• Journal of the Korea Institute of Building Construction
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• v.2 no.4
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• pp.89-98
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• 2002

Self-leveling material(SLM) is one of the floor finishing materials which make flat surface like as water level by itself in a short time. So it is possible to increase construction speed and enhance economical efficiency In this study, author intended to develop SLM for the industrial warehouse and factory loading heavy weight machinery and vehicles. The demanded properties for this type of SLM are above 200mm of flow value and above 300kgf/$cm^2$ of 28-days compressive strength. To possess demended strength and fluidity, SLM have to be composed of many types of binders and chemical additives. So it is difficult to decide suitable mixing proportion of composition materials. In this study, author investigated the weight percentage effect of main composition materials for high-strength self-leveling material, by experimental design such as tables of orthogonal arrays and simplex design, and by statistical analysis such as analysis of variance and analysis of response surface. Variables of experiments were ordinary Portland cement(OPC), alumina cement(AC), anhydrous gypsum(AG), lime stone(LS) and sand, and properties of tests were fluidity of fresh state and strength of hardened state. Results of this study are showed that suitable mix proportions of binders for the high strength self-leveling materials are two groups. One is 78~85.5% OPC, 7.5~9.5% AC, 9~12.5% AG and the other is 72.5~78% OPC, 9~12.5% AC, 13~15% AG.

• Smart Structures and Systems
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• v.31 no.2
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• pp.113-130
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• 2023

Hybrid simulation (HS) has attracted community attention in recent years as an efficient and effective experimental technique for structural performance evaluation in size-limited laboratories. Traditional hybrid simulations usually take deterministic properties for their numerical substructures therefore could not account for inherent uncertainties within the engineering structures to provide probabilistic performance assessment. Reliable structural performance evaluation, therefore, calls for stochastic hybrid simulation (SHS) to explicitly account for substructure uncertainties. The experimental design of SHS is explored in this study to account for uncertainties within analytical substructures. Both computational simulation and laboratory experiments are conducted to evaluate the pseudo-random Sobol sequence for the experimental design of SHS. Meta-modeling through polynomial chaos expansion (PCE) is established from a computational simulation of a nonlinear single-degree-of-freedom (SDOF) structure to evaluate the influence of nonlinear behavior and ground motions uncertainties. A series of hybrid simulations are further conducted in the laboratory to validate the findings from computational analysis. It is shown that the Sobol sequence provides a good starting point for the experimental design of stochastic hybrid simulation. However, nonlinear structural behavior involving stiffness and strength degradation could significantly increase the number of hybrid simulations to acquire accurate statistical estimation for the structural response of interests. Compared with the statistical moments calculated directly from hybrid simulations in the laboratory, the meta-model through PCE gives more accurate estimation, therefore, providing a more effective way for uncertainty quantification.

• Journal of the Korean Statistical Society
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• v.36 no.2
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• pp.201-208
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• 2007

Evolutionary operation (EVOP) proposed by Box (1957) is a method for continuous monitoring and improvement of a full-scale manufacturing process with the objective of moving the operating conditions toward the better ones. EVOP consists of systematically making small changes in the levels of the two or three process variables under consideration. Data are collected on the response variable at each point of two level factorial design with the center point and a cycle is said to have been completed. The cycles are replicated sequentially until the decision is made on whether further cycle of experiments is needed to conclude the significance of any of main effects or interaction effects or the curvature. In this paper, an improved flow chart of EVOP is proposed and how to determine the number of cycles is studied based on the size of type II error. In order to reject the alternative hypothesis of interests with more confidence and conclude that we believe in the null hypothesis of no effects, we propose a counter measure $p^*-value$ corresponding to the p-value. The relationship of $p^*-value$ to the probability of type II error ${\beta}$ under the alternative hypothesis of interests is analogous to that of p-value to the probability of type I error ${\alpha}$. Also the implementation of EVOP with a mixture experiment is discussed.

• Transactions on Electrical and Electronic Materials
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• v.7 no.2
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• pp.81-86
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• 2006

In this paper, the response surface modeling of the control of the pretilt angle in the nematic liquid crystal on the homogeneous polyimide surface with different surface treatment is investigated. The pretilt angle is one of the main factors to determine the alignment of the liquid crystal display. The pretilt angle is measured to analyze the variation of the characteristics on the various process conditions. The rubbing strength and the hard baking temperature are considered as input factors. After the design of experiments is performed, the process model is then explored using the response surface methodology. The analysis of variance is used to analyze the statistical significance and the effect plots are also investigated to examine the relationship between the process parameters and the response.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.223-224
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• 2005

In this paper, multiple regression analysis of the electrical characteristics for $HfO_2$ thin films grown by metal organic molecular beam epitaxy (MOMBE) was investigated. The electrical properties, such as, the accumulation capacitance and the hysteresis index, are the main factors to determine the characteristics of $HfO_2$ thin films. The input factors on the process are the substrate temperature, Ar gas flow, and $O_2$ gas flow. For statistical analysis, the design of experiments was carried out and the effect plots were used to analyze the manufacturing process. This methodology can predict the electrical characteristics of the thin film growth mechanism related to the process conditions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.90-96
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• 2016

