• Journal of Korean Academy of Nursing
• /
• v.43 no.2
• /
• pp.185-193
• /
• 2013

Purpose: Simulation-based learning has become a powerful method to improve the quality of care and help students meet the challenges of increasingly complex clinical practice settings. The purpose of this study was to identify the learning effects using high-fidelity SimMan and multi-mode simulation. Methods: Participants in this study were 38 students who were enrolled in an intensive course for a major in nursing at R college. Collected data were analyzed using Chi-square, t-test, and independent t-test with the SPSS 18.0 for Windows Program. Results: There were no statistically significant differences in learning effects between high-fidelity SimMan and multi-mode simulation group. However, skills in clinical performance in the high-fidelity SimMan group were higher than in the multi-mode group (p=.014), communication in clinical performance in multi-mode simulation group was higher than in the high-fidelity SimMan group (p<.001). Conclusion: Multi-mode simulation with a standardized patient is an effective learning method in many ways compared to a high-fidelity simulator. These results suggest that multi-mode simulation be offered to students in nursing colleges which cannot afford to purchase a high-fidelity simulator, or offered as an alternative.

• Journal of the Korea Society for Simulation
• /
• v.22 no.4
• /
• pp.67-82
• /
• 2013

This paper presents multi-fidelity modeling and simulation (M&S) methodology to enhance simulation performance of engineering-level defense models. In this approach, a set of models with varying degrees of fidelity is exercised to reduce computational expense maintaining a similar level of system effectiveness. For multi-fidelity M&S principles, this paper defines model fidelity from two perspectives (i.e., model behavior and execution), and suggests the Fidelity Change Point (FCP) to specify the fidelity conversion. With these concepts, this paper centers on three ideas: 1) two models' structure which are the Behavioral-Fidelity Interchangeable Model (B-FIM) and the Executional-Fidelity Interchangeable Model (E-FIM), 2) modeling formalism, and 3) a simulation algorithm to support them. From an abstract case study regarding a target tracking scenario with the utilization of the proposed method, we can gain interesting experimental results regarding the enhancement of simulation performance. Finally, we expect that this work will serve various M&S-based analysis areas for enhancing simulation performance.

• Nuclear Engineering and Technology
• /
• v.54 no.5
• /
• pp.1825-1834
• /
• 2022

Performing high-fidelity computational fluid dynamics (HF-CFD) to predict the flow and heat transfer state of the coolant in the reactor core is expensive, especially in scenarios that require extensive parameter search, such as uncertainty analysis and design optimization. This work investigated the performance of utilizing a multi-fidelity reduced-order model (MF-ROM) in PWR rod bundles simulation. Firstly, basis vectors and basis vector coefficients of high-fidelity and low-fidelity CFD results are extracted separately by the proper orthogonal decomposition (POD) approach. Secondly, a surrogate model is trained to map the relationship between the extracted coefficients from different fidelity results. In the prediction stage, the coefficients of the low-fidelity data under the new operating conditions are extracted by using the obtained POD basis vectors. Then, the trained surrogate model uses the low-fidelity coefficients to regress the high-fidelity coefficients. The predicted high-fidelity data is reconstructed from the product of extracted basis vectors and the regression coefficients. The effectiveness of the MF-ROM is evaluated on a flow and heat transfer problem in PWR fuel rod bundles. Two data-driven algorithms, the Kriging and artificial neural network (ANN), are trained as surrogate models for the MF-ROM to reconstruct the complex flow and heat transfer field downstream of the mixing vanes. The results show good agreements between the data reconstructed with the trained MF-ROM and the high-fidelity CFD simulation result, while the former only requires to taken the computational burden of low-fidelity simulation. The results also show that the performance of the ANN model is slightly better than the Kriging model when using a high number of POD basis vectors for regression. Moreover, the result presented in this paper demonstrates the suitability of the proposed MF-ROM for high-fidelity fixed value initialization to accelerate complex simulation.

• Wind and Structures
• /
• v.34 no.1
• /
• pp.127-136
• /
• 2022

In this work a multi-fidelity non-intrusive polynomial chaos (MF-NIPC) has been applied to a structural wind engineering problem in architectural design for the first time. In architectural design it is important to design structures that are safe in a range of wind directions and speeds. For this reason, the computational models used to design buildings and bridges must account for the uncertainties associated with the interaction between the structure and wind. In order to use the numerical simulations for the design, the numerical models must be validated by experi-mental data, and uncertainties contained in the experiments should also be taken into account. Uncertainty Quantifi-cation has been increasingly used for CFD simulations to consider such uncertainties. Typically, CFD simulations are computationally expensive, motivating the increased interest in multi-fidelity methods due to their ability to lev-erage limited data sets of high-fidelity data with evaluations of more computationally inexpensive models. Previous-ly, the multi-fidelity framework has been applied to CFD simulations for the purposes of optimization, rather than for the statistical assessment of candidate design. In this paper MF-NIPC method is applied to flow around a rectan-gular 5:1 cylinder, which has been thoroughly investigated for architectural design. The purpose of UQ is validation of numerical simulation results with experimental data, therefore the radius of curvature of the rectangular cylinder corners and the angle of attack are considered to be random variables, which are known to contain uncertainties when wind tunnel tests are carried out. Computational Fluid Dynamics (CFD) simulations are solved by a solver that employs the Finite Element Method (FEM) for two turbulence modeling approaches of the incompressible Navier-Stokes equations: Unsteady Reynolds Averaged Navier Stokes (URANS) and the Large Eddy simulation (LES). The results of the uncertainty analysis with CFD are compared to experimental data in terms of time-averaged pressure coefficients and bulk parameters. In addition, the accuracy and efficiency of the multi-fidelity framework is demonstrated through a comparison with the results of the high-fidelity model.

