• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.686-695
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• 2009

Flow characteristics in linear axial cascade have been studied using large eddy simulation(LES) based on finite element method(FEM) to investigate details of the leakage flow in the tip clearance of axial flow rotor. STAR-CD(FVM) and PAT-Flow(FEM) have been adopted to solve the Navier-Stokes equations for the simulation of the unsteady turbulent flow. Numerical results from the present study have been compared with the existing experimental results to investigate a tip clearance effect on velocity profile and static pressure distribution on blade surface at various spanwise positions. Both simulation results agree well with the experimental data. However, it has been shown that the results of finite-element large-eddy simulation agree better with experimental data than $k-{\varepsilon}$ turbulent model based on finite volume method regarding the tip vortex geometry and static pressure distribution at the center of the tip vortex core. As a result of this study, it is shown that finite-element large-eddy simulation method can predict more exactly on the tip leakage vortex flow and behind flow field.

• Korea-Australia Rheology Journal
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• v.14 no.4
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• pp.161-174
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• 2002

A new technique for numerical calculation of viscoelastic flow based on the combination of Neural Net-works (NN) and Brownian Dynamics simulation or Stochastic Simulation Technique (SST) is presented in this paper. This method uses a "universal approximator" based on neural network methodology in combination with the kinetic theory of polymeric liquid in which the stress is computed from the molecular configuration rather than from closed form constitutive equations. Thus the new method obviates not only the need for a rheological constitutive equation to describe the fluid (as in the original Calculation Of Non-Newtonian Flows: Finite Elements St Stochastic Simulation Techniques (CONNFFESSIT) idea) but also any kind of finite element-type discretisation of the domain and its boundary for numerical solution of the governing PDE's. As an illustration of the method, the time development of the planar Couette flow is studied for two molecular kinetic models with finite extensibility, namely the Finitely Extensible Nonlinear Elastic (FENE) and FENE-Peterlin (FENE-P) models.P) models.

• Journal of Korea Multimedia Society
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• v.23 no.7
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• pp.830-839
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• 2020

As a popular mathematical framework for modeling decision making, Markov decision process (MDP) has been widely used to solve problem in many engineering fields. MDP consists of a set of discrete states, a finite set of actions, and rewards received after reaching a new state by taking action from the previous state. The objective of MDP is to find an optimal policy, that is, to find the best action to be taken in each state to maximize the expected discounted reward of policy (EDR). In practice, MDP is typically unknown, so simulation-based policy improvement (SBPI), which improves a given base policy sequentially by selecting the best action in each state depending on rewards observed via simulation, can be a practical way to find the optimal policy. However, the efficiency of SBPI is still a concern since many simulation samples are required to precisely estimate EDR for each action in each state. In this paper, we propose a method to select the best action accurately in each state using a small number of simulation samples, thereby improving the efficiency of SBPI. The proposed method accumulates the simulation samples observed in the previous states, so it is possible to precisely estimate EDR even with a small number of samples in the current state. The results of comparative experiments on the existing method demonstrate that the proposed method can improve the efficiency of SBPI.

• Proceedings of the Korea Society for Simulation Conference
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• 1992.10a
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• pp.6-6
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• 1992

This work deals with nonlinear least squares method for estimating unknown universial constants C in a computer simulation code real experimental data(or database) and computer simulation data. The best linear unbiased predictor based on a spatial statistical model is fitted from the computer simulation data. Then nonlinear least squares estimation method is applied to the real data using the fitted prediction model(or simulation predictor) as if it were the true simulation model. An application to the computational nuclear fusion device is presented.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1081-1103
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• 2014

Real-time hybrid simulation (RTHS) has emerged as an important tool for testing large and complex structures with a focus on rate-dependent specimen behavior. Due to the real-time constraints, accurate dynamic control of servo-hydraulic actuators is required. These actuators are necessary to realize the desired displacements of the specimen, however they introduce unwanted dynamics into the RTHS loop. Model-based actuator control strategies are based on linearized models of the servo-hydraulic system, where the controller is taken as the model inverse to effectively cancel out the servo-hydraulic dynamics (i.e., model-based feedforward control). An accurate model of a servo-hydraulic system generally contains more poles than zeros, leading to an improper inverse (i.e., more zeros than poles). Rather than introduce additional poles to create a proper inverse controller, the higher order derivatives necessary for implementing the improper inverse can be calculated from available information. The backward-difference method is proposed as an alternative to discretize an improper continuous time model for use as a feedforward controller in RTHS. This method is flexible in that derivatives of any order can be explicitly calculated such that controllers can be developed for models of any order. Using model-based feedforward control with the backward-difference method, accurate actuator control and stable RTHS are demonstrated using a nine-story steel building model implemented with an MR damper.

