• 방사선산업학회지
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• 제17권4호
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• pp.471-479
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• 2023

In In-situ radioactivity measurement techniques, efficiency calibration models use predefined models to simulate a sample's geometry and radioactivity distribution. However, simplified efficiency calibration models lead to uncertainties in the efficiency curves, which in turn affect the radioactivity concentration results. This study aims to develop an efficiency calibration optimization methodology to improve the accuracy of in-situ gamma radiation measurements for byproducts from industrial facilities. To accomplish the objective, a drive mechanism for rotational measurement of an byproduct simulator and a sample was constructed. Using ISOCS, an efficiency calibration model of the designed object was generated. Then, the sensitivity analysis of the efficiency calibration model was performed, and the efficiency curve of the efficiency calibration model was optimized using the sensitivity analysis results. Finally, the radiation concentration of the simulated subject was estimated, compared, and evaluated with the designed certification value. For the sensitivity assessment of the influencing factors of the efficiency calibration model, the ISOCS Uncertainty Estimator was used for the horizontal and vertical size and density of the measured object. The standard deviation of the measurement efficiency as a function of the longitudinal size and density of the efficiency calibration model decreased with increasing energy region. When using the optimized efficiency calibration model, the measurement efficiency using IUE was improved compared to the measurement efficiency using ISOCS at the energy of ²²⁸Ac (911 keV) for the nuclide under analysis. Using the ISOCS efficiency calibration method, the difference between the measured radiation concentration and the design value for each simulated subject measurement direction was 4.1% (1% to 10%) on average. The difference between the estimated radioactivity concentration and the design value was 3.6% (1~8%) on average when using the ISOCS IUE efficiency calibration method, which was closer to the design value than the efficiency calibration method using ISOCS. In other words, the estimated radioactivity concentration using the optimized efficiency curve was similar to the designed radioactivity concentration. The results of this study can be utilized as the main basis for the development of regulatory technologies for the treatment and disposal of waste generated during the operation, maintenance, and facility replacement of domestic byproduct generation facilities.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.428-428
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• 2017

In this study, three optimization techniques efficiency is assessed for calibration of the GR4J model for streamflow simulation in Selmacheon, Boryeong Dam and Kyeongancheon watersheds located in South Korea. The Penman-Monteith equation is applied to estimate the potential evapotranspiration, model calibration, and validation is carried out using the readily available daily hydro-meteorological data. The Shuffled Complex Evolution-University of Arizona(SCE-UA), Uniform Adaptive Monte Carlo (UAMC), and Coupled Latin Hypercube and Rosenbrock (CLHR) optimization techniques has been used to evaluate the robustness, performance and optimized parameters of the three catchments. The result of the three algorithms performances and optimized parameters are within the recommended ranges in the tested watersheds. The SCE-UA and CLHR outputs are found to be similar both in efficiency and model parameters. However, the UAMC algorithms performances differently in the three tested watersheds.

• 한국농공학회논문집
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• 제51권1호
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• pp.1-9
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• 2009

The objective of this paper was to evaluate the auto-calibration with multi-objective optimization method to calibrate the parameters of the Soil and Water Assessment Tool (SWAT) model. The model was calibrated and validated by using nine years (1996-2004) of measured data for the 384-ha Baran reservoir subwatershed located in central Korea. Multi-objective optimization was performed for sixteen parameters related to runoff. The parameters were modified by the replacement or addition of an absolute change. The root mean square error (RMSE), relative mean absolute error (RMAE), Nash-Sutcliffe efficiency index (EI), determination coefficient ($R^2$) were used to evaluate the results of calibration and validation. The statistics of RMSE, RMAE, EI, and $R^2$ were 4.66 mm/day, 0.53 mm/day 0.86, and 0.89 for the calibration period and 3.98 mm/day, 0.51 mm/day, 0.83, and 0.84 for the validation period respectively. The statistical parameters indicated that the model provided a reasonable estimation of the runoff at the study watershed. This result was illustrated with a multi-objective optimization for the flow at an observation site within the Baran reservoir watershed.

