• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1563-1570
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• 2023

In this study, a DeCART/MIG uncertainty quantification (UQ) analysis code system with a multicorrelated cross section stochastic sampling (S.S.) module was established and verified through the UAM (Uncertainty Analysis in Modeling) and the BEAVRS (Benchmark for Evaluation And Validation of Reactor Simulations) benchmark calculations. For the S.S. calculations, a sample of 500 DeCART multigroup cross section sets for two major actinides, i.e., ²³⁵U and ²³⁸U, were generated by the MIG code and covariance data from the ENDF/B-VII.1 evaluated nuclear data library. In the three pin problems (i.e. TMI-1, PB2, and Koz-6) from the UAM benchmark, the uncertainties in k_inf by the DeCART/MIG S.S. calculations agreed very well with the sensitivity and uncertainty (S/U) perturbation results by DeCART/MUSAD and the S/U direct subtraction (S/U-DS) results by the DeCART/MIG. From these results, it was concluded that the multi-group cross section sampling module of the MIG code works correctly and accurately. In the BEAVRS whole benchmark problems, the uncertainties in the control rod bank worth, isothermal temperature coefficient, power distribution, and critical boron concentration due to cross section uncertainties were calculated by the DeCART/MIG code system. Overall, the uncertainties in these design parameters were less than the general design review criteria of a typical pressurized water reactor start-up case. This newly-developed DeCART/MIG UQ analysis code system by the S.S. method can be widely utilized as uncertainty analysis and margin estimation tools for developing and designing new advanced nuclear reactors.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.217-217
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• 2021

우리나라 동해 연안에 영향을 미쳤던 역사지진들과 일본에서 진행된 동해에서의 대규모지진에 관한 조사검토회에서 2014년에 보고된 동해 동연부와 남해 남연부 측에 있는 60개의 지진공백역들에 대한 단층매개변수들이 공개되어있어 수치실험을 통해 지진해일의 재해도를 분석하고 있다. 하지만 이러한 단층매개변수 값들에 대한 불확실성이 존재하기에 이를 대비한 지진해일 대책을 세울 필요가 있다. 단층매개변수의 불확실성을 고려하는 방법 중 한 가지는 해당 변수들을 조정하여 Case 모델들을 다양화하는 것이다. 이 때 매개변수의 변동에 대한 기준이 필요하기에 단층매개변수에 대한 민감도 분석이 진행되어야 한다. 본 연구의 최종목표는 지진해일에 대한 위험성에 대비하기 위해 선정된 연구지역에 대하여 단층매개변수들을 조정한 경우별 모델들을 사용한 수치모형 실험을 실행한 후 도출된 지진해일 처오름높이 및 처내림높이 결과를 분석하여 각 단층매개 변수의 지진해일에 대한 민감도를 결정하는 것이며, 최종적으로 확률론적 지진해일 재해도분석(Probabilistic Tsunami Hazard Analysys : PTHA)을 실시할 때 기준이 되는 로직트리를 작성할 때 명확한 근거를 제시한다. 단층매개변수의 민감도 분석은 일본(Goda et al., 2014), 미국(Sepúlveda and Liu, 2016), 뉴질랜드(D. Burbridge et al., 2015) 등에서 연구가 활발하게 이루어졌으며 현재도 활발한 연구가 진행되고 있다. 민감도 분석 과정은 먼저 역사 지진해일과 우리나라 근해에 영향을 미칠 수 있는 지진해일의 단층매개변수 조사한 후 파향선추적모형(wave ray-tracing)의 결과를 정리하여 대상 지역에 영향을 미치는 단층을 선정하고, 선정한 단층들의 단층매개변수 값을 일정한 기준을 두고 조정하여 실시한 지진해일 수치모형 실험에서 계산한 결과값을 분석하여 민감도를 결정한다.

• Computers and Concrete
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• v.32 no.2
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• pp.119-138
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• 2023

