• Title/Summary/Keyword: response surface method (RSM), analysis

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Cost Reduction Design in Single-phase Line-start Permanent Magnet Motor (단상 유도형 동기 전동기의 Cost 저감 설계)

  • Lee, Byeong-Hwa;Nam, Hyuk;Lee, Jeong-Jong;Fang, Liang;Hong, Jung-Pyo;Ha, Seung-Hyung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.12
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    • pp.2208-2212
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    • 2008
  • This paper deals with the cost reduction design of a single-phase line-start permanent magnet(LSPM) motor. Due to high cost of the permanent magnet(PM), cost reduction can be effectively achieved by reducing PM volume. Therefore, motor characteristics according to the PM volume are calculated by using d-q axis equivalent circuit analysis, and the characteristic map is made. In the characteristic map, maximum torque and efficiency are shown according to motor parameters such as back electromotive force(back emf) and inductances; back emf represents the PM volume. Minimum back emf and inductances satisfying output performance are determined in the characteristic map. Then, motor geometry based on the prototype motor is optimized to get the determined parameters using response surface methodology(RSM) and finite element method(FEM). Through the presented cost reduction design, total PM volume is reduced to 32% of prototype model.

An Optimal Design Method on system of Flexible Manufacturing Cells(FMCs) using Simulation Technology

  • Lee, Seung-Hyun;Yoo, Wang-Jin;Yoon, Hee-Jung;Lim, Ik-Sung
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.22 no.53
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    • pp.89-97
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    • 1999
  • We are concerned with the optimal design of flexible manufacturing cells in this study, thus try to suggest the detail information for each resource on the optimal conditions. Object oriented simulation technology is used to write models more easily and to execute simulation running time more rapidly, and the optimal level of relevant decision variables is probed by response surface methodology(RSM), which is well known for the optimization technology based on experiment design and regression equation. We investigate the optimal level for the number of pallets and the speed of AGVs of FMC systems, carry out the performance analysis of this system. Consequently we suggest systematic procedures for the optimization of FMCs in detail design stage.

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Flow Factor Prediction of Centrifugal Hydraulic Turbine for Sea Water Reverse Osmosis (SWRO)

  • Ma, Ying;Kadaj, Eric;Terrasi, Kevin
    • International Journal of Fluid Machinery and Systems
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    • v.3 no.4
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    • pp.369-378
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    • 2010
  • The creation of the hydraulic turbine flow factor map will undoubtedly benefit its design by decreasing both the design cycle time and product cost. In this paper, the geometry and flow variables, which effectively affect the flow factor, are proposed, analyzed and determined. These flow variables are further used to create the operating condition maps by using different model approaches categorized into Response Surface Method (RSM) and Artificial Neural Network (ANN). The accuracies of models created by different approaches are compared and the performances of model approaches are analyzed. The influences of chosen variables and the combination of Principle Component Analysis (PCA) and model approaches are also studied. The comparison results between predicted and actual flow factors suggest that two-hidden-layer Feed-forward Neural Network (FFNN), and one.hidden-layer FFNN with PCA has the best performance on forming this mapping, and are accurate sufficiently for hydraulic turbine design.

Development of an Automated Aero-Structure Interaction System for Multidisciplinary Design Optimization for the Large AR Aircraft Wing (가로세로비가 큰 항공기 날개의 다분야 통합 최적설계를 위한 자동화 공력-구조 연계 시스템 개발)

  • Jo, Dae-Sik;Yoo, Jae-Hoon;Joh, Chang-Yeol;Park, Chan-Woo
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.38 no.7
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    • pp.716-726
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    • 2010
  • In this research, design optimization of an aircraft wing has been performed using the fully automated Multidisciplinary Design Optimization (MDO) framework, which integrates aerodynamic and structural analysis considering nonlinear structural behavior. A computational fluid dynamics (CFD) mesh is generated automatically from parametric modeling using CATIA and Gambit, followed by an automatic flow analysis using FLUENT. A computational structure mechanics (CSM) mesh is generated automatically by the parametric method of the CATIA and visual basic script of NASTRAN-FX. The structure is analyzed by ABAQUS. Interaction between CFD and CSM is performed by a fully automated system. The Response Surface Method (RSM) is applied for optimization, helping to achieve the global optimum. The optimization design result demonstrates successful application of the fully automated MDO framework.

