• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.662-674
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• 2017

This paper describes the multidisciplinary design optimization (MDO) process of a tailless unmanned combat aerial vehicle (UCAV) using global variable fidelity aerodynamic analysis. The developed tailless UAV design framework combines multiple disciplines that are based on low-fidelity and empirical analysis methods. An automated high-fidelity aerodynamic analysis is efficiently integrated into the MDO framework. Global variable fidelity modeling algorithm manages the use of the high-fidelity analysis to enhance the overall accuracy of the MDO by providing the initial sampling of the design space with iterative refinement of the approximation model in the neighborhood of the optimum solution. A design formulation was established considering a specific aerodynamic, stability and control design features of a tailless aircraft configuration with a UCAV specific mission profile. Design optimization problems with low-fidelity and variable fidelity analyses were successfully solved. The objective function improvement is 14.5% and 15.9% with low and variable fidelity optimization respectively. Results also indicate that low-fidelity analysis overestimates the value of lift-to-drag ratio by 3-5%, while the variable fidelity results are equal to the high-fidelity analysis results by algorithm definition.

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

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.1
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• pp.45-54
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• 2022

There has been necessity to supplement the fin database to improve the accuracy of low-fidelity aerodynamic solver for missile configuration. In this study, fin database is expanded by in-house solver, utilized in the triservice data the previously established into regions beyond means of CFD. Fin alone data of CFD analysis results in the original region is matched well with triservice data originated from the wind tunnel tests. Extensive fin aerodynamic data from CFD analysis is added to the existing database of the low-fidelity solver. For confirmation, aerodynamic characteristics of body-tail and body-canard-tail missile configurations is computed using upgraded low-fidelity solver at transonic region. The result using improved solver shows good agreements with wind tunnel test and CFD analysis results, which implies that it becomes more accurate.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.2
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• pp.149-158
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• 2023

To predict the aerodynamic characteristics of the grid fins from subsonic to supersonic speeds, low fidelity SW as well as CFD SW were applied. VLM(Vortex Lattice Method) and SE(Shock-Expansion) method were used at subsonic and supersonic speed domain respectively for the rapid prediction of low fidelity SW. For 2 configurations of the grid fins, the CFD computations and tests using the trisonic wind tunnel were also performed to compare the results of the grid fins. The results of low fidelity SW, CFD SW and the wind tunnel tests data were agreed well each other. Through further research on the grid fins, the effective parameters of the grid fin configurations according to the speed regime will be investigated.

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

• International conference on construction engineering and project management
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• 2020.12a
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• pp.137-145
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• 2020

Providing safety training to construction workers is essential to reduce safety accidents at the construction site. With the prosperity of visualization technologies, Immersive Virtual Reality (IVR) has been adopted for construction safety training by providing interactive learning experiences in a virtual environment. Previous research efforts on IVR-based training have found that the level of fidelity of interaction between real and virtual worlds is one of the important factors contributing to the sense of presence that would affect training performance. Various interactive devices that link activities between real and virtual worlds have been applied in IVR-based training, ranging from existing computer input devices (e.g., keyboard, mouse, joystick, etc.) to specially designed devices such as high-end VR simulators. However, the need for high-fidelity interactive devices may hinder the applicability of IVR-based training as they would be more expensive than IVR headsets. In this regard, this study aims to understand the impact of the level of fidelity of interactive devices in the sense of presence in a virtual environment and the training performance during IVR-based forklift safety training. We conducted a comparative study by recruiting sixty participants, splitting them into two groups, and then providing different interactive devices such as a keyboard for a low fidelity group and a steering wheel and pedals for a high-fidelity group. The results showed that there was no significant difference between the two groups in terms of the sense of presence and task performance. These results indicate that the use of low-fidelity interactive devices would be acceptable for IVR-based safety training as safety training focuses on delivering safety knowledge, and thus would be different from skill transferring training that may need more realistic interaction between real and virtual worlds.

• Journal of computational fluids engineering
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• v.11 no.3 s.34
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• pp.1-7
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• 2006

Euler and Navier-Stokes flow analyses for helicopter rotor in hover were performed as low and high fidelity analysis models respectively for the future multidisciplinary design optimization(MDO). These design-oriented analyses possess several attributes such as variable complexity, sensitivity-computation capability and modularity which analysis models involved in MDO are recommended to provide with. To realize PC-based analyses for both fidelity models, reduction of flow domain was made by appling farfield boundary condition based on 3-dimensional point sink with simple momentum theory and also periodic boundary condition in the azimuthal direction. Correlations of thrust, torque and their sensitivities between low and high complexity models were tried to evaluate the applicability of these analysis models in MDO process. It was found that the low-fidelity Euler analysis model predicted inaccurate sensitivity derivatives at relatively high angle of attack.

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

• The Journal of Korean Academic Society of Nursing Education
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• v.25 no.3
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• pp.331-343
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• 2019

Purpose: This study focuses on investigating the effectiveness of simulation education on emergency management using a low-fidelity simulator as related to clinical skill performance, self-confidence, knowledge, learning satisfaction, and critical thinking disposition in new nurses. Methods: A pre-post test experimental design of nonequivalent control group was applied. Fifty-five new nurses were recruited, 28 nurses for the experimental group and 27 nurses for the control group. A simulation education for emergency management comprising knowledge lecture, team learning, skill education, team simulation, and debriefing was developed and implemented from Feb. 14 to 27, 2015. Data were analyzed with percentage, average, and standard deviation, chi-square, and t-test using SPSS. Results: The experimental group showed significantly higher knowledge (t=5.81, p<.001), clinical skill performance (t=10.08, p<.001), self-confidence (t=-6.24, p<.001), critical thinking disposition (t=2.42, p=.019), and learning satisfaction (t=4.21, p<.001) for emergency management compared with the control group who had traditional lecture education. Conclusion: The results indicate that a simulation education using a low-fidelity simulator is an efficient teaching method for new nurses to deepen their clinical skill performance, self-confidence, knowledge, learning satisfaction, and critical thinking disposition in learning emergency management.

• Archives of Plastic Surgery
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• v.40 no.4
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• pp.312-319
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• 2013

Over the past decade, driven by advances in educational theory and pressures for efficiency in the clinical environment, there has been a shift in surgical education and training towards enhanced simulation training. Microsurgery is a technical skill with a steep competency learning curve on which the clinical outcome greatly depends. This paper investigates the evidence for educational and training interventions of traditional microsurgical skills courses in order to establish the best evidence practice in education and training and curriculum design. A systematic review of MEDLINE, EMBASE, and PubMed databases was performed to identify randomized control trials looking at educational and training interventions that objectively improved microsurgical skill acquisition, and these were critically appraised using the BestBETs group methodology. The databases search yielded 1,148, 1,460, and 2,277 citations respectively. These were then further limited to randomized controlled trials from which abstract reviews reduced the number to 5 relevant randomised controlled clinical trials. The best evidence supported a laboratory based low fidelity model microsurgical skills curriculum. There was strong evidence that technical skills acquired on low fidelity models transfers to improved performance on higher fidelity human cadaver models and that self directed practice leads to improved technical performance. Although there is significant paucity in the literature to support current microsurgical education and training practices, simulated training on low fidelity models in microsurgery is an effective intervention that leads to acquisition of transferable skills and improved technical performance. Further research to identify educational interventions associated with accelerated skill acquisition is required.