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

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1178-1185
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• 2012

The 4th year medical students were randomly divided and designated as group HF and LF, representing high and low fidelity simulations respectfully. Both groups performed OSCE on 2 topics(adult intubation and IV cannulation) with each composed of the same scenario. Each scenario was developed by a faculty in charge of clinical skill education with supervision from 2 other faculty members. High fidelity simulations were designed as in-situ simulations in real OR. Low fidelity simulations had the same scenarios but the environment was simulated only with a simple task trainer in the classroom. All students participated in series of survey using a Likert scale before and after the simulations. The provided data was anlayzed with paired T-test and Mann-Whiteney test(p<0.05). The post simulations self evaluation score for group HF was lower than pre-simulation self confidence score for both topics of adult intubation and IV cannulation where as for group LF, it was lower only for adult intubation(p<0.05). In group HF, the needs for clinical training on both topics increased after the simulation. In group LF, there was no significant change of needs for clinical training between pre and post simulation survey. This suggest that fidelity may be a helpful factor to improve the motivation of the students and further study on economical aspect should be addressed.

• Wind and Structures
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• v.34 no.6
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• pp.499-510
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• 2022

Computational Wind Engineering has rapidly grown in the last decades and it is currently reaching a relatively mature state. The prediction of wind loading by means of numerical simulations has been proved effective in many research studies and applications to design practice are rapidly spreading. Despite such success, caution in the use of simulations for wind loading assessment is still advisable and, indeed, required. The computational burden and the know-how needed to run high-fidelity simulations is often unavailable and the possibility to use simplified models extremely attractive. In this paper, the applicability of some well-known 2D unsteady RANS models, particularly the k-ω SST, in the aerodynamic characterization of extruded bodies with bluff sections is investigated. The main focus of this paper is on the drag coefficient prediction. The topic is not new, but, in the authors' opinion, worth a careful revisitation. In fact, despite their great technical relevance, a systematic study focussing on sections which manifest a fully detached flow configuration has been overlooked. It is here shown that the considered 2D RANS exhibit a pathological behaviour, failing to reproduce the transition between reattached and fully detached flow regime.

• Child Health Nursing Research
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• v.25 no.4
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• pp.496-506
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• 2019

Purpose: The purpose of this study was to examine the effects of a virtual reality simulation and a blended simulation on nursing care for children with asthma through an evaluation of critical thinking, problem-solving processes, and clinical performance in both education groups before and after the educational intervention. Methods: The participants were 48 nursing students. The experimental group (n=22) received a blended simulation, combining a virtual reality simulation and a high-fidelity simulation, while the control group (n=26) received only a virtual reality simulation. Data were collected from February 25 to 28, 2019 and analyzed using SPSS version 25 for Windows. Results: The pretest and posttest results of each group showed statistically significant improvements in critical thinking, problem-solving processes, and clinical performance. In a comparison of the results of the two education groups, the only statistically significant difference was found for critical thinking. Conclusion: Simulation-based education in child nursing has continued to involve high-fidelity simulations that are currently run in many programs. However, incorporating a new type of blended simulation, combining a virtual reality simulation and a high-fidelity simulation, into the nursing curriculum may contribute to the further development of nursing education.

• The Korean Journal of Emergency Medical Services
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• v.18 no.2
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• pp.7-20
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• 2014

Purpose: This study aims to assess the reliability and validity of a Korean version of the satisfaction with simulation experience (SSE) scale for low-, medium-, and high-fidelity simulations among paramedic students. Methods: Exploratory factor analysis with varimax rotation was used to determine construct validity. Cronbach's alpha was calculated to assess internal consistency reliability. Results: Cronbach's alpha for the overall scale was .841. Exploratory factor analysis yielded a three-factor structure composed of clinical learning, clinical reasoning and debriefing and reflection. Each of the subscales had high internal consistency, with Cronbach's alphas of .852, .790 and .913, respectively. With respect to year, freshmen scored the highest on the SSE scale. With respect to type of simulation, the medium-fidelity group reported the highest satisfaction. Generally, the students were satisfied with debriefing and reflection. Conclusion: The Korean version of the SSE scale was shown to be a reliable and valid instrument for assessing satisfaction with simulation learning in paramedic students.

• Journal of Ship and Ocean Technology
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• v.8 no.1
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• pp.10-30
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• 2004

High-fidelity RANS simulations are presented for a ducted marine propulsor, including verification ＆ validation (V＆V) using available experimental fluid dynamics (EFD) data. CFDSHIP-IOWA is used with $\textsc{k}-\omega$ turbulence model and extensions for relative rotating coordinate system and Chimera overset grids. The mesh interpolation code PEGASUS is used for the exchange of the flow information between the overset grids. Intervals V＆V for thrust, torque, and profile averaged radial velocity just downstream of rotor tip are reasonable in comparison with previous results. Flow pattern displays interaction and merging of tip-leakage and trailing edge vortices. In interaction region, multiple peaks and vorticity are smaller, whereas in merging region, better agreement with EFD. Tip-leakage vortex core position, size, circulation, and cavitation patterns for $\sigma=5$ also show a good agreement with EFD, although vortex core size is larger and circulation in interaction region is smaller.

