• Journal of Digital Convergence
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• v.12 no.12
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• pp.589-599
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• 2014

Critical thinking includes creative thinking, open-mindedness, inquisitiveness. Critical Thinking Disposition was significantly higher in experimental group that was enhanced by the scenario-based learning contents than that of the control group(t=4.102, p<.001). Problem Solving process was significantly higher in experimental group that was enhanced by the scenario-based learning contents than that of the control group(t=5.082, p<.001). However, there was no significant difference between the two groups in Clinical Competence(t=2.646, p=.009). But experimental group was significantly higher score than that of the control group score decreased. These results support that the implementation of a scenario-based learning contents need to be continued as an effective educational material but we need more research to establish how this can be effectively implemented in a students' practicum.

• Journal of Radiation Industry
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• v.17 no.3
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• pp.265-273
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• 2023

To effectively and safely manage the radiation exposure to nuclear power plant (NPP) workers in accidents, major overseas NPP operators such as the United States, Germany, and France have developed and applied realistic 3D model radiation dose assessment software for workers. Continuous research and development have recently been conducted, such as performing NPP accident management using 3D-VR based on As Low As Reasonably Achievable (ALARA) planning tool. In line with this global trend, it is also required to secure technology to manage radiation exposure of workers in Korea efficiently. Therefore, in this paper, it is described the application method and assessment results of radiation exposure scenarios for workers in response to accidents assessment technology, which is one of the fundamental technologies for constructing a realistic platform to be utilized for radiation exposure prediction, diagnosis, management, and training simulations following accidents. First, the post-accident sampling after the Loss of Coolant Accident(LOCA) was selected as the accident and response scenario, and the assessment area related to this work was established. Subsequently, the structures within the assessment area were modeled using MCNP, and the radiation source of the equipment was inputted. Based on this, the radiation dose distribution in the assessment area was assessed. Afterward, considering the three principles of external radiation protection (time, distance, and shielding) detailed work scenarios were developed by varying the number of workers, the presence or absence of a shield, and the location of the shield. The radiation exposure doses received by workers were compared and analyzed for each scenario, and based on the results, the optimal accident response scenario was derived. The results of this study plan to be utilized as a fundamental technology to ensure the safety of workers through simulations targeting various reactor types and accident response scenarios in the future. Furthermore, it is expected to secure the possibility of developing a data-based ALARA decision support system for predicting radiation exposure dose at NPP sites.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.434-441
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• 2017

Containment venting is one of several essential measures to protect the integrity of the final barrier of a nuclear reactor during severe accidents, by which the uncontrollable release of fission products can be avoided. The authors seek to develop an optimization approach to venting operations, from a simulation-based perspective, using an integrated severe accident code, THALES2/KICHE. The effectiveness of the containment-venting strategies needs to be verified via numerical simulations based on various settings of the venting conditions. The number of iterations, however, needs to be controlled to avoid cumbersome computational burden of integrated codes. Bayesian optimization is an efficient global optimization approach. By using a Gaussian process regression, a surrogate model of the "black-box" code is constructed. It can be updated simultaneously whenever new simulation results are acquired. With predictions via the surrogate model, upcoming locations of the most probable optimum can be revealed. The sampling procedure is adaptive. Compared with the case of pure random searches, the number of code queries is largely reduced for the optimum finding. One typical severe accident scenario of a boiling water reactor is chosen as an example. The research demonstrates the applicability of the Bayesian optimization approach to the design and establishment of containment-venting strategies during severe accidents.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3788-3794
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• 2022

The possibility of denuclearization of the Korean Peninsula has been continuously debated, and the initiative participation of the Republic of Korea has necessitated preemptive measures against neighboring countries. In this study, we present a proposal for formulating a site survey plan when the amount of site information provided is insufficient and the accuracy of the information is not guaranteed. Considering a case wherein "a soil sample analysis is used to determine the presence or absence of nuclear activity" in a radiochemical laboratory, which is a typical key facility for denuclearization, the optimal soil sample collection plan is designed based on international guidelines and public information. In the event of denuclearization, a scenario that is not based on the expertise of the sample collector is set, and the data quality objective (DQO) process is applied to ensure reality. Consequently, the primary sample collection points can be derived in consideration of accessibility, and the sample collection scale can be adjusted according to the cost. By applying the DQO process to ensure sample representativeness and reality, reliable and resource-efficient soil sample collection can be achieved in radiochemical laboratories and other denuclearization facilities.

