• Structural Engineering and Mechanics
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• 제69권1호
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• pp.33-42
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• 2019

Thermal cracks are cracks that commonly form at early ages in mass concrete. During the concrete pouring process, the elastic modulus changes continuously. This requires the time domain to be divided into several steps in order to solve for the temperature, stress, and displacement of the concrete. Numerical simulations of thermal crack propagation in concrete are more difficult at early ages. To solve this problem, this study divides crack propagation in concrete at early ages into two cases: the case in which cracks do not propagate but the elastic modulus of the concrete changes and the case in which cracks propagate at a certain time. This paper provides computational models for these two cases by integrating the characteristics of the extended finite element algorithm, compiles the corresponding computational programs, and verifies the accuracy of the proposed model using numerical comparisons. The model presented in this paper has the advantages of high computational accuracy and stable results in resolving thermal cracking and its propagation in concrete at early ages.

• 한국태양에너지학회 논문집
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• 제36권5호
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• pp.73-89
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• 2016

To assure maximum economic benefits and the energy performance of solar water heating systems, the proper sizing of components and operating conditions need to be optimized. In recent years, a number of studies to design optimally solar water heating systems have been tried. This paper presents a design method for optimizing the various capacity-related and installation-related design variables based on life cycle cost using a genetic algorithm. The design variables considered in this study included the types and numbers of solar collector and auxiliary heaters; the types of storage tanks and heat exchangers; the solar collector slope; mass flow rates of the fluid on the hot and cold sides. The suggested method was applied for optimizing a solar water heating system for an elementary school in Seoul, South Korea. In addition, the effectiveness of the proposed optimization method was assessed by analyzing the obtained optimal solutions of six case studies, each of which was simulated with different solar fractions. It is observed that a trade-off between the equipment cost and the energy cost results in an optimal design that yields the lowest life cycle cost. Therefore, it could be helpful to apply the optimal solar water heating system by comparing the various design solutions obtained by using the optimization method instead of the engineer's experience and intuition.

• Smart Structures and Systems
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• 제29권5호
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• pp.677-691
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• 2022

Water cycle algorithm (WCA) has been a very effective optimization technique for complex engineering problems. This study employs the WCA for simultaneous prediction of heating load (L_H) and cooling load (L_C) in residential buildings. This algorithm is responsible for optimally tuning a neural network (NN). Utilizing 614 records, the behavior of the L_H and L_C is explored and the captured knowledge is then used to predict for 154 unanalyzed building conditions. Since the WCA is a population-based algorithm, different numbers of the searching agents were tested to find the most optimum configuration. It was observed that the best solution is discovered by 500 agents. A comparison with five newly-developed benchmark optimizers, namely equilibrium optimizer (EO), multi-tracker optimization algorithm (MTOA), slime mould algorithm (SMA), multi-verse optimizer (MVO), and electromagnetic field optimization (EFO) revealed that the WCANN predicts the desired parameters with considerably larger accuracy. Obtained root mean square errors (1.4866, 2.1296, 2.8279, 2.5727, 2.5337, and 2.3029 for the L_H and 2.1767, 2.6459, 3.1821, 2.9732, 2.9616, and 2.6890 for the L_C) indicated that the most reliable prediction was presented by the proposed model. The EFONN, however, provided a more time-effective solution. Lastly, an explicit predictive formula was elicited from the WCANN.

• 제어로봇시스템학회논문지
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• 제14권3호
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• pp.221-225
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• 2008

This paper presents a self-tuning controller for pressurized water reactor (P.W.R.). This self-tuning controller includes two substantial steps, such as parameter identification and control-law building in each cycle. Extended least square algorithm is used for parameter identification, Kalman filter is used for state estimation, and discrete Riccati equation is used for optimal control. Effectiveness of this algorithm is shown through computer simulation and sensitivity analysis.

