• Structural Engineering and Mechanics
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• 제23권5호
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• pp.455-468
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• 2006

Smart structural systems are defined as ones that demonstrate the ability to modify their characteristics and/or properties in order to respond favorably to unexpected severe loading conditions. The performance of such a task requires a set of additional components to be integrated within such systems. These components belong to three major categories, sensors, processors and actuators. It is wellknown that all structural systems entail some level of uncertainty, because of their extremely complex nature, lack of complete information, simplifications and modeling. Similarly, sensors, processors and actuators are expected to reflect a similar uncertain behavior. As it is imperative to be able to evaluate the impact of such components on the behavior of the system, it is as important to ensure, or at least evaluate, the reliability of such components. In this paper, a system model for reliability assessment of smart structural systems is outlined. The presented model is considered a necessary first step in the development of a reliability assessment algorithm for smart structural systems. The system model outlines the basic components of the system, in addition to, performance functions and inter-relations among individual components. A fault tree model is developed in order to aggregate the individual underlying component reliabilities into an overall system reliability measure. Identification of appropriate limit states for all underlying components are beyond the scope of this paper. However, it is the objective of this paper to set up the necessary framework for identifying such limit states. A sample model for a three-story single bay smart rigid frame, is developed in order to demonstrate the proposed framework.

• Structural Engineering and Mechanics
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• 제56권5호
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• pp.787-796
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• 2015

When the temperature of a structure varies, there is a tendency to produce changes in the shape of the structure. The resulting actions may be of considerable importance in the analysis of the structures having non-prismatic members. The computation of design forces for the non-prismatic beams having symmetrical parabolic haunches (NBSPH) is fairly difficult because of the parabolic change of the cross section. Due to their non-prismatic geometrical configuration, their assessment, particularly the computation of fixed-end horizontal forces and fixed-end moments becomes a complex problem. In this study, the efficiency of the Artificial Neural Networks (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS) in predicting the design forces and the design moments of the NBSPH due to temperature changes was investigated. Previously obtained finite element analyses results in the literature were used to train and test the ANN and ANFIS models. The performances of the different models were evaluated by comparing the corresponding values of mean squared errors (MSE) and decisive coefficients ($R^2$). In addition to this, the comparison of ANN and ANFIS with traditional methods was made by setting up Linear-regression (LR) model.

• 해양환경안전학회지
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• 제27권2호
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• pp.228-237
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• 2021

최근 부산시는 선박관리산업의 관심을 증대시키고, 경쟁력을 강화 및 지원하기 위한 조례를 제정하였다. 본 연구는 직관적퍼지 DEMATEL&ISM법을 이용하여 선박관리산업 경쟁력 강화의 원인요인을 도출하는데 있다. 이를 위해 먼저 선박관리산업발전법에 명시된 내용을 기반으로 8개의 요인을 추출한다. 두번째는 직관적 퍼지수를 표준퍼지수를 이용하여 크리습 수로 변환한다. 세번째는 DEMATEL법을 이용하여 영향관계를 분석하고 ISM법을 이용하여 요인에 대해 우선순위를 결정한다. 영향관계 분석결과 원인요인은 기술적 선박관리 역량 제고, 육상관리인력 전문성 제고, 한국선원인력 자질향상으로 나타났다. ISM법에 의한 우선순위는 한국선원 자질향상, 육상관리인력 전문성 제고, 기술적 선박관리 역량제고, 상업적 선박관리 역량 제고, 종합정보시스템구축 = 선원 근로조건 및 고용환경 개선 = 금융 등 지원 = 외국인 선원 공급 강화 등의 순으로 나타났다. 따라서 전체 영역에서 원인요인이며 우선순위가 높은 상위 3개의 요인에 대해 우선적인 정책추진이 필요하다.

• Smart Structures and Systems
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• 제20권1호
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• pp.61-74
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• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.

• 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.

• 한국지진공학회논문집
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• 제3권3호
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• pp.63-74
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• 1999

대형구조물의 진동감소를 위한 슬라이딩 모드 퍼지 제어기(Sliding Mode Fuzzy Control SMFC)에 대하여 연구하였다 본 제어기에 사용된 퍼지 추론기의 규칙은 비선형 제어기법의 하나인 슬라이딩 모드 제어기를 기반으로 하여 구성되었다 그결과 제어기의 퍼지성은 제어시스템을 시스템 계수의 불확실성과 구조물에 작용되는 외부하중의 불확실성에 대하여 강인한 성질은 갖게 하였으며 제어 규칙의 비선형성으로 인하여 제어기는 선형제어기에 비하여 보다 효율적인 되었다 복잡한 수학 해석에 기반한 종래의 제어기법에 비하여 퍼지 이론에 기반한 본 제어기법은 제어기의 설계절차가 매우 편리하다는 장점을 갖게 된다. 제안된 제어기법의 검증을 위하여 미국 토목학회 산하 구조제어위원회(ASCE Committee on Structural Control)에서 주도한 벤치마크 문제에 대하여 적용시켜 보았다 본 연구의 제어결과를 다른 연구자들에 의하여 발표된 {{{{ ETA _mixed _2$\infty$ }}, optimal polynomial control neural networks control 슬라이딩 모드 제어의 벤치마크 결과와 비교하였으며 그 결과 제안된 제어기법이 구조물의 진동을 매우 효율적으로 감소시키며 제어기의 설계절차가 쉽고 편리함을 확일 할 수 있었다.

