• International Journal of Advanced Culture Technology
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• 제11권3호
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• pp.310-314
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• 2023

The purpose of this study is to predict the remaining capacity of lithium-ion batteries and evaluate their performance using five artificial intelligence models, including linear regression analysis, decision tree, random forest, neural network, and ensemble model. We is in the study, measured Excel data from the CS2 lithium-ion battery was used, and the prediction accuracy of the model was measured using evaluation indicators such as mean square error, mean absolute error, coefficient of determination, and root mean square error. As a result of this study, the Root Mean Square Error(RMSE) of the linear regression model was 0.045, the decision tree model was 0.038, the random forest model was 0.034, the neural network model was 0.032, and the ensemble model was 0.030. The ensemble model had the best prediction performance, with the neural network model taking second place. The decision tree model and random forest model also performed quite well, and the linear regression model showed poor prediction performance compared to other models. Therefore, through this study, ensemble models and neural network models are most suitable for predicting the remaining capacity of lithium-ion batteries, and decision tree and random forest models also showed good performance. Linear regression models showed relatively poor predictive performance. Therefore, it was concluded that it is appropriate to prioritize ensemble models and neural network models in order to improve the efficiency of battery management and energy systems.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2005년도 추계 학술발표회 제17권2호
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• pp.93-96
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• 2005

Since the columns with flexure-shear failure have lower ductility than those with flexural failure, shear capacity curve models shall be applied as well as flexural capacity curve in order to determine ultimate displacement for seismic design or performance evaluation. In this paper, a modified shear capacity curve model is proposed and compared with the other models such as the CALTRANS model, Aschheim et al.'s model, and Priestley et al.'s model. Four shear capacity curve models are applied to the 4 full scale circular bridge column test results and the accuracy of each model is discussed. It may not be fully adequate to drive a final decision from the application to the limited number of test results, however the proposed model provides the better prediction of failure mode and ultimate displacement than the other models for the selected column test results.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2006년도 춘계학술발표회 논문집(I)
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• pp.186-189
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• 2006

Since the columns with flexure-shear failure have lower ductility than those with flexural failure, shear capacity curve models shall be applied as well as flexural capacity curve in order to determine ultimate displacement for seismic design or performance evaluation. In this paper, a proposed modified shear capacity curve model is compared with the other models such as the CALTRANS model, Aschheim et al.'s model, and Priestley et al.'s model. Four shear capacity curve models are applied to the 4 full scale and 7 small scale circular bridge column test results and the accuracy of each model is discussed. It may not be fully adequate to drive a final decision from the application to the limited number of test results, however the proposed model provides the better prediction of failure mode and ultimate displacement than the other models for the selected column test results.

• 대한교통학회지
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• 제32권6호
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• pp.651-661
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• 2014

최근 국내 회전교차로의 도입에 따라 다양한 연구가 수행되어 왔다. 하지만 회전교차로의 용량에 대한 연구는 아직 부족한 실정이다. 이에 이 연구의 목적은 실 자료를 바탕으로 용량 모형을 개발하는데 있다. 연구의 주요 결과는 다음과 같다. 첫째, 프로빗 모형을 이용하여 산정한 임계간격과 추종시간에 근거한 미국 HCM 용량모형을 이용하여 국내 회전교차로의 용량이 분석되었다. 국내의 진입용량은 회전교통류율($Q_c$)이 적을 경우에는 미국과 비슷한 수준이지만, 회전교통류율($Q_c$)이 많아지면 미국보다 높은 것으로 평가되었다. 둘째, 실 교통량 자료를 기반으로 국내 회전교차로의 기본용량모형이 새롭게 개발되었다. 셋째, 기본용량모형을 근거로 기하구조를 고려한 모형이 개발되었다. 마지막으로 위에서 개발된 모든 모형은 통계적으로 유의한 것으로 분석되었다.

• Ocean Systems Engineering
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• 제5권1호
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• pp.41-54
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• 2015

This study presents the development of predictive models for uplift capacity of suction caisson in clay using an artificial intelligence technique, extreme learning machine (ELM). Other artificial intelligence models like artificial neural network (ANN), support vector machine (SVM), relevance vector machine (RVM) models are also developed to compare the ELM model with above models and available numerical models in terms of different statistical criteria. A ranking system is presented to evaluate present models in identifying the 'best' model. Sensitivity analyses are made to identify important inputs contributing to the developed models.