Concrete carbonation is a prevalent phenomenon that leads to steel reinforcement corrosion in reinforced concrete (RC) structures, thereby decreasing their service life as well as durability. The process of carbonation results in a lower pH level of concrete, resulting in an acidic environment with a pH value below 12. This acidic environment initiates and accelerates the corrosion of steel reinforcement in concrete, rendering it more susceptible to damage and ultimately weakening the overall structural integrity of the RC system. Lower pH values might cause damage to the protective coating of steel, also known as the passive film, thus speeding up the process of corrosion. It is essential to estimate the carbonation factor to reduce the deterioration in concrete structures. A lot of work has gone into developing a carbonation model that is precise and efficient that takes both internal and external factors into account. This study presents an ML-based adaptive-neuro fuzzy inference system (ANFIS) approach to predict the carbonation depth of fly ash (FA)-based concrete structures. Cement content, FA, water-cement ratio, relative humidity, duration, and CO2 level have been used as input parameters to develop the ANFIS model. Six performance indices have been used for finding the accuracy of the developed model and two analytical models. The outcome of the ANFIS model has also been compared with the other models used in this study. The prediction results show that the ANFIS model outperforms analytical models with R-value, MAE, RMSE, and Nash-Sutcliffe efficiency index values of 0.9951, 0.7255 mm, 1.2346 mm, and 0.9957, respectively. Surface plots and sensitivity analysis have also been performed to identify the repercussion of individual features on the carbonation depth of FA-based concrete structures. The developed ANFIS-based model is simple, easy to use, and cost-effective with good accuracy as compared to existing models.

• Computers and Concrete
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• v.32 no.2
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• pp.217-232
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• 2023

Numerous studies have been performed on the behavior of pile foundations in cold regions. This study first attempted to employ artificial neural networks (ANN) to predict pile-bearing capacity focusing on pile data recorded primarily on cold regions. As the ANN technique has disadvantages such as finding global minima or slower convergence rates, this study in the second phase deals with the development of an ANN-based predictive model improved with an Elephant herding optimizer (EHO), Dragonfly Algorithm (DA), Genetic Algorithm (GA), and Evolution Strategy (ES) methods for predicting the piles' bearing capacity. The network inputs included the pile geometrical features, pile area (m²), pile length (m), internal friction angle along the pile body and pile tip (Ø°), and effective vertical stress. The MLP model pile's output was the ultimate bearing capacity. A sensitivity analysis was performed to determine the optimum parameters to select the best predictive model. A trial-and-error technique was also used to find the optimum network architecture and the number of hidden nodes. According to the results, there is a good consistency between the pile-bearing DA-MLP-predicted capacities and the measured bearing capacities. Based on the R2 and determination coefficient as 0.90364 and 0.8643 for testing and training datasets, respectively, it is suggested that the DA-MLP model can be effectively implemented with higher reliability, efficiency, and practicability to predict the bearing capacity of piles.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.587-595
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• 2008

Many studies on bus scheduling optimization have been done from the 1960s to recent years for establishing rational bus schedule plan that can improve convenience of bus passengers and minimize unnecessary runs. After 2000, as part of the Intelligent Transport Systems (ITS), the importance of the schedule management and providing schedule information through bus schedule optimization has become a big issue, and much research is being done to develop optimization models that will increase bus passenger convenience and, on the side of bus management, minimize unnecessary bus operation. The purpose of this study is to calculate the optimal bus frequency and create a timetable for each bus stop by applying DTR or DTRC model that use data for each bus stop and route segment. Model verification process was implemented using data collected from bus management system (BMS) and integrated transit-fare card system for bus route of Seoul's No. 472 line. In order to evaluate the reliability and uncertainty of optimal solution, sensitivity analysis was implemented for the various parameters and assumptions used in the bus scheduling model.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.99-99
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• 2022

Jeju island has a humid subtropical climate and this climate zone is expected to migrate northward toward the main land, Korea Peninsula, as temperature increases are accelerated. Vegetation type has been inevitably shifted along with the climatic change, having more subtropical species native in southeast Asia or even in Africa. With the forest composition shift, it becomes more important than ever to analyze the water balance of the forest wihth the ongoing as well as upcoming climate change. Here, we implemented the Ecosystem Demography Biosphere Model (ED2) by initializing the key variables using forest inventory data (diameter at breast height in 2012). Out of 10,000 parameter sets randomly generated from prior distribution distributions of each parameter (i.e., Monte-Carlo Method), we selected four behavioral parameter sets using remote-sensing data (LAI-MOD15A2H, GPP-MOD17A2H, and ET-MOD16A2, 8-days at 500-m during 2001-2005), and evaluated the performances using eddy-covariance carbon flux data (2012 Mar.-Sep. 30-min) and remote sensing data between 2006-2020. We simulated each of the four RCP scenarios (2.6, 4.5, 6.0, and 8.5) from four climate forcings (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5 from ISIMIP2b). Based on those 64 simulation sets, we estimate the changes in water balance resulting from the forest composition shift, and also uncertainty in the estimates and the sensitivity of the estimates to the parameters, climate forcings, and RCP scenarios.

