• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.708-711
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• 1997

This paper proposes the hybrid algorithm for the optimization of the structure and parameters of the fuzzy neural networks by genetic algorithms (GA) to improve the behaviour and the design of fuzzy neural networks. Fuzzy neural networks have a distinguishing feature in that they can possess the advantage of both neural networks and fuzzy systems. In this way, we can bring the low-level learning and computational power of neural networks into fuzzy systems and also high-level, human like IF-THEN rule thinking and reasoning of fuzzy systems into neural networks. As a result, there are many research works concerning the optimization of the structure and parameters of fuzzy neural networks. In this paper, we propose the hybrid algorithm that can optimize both the structure and parameters of fuzzy neural networks. Numerical example is provided to show the advantages of the proposed method.

• Smart Structures and Systems
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• 제15권2호
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• pp.259-281
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• 2015

In this study, a structural identification method is proposed to assess the integrity of gravity-type caisson structures by analyzing vibration features. To achieve the objective, the following approaches are implemented. Firstly, a simplified structural model with a few degrees-of-freedom (DOFs) is formulated to represent the gravity-type caisson structure that corresponds to the sensors' DOFs. Secondly, a structural identification algorithm based on the use of vibration characteristics of the limited DOFs is formulated to fine-tune stiffness and damping parameters of the structural model. Finally, experimental evaluation is performed on a lab-scaled gravity-type caisson structure in a 2-D wave flume. For three structural states including an undamaged reference, a water-level change case, and a foundation-damage case, their corresponding structural integrities are assessed by identifying structural parameters of the three states by fine-tuning frequency response functions, natural frequencies and damping factors.

• 콘크리트학회논문집
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• 제12권1호
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• pp.33-44
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• 2000

Since the mechanism of chloride diffusion and its ratio in concrete depend on structural conditions and concrete as a micro-structure, if these are analyzed quantitatively, the long-term ageing of structures can be predicted. Although, a quantitative analysis of concrete micro-structure, in which the results are affected by various parameters, is very difficult, this can be done indirectly by the durability test of concrete. In this study, the compressive strength, void ratio and air permeability of concrete. In this study, the compressive strength, void ratio and air permeability of concrete are chosen as the parameters in concrete durability test, and these effects on test results are analysed according to changes of mixing properties. The relationships between parameters and chloride diffusion velocity is used for prediction models of chloride diffusion. The developed prediction models for the chloride diffusion according to mixing and physical properties, can be used to estimate the service life and corrosion initiation of reinforcing bars in marine structures.

• Smart Structures and Systems
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• 제19권3호
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• pp.259-268
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• 2017

System identification of structures is one of the important aspects of structural health monitoring. The accuracy and efficiency of identification results is affected severely by measurement noises, especially when the structure system is large, such as bridge structures, and when online system identification is required. In this paper, the least square estimation (LSE) method is used combined with the substructure approach for identifying structural parameters of a cable-stay bridge with large degree of freedoms online. Numerical analysis is carried out by first dividing the bridge structure into smaller substructures and then estimates the parameters of each substructure online using LSE method. Simulation results demonstrate that the proposed approach is capable of identifying structural parameters, however, the accuracy and efficiency of identification results depend highly on the noise sensitivities of loading region, loading pattern as well as element size.

• Structural Engineering and Mechanics
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• 제53권6호
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• pp.1127-1141
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• 2015

The optimum design of liquid column dampers in seismic vibration control considering system parameter uncertainty is usually performed by minimizing the unconditional response of a structure without any consideration to the variation of damper performance due to uncertainty. However, the system so designed may be sensitive to the variations of input system parameters due to uncertainty. The present study is concerned with robust design optimization (RDO) of liquid column vibration absorber (LCVA) considering random system parameters characterizing the primary structure and ground motion model. The RDO is obtained by minimizing the weighted sum of the mean value of the root mean square displacement of the primary structure as well as its standard deviation. A numerical study elucidates the importance of the RDO procedure for design of LCVA system by comparing the RDO results with the results obtained by the conventional stochastic structural optimization procedure and the unconditional response based optimization.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1995년도 가을 학술발표회 논문집
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• pp.87-94
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• 1995

In highway bridges robust damage detection exercises are mandatory to secure the safety of the structures from hostile environmental conditions such as fatigue earthquake, wind, and corrosion. This paper presents a damage detection practice in a full-scale highway bridge by utilizing modal response parameters of as-built and damaged states of the structure. first the test structure is described and modal testing procedures are outlined. Next, a damage detection model which yields information on the location of damage directly from changes in mode shapes is outlined. Finally, the damage detection model is implemented to predict the location of damage in the ten structure. From the results, it was found that the damage detection model accurately locates damage in the test structures for which modal parameters of only a single mode are available for pre-damage (as-built) and post-damage stages.

