• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.5 no.4
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• pp.249-256
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• 1993

Numerical method is applied to predict the time variation behavior of flammable mixture formation in a two dimensional enclosure from the beginning of gas leak. Additionally experimental method is used to consider qualitative aspects. Characteristics of flammable mixture formation such as distribution of flow and fuel mass fraction at various locations in the enclosure are determined for the following parameters: the various locations of leak at the bottom and aspect ratio of the enclosure. In the case of gas leak with small leak velocity from the bottom of enclosure gravitational force affects the formation of flammable mixture. Aspect ratio of the enclosure also affects the formation of flammable mixture. The volume of the region of recirculating flow is dominant factor affecting the formation mixture.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.3
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• pp.79-84
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• 1998

It is very difficult to analyze the transient temperature distribution during quenching of the steel because of coupled effects among temperature, structures and stresses. In this paper, using Inoue's equation of evolution and mixture rule, transient temperature distribution is calculated by the finite element method considering latent heat of transformation structure and temperature dependence of physical and mechanical prperties for the 0.45% carbon cylindrical steel bar with 40mm diameter and 20mm height during end-quenching.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.12
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• pp.1605-1612
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• 2012

The distribution of a response usually depends on the distribution of the variables. When a variable shows a distribution with two different modes, the response also shows a distribution with two different modes. In this case, recently developed methods for reliability analysis assume that the distribution functions are continuous with a mode. In actual problems, however, because information is often provided in a discrete form with two or more modes, it is important to estimate the distributions for such information. In this study, we employ the finite mixture model to estimate the response distribution with two different modes, and we select the best candidate distribution through AIC. Mathematical examples are illustrated to verify the proposed method.

• Transactions of Materials Processing
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• v.8 no.4
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• pp.399-406
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• 1999

It is more appropriate to treat that the semi-solid mixture as a single phase material that obeys incompressibility in the global sense and to analyze the liquid flow only locally than the approach based on compressible yield criteria. In the present study, a numerical algorithm of updating the solid volume fraction based on mixture theory has been developed. Finite element analysis of simple upsetting was carried out using the proposed algorithm to investigate the degree of macro-segregation according to friction conditions and compressive strain rates under the isothermal condition. The simulation results were compared to experimental results available in reference to test the validity of the currently proposed algorithm. Since the comparison results show a good agreement it is construed that the proposed algorithm can contribute to the development of numerical analysis of determining the solid volume fraction semi-solid processing.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.57-68
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• 2017

Clustering algorithms attempt to find a partition of a finite set of objects in to a potentially predetermined number of nonempty subsets. Gibbs sampling of a normal mixture of linear mixed regressions with a Dirichlet prior distribution calculates posterior probabilities when the number of clusters was known. Our approach provides simultaneous partitioning and parameter estimation with the computation of classification probabilities. A Monte Carlo study of curve estimation results showed that the model was useful for function estimation. Examples are given to show how these models perform on real data.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.809-824
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• 2017

The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.

• Communications of the Korean Mathematical Society
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• v.14 no.2
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• pp.405-423
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• 1999

We consider a statistical multiplexer model with finite buffer capacity and finite number of independent identical 3-state bursty voice sources. The burstiness of the sources is modeled by describing both two different active periods (at the rate of one packet perslot) and the passive periods during which no packets are generated. Assuming a mixture of two geometric distributions for active period and a geometric distribution for passive period and geometric distribution for passive period, we derive the recursive algorithm for the probability mass function of the buffer contents (in packets). We also obtain loss probability and the distribution of packet delay. Numerical results show that the system performance deteriorates considerably as the variance of the active period increases. Also, we see that the loss probability of 2-state Markov models is less than that of 3-state Markov models.

• Structural Engineering and Mechanics
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• v.74 no.1
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• pp.55-67
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• 2020

The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.9 no.3
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• pp.161-169
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• 1980

In order to enhance the thermal energy storage capacity of cement mortar and to improve the effective thermal conductivity of paraffin waxes, cement- sand- paraffin wax mixture was investigated. By means of finite difference method, the transient temperature distribution in a hollow cylinder with phase change using average composite properties was obtained, and compared with experimental results. It was shown that the heat absorbed by mixture with $25\%$ paraffin fraction was as much as $50\%$ more than either a concrete mortar or pure paraffin wax in the case of ${\Delta}T=\;18.25^{\circ}C$.

• Steel and Composite Structures
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• v.43 no.1
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• pp.1-17
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• 2022

The free and forced nonlinear dynamic behaviors of Porous Functionally Graded Material (PFGM) plates are examined by means of a High-Order Implicit Algorithm (HOIA). The formulation is developed using the Third-order Shear Deformation Theory (TSDT). Unlike previous works, the formulation is written without resorting to any homogenization technique neither rule of mixture nor considering FGM as a laminated composite, and the distribution of the porosity is assumed to be gradually variable through the thickness of the PFGM plates. Using the Hamilton principle, we establish the governing equations of motion. The Finite Element Method (FEM) is used to compute approximations of the resulting equations; FEM is adopted using a four-node quadrilateral finite element with seven Degrees Of Freedom (DOF) per node. Nonlinear equations are solved by a HOIA. The accuracy and the performance of the proposed approach are verified by presenting comparisons with literature results for vibration natural frequencies and dynamic response of PFGM plates under external loading. The influences of porosity volume fraction, porosity distribution, slenderness ratio and other parameters on the vibrations of PFGM plate are explored. The results demonstrate the significant impact of different physical and geometrical parameters on the vibration behavior of the PFGM plate.