• 한국산학기술학회논문지
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• 제16권6호
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• pp.4216-4227
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• 2015

상수관망은 중요 사회기반 시설물 중 하나로, 상수관망을 구성하는 수 많은 관을 통해 각 수요지로 물을 공급 및 배분하는 역할을 한다. 수 많은 관들로 구성된 상수관망의 설계는 여러 수리학적 조건을 고려하여 진행되기에 그리 간단한 문제는 아니다. 이에 많은 연구자들이 최적화 기법을 도입하여 상수관망의 설계에 사용을 하고 있다. 본 연구에서는 생애주기 에너지 분석을 통한 최적 관경을 결정하기 위한 모형을 개발하였다. 개발한 모형은 최적 설계를 위해 유전자 알고리즘을 도입하였고, 수리해석을 위해 EPANET2.0을 연동하고 생애주기 동안에 관의 변화를 모의하기 위한 노후도식과 관 파손확률 공식을 적용하였다. 모형은 총 두 곳의 샘플 관망에 적용하였으며, 두 관망에 대한 에너지 기반 최적 설계를 진행하였다. 에너지 최적 관경 조합에 대한 비용을 계산하여 비용 최적 관경 조합과 비교를 하였으며, 이를 통해 에너지 기반 최적 설계가 비용 측면에서도 큰 불이익이 없이 진행될 수 있음을 보였다.

• 한국산학기술학회논문지
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• 제20권6호
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• pp.314-321
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• 2019

본 연구에서 개발된 Self-Adaptive Vision Correction Algorithm (SAVCA)은 광학적 특성을 모방하여 개발된 Vision Correction Algorithm (VCA)의 총 6개의 매개변수 중 자가 적응형태로 구축된 Division Rate 1 (DR1) 및 Division Rate 2 (DR2)를 제외한 Modulation Transfer Function Rate (MR), Astigmatic Rate (AR), Astigmatic Factor (AF) 및 Compression Factor (CF) 등 4개의 매개변수를 변경하여 사용성을 증대시키기 위해 제시되었다. 개발된 SAVCA의 검증을 위해 기존 VCA를 적용하였던 2개 변수를 갖는 수학 문제 (Six hump camel back 및 Easton and fenton) 및 30개 변수를 갖는 수학 문제 (Schwefel 및 Hyper sphere)에 적용한 결과 SAVCA는 비교한 다른 알고리즘 (Harmony Search, Water Cycle Algorithm, VCA, Genetic Algorithms with Floating-point representation, Shuffled Complex Evolution algorithm 및 Modified Shuffled Complex Evolution)에 비해 우수한 성능을 보여주었다. 마지막으로 공학 문제인 Speed reducer design에서도 SAVCA는 가장 좋은 결과를 보여주었다. 복잡한 매개변수 조절과정을 거치지 않은 SAVCA는 여러 분야에서 적용이 가능할 것이다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.145-145
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• 2021

Water distribution networks (WDNs) are designed to satisfy water requirement of an urban community. One of the central issues in human history is providing sufficient quality and quantity of water through WDNs. A WDN consists of a great number of pipelines with different ages, lengths, materials, and sizes in varying degrees of deterioration. The available annual budget for rehabilitation of these infrastructures only covers part of the network; thus it is important to manage the limited budget in the most cost-effective manner. In this study, a novel pipe replacement scheduling approach is proposed in order to smooth the annual investment time series based on a life cycle cost assessment. The proposed approach is applied to a real WDN currently operating in South Korea. The proposed scheduling plan considers both the annual budget limitation and the optimum investment on pipes' useful life. A non-dominated sorting genetic algorithm is used to solve a multi-objective optimization problem. Three decision-making objectives, including the minimum imposed LCC of the network, the minimum standard deviation of annual cost, and the minimum average age of the network, are considered to find optimal pipe replacement planning over long-term time period. The results indicate that the proposed scheduling structure provides efficient and cost-effective rehabilitation management of water network with consistent annual budget.

