• Structural Engineering and Mechanics
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• v.69 no.3
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• pp.243-255
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• 2019

Utilization of fiber beam-column element has gained considerable attention in recent years due mainly to its ability to model distributed plasticity over the length of the element through a number of integration points. However, the relatively high sensitivity of the method to modeling parameters as well as material behavior models can pose a significant challenge. Residual drift is one of the seismic demands which is highly sensitive to modeling parameters and material behavior models. Permanent deformations play a prominent role in the post-earthquake evaluation of serviceability of bridges affected by a near-fault ground shaking. In this research, the influence of distributed plasticity modeling parameters using both force-based and displacement-based fiber elements in the prediction of internal forces obtained from the nonlinear static analysis is studied. Having chosen suitable type and size of elements and number of integration points, the authors take the next step by investigating the influence of material behavioral model employed for the prediction of permanent deformations in the nonlinear dynamic analysis. The result shows that the choice of element type and size, number of integration points, modification of cyclic concrete behavior model and reloading strain of concrete significantly influence the fidelity of fiber element method for the prediction of permanent deformations.

• Journal of Astronomy and Space Sciences
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• v.36 no.3
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• pp.213-223
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• 2019

This paper analyzes delta-Vs to maintain an extremely low altitude on the Moon and investigates the possibilities of performing a CubeSat mission. To formulate the station-keeping (SK) problem at an extremely low altitude, current work has utilized real-flight performance proven software, the Systems Tool Kit Astrogator by Analytical Graphics Inc. With a high-fidelity force model, properties of SK maneuver delta-Vs to maintain an extremely low altitude are successfully derived with respect to different sets of reference orbits; of different altitudes as well as deadband limits. The effect of the degree and order selection of lunar gravitational harmonics on the overall SK maneuver strategy is also analyzed. Based on the derived SK maneuver delta-V costs, the possibilities of performing a CubeSat mission are analyzed with the expected mission lifetime by applying the current flight-proven miniaturized propulsion system performances. Moreover, the lunar surface coverage as well as the orbital characteristics of a candidate reference orbit are discussed. As a result, it is concluded that an approximately 15-kg class CubeSat could maintain an orbit (30-50 km reference altitude having ${\pm}10km$ deadband limits) around the Moon for 1-6 months and provide almost full coverage of the lunar surface.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.33-43
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• 2019

A comparison between sea trial measurements and full-scale CFD results is presented for two self-propelled ships. Two ships considered in the present study are: a general cargo carrier at Froude number $F_n=0:182$ and a car carrier at $F_n=0:254$. For the general cargo carrier, the propeller rotation rate is fixed and the achieved speed and trim are compared to sea trials, while for the car carrier, the propeller rotation rate is adjusted to achieve the 80% MCR. In addition, three grids are used for each ship in order to assess the grid refinement sensitivity. All simulations are performed using the Naval Hydro pack based on foam-extend, a community driven fork of the OpenFOAM software. The results demonstrate the possibility of using high-fidelity numerical methods to directly calculate ship scale flow characteristics, including the effects of free surface, non-linearity, turbulence and the interaction between propeller, hull and the flow field.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.116-122
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• 2021

This study evaluated the effect of simulation training on cardiac arrest in hospitals for inactive nurses with 360 VR content, and attempted to prepare basic data for simulation training for inactiv nurses in the future. The design of this study is an experiment study before and after a single group. The study period was from October 13, 2020 to December 17, 2020. The subjects of the study were a total of 21 nurses who participated in the education program for inactive nurses. For simulation training for inactive nurses, Microsoft Powerpoint, hybrid simulation, high-fidelity simulation, and 360 VR content were applied for theories education and practical education. As a result of the study, the satisfaction level of the curriculum for the cardiac arrest situation in the hospital for inactive nurses was 4.78±0.36 points out of 5 points. Understanding of education was 4.71±0.46 points out of 5 points. Usefulness of education was 4.80±0.40 points out of 5 points. Confidence in airway maintenance before and after training, BLS review, manual defibrillator, emergency medication administration, airway maintenance, emergency situation simulation, and debriefing were all significant. According to the results of this study, simulation training of the situation of cardiac arrest in the hospitals for inactive nurses was effective. In future studies, it will be necessary to develope and verify specific teaching and learning methods by applying various cases of cardiac arrest situations in consideration of the type of hospitals.

• Journal of Korean Academy of Nursing
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• v.51 no.6
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• pp.648-660
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• 2021

Purpose: This study aimed to develop an emerging infectious disease (COVID-19) simulation module for nursing students and verify its effectiveness. Methods: A one-group pretest-posttest quasi-experimental study was conducted with 78 under-graduate nursing students. A simulation module was developed based on the Jeffries simulation model. It consisted of pre-simulation lectures on disaster nursing including infectious disease pandemics, practice, and debriefings with serial tests. The scenarios contained pre-hospital settings, home visits, arrival to the emergency department, and follow-up home visits for rehabilitation. Results: Disaster preparedness showed a statistically significant improvement, as did competencies in disaster nursing. Confidence in disaster nursing increased, as did willingness to participate in disaster response. However, critical thinking did not show significant differences between time points, and neither did triage scores. Conclusion: The developed simulation program targeting an infectious disease disaster positively impacts disaster preparedness, disaster nursing competency, and confidence in disaster nursing, among nursing students. Further studies are required to develop a high-fidelity module for nursing students and medical personnel. Based on the current pandemic, we suggest developing more scenarios with virtual reality simulations, as disaster simulation nursing education is required now more than ever.