Incremental sheet forming (ISF) is a highly versatile and flexible process for rapid manufacturing of complex sheet metal parts. Compared to conventional sheet forming processes, ISF is of a clear advantage in manufacturing small batch or customized parts. ISF needs die-less machine alone, while conventional sheet forming requires highly expensive facilities like dies, molds, and presses. This equipment takes long time to get preparation for manufacturing. However, ISF does not need the full facilities nor much cost and time. Because of the facts, ISF is continuously being used for small batch or prototyping manufacturing in current industries. However, spring-back induced in the process of incremental forming becomes a critical drawback on precision manufacturing. Since sheet metal, being a raw material for ISF, has property to resilience, spring-back would come in the case. It is the research objective to investigate how geometrical shaping parameters make effect on shape dimensional errors. In order to analyze the spring-back occurred in the process, this study experimented on Al 1015 material in the ISF. The statistical tool employed experimental design with factors. The table of orthogonal arrays of $L_8(2^7)$ are used to design the experiments and ANOVA method are employed to statistically analyze the collected data. The results of the analysis from this study shows that the type of shape and the slope of bottom are the significant, whereas the shape size, the shape height, and the side angle are not significant factors on dimensional errors. More error incurred on the pyramid than on the circular type in the experiments. The sloped bottom showed higher errors than the flat one.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.457-461
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• 2007

In many applications, received signal strength indicator is used for location tracking and sensor nodes localization. For location finding, the distances between sensor nodes can be estimated by converting received signal's power into distance using path loss prediction model. Many researches have done the analysis of power-distance relationship for radio channel characterization. In indoor environment, the general conclusion is the non-linear variation of RSSI values as distance varied linearly. This has been one of the difficulties for indoor localization. This paper presents works on indoor RSSI characterization based on statistical methods to find the overall trend of RSSI variation at different places and times within the same room From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. This two factors are directly indicated by the two main parameters of path loss prediction model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. Using this relationship, the characterization for location estimation can be more efficient and accurate.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.711-714
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• 2002

At the lift-off condition, the combustion and Jet noise of launch vehicle produces a severe acoustic environment and the acoustic loads may be damaging to paylaod and equipments. Prediction of the acoustic environment is thus needed to support the load-resistive design and test-qualification of components. Currently, such a high frequency problem is usually dealt with by using the SEA technique, for which the assumptions should match reasonably well with the vibro-acoustic condition of system. The subsystems of SEA model was composed of 16 flat plates, 8 L-shaped beams, and 2 acoustic cavities. The frequency range was 400 Hz - 4 kHz considering the modal parameter. The experiment was performed in a high intensity acoustic chamber, in which the diffuse acoustic field was assured. By comparing the SEA analysis and the experiments, the error less than 5 dB was observed.

• The Journal of Korean Academy of Prosthodontics
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• v.44 no.2
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• pp.185-196
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• 2006

Statement of problem: The researches on the influence of design variables on the stress distribution in cortical and trabecular bones and on optimal design for implant system were limited. Purpose: The purpose of this study is to identify the sensitivities of design parameters and to suggest the optimal parameters for designing the onebody type implant system. Material and methods: Stresses arising in the implant system were obtained by finite element analysis using a three dimensional model. An onebody type implant system[Oneplant (Warrantec. Co. Ltd., Korea)] was considered in this study. Vortical load(150 N) was applied on the top of the abutment along the axial direction. The initial design variables set for sensitivity analysis were radius of fixture, numbers of micro thread, numbers of power thread, height of micro thread, future length, tapered angle of future, inclined angle of thread, width of micro thread and width of power thread. The statistical technique of Design of Experiments(DOE) was applied tn the simulation model to deduce effective design parameters on stress distributions in bones. The deduced design parameters were incorporated into a fully automated design tool which is coupled with the finite element analysis and numerical optimization to determine the optimal design parameters. Results: 1. The result of sensitivity analysis showed six design variables - radius of future, tapered angle of fixture, inclined angle of thread, numbers of power thread, numbers of micro thread and height of micro thread - were more influential than the others. 2. The optimal values of design variables can be deduced by coupling finite element analysis (FEA) and design optimization tool(DOT).

• Structural Engineering and Mechanics
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• v.75 no.5
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• pp.633-642
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• 2020

Artificial neural networks (ANNs) are known as intelligent methods for modeling the behavior of physical phenomena because of it is a soft computing technique and takes data samples rather than entire data sets to arrive at solutions, which saves both time and money. ANN is successfully used in the civil engineering applications which are suitable examining the complicated relations between variables. Functionally graded materials (FGMs) are advanced composites that successfully used in various engineering design. The FGMs are nonhomogeneous materials and made of two different type of materials. In the present study, the bending analysis of functionally graded material (FGM) beams presents on theoretical based on combination of mixed-finite element method, Gâteaux differential and Timoshenko beam theory. The main idea in this study is to build a model using ANN with four parameters that are: Young's modulus ratio (E_t/E_b), a shear correction factor (k_s), power-law exponent (n) and length to thickness ratio (L/h). The output data is the maximum displacement (w). In the experiments: 252 different data are used. The proposed ANN model is evaluated by the correlation of the coefficient (R), MAE and MSE statistical methods. The ANN model is very good and the maximum displacement can be predicted in ANN without attempting any experiments.