• 대한토목학회논문집
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• 제26권1B호
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• pp.7-14
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• 2006

영춘 지점의 유출량이 1,000CMS에서 9,000CMS로 나타난 강우사상을 이용하여 레이더 관계식을 산정하였다. 레이더 강우량의 정확성을 높이기 위하여 소유역별 보정계수를 산정하였다. 레이더 관계식, Thiessen, 등우선, 역거리법을 이용하여 유역의 강우량을 비교하였다. 유역의 하천망을 형성 할 수 있는 HEC-GeoHMS 모형을 구축하고, 유출모형인 HEC-HMS 모형의 입력 인자로 이용하였다. 레이더 관계식으로 산정된 강우량을 적용한 유출모의가 가장 좋은 결과를 보였다. 기후 변화로 인한 집중 호우시 레이더관계식을 이용한 유출량 예측시 신속하고 정확한 것으로 판단된다. 레이더 관계식을 이용하여 충주댐 유역의 강우량 산정할 수 있을 것이다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2022년도 하계학술대회
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• pp.205-208
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• 2022

Multi-exposure high dynamic range (HDR) image reconstruction, the task of reconstructing an HDR image from multiple low dynamic range (LDR) images in a dynamic scene, often produces ghosting artifacts caused by camera motion and moving objects and also cannot deal with washed-out regions due to over or under-exposures. While there has been many deep-learning-based methods with motion estimation to alleviate these problems, they still have limitations for severely moving scenes. They also require large parameter counts, especially in the case of state-of-the-art methods that employ attention modules. To address these issues, we propose a frequency domain approach based on the idea that the transform domain coefficients inherently involve the global information from whole image pixels to cope with large motions. Specifically we adopt Residual Fast Fourier Transform (RFFT) blocks, which allows for global interactions of pixels. Moreover, we also employ Depthwise Overparametrized convolution (DO-conv) blocks, a convolution in which each input channel is convolved with its own 2D kernel, for faster convergence and performance gains. We call this LFFNet (Lightweight Frequency Fusion Network), and experiments on the benchmarks show reduced ghosting artifacts and improved performance up to 0.6dB tonemapped PSNR compared to recent state-of-the-art methods. Our architecture also requires fewer parameters and converges faster in training.

• Geomechanics and Engineering
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• 제31권2호
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• pp.129-147
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• 2022

The properties of soil are naturally highly variable and thus, to ensure proper safety and reliability, we need to test a large number of samples across the length and depth. In pile foundations, conducting field tests are highly expensive and the traditional empirical relations too have been proven to be poor in performance. The study proposes a state-of-art Particle Swarm Optimization (PSO) hybridized Artificial Neural Network (ANN), Extreme Learning Machine (ELM) and Adaptive Neuro Fuzzy Inference System (ANFIS); and comparative analysis of metaheuristic models (ANN-PSO, ELM-PSO, ANFIS-PSO) for prediction of bearing capacity of pile foundation trained and tested on dataset of nearly 300 dynamic pile tests from the literature. A novel ensemble model of three hybrid models is constructed to combine and enhance the predictions of the individual models effectively. The authenticity of the dataset is confirmed using descriptive statistics, correlation matrix and sensitivity analysis. Ram weight and diameter of pile are found to be most influential input parameter. The comparative analysis reveals that ANFIS-PSO is the best performing model in testing phase (R² = 0.85, RMSE = 0.01) while ELM-PSO performs best in training phase (R² = 0.88, RMSE = 0.08); while the ensemble provided overall best performance based on the rank score. The performance of ANN-PSO is least satisfactory compared to the other two models. The findings were confirmed using Taylor diagram, error matrix and uncertainty analysis. Based on the results ELM-PSO and ANFIS-PSO is proposed to be used for the prediction of bearing capacity of piles and ensemble learning method of joining the outputs of individual models should be encouraged. The study possesses the potential to assist geotechnical engineers in the design phase of civil engineering projects.

• 한국정보전자통신기술학회논문지
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• 제16권5호
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• pp.223-229
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• 2023

본 논문에서는 벡터제어 기법을 적용하는 교류 전동기 PI(비례-적분) 전류제어를 위한 주요 시스템 파라미터를 측정하는 방법을 제시한다. 전류제어를 위해서 PI 제어입력은 여러 선택적 방법에 의해 튜닝될 수 있다. 그 여러 방법들 중에서 주요 계통 파라미터인 권선 저항과 인덕턴스를 이용하는 방법이 빈번히 사용된다. 본 연구에서는 단순 궤환 제어의 결과들을 통해서 이 두 파라미터를 분석, 계측하는 기법을 제시한다. 이 분석적 측정 방법은 단위 계단 또는 다중 계단 기준 명령에 대해 단순 비례 궤환 이득을 이용하는 P 제어의 출력들을 분석하여 단계적으로 파라미터들을 계측해 내는 방법이다. 이 기법은 실시간적인 해석적 계측 방법으로 추가 계측 회로들 및 복잡한 계측 알고리즘들을 사용하지 않고 교류전동기의 벡터제어를 위한 토크성분과 자속성분 전류 제어이득을 같이 연산할 수 있는 방법이다.

