• 품질경영학회지
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• 제49권4호
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• pp.539-550
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• 2021

Purpose: The purpose of this study is to propose a multivariate CUSUM control chart that can detect the out-of-control state fast while monitoring the cross- and auto- correlated multivariate time series data. Methods: We first build models to estimate the observation data and calculate the corresponding residuals. After then, a multivariate CUSUM chart is applied to monitor the residuals instead of the original raw observation data. Vector Autoregression and Artificial Neural Net are selected for the modelling, and Separated-MCUSUM chart is selected for the monitoring. The suggested methods are tested under a number of experimental settings and the performances are compared with those of other existing methods. Results: We find that Artificial Neural Net is more appropriate than Vector Autoregression for the modelling and show the combination of Separated-MCUSUM with Artificial Neural Net outperforms the other alternatives considered in this paper. Conclusion: The suggested chart has many advantages. It can monitor the complicated multivariate data with cross- and auto- correlation, and detects the out-of-control state fast. Unlike other CUSUM charts finding their control limits by trial and error simulation, the suggested chart saves lots of time and effort by approximating its control limit mathematically. We expect that the suggested chart performs not only effectively but also efficiently for monitoring the process with complicated correlations and frequently-changed parameters.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.921-927
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• 1988

The process and results of computer simulation using bond graphs for a hydraulic system driving large rotational inertia are presented in this paper. As the large rotational inertia and its application characteristics, control criteria of this system is not position-control nor velocity-control but appropriate acceleration, deceleration and inching ability. All the components' nonlinear characteristics are modelled using bond graphs. The equationing and solution process is carried out by a package. Finally it is concluded that modelling of this kind of system by bond graphs and using a software as its solver shows good approximated results to actual experimental data, and that the proposed modelling may be useful to actual design process for this kind of hydraulic system.

• Computers and Concrete
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• 제20권5호
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• pp.511-519
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• 2017

The reliability of reinforced concrete structures is frequently compromised by the deterioration caused by reinforcement corrosion. Evaluating the effect caused by reinforcement corrosion on structural behaviour of corrosion damaged concrete structures is essential for effective and reliable infrastructure management. In lifecycle management of corrosion affected reinforced concrete structures, it is difficult to correctly assess the lifecycle performance due to the uncertainties associated with structural resistance deterioration. This paper presents a stochastic deterioration modelling approach to evaluate the performance deterioration of corroded concrete structures during their service life. The flexural strength deterioration is analytically predicted on the basis of bond strength evolution caused by reinforcement corrosion, which is examined by the experimental and field data available. An assessment criterion is defined to evaluate the flexural strength deterioration for the time-dependent reliability analysis. The results from the worked examples show that the proposed approach is capable of evaluating the structural reliability of corrosion damaged concrete structures.

• 한국측량학회지
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• 제13권2호
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• pp.291-298
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• 1995

본 연구에서는 중력장모델링에 있어서 단 파장의 효과인 지형보정량을 계산하고 지오이드의 효과에 미치는 DTM 데이타를 사용하여 계산하였다. 정밀한 지형보정량을 계산하기 위하여 $500\times{500m}$격자 간격의 DTM 데이타를 준비하여 매스프리즘 모델과 매스라인모델을 적용하였다. 적용결과 지형효과가 다소 크게 나타났으며, 이 결과는 정밀한 지오이드의 계산을 위하여는 지형효과가 고려되어야 한다는 것을 알 수 있었다.

• Coupled systems mechanics
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• 제4권1호
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• pp.19-36
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• 2015

Modelling and analysis of a brick masonry building involves uncertainties like modelling assumptions and properties of local material. Therefore, it is necessary to perform a calibration to evaluate the dynamic properties of the structure. The response of the finite element model is improved by predicting the parameter by performing linear dynamic analysis on experimental data by comparing the acceleration. Further, a nonlinear dynamic analysis was also performed comparing the roof acceleration and damage pattern of the structure obtained analytically with the test findings. The roof accelerations obtained analytically were in good agreement with experimental roof accelerations. The damage patterns observed analytically after every shock were almost similar to that of experimental observations. Damage pattern with amplification in roof acceleration exhibit the potentiality of earthquake resistant measures in brick masonry models.

• Computers and Concrete
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• 제15권4호
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• pp.547-562
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• 2015

A two-dimensional multi-layered finite elements modeling of reinforced concrete structures at non-linear behaviour under monotonic and cyclical loading is presented. The non-linearity material is characterized by several phenomena such as: the physical non-linearity of the concrete and steels materials, the behaviour of cracked concrete and the interaction effect between materials represented by the post-cracking filled. These parameters are taken into consideration in this paper to examine the response of the reinforced concrete structures at the non-linear behaviour. Four examples of application are presented. The numerical results obtained, are in a very good agreement with available experimental data and other numerical models of the literature.

