• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.1960-1965
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• 2001

In the practical design, it is important to extract the design space information of a complex system in order to optimize the design because the design contains huge amount of design conflicts in general. In this research FEA (finite element analysis) has been successfully implemented and integrated with a statistical approach such as DOE (design of experiments) based RSM (response surface model) to optimize the thermal deformation of an automotive disk brake. The DOE is used for exploring the engineer's design space and for building the RSM in order to facilitate the effective solution of multi-objective optimization problems. The RSM is utilized as an efficient means to rapidly model the trade-off among many conflicting goals existed in the FEA applications. To reduce the computational burden associated with the FEA, the second-order regression models are generated to derive the objective functions and constraints. In this approach, the multiple objective functions and constraints represented by RSM are solved using the sequential quadratic programming to archive the optimal design of disk brake.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1777-1781
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• 2008

This paper deals with optimum design criteria for maximum torque density & minimum torque ripple of Synchronous Reluctance Motor (SynRM) according to the rated wattage using response surface methodology (RSM). The RSM has been achieved to use the experimental design method in combination with Finite Element Method and well adapted to make analytical model for a complex problem considering of a number of interaction of design variables. The proposed procedure allows the definition of the rotor shape according to flux barrier number, starting from an existing motor or a preliminary design.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.12
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• pp.623-627
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• 2006

This paper deals with the optimum rotor design solution on torque ripple reduction for a SynRM with concentrated winding using response surface methodology (RSM). The RSM has been achieved to use the experimental design method in combination with finite element method (FEM)and well adapted to make analytical model for a complex problem considering a lot of interaction of design variables. Comparisons are given with characteristics of a SynRM according to flux barrier number, flux barrier width variation, respectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1080-1089
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• 2013

Interior Permanent Magnet Synchronous Machines (IPMSMs) with rare earth magnet are widely used in electric vehicles and hybrid electric vehicles. IPMSMs having high efficiency, high torque, and a wide speed range are employed in propulsion system. And the rotor in an IPMSM is generally made of a rare earth magnet to achieve a large energy product and high torque. This paper discusses issues regarding design and performance of IPMSMs using different factors of BH magnetic characteristic. It is necessary to choose factors of magnetic material according to permanent magnet shape in rotor for high performance. Response Surface Methodology (RSM) is selected to obtain factors of magnetic material according to variety of rotor shapes. The RSM is a collection of mathematical and statistical techniques useful for the analysis of problems in which a response of interest in influenced by several variables and the objective is to optimize response. Therefore, it is necessary to analyze the torque characteristics of an IPMSM having magnet BH hysteresis curve with different rotor shape. Factors of residual flux density (Br) factor and intrinsic coercive force (Hc) are important parameters in RSM for rotor shape. The rotor shapes for IPMSMs having magnet BH characteristic were investigated using the RSM, and three shapes were analyzed in detail using FEA. The results lead to design consequence of IPMSMs in the various rare earth magnet materials.

• Structural Engineering and Mechanics
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• v.49 no.1
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• pp.111-128
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• 2014

The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.6
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• pp.461-468
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of the given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a surrogate model that has a regression model performed on a data sampling of the simulation. In general, metamodels(surrogate model) take the form y($\chi$)＝f($\chi$)＋$\varepsilon$, where y($\chi$) is the true output, f($\chi$) is the metamodel output, and is the error. In this paper, a second order polynomial equation is used as the RSM(response surface model) for high speed train that have twenty-nine design variables and forty-six responses. After the RSM is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called VMM(variable matric method) This paper shows that the RSM is a very efficient model to solve the complex optimization problem.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.202-207
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• 2011

Numerous methodologies have been developed in an effort to reduce cogging torque. However, most of these methodologies have side effects that limit their applications. One approach is the optimization methodology that determines an optimized design variable within confined conditions. The response surface methodology (RSM) and the genetic algorithm (GA) are powerful instruments for such optimizations and are matters of common interest. However, they have some weaknesses. Generally, the RSM cannot accurately describe an object function, whereas the GA is time consuming. The current paper describes a novel GA and RSM hybrid algorithm that overcomes these limitations. The validity of the proposed algorithm was verified by three test functions. Its application was performed on a surface-mounted permanent magnet.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.11
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• pp.1097-1104
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• 2008

Working condition is one of the most important factors in precision working. In this study, we optimized the vibration acceleration of working progress direction using RSM(response surface methodology) by table of orthogonal array. RSM was well adapted to make analytic model for minimizing vibration acceleration, created the objective function and saved a great deal of computational time. Therefore, it is expected that the proposed optimization procedure using RSM can be easily utilized to solve the optimization problem of working condition. The experimental results of the surface roughness and vibration acceleration showed the validity of the proposed working condition of side wall end-milling as it can be observed.

• 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.

• CELLMED
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• v.11 no.3
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• pp.15.1-15.9
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• 2021

The chemical constitution of a drug has been accepted as an important basis for pharmacological action in Unani medicine. Various dosage forms have been developed on this concept, such as decoctions (Joshanda), infusions (Khesanda), extract (Rub / Usara), and syrup. Zarawand Mudaharaj (ZM.) / Aristolochia rotunda L. root was subjected to extraction process using Soxhlet's apparatus by using Response Surface Methodology (RSM) to design the number of random runs of the extracts with variation in the factors of temperature, the concentration of ethanol in water, time for extraction, for optimizing and maximizing the yield concentration. The data obtained, was analyzed with regression equation and ANOVA two-way summary to interpret the interaction of the factors for yield maximization. Minitab version 18 was used to design and analyze data. Validation of the optimum conditions for maximum yield of the whole extract of ZM. Root was carried out by re-run of the extract using the optimized conditions. The maximum yield percentage thus obtained using RSM was 20.87% whereas using these optimum conditions 21.35 % yield was obtained thereby validating the method. The association between the response functions and the process variables was identified by a three-factor recorded Box-Behnken design. In the present study RSM is used because itis a cheap and affordable method to optimize maximum yield percentage which may be reliably used by researchers. The study set in the surface conditions for ZM. root extraction by the Soxhlet apparatus for maximizing the yield percentage.