• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.87-88
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• 2020

The purpose of this study is to explore the possibility of estimating optimum surface finish time of the fresh concrete placed at the job site by applying a surface hardness test meter(Durometer). Tests are carried out by measuring and comparing the Penetration resistance test and hardness test by Durometer. Penetration resistance tester and improved Durometer are similar, but the higher the temperature, the higher the setting time, and the higher the correlation was shown. When the hardness value of the improved Durometer is about 50 HD, it is found that the initial and 80 HD represent the end. It is expected that this will be useful in determining the finish time of the surface at the actual site.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.102-103
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• 2020

In this study, the effect of the change in the cement contents on the basic properties of the concrete and the estimation of the cement contents of hardened concretes using the hydrochloric acid melting heat. As a result of the study, as the cement contents increased, the fluidity and compressive strength increased, and there was no significant difference in the air contents and the unit volume mass. In addition, it showed a high correlation when compared with the estimated cement contents derived using the hydrochloric acid melting and the cement contents at the time of mixing. Therefore, it is considered that the hydrochloric acid melting is possible as a method of estimating the cement contents of concrete.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.169-170
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• 2020

The purpose of this study is to explore the possibility of estimating optimum surface finish time of the fresh concrete placed at the job site by applying a surface hardness test meter(Durometer). Tests are carried out by measuring and comparing the Penetration resistance test and hardness test by Durometer. Penetration resistance tester and improved Durometer are similar, but the higher the temperature, the higher the setting time, and the higher the correlation was shown. When the hardness value of the improved Durometer is about 50 HD, it is found that the initial and 80 HD represent the end. It is expected that this will be useful in determining the finish time of the surface at the actual site.

• Proceedings of the KIPE Conference
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• 2020.08a
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• pp.43-45
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• 2020

본 논문에서는 급속 충전 시 배터리의 상한 온도를 초과하지 않는 최대 가용 충전 전류의 실시간 추정 알고리즘을 제안한다. 제안하는 알고리즘은 배터리 열 모델을 기반으로 상한 온도에 도달하는 발열량을 추정하고, 충전 상태에 따른 내부 저항의 변화 양성을 고려하여 최대 급속 충전 전류를 도출한다. 알고리즘의 유효성을 검증하기 위하여 전기자동차용 배터리 팩을 이용한 시뮬레이션 및 실험을 진행한다.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.25-26
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• 2020

In this study, by applying the concrete compressive strength estimation system Concrete IoT Management System (hereinafter referred to as CIMS) to the concrete slab concrete in the domestic field, the purpose of this study is to confirm the practical use of CIMS and to verify the accuracy of estimating the initial strength of concrete. As a result, it shows a high correlation when the compressive strength and CIMS estimated strength of the specimen for structural management are converted and compared with the integrated temperature. However, in order to determine a more accurate experimental constant, it is necessary to consider the results up to 28 days.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.115-116
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• 2020

Due to the nature of modern society, buildings are becoming larger and more complex. As a result, the design conditions of the building are changing. However, despite the complexities of buildings, the fire resistance performance is still equalized to one hour without considering fire engineering analysis in Korea, so there is a risk according to actual fire design conditions. Therefore, the purpose of this study is to calculate the required fire resistance time for actual fire through fire mechanics analysis and case study.

• Proceedings of the KIPE Conference
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• 2020.08a
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• pp.49-51
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• 2020

본 논문에서는 전기자동차 급속 충전 시 배터리 팩의 온도 모사를 위한 열 모델링 기법을 제안한다. 배터리 등가 회로 모델을 기반으로 배터리 팩 내부 발열량을 계산하고, 배터리 열 모델 구성을 위한 파라미터 추출 실험 방안을 제안하다. 또한, 전기자동차 방열 시스템의 영향 등으로 인한 발열량 변화를 실시간으로 보정하여 온도 모사 정확도를 개선한다. 열 모델링 기법의 유효성 검증을 위하여 전기자동차용 배터리 팩 기반의 시뮬레이션 및 실험을 진행한다.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.466-470
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• 2024

This study proposes a deep learning-based LSTM model to predict the state of charge (SOC) of lithium-ion batteries. The model was trained using data collected under various temperature and load conditions, including measurement data from the CS2 lithium-ion battery provided by the University of Maryland College of Engineering. The LSTM model effectively models temporal patterns in the data by learning long-term dependencies. Performance evaluation by epoch showed that the predicted SOC improved from 14.8400 at epoch 10 to 12.4968 at epoch 60, approaching the actual SOC value of 13.5441. The mean absolute error (MAE) and root mean squared error (RMSE) also decreased from 0.9185 and 1.3009 at epoch 10 to 0.2333 and 0.5682 at epoch 60, respectively, indicating continuous improvement in predictive performance. This study demonstrates the validity of the LSTM model for predicting the SOC of lithium-ion batteries and its potential to enhance battery management systems.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Journal of Environmental Science International
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• v.17 no.6
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• pp.623-631
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• 2008

Many recent studies have concentrated upon the radiative effects of atmospheric aerosols. Though their scattering and absorption of radiation, aerosols can also induce some other important environment effects. In this study, new radiation code and aerosol data within Atmosphere General Circulation Model (AGCM) is used to assess the aerosol radiative forcing and to analyze relative climate effects. The new Kangnung National University AGCM Stratospheric-15 (KNU AGCM ST15) was integrated by using two sets of radiative effect of aerosols: CTRL as not a radiative effect of aerosols and AERO as a radiative effect of aerosols. Two cases show the difference of net shortwave radiation budget at top-of-atmosphere (TOA) is found to be about $-3.4Wm^{-2}$, at the surface (SFC) is about $-5.6Wm^{-2}$. Consequently the mean atmospheric absorption due to aerosol layer in global is about $2.2Wm^{-2}$. This result confirms the existence of a negative forcing due to the direct effect of aerosols at the surface and TOA in global annual mean. In addition, it is found that cooling over at the surface air temperature due to radiative effect of aerosols is about $0.17^{\circ}C$. It is estimated that radiative forcing of the net upward longwave radiation taken as the indirect effect of aerosol is much smaller than that of the direct effect as there is about $0.2Wm^{-2}$ of positive forcing both at TOA and at SFC. From this study, It made an accurate estimation of considering effect of aerosols that is negative effect. This may slow the rate of projected global warming during the $21^{st}$ century.