• Korean Chemical Engineering Research
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• 제60권1호
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• pp.51-61
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• 2022

Gas separation via hollow fibre membrane modules (HFMM) is deemed to be a promising technology for natural gas sweetening, particularly for lowering the level of carbon dioxide (CO₂) in natural gas, which can cause various problems during transportation and process operation. Separation performance via HFMM is affected by membrane properties, module specifications and operating conditions. In this study, a mathematical model for HFMM is developed, which can be used to assess the effects of the aforementioned variables on separation performance. Appropriate boundary conditions are imposed to resolve steady-state values of permeate variables and incorporated in the model equations via an iterative numerical procedure. The developed model is proven to be reliable via model validation against experimental data in the literature. Also, the model is capable of capturing axial variations of process variables as well as predicting key performance indicators. It can be extended to simulate a large-scale plant and identify an optimal process design and operating conditions for improved separation efficiency and reduced cost.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.271-275
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• 2015

A variety of evaluation application and initiatives on the adoption of Building Information Modelling (BIM) have been introduced in recent years. Most of which however, focused mainly on evaluating design to construction phase-processes, or BIM utilization performances. Through studying existing publications, it is found that continuous utilization of BIM data throughout the building's life cycle is comparatively less explored or documented. Therefore, this study looks at improving this incomplete life cycle condition with the concept that accumulated BIM data should be carried forward and statistically quantified for cross comparison, in order to facilitate practitioners to better improve the projects the future. Based on this conceptual theory of moving towards a closedloop BIM building life cycle, this study explores, through existing literature, the use of cloud based computing as the means to quantify and adaptively utilize BIM data. Categorization of BIM data relations in adaptive utilization of BIM data is then suggested as a initial step for enhancing cross comparison of BIM data in a cloud environment.

• 한국습지학회지
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• 제22권2호
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• pp.130-138
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• 2020

2017년 기준 서울시 및 광역시의 하수도 보급률은 90% 이상의 높은 하수도 보급률을 보이며, 국내하수처리장의 개소 수는 2010년 3,064개에서 2017년 기준 4,072개로 약 25% 증가 증가하였다. 그중에서도 SBR계열 공법으로 운영 중인 하수처리장은 현재 585개로 2010년 대비 17% 증가한 것으로 나타났다. 상수원의 수질 개선과 소규모하수도 시설의 운영개선을 위해 안동 임하댐 권역 내 하수처리장 500㎥/일 이상 3개소 및 500㎥/일 미만 46개소, 총 49개소 시설을 대상으로 모델링을 적용하여 공정개선방안을 연구하였다. 모델링을 위한 개선안으로 5년간 운영자료 등을 검토하여 후보군을 도출하였다. 49개소의 시설은 총 12가지 종류의 공법으로 운영되고 있으며, 이 중에서 SBR공법의 500㎥/일 이상 시설 1개소와 500㎥/일 미만의 46개소를 3개 유형으로 그룹 분류를 하여 운영 개선이 가능한 9개소를 선정하였다. 500㎥/일 이상 1개소에 모델링를 적용한 결과, SRT 조절을 통해 방류수 수질 개선이 가능했으며, 소규모 처리장 9개소에 적용한 결과 총 인의 제거율을 최대 14.4% 개선할 수 있는 것으로 나타났다. 이에 본 연구의 결과자료는 공공 하수처리시설 및 마을 하수도 시설에 대한 개선 및 운영 개선 방안으로 활용될 수 있을 것으로 판단된다.

• 한국멀티미디어학회논문지
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• 제19권12호
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• pp.1970-1980
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• 2016

The problem of food deficiency is a major discouragement to many low-income developing countries. Most of these countries experience constant danger of hunger, malnutrition and diseases as they are unable to maintain their food supplies mainly due to lack of arable lands and modern crop, livestock and fishery production technologies. In addition, the pollutants resulting from the secondary industries are becoming another serious issue in their food problems. The pollutants mixed in the sands blowing from the mainland China and the toxic waters flowing in the farm land form the industrialized zones are some of the examples. The Vertical Farm, or Plant Factory, proposed in this study could be the best alternative food production system for them. Vertical farm is an efficient food production system that yields relatively a large volume of food materials without environmental risks. The system does not require a large open space and manpower and can minimize the possibility of infiltration of pollutants. This research describes a basic model of the system focusing on determining the optimal sites for it based on the meteorological data concentrating on the atmospheric pollutants. The types and volume of pollutants are analyzed and identified through the big data obtained, followed by visualization of analysis results and their comparisons for better understanding.