• New & Renewable Energy
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• v.17 no.3
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• pp.32-41
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• 2021

A groundwater source heat pump (GWHP) was developed in this study by adapting a borehole heat exchanger with closed-loop and open-loop systems in a new building. In the pilot test building, the air-conditioning on the second floor was designed to employ a closed-loop system and that on the third floor had an open-loop system. The GWHP design is based on the feasibility of groundwater resources at the installation site. For the hydrogeological survey of the study site, pumping and injection tests were conducted, and the feasibility of GWHP installation was evaluated based on the air-conditioning load demand of the building. The site was found to be satisfactory for the design capacity of the thermal load and water quality. In addition, the effect of groundwater movement on the performance of the closed-loop system was tested under three different operational scenarios of groundwater pumping. The performance of the system was sustainable with groundwater flow but declined without appropriate groundwater flow. From long-term observations of the operation, the aquifer temperature change was less than 2℃ at the observation well and 5℃ at the injection well with respect to the initial groundwater temperature. This pilot study is expected to be of guidance for developing GWHPs at fractured rock aquifers.

• 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 Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1023-1030
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• 2021

Korea Maritime Safety Tribunal (KMST) statistics released in of 2019 indicated that most collision accidents involving small-size vessels with less than 20 gross-tonnage occur mainly due to operational carelessness, such as forward-looking negligence and unskilled vessel control. As an effective remedy, training and education for vessel operators are being strengthened to prevent accidents. However, collision accidents are increasing, and technical measures are continuously developed to reduce accidents caused by human factors. In this study, an avoidance algorithm and prototype of terminal-controller against collision between two nearby vessels was developed for implementation on relative navigation control by adopting WAVE telecommunication technology. Moreover, several sea trial tests were performed to verify the collision avoidance algorithm and control system using two fishing vessels for dif erent scenarios.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.246-246
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• 2023

Multi-purpose dams are operated accounting for both physical and socioeconomic factors. This study aims to evaluate the utility of a deep learning algorithm-based model for three multi-purpose dam operation (Seomjin River dam, Juam dam, and Juam Control dam) in Seomjin River. In this study, the Gated Recurrent Unit (GRU) algorithm is applied to predict hourly water level of the dam reservoirs over 2002-2021. The hyper-parameters are optimized by the Bayesian optimization algorithm to enhance the prediction skill of the GRU model. The GRU models are set by the following cases: single dam input - single dam output (S-S), multi-dam input - single dam output (M-S), and multi-dam input - multi-dam output (M-M). Results show that the S-S cases with the local dam information have the highest accuracy above 0.8 of NSE. Results from the M-S and M-M model cases confirm that upstream dam information can bring important information for downstream dam operation prediction. The S-S models are simulated with altered outflows (-40% to +40%) to generate the simulated water level of the dam reservoir as alternative dam operational scenarios. The alternative S-S model simulations show physically inconsistent results, indicating that our deep learning algorithm-based model is not explainable for multi-purpose dam operation patterns. To better understand this limitation, we further analyze the relationship between observed water level and outflow of each dam. Results show that complexity in outflow-water level relationship causes the limited predictability of the GRU algorithm-based model. This study highlights the importance of socioeconomic factors from hidden multi-purpose dam operation processes on not only physical processes-based modeling but also aritificial intelligence modeling.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.162-162
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• 2023

Climate change is a complex phenomenon having its impact on diverse sectors. Temperature and precipitation are two of the most fundamental variables used to characterize climate, and changes in these variables can have significant impacts on ecosystems, agriculture, and human societies. This study evaluated the historical (1981-2010) and future (2011-2100) climatic trends in the Seti-Gandaki basin of Nepal based on 5 km resolution Multi Model Ensemble (MME) of 18 Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for SSP1-2.6, SSP2-4.5 and SSP5-85 scenarios. For this study, ERA5 reanalysis dataset is used for historical reference dataset instead of observation dataset due to a lack of good observation data in the study area. Results show that the basin has experienced continuous warming and an increased precipitation pattern in the historical period, and this rising trend is projected to be more prominent in the future. The Seti basin hosts 13 operational hydropower projects of different sizes, with 10 more planned by the government. Consequently, the findings of this study could be leveraged to design adaptation measures for existing hydropower schemes and provide a framework for policymakers to formulate climate change policies in the region. Furthermore, the methodology employed in this research could be replicated in other parts of the country to generate precise climate projections and offer guidance to policymakers in devising sustainable development plans for sectors like irrigation and hydropower.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3423-3440
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• 2023

