• Nuclear Engineering and Technology
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• 제41권6호
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• pp.821-830
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• 2009

In this paper, modal testing and finite element modeling results to identify the modal parameters of a nuclear fuel rod as well as its cladding tube are discussed. A vertically standing full-size cladding tube and a fuel rod with lead pellets were used in the modal testing. As excessive flow-induced vibration causes a failure in fuel rods, such as fretting wear, the vibration level of fuel rods should be low enough to prevent failure of these components. Because vibration amplitude can be estimated based on the modal parameters, the dynamic characteristics must be determined during the design process. Therefore, finite element models are developed based on the test results. The effect of a lumped mass attached to a cladding tube model was identified during the finite element model optimization process. Unlike a cladding tube model, the density of a fuel rod with pellets cannot be determined in a straightforward manner because pellets do not move in the same phase with the cladding tube motion. The density of a fuel rod with lead pellets was determined by comparing natural frequency ratio between the cladding tube and the rod. Thus, an improved fuel rod finite element model was developed based on the updated cladding tube model and an estimated fuel rod density considering the lead pellets. It is shown that the entire pellet mass does not contribute to the fuel rod dynamics; rather, they are only partially responsible for the fuel rod dynamic behavior.

• Earthquakes and Structures
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• 제14권1호
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• pp.1-10
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• 2018

Seismic retrofitting of existing buildings and design of earth-quake resistant buildings are important issues associated with earthquake-prone zones. Use of metallic-yielding dampers as an energy dissipation system is an acceptable method for controlling damages in structures and improving their seismic performance. In this study, the optimal distribution of dampers for reducing the seismic response of steel frames with multi-degrees freedom is presented utilizing the uniform distribution of deformations. This has been done in a way that, the final configuration of dampers in the frames lead to minimum weight while satisfying the performance criteria. It is shown that such a structure has an optimum seismic performance, in which the maximum structure capacity is used. Then the genetic algorithm which is an evolutionary optimization method is used for optimal arrangement of the steel dampers in the structure. In continuation for specifying the optimal accurate response, the local search algorithm based on the gradient concept has been selected. In this research the introduced optimization methods are used for optimal retrofitting in the moment-resisting frame with inelastic behavior and initial weakness in design. Ultimately the optimal configuration of dampers over the height of building specified and by comparing the results of the uniform deformation method with those of the genetic algorithm, the validity of the uniform deformation method in terms of accuracy, Time Speed Optimization and the simplicity of the theory have been proven.

• 한국항공우주학회지
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• 제30권4호
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• pp.106-113
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• 2002

인공위성에서 위성 구조체의 임무는 위성체의 모든 부품을 제반 환경조건 하에서 안전하게 지지하는 것이다. 위성 구조체의 안전성은 위성체 및 발사체 모델의 결합 및 하중함수로 표현되는 발사하중을 부가한 연성하중해석을 통해 최종적으로 검증된다. 본 연구에서는 구조체 무게의 감소를 위해, 발사하중상태 하에의 위성구조에 대해 직접 최적화알고리듬을 적용하였다. 위성 구조부재의 손상여부의 판단을 위한 가속도 반응은 연성하중해석의 결과를 바탕으로 얻었다. 최적화 결과, 구조부재 중량은 약 12%의 감소를 보였으며, 하니콤 심재의 두께가 성능에 크게 기여함을 알 수 있었다.

