaction Models and Assessment of Decomposition Characteristics by the Statistical Design of Experiment (DOE) based on the Box-Behnken Technique (UV 공정을 이용한 N-Nitrosodimethylamine (NDMA) 광분해 및 부산물 생성에 관한 연구: 박스-벤켄법 실험계획법을 이용한 통계학적 분해특성평가 및 반응모델 수립)

  • Chang, Soon-Woong;Lee, Si-Jin;Cho, Il-Hyoung
    • Journal of Korean Society of Environmental Engineers
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    • v.32 no.1
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    • pp.33-46
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    • 2010
  • We investigated and estimated at the characteristics of decomposition and by-products of N-Nitrosodimethylamine (NDMA) using a design of experiment (DOE) based on the Box-Behken design in an UV process, and also the main factors (variables) with UV intensity($X_2$) (range: $1.5{\sim}4.5\;mW/cm^2$), NDMA concentration ($X_2$) (range: 100~300 uM) and pH ($X_2$) (rang: 3~9) which consisted of 3 levels in each factor and 4 responses ($Y_1$ (% of NDMA removal), $Y_2$ (dimethylamine (DMA) reformation (uM)), $Y_3$ (dimethylformamide (DMF) reformation (uM), $Y_4$ ($NO_2$-N reformation (uM)) were set up to estimate the prediction model and the optimization conditions. The results of prediction model and optimization point using the canonical analysis in order to obtain the optimal operation conditions were $Y_1$ [% of NDMA removal] = $117+21X_1-0.3X_2-17.2X_3+{2.43X_1}^2+{0.001X_2}^2+{3.2X_3}^2-0.08X_1X_2-1.6X_1X_3-0.05X_2X_3$ ($R^2$= 96%, Adjusted $R^2$ = 88%) and 99.3% ($X_1:\;4.5\;mW/cm^2$, $X_2:\;190\;uM$, $X_3:\;3.2$), $Y_2$ [DMA conc] = $-101+18.5X_1+0.4X_2+21X_3-{3.3X_1}^2-{0.01X_2}^2-{1.5X_3}^2-0.01X_1X_2+0.07X_1X_3-0.01X_2X_3$ ($R^2$= 99.4%, 수정 $R^2$ = 95.7%) and 35.2 uM ($X_1$: 3 $mW/cm^2$, $X_2$: 220 uM, $X_3$: 6.3), $Y_3$ [DMF conc] = $-6.2+0.2X_1+0.02X_2+2X_3-0.26X_1^2-0.01X_2^2-0.2X_3^2-0.004X_1X_2+0.1X_1X_3-0.02X_2X_3$ ($R^2$= 98%, Adjusted $R^2$ = 94.4%) and 3.7 uM ($X_1:\;4.5\;$mW/cm^2$, $X_2:\;290\;uM$, $X_3:\;6.2$) and $Y_4$ [$NO_2$-N conc] = $-25+12.2X_1+0.15X_2+7.8X_3+{1.1X_1}^2+{0.001X_2}^2-{0.34X_3}^2+0.01X_1X_2+0.08X_1X_3-3.4X_2X_3$ ($R^2$= 98.5%, Adjusted $R^2$ = 95.7%) and 74.5 uM ($X_1:\;4.5\;mW/cm^2$, $X_2:\;220\;uM$, $X_3:\;3.1$). This study has demonstrated that the response surface methodology and the Box-Behnken statistical experiment design can provide statistically reliable results for decomposition and by-products of NDMA by the UV photolysis and also for determination of optimum conditions. Predictions obtained from the response functions were in good agreement with the experimental results indicating the reliability of the methodology used.

Process Optimization of Dextran Production by Leuconostoc sp. strain YSK. Isolated from Fermented Kimchi (김치로부터 분리된 Leuconostoc sp. strain YSK 균주에 의한 덱스트란 생산 조건의 최적화)

  • Hwang, Seung-Kyun;Hong, Jun-Taek;Jung, Kyung-Hwan;Chang, Byung-Chul;Hwang, Kyung-Suk;Shin, Jung-Hee; Yim, Sung-Paal;Yoo, Sun-Kyun
    • Journal of Life Science
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    • v.18 no.10
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    • pp.1377-1383
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    • 2008
  • A bacterium producing non- or partially digestible dextran was isolated from kimchi broth by enrichment culture technique. The bacterium was identified tentatively as Leuconostoc sp. strain SKY. We established the response surface methodology (Box-Behnken design) to optimize the principle parameters such as culture pH, temperature, and yeast extract concentration for maximizing production of dextran. The ranges of parameters were determined based on prior screening works done at our laboratory and accordingly chosen as 5.5, 6.5, and 7.5 for pH, 25, 30, and $35^{\circ}C$ for temperature, and 1, 5, and 9 g/l yeast extract. Initial concentration of sucrose was 100 g/l. The mineral medium consisted of 3.0 g $KH_2PO_4$, 0.01 g $FeSO_4{\cdot}H_2O$, 0.01 g $MnSO_4{\cdot}4H_2O$, 0.2 g $MgSO_4{\cdot}7H_2O$, 0.01 g NaCl, and 0.05 g $CaCO_3$ per 1 liter deionized water. The optimum values of pH and temperature, and yeast extract concentration were obtained at pH (around 7.0), temperature (27 to $28^{\circ}C$), and yeast extract (6 to 7 g/l). The best dextran yield was 60% (dextran/g sucrose). The best dextran productivity was 0.8 g/h-l.