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.1
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• pp.57-64
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• 2023

Recently, the increased use of anti-ship guided missiles, a weapon system that detects and attacks targets in naval engagement, has come to pose a major threat to the survivability of ships. In order to improve the survivability of ships in response to such anti-ship guided missiles, many studies of means to counteract them have been conducted in militarily advanced countries. The integrated survivability of a ship can be largely divided into susceptibility, vulnerability, and recoverability, and is expressed as the conditional probability, if the ship is hit, of damage and recovery. However, as research on susceptibility is a major military secret of each country, access to it is very limited and there are few publicly available data. Therefore, in this study, a possibility of estimating the susceptibility of ships using an anti-air defense system corresponding to anti-ship guided missiles was reviewed. To this, scenarios during engagement, weapon systems mounted to counter threats, and maximum detection/battle range according to the operational situation of the defense weapon system were defined. In addition, the effectiveness of the anti-air defense system and susceptibility was calculated based on the performance of the weapon system, the crew's ability to operate the weapon system, and the detection probability of the detection/defense system. To evaluate the susceptibility estimation feasibility, the sensitivity of the detailed variables was reviewed, and the usefulness of the established process was confirmed through sensitivity analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.89-98
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• 2006

In this study, a method for flood runoff analysis in main channel connected with interior floodplain, is applied for evaluation of hydraulics of Sapgyo lake for the purpose of flood protection by considering tidal effect of West Sea and runoff from the watershed. Especially, operational condition of sluice gate was explicitly modeled in conjunction with various runoff scenarios from watershed. The change in hydraulics of main channel and interior floodplain was found to be predominantly affected by tidal effect, and explicit modeling of gate operation made possible the evaluation of hydraulic characteristics of different alternatives. Until now, such an analysis was not made due to the lack of models with such capability, however, with the proposed method, it is possible to perform such an analysis and is thought that the proposed method can be a valuable tool for flood protection planning.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.444-455
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• 2023

In this report, a specialization plan for wearable robots by mission profile was investigated and analyzed to derive an application plan. The final goal of this study was to derive the operating requirements of wearable robots according to specialized plans, and to conduct a specialized study on wearable robots by mission profile through investigation/analysis of specialized plans for each mission profile. In the study, 1) Research on technology trends related to military wearable robots such as patents and papers, 2) Research/analysis of mission profiles to characterize wearable robots, 3) Analysis of wearable robot specialization plans according to mission profiles, and 4) Requirements for wearable robot operation were derived. In the first time of the study, a survey on technology trends related to wearable robots for soldiers such as patents and papers was completed, and a military consultative body was conducted to derive measures to characterize wearable robots. In addition, a survey was conducted on mission profiles, and the second time study derived Key Performance Parameters (KPP) for operational performance, core performance, and system performance based on scenarios by mission profile. However, it is revealed that the KPP derived from the research results was not covered in this paper because it was judged that more in-depth research was needed prior to disclosure. In order to prepare for future battlefield situations and increase the usability of wearable robots, this study was conducted to characterize wearable robots by considering the characteristics of soldiers' equipment according to mission profiles and to characterize wearable robots by mission profile.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.77-86
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• 2024

'UAS flight recording system' is a system that is mounted on an unmanned aircraft system consisting of various components and records flight-related data. The data recorded by this system should be used for aviation accident and incident investigations to prevent similar accidents. In particular, for the category of UAS with high operating risk, safety devices close to that of manned aircraft are required, and it is urgent to develop flight recording systems reflecting the characteristics of the UAS to secure airworthiness. This paper highlights the need for UAS flight recording systems for aviation accident and incident investigations and seek a method to derive flight recording system parameters for 'Certified Category' with high operational risk. To this end, Inter-City UAM was used as a concrete use case, and the process of approaching system parameters was devised by assuming accident occurrences and hazards from mission profiles and scenarios. As a result of the study, it was confirmed that parameters could be derived through this process.