• 한국정보전자통신기술학회논문지
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• 제16권6호
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• pp.434-440
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• 2023

본 논문에서는 교류 서보 전동기 PI 전류제어를 위한 주요 시스템 파라미터인 상저항과 상인덕턴스를 측정하는 방법을 제시한다. 서보 전동기 전류제어를 위한 PI 제어이득은 주요 계통 파라미터인 권선간 저항과 인덕턴스 정보를 활용하여 튜닝하는 자동적 방법이 기본적으로 사용된다. 본 연구에서는 이 두 파라미터를 3상 인버터 제어를 통해 계측하는 방법을 제시한다. 이 제어 및 계측 방법은 3상 인버터를 이용하여 3상 권선에 비례입력 만을 이용하는 스텝 전류제어를 수행하고 그 결과로 얻어진 출력 상전류를 측정함으로써 구현된다. 더불어 이 방법은 권선간 인덕턴스 계측을 위해 특정 스위칭모드에서의 인버터 자연-순환(freewheeling) 전류를 이용한다. 이 인버터 제어를 이용하는 측정 방법은 새로운 추가 계측 회로 및 복잡한 계측 알고리즘을 사용하지 않고 실시간으로 파라미터들을 계측 및 연산할 수 있는 해석적 방법이다. 실제 전동기 제어에 사용되어지는 구동기 회로를 그대로 사용하면서 스위칭소자의 도통저항과 각종 결선 저항을 포함하는 합성 저항 및 인덕턴스를 계측할 수 있는 방법이다.

• 한국농공학회논문집
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• 제66권4호
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• pp.41-50
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• 2024

Precipitation is an important component of the hydrological cycle and a key input parameter for many applications in hydrology, climatology, meteorology, and weather forecasting research. Grid-based satellite rainfall products with wide spatial coverage and easy accessibility are well recognized as a supplement to ground-based observations for various hydrological applications. The error properties of satellite rainfall products vary as a function of rainfall intensity, climate region, altitude, and land surface conditions. Therefore, this study aims to evaluate the commonly used new global grid-based satellite rainfall product, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), using data collected at different spatial and temporal scales. Additionally, in this study, grid-based CHIRPS satellite precipitation data were used to evaluate the 2022 extreme drought. CHIRPS provides high-resolution precipitation data at 5 km and offers reliable global data through the correction of ground-based observations. A frequency analysis was performed to determine the precipitation deficit in 2022. As a result of comparing droughts in 2015, 2017, and 2022, it was found that May 2022 had a drought frequency of more than 500 years. The 1-month SPI in May 2022 indicated a severe drought with an average value of -1.8, while the 3-month SPI showed a moderate drought with an average value of 0.6. The extreme drought experienced in South Korea in 2022 was evident in the 1-month SPI. Both CHIRPS precipitation data and observations from weather stations depicted similar trends. Based on these results, it is concluded that CHIRPS can be used as fundamental data for drought evaluation and monitoring in unmeasured areas of precipitation.

• Structural Engineering and Mechanics
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• 제90권1호
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• pp.27-40
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• 2024

The prediction of VIV amplitude is essential for the design and fatigue life estimation of steel tubes in tubular transmission towers. Limited to costly and time-consuming traditional experimental and computational fluid dynamics (CFD) methods, a machine learning (ML)-based method is proposed to efficiently predict the VIV amplitude of steel tubes in transmission towers. Firstly, by introducing the first-order mode shape to the two-dimensional CFD method, a simplified response analysis method (SRAM) is presented to calculate the VIV amplitude of steel tubes in transmission towers, which enables to build a dataset for training ML models. Then, by taking mass ratio M^*, damping ratio ξ, and reduced velocity U^* as the input variables, a Kriging-based prediction method (KPM) is further proposed to estimate the VIV amplitude of steel tubes in transmission towers by combining the SRAM with the Kriging-based ML model. Finally, the feasibility and effectiveness of the proposed methods are demonstrated by using three full-scale steel tubes with C-shaped, Cross-shaped, and Flange-plate joints, respectively. The results show that the SRAM can reasonably calculate the VIV amplitude, in which the relative errors of VIV maximum amplitude in three examples are less than 6%. Meanwhile, the KPM can well predict the VIV amplitude of steel tubes in transmission towers within the studied range of M^*, ξ and U^*. Particularly, the KPM presents an excellent capability in estimating the VIV maximum amplitude by using the reduced damping parameter S_G.

