• Fire Science and Engineering
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• v.32 no.1
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• pp.7-15
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• 2018

The prediction performance of combustion models in the Fire Dynamics Simulator (FDS) were evaluated by comparing with experiment for compartment propane gas fires. The mixture fraction model in the FDS v5.5.3 and Eddy Dissipation Concept (EDC) model in the FDS v6.6.3 were adopted in the simulations. Four chemical reaction mechanisms, such as 1-step Mixing Controlled, 2-step Mixing Controlled, 3-step Mixing Controlled and 3-step Mixed (Mixing Controlled + finite chemical reactions) reactions, were implemented in the EDC model. The simulation results with each combustion model showed similar level for the temperature inside the compartment. The prediction performance of FDS with each combustion model showed significant differences for the CO concentration while no distinguished differences were identified for the $O_2$ and $CO_2$ concentrations. The EDC 3-step Mixing Controlled largely over-predicted the CO concentration obtained by experiment and the mixture fraction model under-predicted the experiment slightly. The EDC 3-step Mixed showed the best prediction performance for the CO concentration and the EDC 2-step Mixing Controlled also predicted the CO concentration reasonably. The EDC 1-step Mixing Controlled significantly under-predict the experimental CO concentration when the previously suggested CO yield was adopted. The FDS simulation with the EDC 1-step Mixing Controlled showed difficulties in predicting the $CO_2$ concentration when the CO yield was modified to predict the CO concentration reasonably.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.169-177
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• 2005

A high resolution scheme for solving gas-liquid two-phase flows with cavitation is described. This scheme uses the curvilinear coordinate grid and solves the density based momentum equations for mixture of gas-liquid medium with a preconditioning method to treat both compressible and incompressible flow characteristics. The present preconditioned method is based on the Runge-Kutta explicit finite-difference scheme, and is improved by using the diagonalization, the flux difference splitting and the MUSCL-TVD schemes to save computational effort and to increase stability and resolvability, especially at gas-liquid contact surfaces. A homogeneous equilibrium cavitation model is used to treat the gas-liquid two-phase medium in cavitating flow as a locally homogeneous pseudo-single-phase medium. Therefore, it is easy to solve cavitating flow, including wave propagation, large density changes and incompressible flow characteristic at low Mach number. Some numerical results obtained by the present scheme are shown.

• Journal of Korean Society for Atmospheric Environment
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• v.12 no.5
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• pp.577-585
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• 1996

A screening study was performed in order to resolve the flow, combustion and emission characteristics of the gas furmace with co-axial diffusion flane burner. A control-valume based finite-difference method with the power-law scheme was employed for discretization. Numerical procedure for the differential equation was used by SIMPLEST to enclosute rapid converge. A k-.varepsilon. model was incorporated for the closure of turbulence. The mass fraction and mixture fraction were calculated by cinserved scalar method. An equilibrium analysis was employed to determine the concentration of radicals in the product stream and conserbation equations were them solved for N amd NO by Zelovich reaction scheme. The method was exercised in a simple one-dimensional case first, to determine the effects of air ratio, temperature and residence time on NO formation and applied to a furnace with co-axial diffusion flame burner.

• 한국연소학회:학술대회논문집
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• 2003.12a
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• pp.3-9
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• 2003

By utilizing a semi-empirical soot model, the applicability of the laminar flamelet concept for simulating the formation and oxidation of soot in the laminar diffusion flame has been studied. The source terms for two transport equations of the soot formation and oxidation are calculated in the mixture fraction/scalar dissipation rate space for laminar flamelets and stored in a library. In this study, emphasis is given to the interaction associated with radiation and soot formation. The radiative heat loss is obtained by solving the radiative transfer equation using the unstructured grid finite volume method with the WSGGM. The calculated temperatures and soot volume fractions agree relatively well with the experimental data and the previous numerical results of Kaplan et al. using the detailed chemistry.

• The KSFM Journal of Fluid Machinery
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• v.11 no.3
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• pp.7-13
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• 2008

The cavitating flow simulation is of practical importance for many engineering systems, such as pump, turbine, nozzle, Infector, etc. In the present work, a solver for two-phase flows has been developed and applied to simulate the cavitating flows past hydrofoils. The governing equation is the two-phase Navier-Stokes equation, comprised of the continuity equation of liquid and vapor phase. The momentum and energy equation is in the mixture phase. The solver employs an implicit, dual time, preconditioned algorithm using finite difference scheme in curvilinear coordinates. An experimental data and other numerical data were compared with the present results to validate the present solver. It is concluded that the present numerical code has successfully accounted for two-phase Navier-Stokes model of cavitation flow.

• Journal of Korean Academy of Nursing
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• v.42 no.1
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• pp.48-55
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• 2012

Purpose: The aim of this study was to compare statistical methods to control response bias in nursing activity surveys. Methods: Data were collected at a medical unit of a general hospital. The number of nursing activities and consumed activity time were measured using self-report questionnaires. Descriptive statistics were used to identify general characteristics of the units. Average, Z-standardization, gamma regression, finite mixture model, and stochastic frontier model were adopted to estimate true activity time controlling for response bias. Results: The nursing activity time data were highly skewed and had non-normal distributions. Among the 4 different methods, only gamma regression and stochastic frontier model controlled response bias effectively and the estimated total nursing activity time did not exceeded total work time. However, in gamma regression, estimated total nursing activity time was too small to use in real clinical settings. Thus stochastic frontier model was the most appropriate method to control response bias when compared with the other methods. Conclusion: According to these results, we recommend the use of a stochastic frontier model to estimate true nursing activity time when using self-report surveys.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.173-184
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• 2018

In medical or public health research, it is common to encounter clustered or longitudinal count data that exhibit excess zeros. For example, health care utilization data often have a multi-modal distribution with excess zeroes as well as a multilevel structure where patients are nested within physicians and hospitals. To analyze this type of data, zero-inflated count models with mixed effects have been developed where a count response variable is assumed to be distributed as a mixture of a Poisson or negative binomial and a distribution with a point mass of zeros that include random effects. However, no study has considered a situation where data are also censored due to the finite nature of the observation period or follow-up. In this paper, we present a weighted version of zero-inflated Poisson model with random effects accounting for variable individual follow-up times. We suggested two different types of weight function. The performance of the proposed model is evaluated and compared to a standard zero-inflated mixed model through simulation studies. This approach is then applied to Medicaid data analysis.

• Smart Structures and Systems
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• v.21 no.5
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• Interaction and multiscale mechanics
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• v.2 no.1
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• pp.45-68
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• 2009

An aim of the study is to develop an efficient numerical simulation technique that can handle the two-scale analysis of fluid permeation filters fabricated by the partial sintering technique of small spherical ceramics. A solid-fluid mixture homogenization method is introduced to predict the mechanical characters such as rigidity and permeability of the porous ceramic filters from the micro-scale geometry and configuration of partially-sintered particles. An extended finite element (X-FE) discretization technique based on the enriched interpolations of respective characteristic functions at fluid-solid interfaces is proposed for the non-interface-fitted mesh solution of the micro-scale analysis that needs non-slip condition at the interface between solid and fluid phases of the unit cell. The homogenization and localization performances of the proposed method are shown in a typical two-dimensional benchmark problem whose model has a hole in center. Three-dimensional applications to the body-centered cubic (BCC) and face-centered cubic (FCC) unit cell models are also shown in the paper. The 3D application is prepared toward the computer-aided optimal design of ceramic filters. The accuracy and stability of the X-FEM based method are comparable to those of the standard interface-fitted FEM, and are superior to those of the voxel type FEM that is often used in such complex micro geometry cases.

• 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.