• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.67-74
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• 2023

A semiconductor fabrication facility(FAB) is one of the most capital-intensive and large-scale manufacturing systems which operate under complex and uncertain constraints through hundreds of fabrication steps. To improve fab performance with intuitive scheduling, practitioners have used weighted-sum scheduling. Since the determination of weights in the scheduling significantly affects fab performance, they often rely on simulation-based decision making for obtaining optimal weights. However, a large-scale and high-fidelity simulation generally is time-intensive to evaluate with an exhaustive search. In this study, we investigated three sampling methods (i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search(DSS)) for the optimization. Our simulation experiments demonstrate that: (1) three methods outperform greedy heuristics in performance metrics; (2) GA and DSS can be promising tools to accelerate the decision-making process.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.3
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• pp.423-431
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• 2016

In this study, wing design optimization for long-endurance unmanned aerial vehicles (UAVs) is investigated. The fluid-structure integration (FSI) analysis is carried out to simulate the aeroelastic characteristics of a high-aspect ratio wing for a long-endurance UAV. High-fidelity computational codes, FLUENT and DIAMOND/IPSAP, are employed for the loose coupling FSI optimization. In addition, this optimization procedure is improved by adopting the design of experiment (DOE) and Kriging model. A design optimization tool, PIAnO, integrates with an in-house codes, CAE simulation and an optimization process for generating the wing geometry/computational mesh, transferring information, and finding the optimum solution. The goal of this optimization is to find the best high-aspect ratio wing shape that generates minimum drag at a cruise condition of $C_L=1.0$. The result shows that the optimal wing shape produced 5.95 % less drag compared to the initial wing shape.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.9
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• pp.859-866
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• 2008

A guidance scheme for controlling the relative geometry of multiple flight vehicle formation flying is proposed. Each flight vehicle in the formation takes the roles of leader and follower simultaneously except for the formation leader. In this scheme, the flight commands for a leader are shared by all the followers and this leaders to a synchronized flight of all flight vehicles comprising the formation. Lyapunov stability theorem is used to obtain the guidance law. High fidelity nonlinear simulation results are presented to show the effectiveness of the proposed guidance law using a reconnaissance and surveillance mission example.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.55-61
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• 2007

Recently simulation model becomes an essential tool for analysis and design of a system but it is often expensive and time consuming as it becomes complicate to achieve reliable results. Therefore, high-fidelity simulation model needs to be replaced by an approximate model, the so-called metamodel. Metamodeling techniques include 3 components of sampling, metamodel and validation. Cross-validation approach has been proposed to provide sequnatially new sample point based on cross-validation error but it is very expensive because cross-validation must be evaluated at each stage. To enhance the cross-validation of metamodel, sequential sampling method using candidate points and representative cross-validation is proposed in this paper. The candidate and representative cross-validation approach of sequential sampling is illustrated for two-dimensional domain. To verify the performance of the suggested sampling technique, we compare the accuracy of the metamodels for various mathematical functions with that obtained by conventional sequential sampling strategies such as maximum distance, mean squared error, and maximum entropy sequential samplings. Through this research we team that the proposed approach is computationally inexpensive and provides good prediction performance.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.3088-3101
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• 2023

A pressurized vessel-pipe-safety valve (PVPSV) combination is a commonly used configuration in nuclear power plants, and a good numerical model is essential for the system design, sizing and performance optimization. However, owing to the large-scale and cross-scale features, it is still a challenge to build a system level numerical model with both high accuracy and efficiency. To overcome this, a novel system level modeling method which can synthesize the advantages of various models is proposed in this paper. For system modeling, the analytical approach, the method of characteristics (MOC) and the surrogate model approach are respectively adopted to predict the dynamics of the pressure vessel, the connecting pipe and the safety valve, and different models are connected through data interfaces. With this system model, dynamic simulations were carried out and both the stable and the unstable system responses were obtained. For the model verification purpose, the simulation results were compared with those obtained from experiments and full CFD simulations. A good agreement and a better efficiency were obtained, verifying the ability of the model and the feasibility of the modeling method proposed in this paper.

• Korean Journal of Computational Design and Engineering
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• v.17 no.5
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• pp.303-311
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• 2012

Laparoscopic surgery is a surgical procedure which uses long laparoscopic instruments through tiny holes in abdomen while watching images from a laparoscopic camera through umbilicus. Laparoscopic surgeries have many advantages rather than open surgeries, however it is hard to learn the surgical skills for laparoscopic surgery. Recently, some virtual simulation systems for laparoscopic surgery are developed to train novice surgeons or resident surgeons. In this study, we introduce the techniques that we developed for laparoscopic surgical training simulator for cholecystectomy (gallbladder removal), which is one of the most frequently performed by laparoscopic surgery. The techniques for cholecystectomy simulation include modeling of human organs (liver, gallbladder, bile ducts, etc.), real-time deformable body calculation, realistic 3D visualization of surgical scene, high-fidelity haptic rendering and haptic device technology, and so on. We propose each simulation technique for the laparoscopic cholecystectomy procedures such as identifying cystic duct and cystic artery to clamp and cut, dissecting connective tissues between the gallbladder and liver. In this paper, we describe the techniques and discuss about the results of the proposed cholecystectomy simulation for laparoscopic surgical training.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1515-1521
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• 2014

