• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3409-3416
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• 2023

Licensing the next-generation of nuclear reactor designs requires extensive use of Modeling and Simulation (M&S) to investigate system response to many operational conditions, identify possible accidental scenarios and predict their evolution to undesirable consequences that are to be prevented or mitigated via the deployment of adequate safety barriers. Deep Learning (DL) and Artificial Intelligence (AI) can support M&S computationally by providing surrogates of the complex multi-physics high-fidelity models used for design. However, DL and AI are, generally, low-fidelity 'black-box' models that do not assure any structure based on physical laws and constraints, and may, thus, lack interpretability and accuracy of the results. This poses limitations on their credibility and doubts about their adoption for the safety assessment and licensing of novel reactor designs. In this regard, Physics Informed Neural Networks (PINNs) are receiving growing attention for their ability to integrate fundamental physics laws and domain knowledge in the neural networks, thus assuring credible generalization capabilities and credible predictions. This paper presents the use of PINNs as surrogate models for accidental scenarios simulation in Nuclear Power Plants (NPPs). A case study of a Loss of Heat Sink (LOHS) accidental scenario in a Nuclear Battery (NB), a unique class of transportable, plug-and-play microreactors, is considered. A PINN is developed and compared with a Deep Neural Network (DNN). The results show the advantages of PINNs in providing accurate solutions, avoiding overfitting, underfitting and intrinsically ensuring physics-consistent results.

• Journal of Industrial Convergence
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• v.22 no.8
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• pp.73-83
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• 2024

The study attempted to examine the effects of hybrid simulation practice program on critical thinking disposition, self-efficacy, communication competency, and clinical competency of nursing students. The study was one group pre-test and post-test design. Data were collected between April 24 to May 5, 2023 from 35 nursing students. The collected data was analyzed using the SPSS 25.0 program, frequency analysis, mean, standard deviation, and paired t-test. Research results showed that nursing students' critical thinking disposition(t=7.01, p<.001), self-efficacy(t=2.17, p=.037), communication competency(t=2.70, p=.011), and clinical competency(t=6.60, p<.001) were improved after the simulation program. The hybrid simulation practice program is significant in that it applies various learning tools, including high-fidelity-low-fidelity-role play to strengthen the connection between nursing students' theory and practice.

• Nutrition Research and Practice
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• v.5 no.5
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• pp.481-488
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• 2011

Street vended food (SVF) includes food and beverages prepared and sold outdoors or in public areas by street merchants for consumption on the scene or later without further preparation. Due to its low price and convenience, SVF has been popular in Korea for a long time, particularly with high school students. Beyond Korea, SVF is also popular in southeast Asia and southern Africa in the form of ready-to-eat food. This study on high school students, who are main consumers of SVF in Korea, focused on the factors that affect consumer loyalty. The study was performed by questionnaire and used AMOS software to develop a structural equation model. The results of verifying the model's fidelity were $X^2$=685.989, df=261, GFI=0.851, AGFI=0.814, NFI=0.901, CFI=0.907, RMR=0.048, indicating a satisfying structural model. SVF quality and service, emotional response, and the physical environment had a statistically significant effect on consumer loyalty. In contrast, SVF sanitation had no statistically significant effect on consumer loyalty. Based on these results, the sanitary management of SVF needs to be addressed immediately combined with education for SVF providers to maintain a clean environment.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.66-75
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• 2008

In this work, we explore the feasibility of roll-pitch-yaw integrated autopilots for high angle-of-attack missiles. An investigation of the aerodynamic characteristics of a surface-to-air missile is presented, which reveals the strong effects of cross coupling between the longitudinal and lateral dynamics. Robust control techniques based on $H_{\infty}$ synthesis are employed to design roll-pitch-yaw integrated autopilots. The performance of the proposed roll-pitch-yaw integrated controller is tested in high-fidelity nonlinear five-degree-of-freedom simulations accounting for kinematic cross-coupling effects between the lateral and longitudinal channels. Against nonlinearity and cross-coupling effects of the missile dynamics, the integrated controller demonstrates superior performance when compared with the controller designed in a decoupled manner.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.5
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• pp.423-443
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• 2009