• Journal of Astronomy and Space Sciences
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• v.38 no.2
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• pp.145-155
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• 2021

In this work, preliminary launch opportunities from NARO Space Center to the Sun-Earth Lagrange point are analyzed. Among five different Sun-Earth Lagrange points, L1 and L2 points are selected as suitable candidates for, respectively, solar and astrophysics missions. With high fidelity dynamics models, the L1 and L2 point targeting problem is formulated regarding the location of NARO Space Center and relevant Target Interface Point (TIP) for each different launch date is derived including launch injection energy per unit mass (C3), Right ascension of the injection orbit Apoapsis Vector (RAV) and Declination of the injection orbit Apoapsis Vector (DAV). Potential launch periods to achieve L1 and L2 transfer trajectory are also investigated regarding coasting characteristics from NARO Space Center. The magnitude of the Lagrange Orbit Insertion (LOI) burn, as well as the Orbit Maintenance (OM) maneuver to maintain more than one year of mission orbit around the Lagrange points, is also derived as an example. Even the current work has been made under many assumptions as there are no specific mission goals currently defined yet, so results from the current work could be a good starting point to extend diversities of future Korean deep-space missions.

• Child Health Nursing Research
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• v.29 no.1
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• pp.24-36
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• 2023

Purpose: This systematic literature review and meta-analysis explored extended reality (XR)-based pediatric nursing simulation programs and analyzed their effectiveness. Methods: A literature search was conducted between May 1 and 30, 2022 in the following electronic databases: MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), and CINAHL. The search period was from 2000 to 2022. In total, 6,095 articles were reviewed according to the inclusion and exclusion criteria, and 14 articles were selected for the final content analysis and 10 for the meta-analysis. Data analysis was performed using descriptive statistics and the Comprehensive Meta-Analysis program. Results: XR-based pediatric nursing simulation programs have increased since 2019. Studies using virtual reality with manikins or high-fidelity simulators were the most common, with six studies. The total effect size was statistically significant at 0.84 (95% confidence interval=0.50-1.19, z=4.82, p<.001). Conclusion: Based on the findings, we suggest developing standardized guidelines for the operation of virtual pediatric nursing simulation education and practice. Simultaneously, the application of more sophisticated research designs for effect measurement and the combined applications of various virtual simulation methods are needed to validate the most effective simulation methodology.

• 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.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.219-231
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• 2023

Intelligent applications are crucial for increasing the popularity of shared urban electric bicycles (EBs). Building an application platform architectural system that can satisfy independent user operations is critical for increasing the intelligent usage of shared EBs. Consequently, we collected online reviews of shared EB applications, conducted semantic processing and sentiment analysis, and refined the positive and negative review data for each function. The positive and negative review indices of each function were calculated using the formulae for positive and negative review indices of product functions, thereby determining the functions that need to be improved. Each function of the Shared EB application was improved according to its business process. The main contributions of this study are to build a user requirement architecture system for the Shared EB application with five dimensions and 22 functions using the Delphi method to design the user interface (UI) of this application based on user satisfaction evaluation results; to create a high-fidelity dynamic interaction prototype and compare user satisfaction before and after improving the Shared EB application functions. The testing results indicate that the changes in the UI significantly improve the user experience satisfaction of the urban Shared EB application, with the positive experience index increasing by 69.21% and the negative experience index decreasing by 75.85% overall. This information can be directly used by relevant companies to improve the functions of the Shared EB application.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.589-603
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• 2023

Deep generative models target to infer the underlying true data distribution, and it leads to a huge success in generating fake-but-realistic data. Regarding such a perspective, the data attributes can be a crucial factor in the data generation process since non-existent counterfactual samples can be generated by altering certain factors. For example, we can generate new portrait images by flipping the gender attribute or altering the hair color attributes. This paper proposes counterfactual disentangled variational autoencoder generative adversarial networks (CDVAE-GAN), specialized for data attribute level counterfactual data generation. The structure of the proposed CDVAE-GAN consists of variational autoencoders and generative adversarial networks. Specifically, we adopt a Gaussian variational autoencoder to extract low-dimensional disentangled data features and auxiliary Bernoulli latent variables to model the data attributes separately. Also, we utilize a generative adversarial network to generate data with high fidelity. By enjoying the benefits of the variational autoencoder with the additional Bernoulli latent variables and the generative adversarial network, the proposed CDVAE-GAN can control the data attributes, and it enables producing counterfactual data. Our experimental result on the CelebA dataset qualitatively shows that the generated samples from CDVAE-GAN are realistic. Also, the quantitative results support that the proposed model can produce data that can deceive other machine learning classifiers with the altered data attributes.