• International Journal of Fluid Machinery and Systems
• /
• v.8 no.3
• /
• pp.209-219
• /
• 2015

A robust multi-fidelity optimization methodology has been developed, focusing on efficiently handling industrial runner design of hydraulic Francis turbines. The computational task is split between low- and high-fidelity phases in order to properly balance the CFD cost and required accuracy in different design stages. In the low-fidelity phase, a physics-based surrogate optimization loop manages a large number of iterative optimization evaluations. Two derivative-free optimization methods use an inviscid flow solver as a physics-based surrogate to obtain the main characteristics of a good design in a relatively fast iterative process. The case study of a runner design for a low-head Francis turbine indicates advantages of integrating two derivative-free optimization algorithms with different local- and global search capabilities.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.42 no.2
• /
• pp.108-118
• /
• 2014

On the optimization design problem using surrogate model, it requires considerable number of sampling points to construct a surrogate model which retains the accuracy. As an alternative to reduce construction cost of the surrogate model, Variable-Fidelity Modeling(VFM) technique, where correct high fidelity model based on the low fidelity surrogate model is introduced. In this study, hierarchical kriging model for variable-fidelity surrogate modeling is used and an optimization framework with multi-objective genetic algorithm(MOGA) is presented. To prove the feasibility of this framework, airfoil design optimization process is performed for the transonic region. The parameters of PARSEC are used to design variables and the optimization process is performed in case of varying number of grid and varying fidelity. The results showed that pareto front of all variable-fidelity models are similar with its single-level of fidelity model and calculation time is considerably reduced. Based on computational results, it is shown that VFM is a more efficient way and has an accuracy as high as that single-level of fidelity model optimization.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.40 no.8
• /
• pp.695-702
• /
• 2012

In this study, Multi-fidelity analysis is performed to improve the accuracy of analysis result during conceptual design stage. Multidisciplinary Design Optimization(MDO) method is also considered to satisfy the total system requirements. Low-fidelity analysis codes which are based on empirical equations are developed and validated for analyzing the Unmanned Aerial Vehicle(UAV) which have unconventional configurations. Analysis codes consist of initial sizing, aerodynamics, propulsion, mission, weight, performance, and stability modules. Design synthesis program which is composed of those modules is developed. To improve the accuracy of the design method for UAV, Vortex Lattice Method is used for the strategy of MFA. Multi-Disciplinary Feasible(MDF) method is used for MDO technique. To demonstrate the validity of presented method, the optimization results of both methods are compared. According to those results, the presented method is demonstrated to be applicable to improve the accuracy of the analyses during conceptual design stage.

• 유체기계공업학회:학술대회논문집
• /
• 2006.08a
• /
• pp.33-36
• /
• 2006

As the computing environment is rapidly improved, the interests of CFD are gradually focused on large-scale computation over complex geometry. Keeping pace with the trend, essential computational tools to obtain solutions of complex aerospace flow analysis and design problems are examined. An accurate and efficient flow analysis and design codes for large-scale aerospace problem are presented in this work. With regard to original numerical schemes for flow analysis, high-fidelity flux schemes such as RoeM, AUSMPW+ and higher order interpolation schemes such as MLP (Multi-dimensional Limiting Process) are presented. Concerning the grid representation method, a general-purpose basis code which can handle multi-block system and overset grid system simultaneously is constructed. In respect to design optimization, the importance of turbulent sensitivity is investigated. And design tools to predict highly turbulent flows and its sensitivity accurately by fully differentiating turbulent transport equations are presented. Especially, a new sensitivity analysis treatment and geometric representation method to resolve the basic flow characteristics are presented. Exploiting these tools, the capability of the proposed approach to handle complex aerospace simulation and design problems is tested by computing several flow analysis and design problems.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2008.11a
• /
• pp.1314-1315
• /
• 2008

Recent research work has unearthed that multi-radio multi-channel wireless mesh networks offer considerable capacity gains over single-radio wireless mesh networks. In this paper, we present a new routing metric for multi-radio multi-channel wireless mesh networks. The goal of the metric is to choose multiple link/node disjoint paths between a source and destination node that, when used concomitantly, impart high end-to-end throughput. The proposed metric selects high fidelity paths that will produce elevated throughput with maximum fault tolerance.

• 한국정보통신설비학회:학술대회논문집
• /
• 2007.08a
• /
• pp.350-353
• /
• 2007

This paper presents an real-time implementation of H.264/AVC High 4:4:4 Predictive profile decoder using general-purpose processors by exploiting multi-threading technique and Single Instruction Multiple Data (SIMD) instructions without any quality degradation. We analyze differences between the existing High profile and High 4:4:4 Predictive profile decoder, and show various optimization techniques to decode high fidelity and high definition (HD) video in real-time. Simulation results show that the proposed decoder can play high fidelity HD video at average 40 frames per seconds (fps) for the IBBrBP bistream and about 50 fps for the Intra-only bitstream.