• Smart Structures and Systems
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• 제14권3호
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• pp.285-305
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• 2014

This study employs a novel beam-type wavelet finite element model (WFEM) to fulfill an adaptive-scale damage detection strategy in which structural modeling scales are not only spatially varying but also dynamically changed according to actual needs. Dynamical equations of beam structures are derived in the context of WFEM by using the second-generation cubic Hermite multiwavelets as interpolation functions. Based on the concept of modal strain energy, damage in beam structures can be detected in a progressive manner: the suspected region is first identified using a low-scale structural model and the more accurate location and severity of the damage can be estimated using a multi-scale model with local refinement in the suspected region. Although this strategy can be implemented using traditional finite element methods, the multi-scale and localization properties of the WFEM considerably facilitate the adaptive change of modeling scales in a multi-stage process. The numerical examples in this study clearly demonstrate that the proposed damage detection strategy can progressively and efficiently locate and quantify damage with minimal computation effort and a limited number of sensors.

• Structural Engineering and Mechanics
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• 제41권4호
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• pp.559-573
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• 2012

An adaptive modeling and simulation technique is introduced for the effective and reliable fluid-structure interaction analysis using MSC/Dytran for large-scale complex pressurized liquid containment. The proposed method is composed of a series of the global rigid sloshing analysis and the locally detailed fluid-structure analysis. The critical time at which the system exhibits the severe liquid sloshing response is sought through the former analysis, while the fluid-structure interaction in the local region of interest at the critical time is analyzed by the latter analysis. Differing from the global coarse model, the local fine model considers not only the complex geometry and flexibility of structure but the effect of internal pressure. The locally detailed FSI problem is solved in terms of multi-material volume fractions and the flow and pressure fields obtained by the global analysis at the critical time are specified as the initial conditions. An in-house program for mapping the global analysis results onto the fine-scale local FSI model is developed. The validity and effectiveness of the proposed method are verified through an illustrative numerical experiment.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 춘계학술발표대회
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• pp.562-565
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• 2018

A wide range of IoT applications use information collected from networks of sensors for monitoring and controlling purposes. However, the frequent appearance of fault data makes it difficult to extract correct information, thereby sending incorrect commands to actuators that can threaten human privacy and safety. For this reason, it is necessary to have a mechanism to detect fault data collected from sensors. In this paper, we present a trend-adaptive multi-scale principal component analysis (Trend-adaptive MS-PCA) model for data fault detection. The proposed model inherits advantages of Discrete Wavelet Transform (DWT) in capturing time-frequency information and advantages of PCA in extracting correlation among sensors' data. Experimental results on a real dataset show the high effectiveness of the proposed model in data fault detection.

• Structural Engineering and Mechanics
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• 제54권2호
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• pp.239-256
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• 2015

An adaptive-scale damage detection strategy based on a wavelet finite element model (WFEM) for thin plate structures is established in this study. Equations of motion and corresponding lifting schemes for thin plate structures are derived with the tensor products of cubic Hermite multi-wavelets as the elemental interpolation functions. Sub-element damages are localized by using of the change ratio of modal strain energy. Subsequently, such damages are adaptively quantified by a damage quantification equation deduced from differential equations of plate structure motion. WFEM scales vary spatially and change dynamically according to actual needs. Numerical examples clearly demonstrate that the proposed strategy can progressively locate and quantify plate damages. The strategy can operate efficiently in terms of the degrees-of-freedom in WFEM and sensors in the vibration test.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• 제10권S_1호
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• pp.23-28
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• 2001

A new numerical weather prediction and dispersion model, the Operational Multi-scale Environment model with Grid Adaptivity(OMEGA) including an embedded Atmospheric Dispersion Model(ADM), is introduced as a next generation atmospheric simulation system for real-time hazard predictions, such as severe weather or the transport of hazardous release. OMEGA is based on an unstructured grid that can facilitate a continuously varying horizontal grid resolution ranging from 100 km down to 1 km and a vertical resolution from 20 -30 meters in the boundary layer to 1 km in the free atmosphere. OMEGA is also naturally scale spanning and time. In particular, the unstructured grid cells in the horizontal dimension can increase the local resolution to better capture the topography or important physical features of the atmospheric circulation and cloud dynamics. This means the OMEGA can readily adapt its grid to a stationary surface, terrain features, or dynamic features in an evolving weather pattern. While adaptive numerical techniques have yet to be extensively applied in atmospheric models, the OMEGA model is the first to exploit the adaptive nature of an unstructured gridding technique for atmospheric simulation and real-time hazard prediction. The purpose of this paper is to provide a detailed description of the OMEGA model, the OMEGA system, and a detailed comparison of OMEGA forecast results with observed data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2787-2800
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• 2022