• Natural Product Sciences
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• 제23권2호
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• pp.75-83
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• 2017

The optimization and microwave assisted extraction of stem bark of Terminalia arjuna, quantitative estimation of the marker compounds arjunic acid and arjunolic acid using HPTLC and the evaluation of free radical scavenging activity has been performed in this study. The central composite design was used for optimization and the values of parameters for optimized batch of microwave assisted extraction were 1000 W (Power), 3 minutes (Time) and 1/120 (Solid/solvent ratio). The solvent system to carry out the HPTLC was toluene: acetic acid: ethyl acetate (5: 5: 0.5) and quantitative estimation was done using standard equations obtained from the marker compounds. The in-vitro free radical scavenging activity was performed spectrophotometrically using ascorbic acid as standard. The value of estimated percentage yield of arjunic acid and arjunolic acid was 1.42% and 1.52% which upon experimentation was obtained as 1.38% and 1.51% respectively. The DPPH assay of the different batches of microwave assisted extraction and marker compounds taken suggested that the marker compounds arjunic acid and the arjunolic acid were responsible for the free radical scavenging activity as the batch having the maximum percentage yield of the marker compounds showed best free radical scavenging effect as compared to standard ascorbic acid. The $IC_{50}$ value of the optimized batch was found to be 24.72 while that of the standard ascorbic acid was 29.83. Hence, the yield of arjunic acid and arjunolic acid has direct correlation with the free radical scavenging activity of stem bark extract of Terminalia arjuna and have potential to serve as active lead compounds for free radical scavenging activity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권7호
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• pp.2389-2413
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• 2015

High data rates in long-term evolution (LTE) networks can affect the mobility of networks and their performance. The speed and motion of user equipment (UE) can compromise seamless connectivity. However, a proper handover (HO) decision can maintain quality of service (QoS) and increase system throughput. While this may lead to an increase in complexity and operational costs, self-optimization can enhance network performance by improving resource utilization and user experience and by reducing operational and capital expenditure. In this study, we propose the self-optimization of HO parameters based on fuzzy logic control (FLC) and multiple preparation (MP), which we name FuzAMP. Fuzzy logic control can be used to control self-optimized HO parameters, such as the HO margin and time-to-trigger (TTT) based on multiple criteria, viz HO ping pong (HOPP), HO failure (HOF) and UE speeds. A MP approach is adopted to overcome the hard HO (HHO) drawbacks, such as the large delay and unreliable procedures caused by the break-before-make process. The results of this study show that the proposed method significantly reduces HOF, HOPP, and packet loss ratio (PLR) at various UE speeds compared to the HHO and the enhanced weighted performance HO parameter optimization (EWPHPO) algorithms.

• 한국전산구조공학회논문집
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• 제29권6호
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• pp.491-498
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• 2016

리벳이나 볼트가 결합되는 구멍은 항공기, 선박 및 기타 구조물에 사용되는 판재의 응력 집중을 유발한다. 과도한 응력 집중 현상이 지속되면 종래에는 파단이 일어날 수 있으므로 설계 단계에서 응력 집중 현상의 명확한 해석이 중요하다. 이 논문에서는 판재위에 리벳을 배치하는 간단한 최적화 방법이 제시되었다. 첫째로 응력 집중 현상 해석에서 FEM 구조 해석이 얼마나 정확한지 검증하였다. 평판 위에 존재하는 단일 구멍의 반경을 바꿔가며 응력 집중 계수의 변화를 분석하였다. 같은 방법으로 일렬로 존재하는 구멍들 사이에서의 응력 집중 계수를 수치 해석하였다. 각각의 응력 집중 계수를 이론값과 비교하여 정확도를 확인하였다. 마지막으로 두 응력 집중 현상을 독립적으로 적용하는 최적화 방법을 확인 및 검증하였다. 이 결과들은 이론적인 예측과 밀접한 경향성을 보여 앞으로의 리벳 배치 최적화에도 활용될 수 있을 것으로 예상된다.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권8호
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• pp.561-570
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• 2004

In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권6호
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• pp.415-424
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• 2004

