• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.339-339
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• 2021

XP-SWMM은 유역의 강우-유출과 1차원 관망 해석 및 2차원 지표면 흐름 해석이 가능하여 도시지역의 침수 모의에 활용도가 높다. 하지만 대부분의 수학적 모형이 그러하듯 XP-SWMM은 많은 입력 변수를 포함하고 있어 사용자의 숙련도에 따라 모의 결과가 달라질 수 있다. 본 연구의 목적은 XP-SWMM을 이용한 침수 모의의 정확도를 향상시키기 위해 침수 모의에 영향을 줄 수 있는 인자를 검토하고, 민감도 분석을 통해 인자별 적정 범위를 제안하는 것이다. 다만, 유역의 강우-유출과 1차원 관망 해석에 사용되는 매개변수는 과거 많은 연구자들이 적정 범위를 제시하였으므로 본 연구에서는 2차원 지표면 흐름 해석에 관한 입력 변수만을 대상으로 하였다. 이를 위해 2차원 계산의 지배방정식인 천수방정식의 매개변수 중 XP-SWMM에서 제어할 수 있는 인자와 XP-SWMM의 사용자 편의환경(graphical user interface; GUI)에서 제어 가능한 인자를 고려하였다. 선정된 인자는 지표면 조도계수, 2차원 계산 시간 간격, 2D 집수유량 계수, Smagorinsky 계수, Wet/dry 깊이이다. 제시된 인자들을 대상으로 침수흔적도의 침수 면적을 기준으로 민감도 분석을 수행하였고, 인자의 변화율을 침수 면적의 변화율로 변화시키는 조건수(condition number)를 활용하여 인자별 민감 여부를 분석하였다. 또한, 영향 인자 변화에 따른 침수 면적과 침수흔적도의 상대오차를 분석하여 영향 인자의 적정 범위를 제안하였다. 그 결과, 지표면 조도계수의 적정범위는 0.02~0.05, 2차원 계산 시간 간격은 0.1-3.5초, Smagorinsky 계수는 0.06~1.0, Wet/dry 깊이는 0.001~0.02 m인 것으로 나타났다. 본 연구는 XP-SWMM을 이용한 2차원 침수 모의에 활용될 수 있는 영향 인자와 적정 범위를 제안한 연구로서, 향후 XP-SWMM을 이용한 많은 침수분석에 참고자료로 활용될 수 있을 것으로 판단된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2B
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• pp.145-152
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• 2006

In the present study, a nonlinear model of rainfall-runoff process using Artficial Neural networks(ANNs) which have no consideration on the physical parameter for the basin was developed at Naju station which is the main stream of Yeongsan-river, and Sunam station which is the main stream of Hwangryong-river. The result from the model of ANN_NJ_9 at the Naju station revealed the best result of the rainfall-runoff process, while the model of ANN_SA_9 for the Sunam station. Also, GUI_FFS developed in the research showed the $R^2$ of more than 0.98 between the observed and predicted values using the rainfall and runoff in the respective stations. Therefore, the GUI_FFS might be expected that it can play a role for the high reliability to operate and manage the water resources and the design of river plan more efficiently in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.386-386
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• 2022

우리나라에서는 '물의 재이용 촉진 및 지원에 관한 법률 시행규칙' 등 다양한 법률에 따라 특정 규모 이상의 시설에 빗물이용시설을 설치하도록 규정하고 있으며, 지자체에서는 빗물이용시설의 이용을 장려하고자 설치비 및 시설 운영비를 지원하고 있다. 현업에서 빗물이용시설의 설계는 간편식을 이용하여 목표 우수이용률 또는 공급보장률을 만족하는 용량으로 결정하고 있다. 또한, 산정된 빗물이용시설의 용량에 대해서만 경제성 분석을 하고 있으며, 경제성 분석에 포함된 수식에 대한 근거가 부족한 실정이다. 본 연구에서는 기 개발된 빗물이용시설 설계 프로그램인 CARAH(capacity design aid for rainwater harvesting)의 추가 기능으로 경제성 분석을 통한 빗물이용시설의 적정 용량 결정 도구 및 사용자 편의 환경 개발 결과를 제시하고자 한다. 본 연구를 통해 개발된 CARAH의 경제성 분석 도구는 빗물이용시설의 용량, 설치비, 유지보수비용, 지자체의 설치비 지원 및 빗물 이용에 따른 요금 감면액 등을 고려하여 빗물이용시설의 비용편익 비율(benefit cost ratio; BCR) 산정 결과를 제시하는 기능이다. 본 연구에서는 개발된 CARAH의 경제성 분석 도구를 이용하여 기 설치된 광교 신도시의 빗물저류조 5호를 대상으로 경제성 분석을 수행하였으며, 경제성을 고려한 적정 저류 용량을 제시하였다. 경제성 분석 기간은 빗물이용시설의 내용 연수인 30년으로 하였으며, 여러 목표 공급보장률에 따른 최소 저류 용량별 BCR 결과를 비교하여 광교 신도시의 빗물저류조 5호의 적정 저류 용량을 결정하였다. 그 결과, 공급보장률이 60%에 해당하는 저류 용량 341 m3의 BCR이 7.28로 가장 경제적인 빗물이용시설의 저류 용량으로 산정되었다.