• 터널과지하공간
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• 제34권2호
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• pp.143-153
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• 2024

TBM 공법은 발파 공법에 비해 굴착 중 소음과 진동 수준이 낮고, 안정성이 높은 터널 굴착 공법이며, 전세계적으로 터널 프로젝트에 TBM 공법을 적용하는 사례가 증가하는 추세이다. 디스크 커터는 TBM의 커터헤드에 장착되는 굴착 도구로 지속적으로 막장면 지반과 상호작용하며, 이때 필연적으로 마모가 발생한다. 본 연구에서는 지질 조건과 TBM 운영파라미터, 머신러닝 알고리즘들을 이용하여 디스크 커터 마모를 정량적으로 예측하였다. 디스크커터 마모 예측의 입력변수 중 UCS 데이터의 수가 다른 기계 데이터 및 마모 데이터에 비해 매우 부족하기 때문에, 먼저 TBM 기계 데이터를 이용하여 전체 구간에 대한 UCS 추정을 진행하고, 완성된 전체 데이터로 마모율 계수 예측을 수행하였다. 마모율 계수 예측 모델의 성능을 비교해 본 결과 XGBoost 모델의 성능이 가장 높게 나타났으며, 복잡한 예측 모델의 해석을 위해 SHapley Additive exPlanation (SHAP) 분석을 진행하였다.

• Nuclear Engineering and Technology
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• 제55권11호
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• pp.3996-4001
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• 2023

The High-flux Advanced Neutron Application Reactor (HANARO) produces radioisotopes (RIs) (¹³¹I, ¹⁹²Ir, etc.) through neutron irradiation on various RI production targets. Among them, ¹⁷⁷Lu and ¹⁶⁶Ho are particularly promising owing to their theranostic characteristics that facilitate simultaneous diagnosis and treatment. Prior to neutron irradiation, evaluating the nuclear heating of the RI production target is essential for ensuring the thermal-hydraulic safety of HANARO. In this study, the feasibility of producing ¹⁷⁷Lu and ¹⁶⁶Ho using irradiation holes of HANARO was investigated in terms of thermal-hydraulic safety. The nuclear heating rates of the RI production target by prompt and delayed radiation were calculated using MCNP6. The calculated nuclear heating rates were used as an input parameter in COMSOL Multiphysics to obtain the temperature distribution in an irradiation hole. The degree of temperature increase of the ¹⁷⁷Lu and ¹⁶⁶Ho production targets satisfied the safety criteria of HANARO. The nuclear heating rates and temperature distribution obtained through the in silico study are expected to provide valuable insight into the production of ¹⁷⁷Lu and ¹⁶⁶Ho using HANARO.

• Nuclear Engineering and Technology
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• 제56권5호
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• pp.1584-1602
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• 2024

It is vital to output the required electrical power following various task requirements when the space reactor power supply is operating in orbit. The dynamic performance of the closed Brayton cycle thermoelectric conversion system is initially studied and analyzed. Based on this, a load tracking power regulation method is developed for the liquid metal cooled space reactor power system, which takes into account the inlet temperature of the lithium on the hot side of the intermediate heat exchanger, the filling quantity of helium and xenon, and the input amount of the heat pipe radiator module. After comparing several methods, a power regulation method with fast response speed and strong system stability is obtained. Under various changes in power output, the dynamic response characteristics of the ultra-small liquid metal lithium-cooled space reactor concept scheme are analyzed. The transient operation process of 70 % load power shows that core power variation is within 30 % and core coolant temperature can operate at the set safety temperature. The second loop's helium-xenon working fluid has a 65K temperature change range and a 25 % filling quantity. The lithium at the radiator loop outlet changes by less than ±7 K, and the system's main key parameters change as expected, indicating safety. The core system uses less power during 30 % load power transient operation. According to the response characteristics of various system parameters, under low power operation conditions, the lithium working fluid temperature of the radiator circuit and the high-temperature heat pipe operation temperature are limiting conditions for low-power operation, and multiple system parameters must be coordinated to ensure that the radiator system does not condense the lithium working fluid and the heat pipe.