We present the design and implementation of a unique sensing and actuation application -- the Illuminator: a sensor network-based intelligent light control system for entertainment and media production. Unlike most sensor network applications, which focus on sensing alone, a distinctive aspect of the Illuminator is that it closes the loop from light sensing to lighting control. We describe the Illuminator's design requirements, system architecture, algorithms, implementation and experimental results. The system uses the Illumimote, a multi-modal and high fidelity light sensor module well-suited for wireless sensor networks, to satisfy the high-performance light sensing requirements of entertainment and media production applications. The Illuminator system is a toolset to characterize the illumination profile of a deployed set of fixed position lights, generate desired lighting effects for moving targets (actors, scenic elements, etc.) based on user constraints expressed in a formal language, and to assist in the set up of lights to achieve the same illumination profile in multiple venues. After characterizing deployed lights, the Illuminator computes optimal light settings at run-time to achieve a user-specified actuation profile, using an optimization framework based on a genetic algorithm. Uniquely, it can use deployed sensors to incorporate changing ambient lighting conditions and moving targets into actuation. Experimental results demonstrate that the Illuminator handles various high-level user requirements and generates an optimal light actuation profile. These results suggest that the Illuminator system supports entertainment and media production applications.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.3
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• pp.8-17
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• 2015

In this research, low fidelity air/heat load analysis was conducted for the intake of high speed vehicle. For air/heat load calculations, aerodynamic properties at the surface and the boundary layer edge were estimated using Taylor-Maccoll equation for conical flow, shockwave relation and Prandtl-Meyer expansion equation for internal and external flow. Couette flow assumption and Reynolds analogy were used in order to calculate convective heat transfer coefficient. In order to calculate skin friction coefficient for heat transfer coefficient analysis, Van Driest method II and Reference Enthalpy method were considered. An axis symmetric SCRAMJET model was selected as a reference configuration for verifying the proper implementation of the present method. Comparison of the results using the present method and Computational Fluid Dynamic analysis showed that the present method is valuable for efficiently providing pressure and heat loads for air-intake structure design of the high speed air vehicle.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.882-892
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• 2017

Locally Likely Arrangement Hashing (LLAH) is a method that describes image features based on the geometry between their neighbors. Thus, it has been preferred to implement augmented reality on poorly-textured objects such as text documents. However, LLAH strongly requires that image features be detected with high repeatability and located at a distance from one another. To fulfill the requirement for text document, this paper proposes a method that facilitates the word detection in infrared (IR) range by adjusting the IR-reflectance of words. Specifically, the words are printed out with two different black inks: one is using the K(carbon black) ink only, the other is mixing the C(cyan), M(magenta), Y(yellow) inks. Since only the words printed out with the K ink is visible in IR range, a part of words are selected in advance to be used as features and printed out the K ink. The selected words can be robustly detected with high repeatability in IR range and this enables to implement augmented reality on text documents with high fidelity. The validity of the proposed method was verified through experiments.

• Korean Journal of Materials Research
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• v.26 no.11
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• pp.635-643
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• 2016

Graphene has shown exceptional properties for high performance devices due to its high carrier mobility. Of particular interest is the potential use of graphene nanoribbons as field-effect transistors. Herein, we introduce a facile approach to the fabrication of graphene nanoribbon (GNR) arrays with ~200 nm width using nanoimprint lithography (NIL), which is a simple and robust method for patterning with high fidelity over a large area. To realize a 2D material-based device, we integrated the graphene nanoribbon arrays in field effect transistors (GNR-FETs) using conventional lithography and metallization on highly-doped $Si/SiO_2$ substrate. Consequently, we observed an enhancement of the performance of the GNR-transistors compared to that of the micro-ribbon graphene transistors. Besides this, using a transfer printing process on a flexible polymeric substrate, we demonstrated graphene-silicon junction structures that use CVD grown graphene as flexible electrodes for Si based transistors.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.225-227
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• 2003

Traditional photogrammetry and satellite image rectification technique have been developed based on control-points for many decades. These techniques are driven from linked points in image space and the corresponding points in the object space in rigorous colinearity or coplanarity conditions. Recently, digital imagery facilitates the opportunity to use features as well as points for images rectification. These implementations were mainly based on rigorous models that incorporated geometric constraints into the bundle adjustment and could not be applied to the new high-resolution satellite imagery (HRSI) due to the absence of sensor calibration and satellite orbit information. This research is an attempt to establish a new Line Based Transformation Model (LBTM), which is based on linear features only or linear features with a number of ground control points instead of the traditional models that only use Ground Control Points (GCPs) for satellite imagery rectification. The new model does not require any further information about the sensor model or satellite ephemeris data. Synthetic as well as real data have been demonestrated to check the validity and fidelity of the new approach and the results showed that the LBTM can be used efficiently for rectifying HRSI.