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.1-24
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• 2007

I propose new combined randomized methods for global optimization problems. These methods are based on the Nested Partitions(NP) method, a useful method for simulation optimization which guarantees global optimal solution but has several shortcomings. To overcome these shortcomings I hired various statistical selection methods and combined with NP method. I first explain the NP method and statistical selection method. And after that I present a detail description of proposed new combined methods and show the results of an application. As well as, I show how these combined methods can be considered in case of computing budget limit problem.

• Genomics & Informatics
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• v.20 no.1
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• pp.8.1-8.14
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• 2022

Despite the success of recent genome-wide association studies investigating longitudinal traits, a large fraction of overall heritability remains unexplained. This suggests that some of the missing heritability may be accounted for by gene-gene and gene-time/environment interactions. In this paper, we develop a Bayesian variable selection method for longitudinal genetic data based on mixed models. The method jointly models the main effects and interactions of all candidate genetic variants and non-genetic factors and has higher statistical power than previous approaches. To account for the within-subject dependence structure, we propose a grid-based approach that models only one fixed-dimensional covariance matrix, which is thus applicable to data where subjects have different numbers of time points. We provide the theoretical basis of our Bayesian method and then illustrate its performance using data from the 1000 Genome Project with various simulation settings. Several simulation studies show that our multivariate method increases the statistical power compared to the corresponding univariate method and can detect gene-time/ environment interactions well. We further evaluate our method with different numbers of individuals, variants, and causal variants, as well as different trait-heritability, and conclude that our method performs reasonably well with various simulation settings.

• Journal of Ocean Engineering and Technology
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• v.30 no.1
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• pp.10-17
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• 2016

This paper reports a simulation-based design method for the optimized arrangement design of buoyancy modules in a marine riser system. A buoyancy module is used for the safe operation and structural stability of the riser. Engineers design buoyancy modules based on experience and experimental data. However, they are difficult to design because of the difficulty of conducting real sea experiments and quantifying the data. Therefore, a simulation-based design method is needed to tackle this problem. In this study, we developed a simulation-based design algorithm using a multi-body dynamic simulation and genetic algorithm to perform optimization arrangement design of a buoyancy module. The design results are discussed in this paper.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.170-202
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• 2001

Simulation is used to reduce a risk involved in the new project and decision-making in an organization and to save cost and time by forecasting different situations. The objectives of this research are to acknowledge the need of simulation through the real life sample and to encourage the use of the simulation method in the future consulting project by continuously making the necessary improvements. This research analyzed the effectiveness of the simulation based on the sample use of simulation method in 1994 and 1997 for the BPR project of certification issuance process at the Supreme Court. In order to evaluate the value of the proposed simulation model, we examined the gap, which existed between the simulation result and the operational data collected by visiting the actual sites where AROS (Automated Registry Office System: automation system developed by LG-EDS Systems) is being utilized. We also identified the causes for the existing gap. According to the analysis result, (1) the gap came from the status change of thinking that the concentration of certification issuance request has eased after the computerization, (2) the gap existed in the operational process because they failed to consider the situational factors of each registry office in the simulation model, and (3) lastly the gap came from the difficulty of formulating the mathematical model for predicting the complex and diverse behavior pattern of individuals requesting the certification issuance. In order to narrow the existing gaps, we made a proposal to improve the certification issuance process where software of certification issuance vending machine was upgraded in order to help the people to use the service conveniently, more part time workers were hared when there was a overload of certification issuance request, and the quality of the certification Issuance vending machine is improved, In this research, we examined an efficient way of resource allocation based on the simulation conducted in 1994 and 1997. By reflecting changes since the simulation of 1994 and allocating the clerk and machine based on the predicted results of the simulation, we maximized the efficiency of the certification issuance process. In conclusion, this research examined the future usability of simulation method based on the analysis result and identified the key issues to consider when using the simulation method in the future consulting project.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.10a
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• pp.105-108
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• 1998

기존 시뮬레이션 환경에서 개발한 모델들은 재사용을 하는 데 많은 어려움이 있다. 또한 시스템이 대형화되고 시뮬레이션 결과를 실시간으로 얻어내야 하는 경우에 기존의 순차적 시뮬레이션 방법을 적용하면 시간이 많이 소요되므로 새로운 시뮬레이션 수행 방법이 필요하게 되었다. 본 논문에서는 이러한 제약을 해결하고자 Internet상에서 시뮬레이션이 가능한 Web-Based Simulation 환경을 설계하고 구현하였다. 본 연구는 자바의 분산 객체 모델인 RMI(Remote Method Invocation)를 웹 기술과 통합하고, 대규모 개발 및 많은 유지비를 요구하는 시뮬레이션의 개발에 이용할 수 있는 새로운 분산 환경하에서의 Web-Based Simulation 구조를 제시하고 구현해 본다.