• 설비공학논문집
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• 제22권12호
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• pp.859-866
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• 2010

This study examined the economics of a solar water heating system for an office building using life cycle cost (LCC) optimization simulations. The numerical simulations were conducted with TRNSYS and GenOpt employing the Hooke-Jeeves algorithm. The solar collector area, slope, mass flow rate per collector area and storage tank volume were selected as the main design parameters of the solar water heating system. The LCC optimization simulations of the system were carried out for cases where water temperature was $60^{\circ}C$ and $50^{\circ}C$. The results showed that for water temperature at $60^{\circ}C$ and $50^{\circ}C$ the collector area could be decreased by 17% and 28%, storage tank volume could be decreased by 49% and 54%, and mass flow rate per collector area increased by 5% and 9% respectively compared to a non-optimized system. The LCC of the system was reduced by 4% for $60^{\circ}C$ and 7% for $50^{\circ}C$. The initial installation cost of the system was reduced by 24% for $60^{\circ}C$ and 34% for $50^{\circ}C$. However, the operating cost of the system increased by 16% for $60^{\circ}C$ and 36% for $50^{\circ}C$ compared to a traditional solar water heating system.

• Nuclear Engineering and Technology
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• 제56권5호
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• pp.1654-1666
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• 2024

The goal of this research is to propose a way to maximize small modular reactor (SMR) utilization to gain better market feasibility in support of carbon neutrality. For that purpose, a comprehensive tool was developed, combining off-design thermohydraulic models, economic objective models (levelized cost of electricity, annual profit), non-economic models (saved CO2), a parameter input sampling method (Latin hypercube sampling, LHS), and a multi-objective evolutionary algorithm (Non-dominated Sorting Algorithm-2, NSGA2 method) for optimizing a SMR-combined heat and power cycle (CHP) system design. Considering multiple objectives, it was shown that NSGA2+LHS method can find better optimal solution sets with similar computational costs compared to a conventional weighted sum (WS) method. Out of multiple multi-objective optimal design configurations for a 105 MWe design generation rating, a chosen reference SMR-CHP system resulted in its levelized cost of electricity (LCOE) below $60/MWh for various heat prices, showing economic competitiveness for energy market conditions similar to South Korea. Examined economic feasibility may vary significantly based on CHP heat prices, and extensive consideration of the regional heat market may be required for SMR-CHP regional optimization. Nonetheless, with reasonable heat market prices (e.g. district heating prices comparable to those in Europe and Korea), SMR can still become highly competitive in the energy market if coupled with a CHP system.

• 사물인터넷융복합논문지
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• 제9권1호
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• pp.41-47
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• 2023

오늘날, 세계 인구성장률의 증가로 국제사회는 심각하게 식량문제 해결을 논의하고 있다. 식량문제 해결을 위한 대안으로는 양식산업이 대두되고 있다. 최근 양식산업의 혁신성장을 위해 4차 산업기술을 융합한 스마트 양식장이 보급되고 있으며, 전주기적 디지털화가 추진되고 있다. 양식산업에서 중요한 수질센서는 전기화학방식의 휴대용 센서를 사용하고 있으며, 이를 이용하여 개별적, 간헐적으로 수질을 체크하고 있어서 양식장 수질을 실시간 분석하고 관리하기가 불가능하다. 최근 광학 기반의 모니터링이 가능한 수질센서들이 개발되어 현장에 적용되고 있다. 그러나 수질센서의 상태정보를 알 수 없기 때문에 모니터링 데이터의 신뢰성을 보장할 수 없는 상황이다. 따라서, 본 논문에서는 데이터의 신뢰성을 확보할 수 있도록, 수질센서가 수집하는 모니터링 데이터를 기반으로 고장, 기준일탈, 유지보수, 점검 등의 수질센서 자가진단 상태를 파악할 수 있는 알고리즘을 제안한다.