Optimizing In Vitro Propagation of Sophora koreensis Nakai using Statistical Analysis (다양한 통계분석 기법을 이용한 개느삼(Sophora koreensis Nakai)의 기내 증식 최적 조건 구명)

  • Jeong, Ukhan;Lee, Hwa;Park, Sanghee;Cheong, Eun Ju
    • Journal of Korean Society of Forest Science
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    • v.110 no.1
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    • pp.53-63
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    • 2021
  • Sophora koreensis Nakai is an indigenous plant in Koreawith a restricted natural range, part of which is in Gangwon province. The species is known to contain phytochemicals that have beneficial effects on human health, and it is economically important in bioindustry. Because of the limited number of plants in a small range of habitats, the mass-propagation method should be developed for use and conservation. In vitro tissue culture is a reliable method in terms of mass propagation from selected clones of the species. We investigated the optimal conditions of the medium in this process, especially focusing on the concentrations of plant growth regulators(PGRs) in the culture of stem-containing axillary buds. Three statistical methods, i.e., ANOVA, response surface method(RSM), and fuzzy clustering were used to analyze the plant growth, number of shoots induced, and shoot length with various combinations of PGRs. Results from the RSM differed from those of the other two methods; thus, the method was not suitable. ANOVA and fuzzy clustering showed similar results. However, more accurate results were obtained using fuzzy clustering because it provided a probability for each treatment. On the basis of the fuzzy clustering analysis, stem tissue produced the greatest number of shoots(11.03 per explant; 63.33%) on a medium supplemented with 5-��M 6-benzylaminopurine and 2.5-��M thidiazuron(TDZ). Proliferation of shoots(2.18 ± 0.21 cm, 63.33%) was attained on a medium supplemented with 2.5-��M BA, 2.5-��M TDZ, and 2.5-��M gibberellic acid.

Sustainable controlled low-strength material: Plastic properties and strength optimization

  • Mohd Azrizal, Fauzi;Mohd Fadzil, Arshad;Noorsuhada Md, Nor;Ezliana, Ghazali
    • Computers and Concrete
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    • v.30 no.6
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    • pp.393-407
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    • 2022
  • Due to the enormous cement content, pozzolanic materials, and the use of different aggregates, sustainable controlled low-strength material (CLSM) has a higher material cost than conventional concrete and sustainable construction issues. However, by selecting appropriate materials and formulations, as well as cement and aggregate content, whitethorn costs can be reduced while having a positive environmental impact. This research explores the desire to optimize plastic properties and 28-day unconfined compressive strength (UCS) of CLSM containing powder content from unprocessed-fly ash (u-FA) and recycled fine aggregate (RFA). The mixtures' input parameters consist of water-to-cementitious material ratio (W/CM), fly ash-to-cementitious materials (FA/CM), and paste volume percentage (PV%), while flowability, bleeding, segregation index, and 28-day UCS were the desired responses. The central composite design (CCD) notion was used to produce twenty CLSM mixes and was experimentally validated using MATLAB by an Artificial Neural Network (ANN). Variance analysis (ANOVA) was used for the determination of statistical models. Results revealed that the plastic properties of CLSM improve with the FA/CM rise when the strength declines for 28 days-with an increase in FA/CM, the diameter of the flowability and bleeding decreased. Meanwhile, the u-FA's rise strengthens the CLSM's segregation resistance and raises its strength over 28 days. Using calcareous powder as a substitute for cement has a detrimental effect on bleeding, and 28-day UCS increases segregation resistance. The response surface method (RSM) can establish high correlations between responses and the constituent materials of sustainable CLSM, and the optimal values of variables can be measured to achieve the desired response properties.

Optimization of Extraction Conditions for Mixture of Camellia sinensis L. and Artemisia argyi by Response Surface Methodology (반응표면분석을 이용한 녹차와 애엽 혼합물의 추출조건 최적화)

  • Kim, Young-Hyun;Kim, Woo-Sik;Kim, Jae-Min;Choi, Sun-il;Jung, Tae-Dong;Lee, Jin-Ha;Kim, Jong-Dai;Lim, Jae Kag;Lee, Ok-Hwan
    • Journal of Food Hygiene and Safety
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    • v.31 no.4
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    • pp.278-285
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    • 2016
  • This study used response surface methodology (RSM) in an effort to optimize the ultrasoundassisted extraction condition of Camellia sinensis L. and Artemisia argyi mixture in order to increase extraction yield in the extract. The effects of three independent variables, $X_1$ (Mixture ratio, 60-80%), $X_2$ (Ratio of water to raw material, 20~100 mL/g), and $X_3$ (Extraction time, 25-145 min), were investigated at three levels using Box-Behnken design (BBD) to obtain the highest extraction efficiency. Y (Extraction yield) was chosen as dependent variable. Our result showed that the coefficient of determination ($R^2$) of the model was 0.9747, with significant at the level of p < 0.002. Furthermore, the predicted values of each variable were similar to the actual values. The optimum extraction conditions were as follows: mixture ratio of 85.86%, ratio of water to raw material of 92.73 mL/g, and extraction time of 56.52 min. At these conditions, predicted extraction yield was 30.03%. The analysis of variance (ANOVA) indicated a high goodness of model fit and the success of the RSM method for optimizing extraction conditions of Camellia sinensis L. and Artemisia argyi mixture.