This study applies simulation-based education and care for acute myocardial infarction nursing students to investigate the effect of critical thinking, problem solving, and academic achievement of a single group before and after the raw experimental design. A total of 137 subjects were arbitration period September-October 2011, enforcement and arbitration were evaluated after simulation-based training six weeks total. Data analysis was performed using SPSS Win17.0, Paired t-test, the mean and standard deviation, Pearson's correlation coefficient was used. Research results of simulation-based training program to improve critical thinking, problem solving, and academic achievement were As increase critical thinking and problem solving ability was improved. whereas, Critical thinking skills and problem solving ability was no significant difference with academic achievement. Simulation-based training program to improve the practical skills of nursing students learning was found how useful it, that there is a need to take advantage of hands-on training in a variety of cases that can be common in the field of clinical scenarios developed by. To do this, It seems to be necessary to the development and operation more varied and appropriate hands-on training method.

• Journal of Korean Academy of Nursing
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• v.47 no.6
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• pp.842-853
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• 2017

Purpose: This study was conducted to identify effects of debriefing based on the clinical judgment model for nursing students on their knowledge, skill performance, clinical judgment, self-confidence and learner satisfaction during simulation based end-of-life care (ELC) education. Methods: Simulation based ELC education was developed in six steps as follows: selection of learning subjects and objects, development of learning tools, a trial run of simulation-based education, students' skill training, and evaluators' training. Forty-eight senior nursing students (25 in the experimental group and 23 in the control group) participated in the simulation-based ELC education using a high-fidelity simulator. Debriefing based on the clinical judgment was compared with the usual debriefing. Results: ANCOVA showed that there were differences in knowledge (F=4.81, p=.034), skill performance (F=68.33, p<.001), clinical judgment (F=18.33, p<.001) and self-confidence (F=4.85, p=.033), but no difference in satisfaction (t=-0.38, p=.704) between the experimental and control groups. Conclusion: This study found that debriefing based on the clinical judgement model is effective for supporting nursing students for reflecting on clinical judgment and improving their diverse competencies in complex clinical settings such as ELC.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.353-361
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• 2024

Simulation education is a method that allows learners to learn repeatedly in realistic simulated situations. It solves the limitations of clinical practice that lacks direct nursing performance and is useful for acquiring and developing the knowledge, nursing skills, communication skills, learning self-efficacy, and clinical reasoning required for nursing students. The purpose of this study was identify the effects of High fidelity simulation-based education on communication ability, learning self-efficacy and clinical reasoning of nursing students. The subjects were 84 nursing students who were enrolled in the senior who had received simulation training using dysphagia patient care scenario. Data were analyzed using SPSS/WIN 22.0. As a result, There was a statistically significant difference in the communication ability, learning self-efficacy, clinical reasoning. And the mean score of simulation effectiveness is 2.64 points (a perfect score of three). Therefore, In order to improve the communication ability, learning self-efficacy and clinical reasoning of nursing students, it is necessary to develop and apply realistic scenarios that reflect various clinical situations.

• Journal of Auto-vehicle Safety Association
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• v.15 no.2
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• pp.42-48
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• 2023

In recent years, automated vehicles have garnered attention in the multidisciplinary research field, promising increased safety on the road and new opportunities for passengers. High-Definition (HD) maps have been in development for many years as they offer roadmaps with inch-perfect accuracy and high environmental fidelity, containing precise information about pedestrian crossings, traffic lights/signs, barriers, and more. Demonstrating autonomous driving requires verification of driving on actual roads, but this can be challenging, time-consuming, and costly. To overcome these obstacles, creating HD maps of real roads in a simulation and conducting virtual driving has become an alternative solution. However, existing HD maps using high-precision data are expensive and time-consuming to build, which limits their verification in various environments and on different roads. Thus, it is challenging to demonstrate autonomous driving on anything other than extremely limited roads and environments. In this paper, we propose a new and simple method for implementing HD maps that are more accessible for autonomous driving demonstrations. Our HD map combines the CARLA simulator and OpenStreetMap (OSM) data, which are both open-source, allowing for the creation of HD maps containing high-accuracy road information globally with minimal dependence. Our results show that our easily accessible HD map has an accuracy of 98.28% for longitudinal length on straight roads and 98.42% on curved roads. Moreover, the accuracy for the lateral direction for the road width represented 100% compared to the manual method reflected with the exact road data. The proposed method can contribute to the advancement of autonomous driving and enable its demonstration in diverse environments and on various roads.