• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.192-197
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• 2015

In many fields, the importance of reducing weight is increasing. A product should be designed such that it is profitable, by lowering costs and exhibiting better performance than other similar products. In this study, the mass and deflection of steel structures have to be reduced as objective functions under constraint conditions. To reduce computational analysis time, central composite design(CCD) and D-Optimal are used in design of experiments(DOE). The accuracy of approximate models is evaluated using the $R^2$ value. In this study, the objective functions are multiple, so the non-dominant sorting genetic algorithm(NSGA-II), which is highly efficient, is used for such a problem. In order to verify the validity of Pareto solutions, CAE results and Pareto solutions are compared.

• Communications for Statistical Applications and Methods
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• v.21 no.2
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• pp.161-168
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• 2014

In mixture experiments with process variables, we consider the case that some of process variables are either uncontrollable or hard to control, which are called noise variables. Given the such mixture experimental data with process variables, first we study how to search for candidate models. Good candidate models are screened by the sequential variables selection method and checking the residual plots for the validity of the model assumption. Two methods, which use numerical optimization methods proposed by Derringer and Suich (1980) and minimization of the weighted expected loss, are proposed to find a cost-effective robust optimal condition in which the performance of the mean as well as the variance of the response for each of the candidate models is well-behaved under the cost restriction of the mixture. The proposed methods are illustrated with the well known fish patties texture example described by Cornell (2002).

• Journal of Korean Society for Quality Management
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• v.33 no.1
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• pp.73-82
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• 2005

This article proposes a practical approach, which is based on the concept of the expected squared relative error, that can consider both the prediction quality and the practitioner's subjectivity in simultaneously optimizing multiple responses. Through a case study, multiresponse optimization using the expected squared relative error approach is illustrated, and the SAS program to implement the proposed method is provided.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.10a
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• pp.42-49
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• 1997

In this paper, the method for soil-structure interaction analyses in the time domain is proposed. The far field soil region which is the outside of the artificial boundary is modeled by using explicit frequency-dependent two dimensional infinite elements which can include multiple wave components propagating into the unbounded medium. Since the dynamic stiffness matrix of the far field soil region using the proposed infinite elements is obtained explicitly in terms of exciting frequencies and constants in the frequency domain, the matrix can be easily transformed into the displacement unit-impulse response matrix, which corresponds to a convolution integral of it in the time domain. To verify the proposed method for soil-structure interaction analyses in the time domain, the displacement responses due to an impulse load on the surface of a soil layer with the rigid bed rock are compared with those obtained by the method in the frequency domain and those by models with extend finite element meshes. Good agreements have been found between them.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.4
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• pp.67-74
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• 2008

The important dynamic specifications in the aluminum automobile body design are the vibrations and crashworthiness in the views of ride comforts and safety. Thus, considerable effort has been invested into improving the performance of mechanical structures comprised of the interactive multiple sub-structures. Most mechanical structures are complex and are essentially multi-criteria optimization problems with objective functions retained as constraints. Each weight factor can be defined according to the effects and priorities among objective functions, and a feasible Pareto-optimal solution exists for the criteria-defined constraints. In this paper, a multi-criteria design based on the Pareto-optimal sensitivity is applied to the vibration qualities and crushing characteristics of front structure in the automobile body design. The vibration qualities include the idle, wheel unbalance and road shake. The crushing characteristic of front structure is the axial maximum peak load.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.3
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• pp.232-238
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• 2011

In the present study, Taguchi method is used to determine the rough region first, followed by RSM technique to determine the exact optimum value during milling on a machining center. A region reducing algorithm is applied to narrow down the region of the Taguchi method for RSM. The result from the Taguchi method is fed to train the artificial neural network (ANN), whose optimum value is used to drive the region reducing algorithm. The proposed algorithm is tested under different cutting condition and results show that the introduced algorithm works well during milling process. It is also shown that theoretically obtained optimal cutting condition is very close to experimentally obtained result.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1412-1420
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• 2018

An experiment was performed using the large-scale test facility (LSTF), which simulated a 1% vessel upper head small-break loss-of-coolant accident with an accident management (AM) measure under an assumption of total-failure of high-pressure injection (HPI) system in a pressurized water reactor (PWR). In the LSTF test, liquid level in the upper head affected break flow rate. Coolant was manually injected from the HPI system into cold legs as the AM measure when the maximum core exit temperature reached 623 K. The cladding surface temperature largely increased due to late and slow response of the core exit thermocouples. The AM measure was confirmed to be effective for the core cooling. The RELAP5/MOD3.3 code indicated insufficient prediction of primary coolant distribution. The author conducted uncertainty analysis for the LSTF test employing created phenomena identification and ranking table for each component. The author clarified that peak cladding temperature was largely dependent on the combination of multiple uncertain parameters within the defined uncertain ranges.

• Advances in nano research
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• v.15 no.2
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• pp.129-139
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• 2023

Emerge of nanotechnology has affected many aspects of our life and also triggers research studies in many fields. Nano-medicine are proven to be effective in encountering diseases. In the present study, aspects of the applications and effectiveness of nano-medicine in pediatrics patients are studied. In this regard, using experimental data of previous published researches, combination and dose of nano-medicines are optimized using response surface method and neural-fuzzy inference network. The input parameters of the selected multiple nano-medicines are dose and type and the output is the effectiveness of the combinations using IC50 parameter. A detailed parameter study is presented to observe effects of each inputs on the IC50. The results indicate that personalized scaling of nano-medicine is required in therapy of pediatric diseases such as cancers.

• Design & Manufacturing
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• v.17 no.3
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• pp.1-7
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• 2023

Blow molding is a manufacturing process in which thermoplastic preforms are preheated and then pneumatically expanded within a mold to produce hollow products of various shapes. The two-step process, a type of blow molding method, requires the output of multiple infrared lamps to be adjusted individually, so the process of finding initial conditions hinders productivity. In this study, digital twin technology was applied to solve this problem. A blow molding simulation technique was established and simulation-based metadata was generated. A response surface ROM (Reduced Order Model) was built using the generated metadata. Then, a dynamic ROM was constructed using the results of 3D heat transfer analysis. Through this, users can quickly check the product wall thickness uniformity according to changes in the control value of the heating lamp for products of various shapes, and at the same time, check the temperature distribution of the preform in real time.

• 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).