• Steel and Composite Structures
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• v.45 no.2
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• pp.159-173
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• 2022

This paper proposes a hybrid machine-learning model, which is called DANN-IP, that combines a deep artificial neural network (DANN) and an interior-point (IP) algorithm in order to improve the prediction capacity on the patch loading resistance of steel plate girders. For this purpose, 394 steel plate girders that were subjected to patch loading were tested in order to construct the DANN-IP model. Firstly, several DANN models were developed in order to establish the relationship between the patch loading resistance and the web panel length, the web height, the web thickness, the flange width, the flange thickness, the applied load length, the web yield strength, and the flange yield strength of steel plate girders. Accordingly, the best DANN model was chosen based on three performance indices, which included the R^2, RMSE, and a20-index. The IP algorithm was then adopted to optimize the weights and biases of the DANN model in order to establish the hybrid DANN-IP model. The results obtained from the proposed DANN-IP model were compared with of the results from the DANN model and the existing empirical formulas. The comparison showed that the proposed DANN-IP model achieved the best accuracy with an R^2 of 0.996, an RMSE of 23.260 kN, and an a20-index of 0.891. Finally, a Graphical User Interface (GUI) tool was developed in order to effectively use the proposed DANN-IP model for practical applications.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3854-3859
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• 2023

Background: This study aims to develop an evaluator that can quickly and accurately evaluate the shielding of low-energy industrial radiation generators. Methods: We used PyQt to develop a graphical user interface (GUI)-based program and employed the calculation methodology reported in the National Council on Radiation Protection and Measurements (NCRP)-49 for shielding calculations. We gathered the necessary factors for shielding evaluation using two libraries designed for Python, pandas and NumPy, and processed them into a database. We verified the effectiveness of the proposed program by comparing the results with those from safety reports of six domestic facilities. Results: After verifying the effectiveness of the program using the NCRP-49 example, we obtained an average error rate of 1.73%. When comparing the facility safety report and results obtained using the program, we found that the error rate was between 1.09% and 6.51%. However, facilities that did not use a defined shielding methodology were underestimated by 31.82% compared with the program (the final barrier thickness satisfied the shielding standard). Conclusion: The developed program provides a fast and accurate shielding evaluation that can assist personnel that work in radiation generator facilities and government officials in reviewing safety.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1315-1323
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• 2023

Rehabilitation assistive devices not only assist the rehabilitation therapy and daily life of the disabled and the elderly, but also assist the labor of their caregivers, so various functions are required to improve their quality of life. In this study, a design method considering its practicality is introduced for an active rehabilitation assistive device that can perform both standing and walking assistance by driving various actuators. For this purpose, the force required to assist standing was calculated using statics with the body segmentation method. Also, the overturning stability of the device was verified for various physical conditions and postures. The actuator in the active rehabilitation assistive device was operated by a patient using a graphical user interface in an embedded computer and a touch panel for easy usage. The detailed design was performed for implementation through the help of 3D-CAD and the finite element analysis, and a prototype was produced. Finally, it was proven that the design goal was satisfied by experimental validation.