• 한국ITS학회 논문지
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• 제18권2호
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• pp.29-43
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• 2019

미시적 교통류 모형의 정산은 시뮬레이션 분석에 있어 매우 중요한 요소이다. 유전자 알고리즘은 교통류 모형의 정산에 널리 활용되어 왔으며, 일반적으로 이러한 최적화 문제에 있어 높은 효율성을 보이는 것으로 알려져 있다. 하지만 제한된 시간내에 신속한 의사결정을 위한 시뮬레이션 분석에 있어 유전자알고리즘의 모형 정산속도는 여전히 느리다. 이에 본 연구에서는 정산 효율 향상을 위해 중심합성계획법 기반의 이중유전자알고리즘을 활용한 차량추종모형 정산방법론을 개발하였다. 개발된 정산 방법론에서는 실험계획법 중 하나인 중심합성계획법과 유전자알고리즘을 결합하여 준최적해를 찾고, 이를 다시 유전자알고리즘의 초기 값으로 하여 모형 파라미터의 최적해를 찾는다. 개발된 방법을 활용하여 Gipps의 차량추종모형을 정산하였다. 선행연구에서 사용된 단일 유전자알고리즘을 활용한 방법과 비교한 결과, 본 연구에서 개발한 방법이 더 짧은 시간내에 최적해를 찾는 것으로 확인되었다. 개발된 방법론은 유전자알고리즘을 사용하는 다양한 교통분석에 활용될 수 있을 것으로 기대된다.

• Nuclear Engineering and Technology
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• 제56권8호
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• pp.3347-3358
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• 2024

Addressing the challenge of identifying an appropriate set of material and irradiation parameters for accurate simulation models using crystal plasticity finite element method (CPFEM), this study proposes a novel two-stage method for nano-indentation modeling of ion-irradiated face-centered cubic (FCC) materials. It includes implementing the strain-gradient crystal plasticity (SGCP) theory with irradiation effects and the calibration of simulation parameters using the particle swarm optimization (PSO) algorithm with experimental data. The proposed method consists of two stages: establishing CPFEM without irradiation effects in stage 1 and modeling irradiation effects based on CPFEM in stage 2. Modeling the nano-indentation test of ion-irradiated stainless steel 304 (SS304) using real experimental data is conducted to evaluate the efficiency of the proposed method. The accuracy of the calibration method using PSO is verified through comparisons between simulation and experimental results for force-indentation depth and hardness-indentation depth relationships under both unirradiated and irradiated conditions. Moreover, effect of ion-irradiation on the mechanical behavior during the nano-indentation of single crystal SS304 is also examined to demonstrate that the proposed method is a powerful approach for nano-indentation modeling of ion-irradiated FCC single crystals using SGCP theory and the PSO algorithm.

• 한국자동차공학회논문집
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• 제24권3호
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• pp.319-329
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• 2016

Globally, many researchers have been trying to improve the fuel economy of a vehicle for satisfying future $CO_2$ regulation and minimizing air pollution problem. For the same background, diesel engine and vehicle system optimization using simulation models have been key technologies for the improvement of vehicle system efficiency. Therefore, in this study, calibration method for the air breathing system of a WGT diesel engine using mean value model has been composed for efficient engine and vehicle optimization simulation researches. And virtual WGT performances have been calculated for a 2 cylinder downsized diesel engine system. From these researches, the calibration method for the boost pressure and EGR rate of a virtual diesel engine related with WGT performances could be composed and some of technical issue related with downsized diesel engine could be investigated.

• 한국습지학회지
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• 제11권2호
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• pp.107-121
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• 2009

현재 홍수예보를 위하여 많은 강우-유출 모형이 사용되고 있으나, 이러한 모형의 매개변수를 결정하는 것은 매우 난해하다. 본 연구에서는 저류함수모형과 Tank 모형, SSARR 모형을 이용하여 미호천 유역에 대하여 홍수모의 예측을 수행하고 그 효율성을 분석하였다. 연구에 적용된 강우-유출 모형에 최적화 방법을 적용하여 매개 변수 산정을 수행하였으며, 패턴탐색과 유전자 알고리즘의 최적화 방법을 적용 시, 보정과정 내에서 매개변수 간 민감도를 분석하고 이를 바탕으로 매개변수를 소군집으로 분류하여 민감도에 따른 순차 보정 방법을 적용하고 이 결과를 비교 분석하였다. 매개변수 소군집을 이용한 보정 방법과 기존에 사용되는 매개변수 군집을 이용한 보정 방법을 비교한 결과, SSR에 소군집을 이용한 순차보정 방법을 적용하였을 때 첨두 유량과 보정 시간 면에서 유리한 것으로 나타났다.