The aging society increases emergency situations of the elderly living alone and a variety of social crimes. In order to prevent them, techniques to detect emergency situations through voice are actively researched. This study proposes CutPaste-based anomaly detection model using multi-scale feature extraction in time series streaming data. In the proposed method, an audio file is converted into a spectrogram. In this way, it is possible to use an algorithm for image data, such as CNN. After that, mutli-scale feature extraction is applied. Three images drawn from Adaptive Pooling layer that has different-sized kernels are merged. In consideration of various types of anomaly, including point anomaly, contextual anomaly, and collective anomaly, the limitations of a conventional anomaly model are improved. Finally, CutPaste-based anomaly detection is conducted. Since the model is trained through self-supervised learning, it is possible to detect a diversity of emergency situations as anomaly without labeling. Therefore, the proposed model overcomes the limitations of a conventional model that classifies only labelled emergency situations. Also, the proposed model is evaluated to have better performance than a conventional anomaly detection model.

• Smart Structures and Systems
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• 제13권4호
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• pp.501-515
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• 2014

This paper presents a linear computational homogenization framework to evaluate the effective (or generalized) electromechanical coupling coefficient (EMCC) of adaptive structures with piezoelectric structural fiber (PSF) composite elements. The PSF consists of a silicon carbide (SiC) or carbon core fiber as reinforcement to a fragile piezo-ceramic shell. For the micro-scale analysis, a micromechanics model based on the variational asymptotic method for unit cell homogenization (VAMUCH) is used to evaluate the overall electromechanical properties of the PSF composites. At the macro-scale, a finite element (FE) analysis with the commercial FE code ABAQUS is performed to evaluate the effective EMCC for structures with the PSF composite patches. The EMCC is postprocessed from free-vibrations analysis under short-circuit (SC) and open-circuit (OC) electrodes of the patches. This linear two-scale computational framework may be useful for the optimal design of active structure multi-functional composites which can be used for multi-functional applications such as structural health monitoring, power harvest, vibration sensing and control, damping, and shape control through anisotropic actuation.

• Current Optics and Photonics
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• 제8권3호
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• pp.215-224
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• 2024

In medium- and long-range optical imaging systems, atmospheric turbulence causes blurring and distortion of images, resulting in loss of image information. An image-restoration method based on an adaptive feature-fusion multi-input-multi-output (MIMO) dense U-shaped network (Unet) is proposed, to restore a single image degraded by atmospheric turbulence. The network's model is based on the MIMO-Unet framework and incorporates patch-embedding shallow-convolution modules. These modules help in extracting shallow features of images and facilitate the processing of the multi-input dense encoding modules that follow. The combination of these modules improves the model's ability to analyze and extract features effectively. An asymmetric feature-fusion module is utilized to combine encoded features at varying scales, facilitating the feature reconstruction of the subsequent multi-output decoding modules for restoration of turbulence-degraded images. Based on experimental results, the adaptive feature-fusion MIMO dense U-shaped network outperforms traditional restoration methods, CMFNet network models, and standard MIMO-Unet network models, in terms of image-quality restoration. It effectively minimizes geometric deformation and blurring of images.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1999년도 가을 학술발표회 논문집
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• pp.351-358
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• 1999

The structural responses of underground structures are examined in probability by using the elasto-plastic stochastic finite element method in which the spatial distributions of material properties are assumed to be stochastic fields. In addition, the adaptive importance sampling method using the response surface technique is used to improve simulation efficiency. The method is found to provide appropriate information although the nonlinear Limit State involves a large number of basic random variables and the failure probability is small. The probability of plastic local failures around an excavated area is effectively evaluated and the reliability for the limit displacement of the ground is investigated. It is demonstrated that the adaptive importance sampling method can be very efficiently used to evaluate the reliability of a large scale stochastic finite element model, such as the underground structures located in the multi-layered ground.

• Smart Structures and Systems
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• 제23권6호
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• pp.553-564
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• 2019

Modeling of magnetorheological (MR) dampers for cable vibration control to facilitate the design of even more effective and economical systems is still a challenging task. In this study, a parameter-adaptive three-element model is first established for a full-scale MR damper based on laboratory tests. The parameters of the model are represented by a set of empirical formulae in terms of displacement amplitude, voltage input, and excitation frequency. The model is then incorporated into the governing equation of cable-damper system for investigation of open-loop vibration control of stay cables in a cable-stayed bridge. The concept of optimal voltage/current input achieving the maximum damping for the system is put forward and verified. Multi-mode suboptimal and Single-mode optimal open-loop control method is then developed. Important conclusions are drawn on application issues and unique characteristics of open-loop cable vibration control using MR dampers.