• Structural Engineering and Mechanics
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• 제47권3호
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• pp.401-419
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• 2013

In this study, the efficiency of adaptive neuro-fuzzy inference system (ANFIS) and genetic expression programming (GEP) in predicting the effects of infill walls on base reactions and roof drift of reinforced concrete frames were investigated. Current standards generally consider weight and fundamental period of structures in predicting base reactions and roof drift of structures by neglecting numbers of floors, bays, shear walls and infilled bays. Number of stories, number of bays in x and y directions, ratio of shear wall areas to the floor area, ratio of bays with infilled walls to total number bays and existence of open story were selected as parameters in GEP and ANFIS modeling. GEP and ANFIS have been widely used as alternative approaches to model complex systems. The effects of these parameters on base reactions and roof drift of RC frames were studied using 3D finite element method on 216 building models. Results obtained from 3D FEM models were used to in training and testing ANFIS and GEP models. In ANFIS and GEP models, number of floors, number of bays, ratio of shear walls and ratio of infilled bays were selected as input parameters, and base reactions and roof drifts were selected as output parameters. Results showed that the ANFIS and GEP models are capable of accurately predicting the base reactions and roof drifts of RC frames used in the training and testing phase of the study. The GEP model results better prediction compared to ANFIS model.

• 한국항해항만학회지
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• 제27권2호
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• pp.137-143
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• 2003

지금까지 IMO를 비롯한 해운산업분야에서는 해상의 인명 재산, 해양환경보호에 항상 큰 관심을 가지고 해양사고예방을 위한 많은 노력들이 견주되어 왔다. 하지만 이러한 노력에도 불구하고 크고 작은 해양사고가 지속적으로 발생하고 있는 것이 오늘날의 현실이다. 한편, 선박충돌사고는 수많은 원인이 서로 복잡하게 상호작용을 하고 있어서 사고예방대책마련에 어려움이 많다 따라서, 선박충돌사고의 정량적인 분석을 위해서는 이들 상호작용요소간의 관계를 시스템적으로 파악하고 분석하는 것이 선행되어야 한다. 본 연구에서는 먼저, 지난 10년(1991-2000)간 국내에서 발생한 선박충돌사고에 대한 위험성을 분석하였고, 또한 사고발생에 가장 큰 영향을 미치는 위해요소(Hazard)인 인적요소(Human Factor)에 대해서 전문가집단의 의견을 수렴하여 FSM기법을 이용하여 인적 위해요소를 계층화한 후 각 요소 상호간의 관련성을 분석하였다. 그 결과로써 인적요소에 의한 선박충돌사고의 발생과정과 각 계층에 속한 요소가 사고에 미치는 영향력을 규명하고, 각 요소간 상호관계를 파악하여 사고예방대책마련을 위한 우선순위를 결정할 수 있는 선박충돌사고의 인적요소 구조그래프를 제시하였다.

• 제어로봇시스템학회논문지
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• 제16권11호
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• pp.1074-1081
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• 2010

Today, the research related to the robot is achieved in various part. With the high interest in means of transport, various researches about autonomous mobile robot and next generation transport is continuing. The unicycle robot among these needs much control technique like balance control model and driving model. For autonomous driving of this unicycle robot, from the basic balance control to direction switching control and velocity control are needed. But the environment elements like a gradient and frictional force or unbalanced elements from the structural feature. The unicycle needs the real time balance control so more complex, harder to control. And when functional addition is made, the problem that fall entire reaction velocity or accuracy would be happen. This paper introduces entire dynamics modeling of the unicycle robot and reduced model. And propose the new balance control algorithm using fuzzy controller. Also the evaluation about performance would be made through the test.

• 대한조선학회논문집
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• 제41권3호
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• pp.41-48
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• 2004

Ship is being operated under a highly dynamic environments and many factors are related with ship's collision and those factors are interacting. So, the analysis on ship's collision causes are very important to prepare countermeasures which will ensure the safe navigation. This study analysed the ship's collision data over the past 10 years(1991-2000), which is compiled by Korea Marine Accidents Inquiry Agency. The analysis confirmed that ‘ship's collision' is occurred most frequently and the cause is closely related with human factor. The main purpose of this study is to propose risk control measures of ship's collision. For this, the structure of human factor is analysed by the questionnaire methodology. Marine experts were surveyed based on major elements that were extracted from the human factor affecting to ship's collision. FSM has been widely adopted in modeling a dynamic system which is composed of human factors. Then, the structure analysis on the causes of ship's collision are performed using FSM. This structure model could be used in understanding and verifying the procedure of real ship's collision. Furthermore it could be used as the model to prevent ship's collision and reduce marine accidents.