• 한국전산구조공학회논문집
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• 제23권6호
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• pp.579-592
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• 2010

This paper presents a multi-phase model update approach for system identification of prestressed concrete (PSC) girders under various prestress forces. First, a multi-phase model update approach designed on the basis of eigenvalue sensitivity concept is newly proposed. Next, the proposed multi-phase approach is evaluated from controlled experiments on a lab-scale PSC girder for which forced vibration tests are performed for a series of prestress forces. On the PSC girder, a few natural frequencies and mode shapes are experimentally measured for the various prestress forces. The corresponding modal parameters are numerically calculated from a three-dimensional finite element (FE) model which is established for the target PSC girder. Eigenvalue sensitivities are analyzed for potential model-updating parameters of the FE model. Then, structural subsystems are identified phase-by-phase using the proposed model update procedure. Based on model update results, the relationship between prestress forces and model-updating parameters is analyzed to evaluate the influence of prestress forces on structural subsystems.

• Structural Engineering and Mechanics
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• 제43권3호
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• pp.371-394
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• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• 대한전자공학회논문지SP
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• 제42권4호
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• pp.39-48
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• 2005

본 논문에서는 Bayesian 추정법과 신경회로망을 이용한 새로운 결 분할 방법을 제안한다 신경회로망의 입력으로는 다중스케일을 가지는 웨이블릿 계수와 인접한 이웃 웨이블릿 계수들의 문맥정보를 사용하고, 신경회로망의 출력을 사후 확률로 모델링한다. 문맥정보는 HMT(Hidden Markov Tree) 모델을 이용하여 구한다. 제안 방법은 HMT를 이용한 ML(Maximum Likelihood) 분할 보다 더 우수한 결과를 보여준다. 또한 HMT를 이용한 결 분할 방법과 제안 방법을 이용한 결 분할 각각에 HMTseg라고 불리는 다중 스케일 Bayesian 영상 분할 기술을 이용하여 후처리를 행한 결 분할 또한 제안 방법이 우수함을 보여준다.

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1494-1503
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• 2018

This paper proposes a novel probabilistic load flow model for power systems integrated with large-scale wind power, which considers the multi-time scale dispatching features. The ramp limitations of the units and the steady-state security constraints of the network have been comprehensively considered for the entire duration of the study period; thus, the coupling of the system operation states at different time sections has been taken into account. For each time section, the automatic generation control (AGC) strategy is considered, and all variations associated with the wind power and loads are compensated by all AGC units. Cumulants and the Gram-Charlier expansion are used to solve the proposed model. The effectiveness of the proposed method is validated using the modified IEEE RTS 24-bus system and the modified IEEE 118-bus system.

• Nuclear Engineering and Technology
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• 제56권3호
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• pp.980-992
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• 2024

Steam line break accident (SLB) in the nuclear reactor is one of the representative Non-LOCA accidents in which thermal-hydraulics and neutron kinetics are strongly coupled each other. Thus, the multi-scale and multi-physics approach is applied in this study in order to examine a realistic safety margin. An entire reactor coolant system is modelled by system scale node, whereas sub-channel scale resolution is applied for the region of interest such as the reactor core. Fuel performance code is extended to consider full core pin-wise fuel behaviour. The MARU platform is developed for easy integration of the codes to be coupled. An initial stage of the steam line break accident is simulated on the MARU platform. As cold coolant is injected from the cold leg into the reactor pressure vessel, the power increases due to the moderator feedback. Three-dimensional coolant and fuel behaviour are qualitatively visualized for easy comprehension. Moreover, quantitative investigation is added by focusing on the enhancement of safety margin by means of comparing the minimum departure from nucleate boiling ratio (MDNBR). Three factors contributing to the increase of the MDNBR are proposed: Various geometric parameters, realistic power distribution by neutron kinetics code, Radial coolant mixing including sub-channel physics model.