• 소성∙가공
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• 제11권8호
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• pp.701-709
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• 2002

Aluminium foam material is highly porous material, which has the complicated cellular structure defined by randomly distributed pores in metallic matrix. This structure gives the characteristic properties which cannot be achieved by any other conventional processes. As the properties of aluminium foam material significantly depend on its porosity, a desired profile of properties can be tailored by changing the foam density. But various defects lead to undesirable effects on the mechanical properties. Mechanical properties are dependent on cell sizes and aspect ratios. Therefore, this paper presents the effects of various processing parameters of various parameters on the mechanical properties. For the sake of this, combined stirring was used to fabricate aluminum foam materials by the parameters. Compression and bending tests were performed to investigate the effects of cell sizes and aspect ratios on the mechanical properties.

• Journal of Information Processing Systems
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• 제18권1호
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• pp.12-25
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• 2022

In recent years, deep convolutional neural networks have made significant progress in the research of single image super-resolution. However, it is difficult to be applied in practical computing terminals or embedded devices due to a large number of parameters and computational effort. To balance these problems, we propose CSRNet, a lightweight neural network based on channel split residual learning structure, to reconstruct highresolution images from low-resolution images. Lightweight refers to designing a neural network with fewer parameters and a simplified structure for lower memory consumption and faster inference speed. At the same time, it is ensured that the performance of recovering high-resolution images is not degraded. In CSRNet, we reduce the parameters and computation by channel split residual learning. Simultaneously, we propose a double-upsampling network structure to improve the performance of the lightweight super-resolution network and make it easy to train. Finally, we propose a new evaluation metric for the lightweight approaches named 100_FPS. Experiments show that our proposed CSRNet not only speeds up the inference of the neural network and reduces memory consumption, but also performs well on single image super-resolution.

• Coupled systems mechanics
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• 제13권4호
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• pp.293-310
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• 2024

This paper investigates the dynamic response of structures during earthquakes and provides a clear understanding of soil-structure interaction phenomena. It analyses various parameters, comprising ground shear wave velocity and structure properties. The effect of soil impedance function form on the structural response of the system through the use of springs and dashpots with two frequency cases: independent and dependent frequencies. The superstructure and the ground were modeled linearly. Using the substructure method, two different approaches are used in this study. The first is an analytical formulation based on the dynamic equilibrium of the soil-structure system modeled by an analog model with three degrees of freedom. The second is a numerical analysis generated with 2D finite element modeling using ABAQUS software. The superstructure is represented as a SDOF system in all the SSI models assessed. This analysis establishes the key parameters affecting the soil-structure interaction and their effects. The different results obtained from the analysis are compared for each studied case (frequency-independent and frequency-dependent impedance functions). The achieved results confirm the sensitivity of buildings to soil-structure interaction and highlight the various factors and effects, such as soil and structure properties, specifically the shear wave velocity, the height and mass of the structure. Excitation frequency, and the foundation anchoring height, also has a significant impact on the fundamental parameters and the response of the coupled system at the same time. On the other hand, it have been demonstrated that the impedance function forms play a critical role in the accurate evaluation of structural behavior during seismic excitation. As a result, the evaluation of SSI effects on structural response must take into account the dynamic properties of the structure and soil accordingly.

• Earthquakes and Structures
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• 제5권2호
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• pp.225-237
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• 2013

Excessive vibrations induced by earthquake excitation and wind load are an obstacle in design and construction of tall and super tall buildings. An innovative vibration control structure system (Mega-Sub Controlled Structure System-MSCSS) was recently proposed to further improve humans comfort and their safeties during natural disasters. Preliminary investigations were performed using a two dimensional equivalent simplified model, composed by 3 mega-stories. In this paper, a more reasonable and realistic scaled model is design to investigate the dynamical characteristics and controlling performances of this structure when subjected to strong earthquake motion. The control parameters of the structure system, such as the modulated sub-structures disposition; the damping coefficient ratio (RC); the stiffness ratio (RD); the mass ratio of the mega-structure and sub-structure (RM) are investigated and their optimal values (matched values) are obtained. The MSCSS is also compared with the so-called Mega-Sub Structure (MSS) regarding their displacement and acceleration responses when subjected to the same load conditions. Through the nonlinear time history analysis, the effectiveness and the feasibility of the proposed mega-sub controlled structure system (MSCSS) is demonstrated in reducing the displacement and acceleration responses and also improving human comfort under earthquake loads.