• Geomechanics and Engineering
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• v.37 no.5
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• pp.475-498
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• 2024

The prediction of the susceptibility of soil to liquefaction using a limited set of parameters, particularly when dealing with highly unbalanced databases is a challenging problem. The current study focuses on different ensemble learning classification algorithms using highly unbalanced databases of results from in-situ tests; standard penetration test (SPT), shear wave velocity (V_s) test, and cone penetration test (CPT). The input parameters for these datasets consist of earthquake intensity parameters, strong ground motion parameters, and in-situ soil testing parameters. liquefaction index serving as the binary output parameter. After a rigorous comparison with existing literature, extreme gradient boosting (XGBoost), bagging, and random forest (RF) emerge as the most efficient models for liquefaction instance classification across different datasets. Notably, for SPT and V_s-based models, XGBoost exhibits superior performance, followed by Light gradient boosting machine (LightGBM) and Bagging, while for CPT-based models, Bagging ranks highest, followed by Gradient boosting and random forest, with CPT-based models demonstrating lower G_mean(error), rendering them preferable for soil liquefaction susceptibility prediction. Key parameters influencing model performance include internal friction angle of soil (ϕ) and percentage of fines less than 75 µ (F₇₅) for SPT and V_s data and normalized average cone tip resistance (q_c) and peak horizontal ground acceleration (a_max) for CPT data. It was also observed that the addition of V_s measurement to SPT data increased the efficiency of the prediction in comparison to only SPT data. Furthermore, to enhance usability, a graphical user interface (GUI) for seamless classification operations based on provided input parameters was proposed.

• Steel and Composite Structures
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• v.52 no.2
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• pp.145-163
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• 2024

This paper presents six novel hybrid machine learning (ML) models that combine support vector machines (SVM), Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), extreme gradient boosting (XGB), and categorical gradient boosting (CGB) with the Harris Hawks Optimization (HHO) algorithm. These models, namely HHO-SVM, HHO-DT, HHO-RF, HHO-GB, HHO-XGB, and HHO-CGB, are designed to predict the ultimate strength of both rectangular and circular reinforced concrete (RC) columns. The prediction models are established using a comprehensive database consisting of 325 experimental data for rectangular columns and 172 experimental data for circular columns. The ML model hyperparameters are optimized through a combination of cross-validation technique and the HHO. The performance of the hybrid ML models is evaluated and compared using various metrics, ultimately identifying the HHO-CGB model as the top-performing model for predicting the ultimate shear strength of both rectangular and circular RC columns. The mean R-value and mean a20-index are relatively high, reaching 0.991 and 0.959, respectively, while the mean absolute error and root mean square error are low (10.302 kN and 27.954 kN, respectively). Another comparison is conducted with four existing formulas to further validate the efficiency of the proposed HHO-CGB model. The Shapely Additive Explanations method is applied to analyze the contribution of each variable to the output within the HHO-CGB model, providing insights into the local and global influence of variables. The analysis reveals that the depth of the column, length of the column, and axial loading exert the most significant influence on the ultimate shear strength of RC columns. A user-friendly graphical interface tool is then developed based on the HHO-CGB to facilitate practical and cost-effective usage.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.831-845
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• 1997

In this paper,we proposed and developed a compiler and interactive programming enviroments for C++ wich is mostly worth of nitice among the object -oriented languages.To develope the compiler for C++ we took front=end/back-end model using EM virtual machine.In develpoing Front-End,we formailized C++ gram-mar with the context semsitive tokens which must be manipulated by dexical scanner and designed a AST class li-brary which is the hierarchy of AST node class and well defined interface among them,In develpoing Bacik-End,we proposed model for three major components :code oprtimizer,code generator and run-time enviroments.We emphasized the retargatable back-end which can be systrmatically reconfigured to genrate code for a variety of distinct target computers.We also developed terr pattern matching algorithm and implemented target code gen-erator which produce SPARC code.We also proposed the theroy and model for construction interative pro-gramming enviroments. To represent language features we adopt AST as internal reprsentation and propose uncremental analysis algorithm and viseal digrams.We also studied unparsing scheme, visual diagram,graphical user interface to generate interactive environments automatically Results of our resarch will be very useful for developing a complier and programming environments, and also can be used in compilers for parallel and distributed enviroments.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.96-108
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• 2011

Going abreast of high public concerns on the environment, the need of environmental modeling has been increased to assess the impact of space exploitation of environment. GIS offers potential solutions to the many problems encountered during water-quality modeling. But there are also many problems associated with the modeling. The preparation of necessary parameters for the modeling can be complicated. Also, the results from one model can be different from each other even the same area is analyzed. This paper aims to develop the data processing system to couple the Qual2E and HyGIS in which Qual2E input and output data files can be created, modified and processed using HyGIS and assess the performance of the system. A structural analysis and standardization of modeling are conducted to identify data flow and processing of Qual2E. Algorithms of the defined processors are designed and developed as component modules. The data model of HyGIS-Qual2E is designed, and GUI(Graphical User Interface) is developed using Visual Basic 6.0 and GDK.