• 문화기술의 융합
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• 제6권4호
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• pp.767-776
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• 2020

GcGAN은 기하학적 일관성을 유지하며 영상 간 스타일을 변환하는 딥러닝 모델이다. 그러나 GcGAN은 회전이나 반전(flip) 등의 한정적인 기하 변환으로 영상의 형태를 보존하기 때문에 영상의 세밀한 형태 정보를 제대로 유지하지 못하는 단점을 가지고 있다. 그래서 본 연구에서는 이런 단점을 개선한 새로운 영상 간 변환 기법인 MSGcGAN(Multi-Scale GcGAN)을 제안한다. MSGcGAN은 GcGAN을 확장한 모델로서, 다중 스케일의 영상을 동시에 학습하여 스케일 불변 특징을 추출함으로써, 영상의 의미적 왜곡을 줄이고 세밀한 정보를 유지하는 방향으로 영상 간 스타일 변환을 수행한다. 실험 결과에 의하면 MSGcGAN은 GcGAN보다 정량적 정성적 측면에서 모두 우수하였고, 영상의 전체적인 형태 정보를 잘 유지하면서 스타일을 자연스럽게 변환함을 확인할 수 있었다.

• Journal of Multimedia Information System
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• 제8권2호
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• pp.101-110
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• 2021

In computer vision, single-image super resolution has been an area of research for a significant period. Traditional techniques involve interpolation-based methods such as Nearest-neighbor, Bilinear, and Bicubic for image restoration. Although implementations of convolutional neural networks have provided outstanding results in recent years, efficiency and single model multi-scalability have been its challenges. Furthermore, previous works haven't placed enough emphasis on real-number scalability. Interpolation-based techniques, however, have no limit in terms of scalability as they are able to upscale images to any desired size. In this paper, we propose a convolutional neural network possessing the advantages of the interpolation-based techniques, which is also efficient, deeming it suitable in practical implementations. It consists of convolutional layers applied on the low-resolution space, post-up-sampling along the end hidden layers, and additional layers on high-resolution space. Up-sampling is applied on a multiple channeled feature map via bicubic interpolation using a single model. Experiments on architectural structure, layer reduction, and real-number scale training are executed with results proving efficient amongst multi-scale learning (including scale multi-path-learning) based models.

• Coupled systems mechanics
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• 제8권2호
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• pp.99-109
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• 2019

This work investigates the accuracy and performance of a $FE^2$ multi-scale implementation used to predict the behavior of composite materials. The equations are formulated assuming the small deformations solid mechanics approach in non-linear material models with hardening plasticity. The uniform strain boundary conditions are applied for the macro-to-micro transitions. A parallel algorithm was implemented in order to solve large engineering problems. The scheme proposed takes advantage of the domain decomposition method at the macro-scale and the coupling between each subdomain with a micro-scale model. The precision of the method is validated with a composite material problem and scalability tests are performed for showing the efficiency.

• Computers and Concrete
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• 제15권5호
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• pp.735-758
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• 2015

This work deals with unilateral effect of quasi-brittle materials, such as concrete. For this propose, a two-dimensional meso-scale model is presented. The material is considered as a three-phase material consisting of interface zone, matrix and inclusions - each constituent modeled by an appropriate constitutive model. The Representative Volume Element (RVE) consists of inclusions idealized as circular shapes randomly placed into the specimen. The interface zone is modeled by means of cohesive contact finite elements developed here in order to capture the effects of phase debonding and interface crack closure/opening. As an initial approximation, the inclusion is modeled as linear elastic as well as the matrix. Our main goal here is to show a computational homogenization-based approach as an alternative to complex macroscopic constitutive models for the mechanical behavior of the quasi-brittle materials using a finite element procedure within a purely kinematical multi-scale framework. A set of numerical examples, involving the microcracking processes, is provided. It illustrates the performance of the proposed model. In summary, the proposed homogenization-based model is found to be a suitable tool for the identification of macroscopic mechanical behavior of quasi-brittle materials dealing with unilateral effect.

• Structural Engineering and Mechanics
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• 제30권5호
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• pp.619-645
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• 2008

This study presents the efficiency of simulating structural systems using a method that combines a simplified component model (SCM) and rigorous component model (RCM). To achieve a realistic simulation of structural systems, a numerical model must be adequately capturing the detailed behaviors of real systems at various scales. However, capturing all details represented within an entire structural system by very fine meshes is practically impossible due to technological limitations on computational engineering. Therefore, this research develops an approach to simulate large-scale structural systems that combines a simplified global model with multiple detailed component models adjusted to various scales. Each correlated multi-scale simulation model is linked to others using a multi-level hierarchical modeling simulation method. Simulations are performed using nonlinear finite element analysis. The proposed method is applied in an analysis of a simple reinforced concrete structure and the Reuipu Elementary School (an existing structure), with analysis results then compared to actual onsite observations. The proposed method obtained results very close to onsite observations, indicating the efficiency of the proposed model in simulating structural system behavior.