• 한국시뮬레이션학회논문지
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• 제5권1호
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• pp.53-66
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• 1996

Container handling facilities in Korean ports have increased rapidly according to Korean industrialization and the worldwide containerization. Over 98% of total containers handles in Korean ports are handled in Puan ports. This paper presents the estimation method of annual container handling capacity of container terminals by the computer simulation models. Simulation models are developed utilizing SIMAN IV simulation package. Annual handling capacity of real container terminals such as BCTOC and PECT was estimated by the proposed simulation models. Also, Annual handling capaicty of planned or expected terminals in Puan port was estimated. The comparisons between container forecast demand and estimated handling capacity of Pusan port from 1996 through 2001 were made. It showed that Pusan port will have over two million TEU handling capacity shortage during that period and will face enormous port congestion. Lastly, mid term and long-term capacity expansion plansof container terminals in korean ports were discussed.

• 대한산업공학회지
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• 제33권1호
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• pp.126-137
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• 2007

This study addresses the analytic models for estimating the capacity and performance of the multi-carrierCDMA system where several carriers would be assigned to a single cell to accommodate the required trafficdemand. Two key features of the multi-carrier CDMA system, carrier selections of new calls and inter-camerhard handoffs, are accommodated in the models, Computation experiments are conducted to show the effectiveness of the proposed model.

• Structural Monitoring and Maintenance
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• 제9권1호
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• pp.81-105
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• 2022

The use of concrete filled steel tube (CFST) column is widely accepted due to its property of high axial load carrying capacity, more ductility and more resistant to earthquake specially using in bridges and high-rise buildings. The initial imperfection (δ) that produces during casting or fixing causes the reduction in load carrying capacity, this is the reason, experimental capacity is always less then theoretical one. In this research, the effect of δ on load carrying capacity and behavior of concrete filled steel tube (CFST) column have been investigated by numerically simulation of large number of models with different δ and other geometric parameters that include length (L), width (B), steel tube thickness (t), f'_c and f_y. Finite element analysis software ANSYS v18 is used to develop model of SCFST column to evaluate strength capacity, buckling and failure pattern of member which is applied during experimental study under cyclic axial loading. After validation of results, 42 models with different parameters are evaluated to develop empirical equation predicting axial load carrying capacity for different value of δ. Results indicate that empirical equation shows the 0 to 9% error for finite element analysis Forty-two models in comparison with ANSYS results, respectively. Empirical equation can be used for predicting the axial capacity of early estimating the axial capacity of SCFT column including 𝛿.

• Earthquakes and Structures
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• 제19권5호
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• pp.379-393
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• 2020

The purpose of this study is to first evaluate the seismic behavior of ageing arch bridges by using the Intensity Measure - based demand and DCFD format, which is referred to as the fragility-hazard format. Then, an investigation is performed for their seismic vulnerability. Analytical models are created for bridges concerning different features and these models are subjected to Incremental Dynamic Analysis (IDA) analysis using a set of 22 earthquake records. The hazard curve and results of IDA analysis are employed to evaluate the return period of exceeding the limit states in the IM-based probabilistic performance-based context. Subsequently, the fragility-hazard format is used to assess factored demand, factored capacity, and the ratio of the factored demand to the factored capacity of the models with respect to different performance objectives. Finally, the vulnerability curves are obtained for the investigated bridges in terms of the loss ratio. The results revealed that decreasing the span length of the unreinforced arch bridges leads to the increase in the return period of exceeding various limit states and factored capacity and decrease in the displacement demand, the probability of failure, the factored demand, as well as the factored demand to factored capacity ratios, loss ratio, and seismic vulnerability. Finally, it is derived that the probability of the need for rehabilitation increases by an increase in the span length of the models.

• Steel and Composite Structures
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• 제50권4호
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• pp.383-401
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• 2024

The research comprehensively studies the axial compression performance of T-shaped concrete-filled thin-walled steel tubular (CTST) long columns after fire exposure. Initially, a series of tests investigate the effects of heating time, load eccentricity, and stiffeners on the column's performance. Furthermore, Finite Element (FE) analysis is employed to establish temperature and mechanical field models for the T-shaped CTST long column with stiffeners after fire exposure, using carefully determined key parameters such as thermal parameters, constitutive relations, and contact models. In addition, a parametric analysis based on the numerical models is conducted to explore the effects of heating time, section diameter, material strength, and steel ratio on the axial compressive bearing capacity, bending bearing capacity under normal temperature, as well as residual bearing capacity after fire exposure. The results reveal that the maximum lateral deformation occurs near the middle of the span, with bending increasing as heating time and eccentricity rise. Despite a decrease in axial compressive load and bending capacity after fire exposure, the columns still exhibit desirable bearing capacity and deformability. Moreover, the obtained FE results align closely with experimental findings, validating the reliability of the developed numerical models. Additionally, this study proposes a simplified design method to calculate these mechanical property parameters, satisfying the ISO-834 standard. The relative errors between the proposed simplified formulas and FE models remain within 10%, indicating their capability to provide a theoretical reference for practical engineering applications.