In this paper, we introduce and investigate a new category of rule-based fuzzy inference system based on Information Granulation(IG). The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of “If..., then...” statements, and exploits the theory of system optimization and fuzzy implication rules. The form of the fuzzy rules comes with three types of fuzzy inferences: a simplified one that involves conclusions that are fixed numeric values, a linear one where the conclusion part is viewed as a linear function of inputs, and a regression polynomial one as the extended type of the linear one. By the nature of the rule-based fuzzy systems, these fuzzy models are geared toward capturing relationships between information granules. The form of the information granules themselves becomes an important design features of the fuzzy model. Information granulation with the aid of HCM(Hard C-Means) clustering algorithm hell)s determine the initial parameters of rule-based fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial function being used in the Premise and consequence Part of the fuzzy rules. And then the initial Parameters are tuned (adjusted) effectively with the aid of the improved complex method(ICM) and the standard least square method(LSM). In the sequel, the ICM and LSM lead to fine-tuning of the parameters of premise membership functions and consequent polynomial functions in the rules of fuzzy model. An aggregate objective function with a weighting factor is proposed in order to achieve a balance between performance of the fuzzy model. Numerical examples are included to evaluate the performance of the proposed model. They are also contrasted with the performance of the fuzzy models existing in the literature.

• 한국음향학회지
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• 제41권6호
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• pp.680-690
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• 2022

일반적으로 배관에서 발생하는 진동은 배관을 파손시키는 문제를 넘어 배관 파손으로 유발되는 다른 위험한 문제의 원인이 된다. 배관 진동의 원인 분석과 이를 줄이기 위한 수많은 연구들이 존재하는데, 그 중 마찰 지지대를 이용한 배관 진동저감에 대한 연구가 소수 진행되고 있다. 하지만 마찰 지지대에 관한 연구들은 마찰 지지대 성능 예측과 평가에만 집중하였고, 지지대 설치 위치에 따라 달라지는 마찰 지지대의 효과는 고려하지 않았다. 따라서, 본 연구에서는 마찰 지지대의 설치 위치에 따른 배관 진동 저감 효과를 입증하고 전체 시스템의 진동을 줄이기 위한 마찰 지지대 위치 선정 방법을 제시한다. 설계단계에서 최적화 방법을 효과적으로 적용하기 위해 선형 해석으로만 마찰 지지대의 최적 위치를 예측하고, 설계된 마찰 지지대를 시간 영역 해석을 통해 방법론의 타당성을 입증하였다. 또한, 배관 시스템에서 마찰 지지대의 우수한 진동 저감 효과를 정량적으로 해석하여, 지지대 설치 위치를 예측하는 방법의 효용성을 증명하였다.

• 대한의용생체공학회:의공학회지
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• 제45권4호
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• pp.139-147
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• 2024

This study enhances AI algorithms for extracting spinal regions from Whole Spine X-rays, aiming for higher accuracy while minimizing learning and detection times. Whole Spine X-rays, critical for diagnosing conditions such as scoliosis and kyphosis, necessitate precise differentiation of spinal contours. The conventional manual methodology encounters challenge due to the overlap of anatomical structures, prompting the integration of AI to overcome these limitations and enhance diagnostic precision. In this study, 1204 AP and 500 LAT Whole Spine X-ray images were meticulously labeled, spanning the third cervical to the fifth lumbar vertebrae. We based our efforts on the HR-Net algorithm, which exhibited the highest accuracy, and proceeded to simplify its network architecture and enhance the block structure for optimization. The optimized HR-Net algorithm demonstrates an improvement, increasing accuracy by 2.98% for the AP dataset and 1.59% for the LAT dataset compared to its original formulation. Additionally, the modification resulted in a substantial reduction in learning time by 70.06% for AP images and 68.43% for LAT images, along with a decrease in detection time by 47.18% for AP and 43.07% for LAT images. The time taken per image for detection was also reduced by 47.09% for AP and 43.07% for LAT images. We suggest that the application of the proposed HR-Net in this study can lead to more accurate and efficient extraction of spinal regions in Whole Spine X-ray images. This can become a crucial tool for medical professionals in the diagnosis and treatment of spinal-related conditions, and it will serve as a foundation for future research aimed at further improving the accuracy and speed of spinal region segmentation.