• Computers and Concrete
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• v.9 no.4
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• pp.293-310
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• 2012

This paper discusses a new constitutive model called the high-rate brittle microplane (HRBM) model and also presents the details of a new software package called the Virtual Materials Laboratory (VML). The VML software package was developed to address the challenges of fitting complex material models such as the HRBM model to material property test data and to study the behavior of those models under a wide variety of stress- and strain-paths. VML employs Continuous Evolutionary Algorithms (CEA) in conjunction with gradient search methods to create automatic fitting algorithms to determine constitutive model parameters. The VML code is used to fit the new HRBM model to a well-characterized conventional strength concrete called WES5000. Finally, the ability of the new HRBM model to provide high-fidelity simulations of material property experiments is demonstrated by comparing HRBM simulations to laboratory material property data.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1310-1319
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• 2024

The reactor cavity cooling system (RCCS) is a passive reactor safety system commonly present in the designs of High-Temperature Gas-cooled Reactors (HTGR) that removes heat from the reactor pressure vessel by means of natural convection and radiation. It is one of the factors responsible for ensuring that the reactor does not melt down under any plausible accident scenario. For the simulation of accident scenarios, which are transient phenomena unfolding over a span of up to several days, intermediate fidelity methods and system codes must be employed to limit the models' execution time. These models can quantify radiation heat transfer well, but heat transfer caused by natural convection must be quantified with the use of correlations for the heat transfer coefficient. It is difficult to obtain reliable correlations for HTGR RCCS heat transfer coefficients experimentally due to such a system's size. They could, however, be obtained from high-fidelity steady-state simulations of RCCSs. The Rayleigh number in RCCSs is too high for using a Direct Numerical Simulation (DNS) technique; thus, a Reynolds-Averaged Navier-Stokes (RANS) approach must be employed. There are many RANS models, each performing best under different geometry and fluid flow conditions. To find the most suitable one for simulating an RCCS, the RANS models need to be validated. This work benchmarks various RANS models against three experiments performed on the HTTR RCCS Mockup by the Japanese Atomic Energy Agency (JAEA) in 1993. This facility is a 1/6 scale model of a vessel cooling system (VCS) for the High Temperature Engineering Test Reactor (HTTR), which is operated by JAEA. Multiple RANS models were evaluated on a simplified 2d-axisymmetric geometry. They were found to reproduce the experimental temperature profiles with errors of up to 22% for the lowest temperature benchmark and 15% for the higher temperature benchmarks. The results highlight that the pragmatic turbulence models need to be validated for high Rayleigh natural convection-driven flows and improved accordingly, more publicly available experimental data of RCCS resembling experiments is needed and indicate that a 2d-axisymmetric geometry approximation is likely insufficient to capture all the relevant phenomena in RCCS simulations.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.4
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• pp.158-168
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• 2000

Vehicle driving simulators can provide engineers with benefits on the development and modification of vehicle models. One of the most important factors to realistic simulations is the fidelity given by a motion system and a real-time visual image generation system. Virtual reality technology has been widely used to achieve high fidelity. In this paper the virtual environment including a visual system like a head-mounted display is developed for a vehicle driving simulator system by employing the virtual reality technique. virtual vehicle and environment models are constructed using the object-oriented analysis and design approach. Accordint to the object model a three dimensional graphic model is developed with CAD tools such as Rhino and Pro/E. For the real-time image generation the optimized IRIS Performer 3D graphics library is embedded with the multi-thread methodology. Compared with the single loop apprach the proposed methodology yields an acceptable image generation speed 20 frames/sec for the simulator.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.287-295
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• 2020

Group method of data handling (GMDH) is considered one of the earliest deep learning methods. Deep learning gained additional interest in today's applications due to its capability to handle complex and high dimensional problems. In this study, multi-layer GMDH networks are used to perform uncertainty quantification (UQ) and sensitivity analysis (SA) of nuclear reactor simulations. GMDH is utilized as a surrogate/metamodel to replace high fidelity computer models with cheap-to-evaluate surrogate models, which facilitate UQ and SA tasks (e.g. variance decomposition, uncertainty propagation, etc.). GMDH performance is validated through two UQ applications in reactor simulations: (1) low dimensional input space (two-phase flow in a reactor channel), and (2) high dimensional space (8-group homogenized cross-sections). In both applications, GMDH networks show very good performance with small mean absolute and squared errors as well as high accuracy in capturing the target variance. GMDH is utilized afterward to perform UQ tasks such as variance decomposition through Sobol indices, and GMDH-based uncertainty propagation with large number of samples. GMDH performance is also compared to other surrogates including Gaussian processes and polynomial chaos expansions. The comparison shows that GMDH has competitive performance with the other methods for the low dimensional problem, and reliable performance for the high dimensional problem.