• Advances in concrete construction
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• v.14 no.3
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• pp.195-204
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• 2022

As a brittle failure mode, punching-shear failure can be widely found in traditional RC slab-column connections, which may lead to the entire collapse of a flat plate structure. In this paper, a novel RC slab-column connection with inner steel truss was proposed to enhance the punching strength. In the proposed connection, steel trusses, each of which was composed of four steel angles and a series of steel strips, were pre-assembled at the periphery of the column capital and behaved as transverse reinforcements. With the aim of exploring the punching behavior of this novel RC slab-column connection, a static punching test was conducted on two full-scaled RC slab specimens, and the crack patterns, failure modes, load-deflection and load-strain responses were thoroughly analyzed to explore the contribution of the applied inner steel trusses to the overall punching behavior. The test results indicated that all the test specimens suffered the typical punching-shear failure, and the higher punching strength and initial stiffness could be found in the specimen with inner steel trusses. The numerical models of tested specimens were analyzed in ABAQUS. These models were verified by comparing the results of the tests with the results of the analyzes, and subsequently the sensitivity of the punching capacity to different parameters was studied. Based on the test results, a modified critical shear crack theory, which could take the contribution of the steel trusses into account, was put forward to predict the punching strength of this novel RC slab-column connection, and the calculated results agreed well with the test results.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.18-18
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• 2022

Barley has been used for the production of malt in the brewing industry. Malting is the process of preparing barley through partial germination. Malt extract is the most important quality parameter for malt quality. The grain and malt quality parameters of ten Korean malting barley varieties were studied. Malts was prepared using Phoeix automated micro malting system(Phoenix Bio, Australia). Quality analysis of Barley and malt was determined according to European brewery convention(EBC, 1998) and American society of brewing chemists(ASBC, 1997) method. And the hordeins of barley and malt were extracted with 50% isopropyl alcohol(IPA, 2-propanol) of 1% dithiothreitol(DTT). The analysis of hordeins was carried out by ultra-performance liquid chromatography(UPLC). The mean values of 1000-grains weight, assortment rate, protein content, starch content, beta-glucan content, husk rate, germination energy, germination capacity and water sensitivity of grain were 45.8g, 86.8%, 11.9%, 58.0%, 3.8%, 14.0%, 96.2%, 97.2%, 10.0%, respectively. The mean values of protein content, friability, diastatic power, extract, soluble protein, Kolbach index, beta-glucan of malt and wort were 11.3%, 87.6%, 201WK(Windish Kolbach), 79.3%, 4.6%, 41%, 85mg/L, respectively. UPLC analysis of grain and malt hordeins revealed that the amount of hordeins significantly degraded during malting. Also, we could successfully be used to compare hordein polypeptide patterns with malt quality.

• Journal of the Microelectronics and Packaging Society
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• v.29 no.4
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• pp.55-61
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• 2022

There is a major interest in diagnostic technology for multiple cancers worldwide. In order to reduce the difficulty of cancer diagnosis, a liquid biopsy technology based on a microfluidic device using trace amounts of biofluids such as blood is being studied. And optical biosensing, which measures the concentration of analytes through fluorescence imaging using biofluids, requires various strategies to improve sensitivity, and specialists and equipment are needed to carry out these strategies. This leads to an increase in diagnostic and production costs, and it is necessary to develop a technology to solve this problem. In this paper, we design and propose a fluorescent multi-cancer diagnostic sensing platform structure that implements passive self-separation technology and molecular recognition activation functions by fluid mixing, only with the geometry and microfluidic phenomena of microchannels based on self-driven flow by capillary force. In order to check the parameters affecting the performance of the plasma separation part of the designed sensor, the hydrodynamic diameter of the channel and the viscosity of the fluid were set as variables to confirm the formation of plasma separation flow through simulation. And finally, we propose an optimal sensor platform structure.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.15-20
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• 2024

The utilization of small unmanned aerial vehicles (UAVs) has expanded into both military and civilian domains, increasing the necessity for research to ensure operational safety and the efficient utilization of airspace. In this study, the calculation of minimum separation distances for the safe operation of small UAVs at low altitudes was conducted. The determination of minimum separation distances requires a comprehensive analysis of the total system errors associated with small UAVs, necessitating sensitivity analysis to identify key factors contributing to flight technology errors. Flight data for small UAVs were acquired by integrating the control system of an actual small UAV with a flight simulation program. Based on this data, operational scenarios for small UAVs were established, and the minimum separation distances for each scenario were calculated. This research contributes to proposing methods for utilizing calculated minimum separation distances as crucial parameters for ensuring the safe operation of small unmanned aerial vehicles in real-world scenarios.