Damage index based seismic risk generalization for concrete gravity dams considering FFDI

  • Nahar, Tahmina T.;Rahman, Md M.;Kim, Dookie
    • Structural Engineering and Mechanics
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    • v.78 no.1
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    • pp.53-66
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    • 2021
  • The determination of the damage index to reveal the performance level of a structure can constitute the seismic risk generalization approach based on the parametric analysis. This study implemented this concept to one kind of civil engineering structure that is the concrete gravity dam. Different cases of the structure exhibit their individual responses, which constitute different considerations. Therefore, this approach allows the parametric study of concrete as well as soil for evaluating the seismic nature in the generalized case. To ensure that the target algorithm applicable to most of the concrete gravity dams, a very simple procedure has been considered. In order to develop a correlated algorithm (by response surface methodology; RSM) between the ground motion and the structural property, randomized sampling was adopted through a stochastic method called half-fractional central composite design. The responses in the case of fluid-foundation-dam interaction (FFDI) make it more reliable by introducing the foundation as being bounded by infinite elements. To evaluate the seismic generalization of FFDI models, incremental dynamic analysis (IDA) was carried out under the impacts of various earthquake records, which have been selected from the Pacific Earthquake Engineering Research Center data. Here, the displacement-based damage indexed fragility curves have been generated to show the variation in the seismic pattern of the dam. The responses to the sensitivity analysis of the various parameters presented here are the most effective controlling factors for the concrete gravity dam. Finally, to establish the accuracy of the proposed approach, reliable verification was adopted in this study.

A Study on the Process Optimization of Microcellular Foaming Injection Molded Ceiling Air-Conditioner 4-Way Panel (초미세발포 사출성형을 이용한 천정형 에어컨 4-way 판넬의 공정 최적화에 관한 연구)

  • Kim, Joo-Kwon;Lee, Jung-Hee;Kim, Jong-Sun;Lee, Jun-Han;Kwak, Jae-Seob
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.17 no.6
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    • pp.98-104
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    • 2018
  • Deflected 4-way panels of ceiling air conditioners produced by injection molding process have caused dew condensation at the edge of products. In order to prevent this drawback with reducing weight and deformation, this study proposed renovated process adopting microcellular foaming. According to results from 2-sample t-test and analysis of variance(ANOVA), the critical factors affecting weight were melt temperature and injection speed. In addition, the vital effects on deformation were structure at the edge, mold temperature and cooling time. Optimal conditions of these parameters were derived by regressive analysis with CAE and response surface method(RSM), and then applied to an actual design and process stage to analyze performance. As a results, it clearly showed that new process improved process capability as well as reduced both weight and deformation by 18.8% and 71.9% respectively compared to the conventional method.

Optimization of uranium biosorption in solutions by Sargassum boveanum using RSM method

  • Hashemi, Nooshin;Dabbagh, Reza;Noroozi, Mostafa;Baradaran, Sama
    • Advances in environmental research
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    • v.9 no.1
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    • pp.65-84
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    • 2020
  • The potential use of Sargassum boveanum algae for the removal of uranium from aqueous solution has been studied by varying three independent parameters (pH, initial uranium ion concentration, S. boveanum dosage) using a central composite design (CCD) under response surface methodology (RSM). Batch mode experiments were performed in 20 experimental runs to determine the maximum metal adsorption capacity. In CCD design, the quantitative relationship between different levels of these parameters and heavy metal uptake (q) were used to work out the optimized levels of these parameters. The analysis of variance (ANOVA) of the proposed quadratic model revealed that this model was highly significant (R2 = 0.9940). The best set required 2.81 as initial pH(on the base of design of experiments method), 1.01 g/L S. boveanum and 418.92 mg/L uranium ion concentration within 180 min of contact time to show an optimum uranium uptake of 255 mg/g biomass. The biosorption process was also evaluated by Langmuir, Freundlich, Temkin and Dubinin-Radushkevich isotherm models represented that the experimental data fitted to the Langmuir isotherm model of a suitable degree and showed the maximum uptake capacity of 500 mg/g. FTIR and scanning electron microscopy were used to characterize the biosorbent and implied that the functional groups (carboxyl, sulfate, carbonyl and amine) were responsible for the biosorption of uranium from aqueous solution. In conclusion, the present study showed that S. boveanum could be a promising biosorbent for the removal of uranium pollutants from aqueous solutions.