• Earthquakes and Structures
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• v.22 no.2
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1247-1260
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• 2021

For more efficient energy management of nodes in wireless sensor networks, research has been conducted on mobile sink nodes that deliver data from sensor nodes to server recently. UAV (Unmanned Aerial vehicle) is used as a representative mobile sink node. Also, most studies on UAV propose algorithms for calculating optimal paths and have produced rapid advances in the IoD (Internet of Drones) environment. At the same time, some papers proposed mutual authentication and secure key exchange considering nature of the IoD, which requires efficient creation of multiple nodes and session keys in security perspective. However, most papers that proposed secure communication in mobile sink nodes did not protect end-to-end data privacy. Therefore, in this paper, we propose integrated security model that authentication between mobile sink nodes and sensor nodes to securely relay sensor data to base stations. Also, we show informal security analysis that our scheme is secure from various known attacks. Finally, we compare communication overhead with other key exchange schemes previously proposed.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.558-567
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• 2022

The evolution of temperature and thermal stress in a granite specimen is studied via heating experiment in the context of a high-level radioactive waste repository. A heating condition based on the decay-induced heat is applied to a cubic granite specimen to measure the temperature and stress distributions and their evolution over time. The temperature increases quickly due to heat conduction along the heated surfaces, but a significant amount of thermal energy is also lost through other surfaces due to air convection and conduction into the loading machine. A three-dimensional finite element-based model is used to numerically reproduce the experiment, and the thermo-mechanical coupling behavior and modeling conditions are validated with the comparison to the experimental results. The most crucial factors influencing the heating experiment are analyzed and summarized in this paper for future works.

• Herbal Formula Science
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• v.30 no.4
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• pp.293-304
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• 2022

Objectives : Sagunja-Tang is a famous prescription used in Korean medicine for the purpose of promoting vital energy, and there are few studies using Sagunja-Tang on cerebrovascular diseases yet. As previous studies confirmed that Sagunja-tang is highly likely to be used effectively for stroke, this study was intended to predict the mechanism through which Sagunja-tang would act effectively on stroke. Methods : In this study, a network pharmacology analysis method was used, and oral bioavailability (OB), drug likeness (DL), Caco-2 and BBB permeability were utilized to select compounds with potential activity. For the values of each variable used in this study, OB ≥ 30%, DL ≥ 0.18, Caco-2 ≥ 0, and BBB ≥ 0.3 were applied. Using the above variables, the relations between target genes and diseases that are presumed to be involved in the selected bioavailable compounds were constructed in a network format, and proteins thought to play a major role were identified. Results : Among the compounds included in Sagunja-Tang, 26 bioavailable compounds were selected and it was confirmed that these compounds can be effectively used in cerebrovascular diseases such as Alzheimer's disease and stroke. These compounds are considered to act on proteins related in cell death and growth. The most important mechanism of action was predicted to be apoptosis, and the protein that is thought to play the most key action in this mechanism was caspase-3. Conclusions : In our future study, Sagunja-Tang will be used in an ischemic stroke mouse model, and the mechanism of action will be explored focusing on apoptosis and cell proliferation.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.140-148
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• 2022

Hydrogen is expected to be widely applied in most sectors within the current energy system, such as transportation and logistics, and is expected to be economically and technologically utilized as a power source to achieve vehiclebon emission reduction. In particular, the construction of hydrogen charging station infrastructure will not only support the distribution of hydrogen electric vehicles, but also play an important role in building a hydrogen logistics system. Therefore, This paper suggest additional charging infrastructure areas in Seoul with a focus on supply according to the annual average growth rate (CAGR), centering on Seoul, where hydrogen vehicles are most widely distributed. As of February 2022, hydrogen charging infrastructures were installed in Gangseo-gu, Gangdong-gu, Mapo-gu, Jung-gu, and Seocho-gu in downtown Seoul. Next, looking at the number of hydrogen vehicles by administrative dong in Seoul from 2018 to 2022, Seocho-gu has the most with 246 as of 2022, and Dongjak-gu has the highest average growth rate of 215.4% with a CAGR of 215.4%. Therefore, as a result of CAGR analysis, Dongjak-gu is expected to supply the most hydrogen vehicles in the future, and Seocho-gu currently has the most hydrogen vehicles, so it is likely that additional hydrogen charging infrastructure will be needed between Dongjak-gu and Seocho-gu.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Journal of IKEEE
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• v.26 no.4
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• pp.602-613
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• 2022

This paper proposes an algorithm for correcting indirect situations resulting from the wheelchair moving the stairs with wheel-type caterpillar and seat position variable. For analyzing the Yawing movement model, the change of Yaw value was estimated using Roll, Pitch, and Yaw in the driving environment, and it was used as a control variable and the information of the wheel drive controller. The verification confirmed the correction of about 10° of Yawing movement within about 7 seconds. It was confirmed that the angular velocity was reduced by 47.5% in seat position change.