• 한국수자원학회논문집
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• 제51권9호
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• pp.803-812
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• 2018

본 연구는 다목적함수를 고려한 입자군집최적화(Particle Swarm Optimization, PSO) 알고리즘을 Python으로 개발하고, Soil and Water Assessment Tool (SWAT) 모형에 적용하여 자동보정 알고리즘의 적용 가능성을 평가하였다. SWAT 모형의 유출 해석은 안성천의 공도 수위 관측소 상류유역($364.8km^2$)을 대상으로 하였으며, 공도 지점의 2000년부터 2015년까지의 일 유량 자료를 이용하였다. PSO 자동보정은 결정계수(coefficient of determination, $R^2$), 평균제곱근오차(RMSE), NSE 모형효율계수(Nash-Sutcliffe Efficiency, $NSE_Q$), 특히 중간유출과 기저유출의 보정을 위해 $NSE_{INQ}$ (Inverse Q)를 활용하여 SWAT을 보정하였다. PSO을 통한 SWAT 모형의 자동보정과 수동보정의 유출해석 결과, 각각 $R^2$는 0.64, 0.55, RMSE는 0.59, 0.58, $NSE_Q$는 0.78, 0.75, $NSE_{INQ}$는 0.45, 0.09의 상관성 분석결과를 보였다. PSO 자동보정 알고리즘은 수동보정에 비하여 높은 향상을 보였는데 특히 유출의 감수곡선을 개선시켰으며 적절한 매개변수 추가(RCHRG_DP)와 매개변수 범위의 설정으로 수동보정의 한계를 보완하였다.

• 해양환경안전학회지
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• 제24권3호
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• pp.295-301
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• 2018

This study compares optimization algorithms for efficient estimations of ship's hydrodynamic coefficients. Two constrained algorithms, the interior point and the sequential quadratic programming, are compared for the estimation. Mathematical optimization is designed to get optimal hydrodynamic coefficients for modelling a ship, and benchmark data are collected from sea trials of a training ship. A calibration for environmental influence and a sensitivity analysis for efficiency are carried out prior to implementing the optimization. The optimization is composed of three steps considering correlation between coefficients and manoeuvre characteristics. Manoeuvre characteristics of simulation results for both sets of optimized coefficients are close to each other, and they are also fit to the benchmark data. However, this similarity interferes with the comparison, and it is supposed that optimization conditions, such as designed variables and constraints, are not sufficient to compare them strictly. An enhanced optimization with additional sea trial measurement data should be carried out in future studies.

• 한국수자원학회논문집
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• 제39권8호
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• pp.677-690
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• 2006

본 연구에서는 LH-OAT (Latin Hypercube Ore factor At a Time) 민감도분석 방법과 SCE-UA (Shuffled Complex Evolution at University of Arizona) 최적화 기법을 적용하여 보청천 유역에서 SWAT모형에 대한 자동보정 방법을 제시하였다. LH-OAT 방법은 전역 민감도분석과 부분 민감도 분석의 장점을 조합하여 가용매개변수 공간에 대하여 효율적으로 매개변수의 민감도 분석이 가능하게 하였다. LH-OAT민감도 분석으로부터 결정된 매개변수의 민감도 등급은 SWAT 모형의 자동보정 과정에서 요구되는 보정대상 매개변수의 선택에 유용하게 적용될 수 있다. SCE-UA 방법을 적용한 SWAT모형의 자동보정 해석결과는 보정자료, 보정매개변수, 통계적 오차의 선택에 따라서 모형의 성능이 좌우되었다. 보정기간과 보정매개변수가 증가함에 따라 검증기간에 대한 RMSE (Root Mean Square Error), NSEF (Nash-Sutcliffe Model Efficiency), RMAE (Relative Mean Absolute Error), NMSE (Normalized Mean Square Error) 등의 모형오차는 감소하였지만, NAE (Normalized Average Error) 및 SDR(Standard Deviation Ratio)은 개선되지 않았다. SWAT모형의 보정에 적용되는 보정자료, 보정매개변수 및 모형평가를 위한 통계적 오차 선택이 해석결과에 미치는 복잡한 영향을 이해하기 위하여 다양한 대표유역을 대상으로 추가적인 연구가 필요하다.