• Structural Engineering and Mechanics
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• v.87 no.1
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• pp.1-18
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• 2023

The paper presents a Bayesian Finite element (FE) model updating methodology by utilizing modal data. The dynamic condensation technique is adopted in this work to reduce the full system model to a smaller model version such that the degrees of freedom (DOFs) in the reduced model correspond to the observed DOFs, which facilitates the model updating procedure without any mode-matching. The present work considers both the MPV and the covariance matrix of the modal parameters as the modal data. Besides, the modal data identified from multiple setups is considered for the model updating procedure, keeping in view of the realistic scenario of inability of limited number of sensors to measure the response of all the interested DOFs of a large structure. A relationship is established between the modal data and structural parameters based on the eigensystem equation through the introduction of additional uncertain parameters in the form of modal frequencies and partial mode shapes. A novel sampling strategy known as the Metropolis-within-Gibbs (MWG) sampler is proposed to sample from the posterior Probability Density Function (PDF). The effectiveness of the proposed approach is demonstrated by considering both simulated and experimental examples.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.262-274
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• 2019

The purpose of this study is to estimate the minimum proportion of probe vehicles for obtaining expressway traffic information using VISSIM, a micro traffic simulation model, between Yongin IC and Yangji IC on Yeongdong Expressway. 7,200 scenarios were created for the experiment, and 40 scenarios were adopted using the Latin hypercube sampling method because it was difficult to perform all the scenarios through experiments. The reliability of the experiment was improved by adding a situation when the general situation and the accident situation exist. In the experiments, the average travel time of probe vehicles at different market penetration rates were compared with the average travel time of the entire vehicles. As a result, the minimum market penetration rate of probe vehicles for obtaining expressway traffic information was found to be 45%. In addition, it is estimated that 25% market penetration rate of probe vehicle can meet 70% of traffic situations in accident scenario.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.3
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• pp.475-483
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• 2015

We propose a numerical scheme to simulate the time-domain echo signals at tracking radar for a realistic scenario where an EAD (expendable active decoy) and an airborne target are both in dynamic states. On various scenarios where the target takes different maneuvers, the trajectories of the EAD ejected from the target are accurately calculated by solving 6-DOF (Degree-of-Freedom) equations of the motion for the EAD. At each sampling time of the echo signal, the locations of the EAD and the target are assumed to be fixed. Thus, the echo power from the EAD can be simply calculated by using the Friis transmission formula. The returned power from the target can be computed based on the pre-calculated scattering matrix of the target. In this paper, an IPO (iterative physical optics) method is used to construct the scattering matrix database of the target. The sinc function-interpolation formulation (sampling theorem) is applied to compute the scattering at any incidence angle from the database. A simulator is developed based on the proposed scheme to estimate the echo signals, which can consider the movement of the airborne target and EAD, also the scattering of the target and the RF specifications of the EAD. For applications, we consider the detection probability of the target in the presence of the EAD based on Monte Carlo simulation.

• Journal of Soil and Groundwater Environment
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• v.17 no.5
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• pp.68-74
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• 2012

The objective of this study is to examine a releasable asbestos sampler developed for measuring friable asbestos from soil to air controlled by wind velocity and water contents. Asbestos contaminated soil with 3.75% at the Sinsuk-asbestos mine was sampled, air-dried and sieved to 100 mesh, then homogenized during 24 hours' agitation. Various wind velocities, 1 m/s, 2 m/s, 3 m/s, and 5 m/s, were applied to evaluate releasable characteristics of the releasable asbestos sampler. In addition, soils with 1.0%, 3.4%, 4.4%, 11.0%, 16.2%, and 20.0% of water contents were also examined the amount of friable asbestos by the releasable asbestos sampler. Collected soil and air samples were analyzed by polarized light microscopy (PLM) and phase contrast microscopy (PCM), respectively. Those contents were applied to calculate an excess life cancer risk (ELCR). This study also discussed the relationship with risk assessment by a weeding scenario of activity based sampling (ABS) and field applied releasable asbestos sampler. The result was shown that friability of asbestos in soil increased with wind velocity and decreased with water content. In comparison with ELCR results, over 10E-4 of cancer risk was found in condition on < 5% water content and > 3m/s wind velocity.

• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.66-72
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• 2014

This paper introduces an asynchronous multiple radar fusion algorithm for space object tracking. To estimate orbital motion of space object, a multiple radar scenario which jointly measures single object with different sampling time indices is described. STK/ODTK is utilized to determine realization of orbital motion and joint coverage of multiple radars. Then, asynchronous fusion algorithm is adapted to enhance the estimation performance of orbital motion during which multiple radars measure the same time instances. Monte-Carlo simulation results demonstrate that the proposed asynchronous multi-sensor fusion scheme better than single linearized Kalman filter in an aspect of root mean square error.

• ETRI Journal
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• v.38 no.2
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• pp.337-346
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• 2016

We propose a data-driven kinematic control method for a robotic spatial augmented reality (RSAR) system. We assume a scenario where a robotic device and a projector-camera unit (PCU) are assembled in an ad hoc manner with loose kinematic specifications, which hinders the application of a conventional kinematic control method based on the exact link and joint specifications. In the proposed method, the kinematic relation between a PCU and joints is represented as a set of B-spline surfaces based on sample data rather than analytic or differential equations. The sampling process, which automatically records the values of joint angles and the corresponding external parameters of a PCU, is performed as an off-line process when an RSAR system is installed. In an on-line process, an external parameter of a PCU at a certain joint configuration, which is directly readable from motors, can be computed by evaluating the pre-built B-spline surfaces. We provide details of the proposed method and validate the model through a comparison with an analytic RSAR model with synthetic noises to simulate assembly errors.