• Tribology and Lubricants
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• v.38 no.3
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• pp.73-83
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• 2022

This paper is concerned with an analysis of a surface edge crack emanated from a sharp contact edge. For a geometrical model, a square wedge is in contact with a half plane whose materials are identical, and a surface perpendicular crack initiated from the contact edge exists in the half plane. To analyze this crack problem, it is necessary to evaluate the stress field on the crack line which are induced by the contact tractions and pseudo-dislocations that simulate the crack, using the Bueckner principle. In this Part I, the stress filed in the half plane due to the contact is re-summarized using an asymptotic analysis method, which has been published before by the author. Further focus is given to the stress field in the half plane due to a pseudo-edge dislocation, which will provide a stress solution due to a crack (i.e. a continuous distribution of edge dislocations) later, using the Burgers vector. Essential result of the present work is the corrective functions which modify the stress field of an infinite domain to apply for the present one which has free surfaces, and thus the infiniteness is no longer preserved. Numerical methods and coordinate normalization are used, which was developed for an edge crack problem, using the Gauss-Jacobi integration formula. The convergence of the corrective functions are investigated here. Features of the corrective functions and their application to a crack problem will be given in Part II.

• Journal of Veterinary Science
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• v.22 no.1
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• pp.12.1-12.11
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• 2021

Background: Bats have been considered natural reservoirs for several pathogenic human coronaviruses (CoVs) in the last two decades. Recently, a bat CoV was detected in the Republic of Korea; its entire genome was sequenced and reported to be genetically similar to that of the severe acute respiratory syndrome CoV (SARS-CoV). Objectives: The objective of this study was to compare the genetic sequences of SARS-CoV, SARS-CoV-2, and the two Korean bat CoV strains 16BO133 and B15-21, to estimate the likelihood of an interaction between the Korean bat CoVs and the human angiotensin-converting enzyme 2 (ACE2) receptor. Methods: The phylogenetic analysis was conducted with the maximum-likelihood (ML) method using MEGA 7 software. The Korean bat CoVs receptor binding domain (RBD) of the spike protein was analyzed by comparative homology modeling using the SWISS-MODEL server. The binding energies of the complexes were calculated using PRODIGY and MM/GBGA. Results: Phylogenetic analyses of the entire RNA-dependent RNA polymerase, spike regions, and the complete genome revealed that the Korean CoVs, along with SARS-CoV and SARS-CoV-2, belong to the subgenus Sarbecovirus, within BetaCoVs. However, the two Korean CoVs were distinct from SARS-CoV-2. Specifically, the spike gene of the Korean CoVs, which is involved in host infection, differed from that of SARS-CoV-2, showing only 66.8%-67.0% nucleotide homology and presented deletions within the RBD, particularly within regions critical for cross-species transmission and that mediate interaction with ACE2. Binding free energy calculation revealed that the binding affinity of Korean bat CoV RBD to hACE2 was drastically lower than that of SARS-CoV and SARS-CoV-2. Conclusions: These results suggest that Korean bat CoVs are unlikely to bind to the human ACE2 receptor.

• Steel and Composite Structures
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• v.42 no.6
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• pp.779-789
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• 2022

This work presents a non-linear cylindrical bending analysis of functionally graded plate reinforced by single-walled carbon nanotubes (SWCNTs) in thermal environment using a simple integral higher-order shear deformation theory (HSDT). This theory does not require shear correction factors and the transverse shear stresses vary parabolically through the thickness. The material properties of SWCNTs are assumed to be temperature-dependent and are obtained from molecular dynamics simulations. The material properties of functionally graded carbon nanotube-reinforced composites (FG-CNTCRs) are considered to be graded in the thickness direction, and are estimated through a micromechanical model. The non-linear strain-displacement relations in the Von Karman sense are used to study the effect of geometric non-linearity and the solution is obtained by minimization of the total potential energy. The numerical illustrations concern the nonlinear bending response of FG-CNTRC plates under different sets of thermal environmental conditions, from which results for uniformly distributed CNTRC plates are obtained as benchmarks.