• Title/Summary/Keyword: Model Efficiency

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Assessment of sensitivity-based FE model updating technique for damage detection in large space structures

  • Razavi, Mojtaba;Hadidi, Ali
    • Structural Monitoring and Maintenance
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    • v.7 no.3
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    • pp.261-281
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    • 2020
  • Civil structures may experience progressive deterioration and damage under environmental and operational conditions over their service life. Finite element (FE) model updating method is one of the most important approaches for damage identification in structures due to its capabilities in structural health monitoring. Although various damage detection approaches have been investigated on structures, there are limited studies on large-sized space structures. Thus, this paper aims to investigate the applicability and efficiency of sensitivity-based FE model updating framework for damage identification in large space structures from a distinct point of view. This framework facilitates modeling and model updating in large and geometric complicated space structures. Considering sensitivity-based FE model updating and vibration measurements, the discrepancy between acceleration response data in real damaged structure and hypothetical damaged structure have been minimized through adjusting the updating parameters. The feasibility and efficiency of the above-mentioned approach for damage identification has finally been demonstrated with two numerical examples: a flat double layer grid and a double layer diamatic dome. According to the results, this method can detect, localize, and quantify damages in large-scaled space structures very accurately which is robust to noisy data. Also, requiring a remarkably small number of iterations to converge, typically less than four, demonstrates the computational efficiency of this method.

A Study on the Transient State of Deep Bed Filtration by the Network Model (Network 모델을 이용한 입상여과공정의 전이상태 해석에 대한 연구)

  • Choo, Changupp
    • Clean Technology
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    • v.12 no.4
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    • pp.224-231
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    • 2006
  • Collection efficiencies and pressure drops for the removal of small particles from dilute liquid suspensions by granular bed filter were calculated using network model. The network model is composed of a number of nodes connected with cylindrical bond and particles are deposited on the bond surface. The collection efficiency of each cylindrical bond was predicted using unit cell model corresponding to the pore volume of cylindrical pore both at the initial and transient states. Deposited particles on the collector surface may act as additional collector and reduce the pore size of the collector. As a result, the collection efficiency was improved and pressure drop increased with deposition. Even though the stochastic nature of network requires a large number of simulation work, the model proposed in this study can be used in investigating collection efficiency and pressure drop.

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A Study on the Investment Portfolios of Stocks using DEA (DEA를 활용한 주식 포트폴리오 구성에 관한 연구)

  • Gu, Seung Hwan;Jang, Seong Yong
    • Korean Management Science Review
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    • v.31 no.3
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    • pp.1-12
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    • 2014
  • This study suggests the two types DEA models such as DEA CCR model and Super Efficiency model to evaluate the value of a company and to apply them for the investments. 14 kinds of real data of companies such as EV/EBITDA, EPS growth rate, PCR, PER, dividend yield, PBR, stock price/net current asset, debt ratio, current ratio, ROE, operating margin, inventory turnover, accounts receivable turnover, and sales growth ratio were used as input variables of DEA models. 12 year data from December 30, 2000 up to December 30, 2012 were collected, and the data with negative, missing and 0 values were removed reflecting the characteristics of the DEA. In order to verify the effectiveness of the models, we compared the historical variability and rate of return of both models those of the market. Study results are as follows. First, two DEA models are more stable than market in terms of rate of return because the historical variability of both models are less than that of market. Second, Super Efficiency model is more stable than CCR model. Lastly, the cumulative rate of return of Super Efficiency model (434%) is greater than that of the CCR model (420%) and that of the market (269%).

Shear resistance of steel-concrete-steel deep beams with bidirectional webs

  • Guo, Yu-Tao;Nie, Xin;Fan, Jian-Sheng;Tao, Mu-Xuan
    • Steel and Composite Structures
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    • v.42 no.3
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    • pp.299-313
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    • 2022
  • Steel-concrete-steel composite structures with bidirectional webs (SCSBWs) are used in large-scale projects and exhibit good mechanical performances and constructional efficiency. The shear behaviors of SCSBW deep beam members in key joints or in locations subjected to concentrated forces are of concern in design. To address this issue, experimental program is investigated to examine the deep-beam shear behaviors of SCSBWs, in which the cracking process and force transfer mechanism are revealed. Compared with the previously proposed truss model, it is found that a strut-and-tie model is more suitable for describing the shear mechanism of SCSBW deep beams with a short span and sparse transverse webs. According to the experimental analyses, a new model is proposed to predict the shear capacities of SCSBW deep beams. This model uses strut-and-tie concept and introduces web shear and dowel action to consider the coupled multi mechanisms. A stress decomposition method is used to distinguish the contributions of different shear-transferring paths. Based on case studies, a simplified model is further developed, and the explicit solution is derived for design efficiency. The proposed models are verified using experimental data, which are proven to have good accuracy and efficiency and to be suitable for practical application.

Optimizing Intrusion Detection Pattern Model for Improving Network-based IDS Detection Efficiency

  • Kim, Jai-Myong;Lee, Kyu-Ho;Kim, Jong-Seob;Kim, Kuinam J.
    • Convergence Security Journal
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    • v.1 no.1
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    • pp.37-45
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    • 2001
  • In this paper, separated and optimized pattern database model is proposed. In order to improve efficiency of Network-based IDS, pattern database is classified by proper basis. Classification basis is decided by the specific Intrusions validity on specific target. Using this model, IDS searches only valid patterns in pattern database on each captured packets. In result, IDS can reduce system resources for searching pattern database. So, IDS can analyze more packets on the network. In this paper, proper classification basis is proposed and pattern database classified by that basis is formed. And its performance is verified by experimental results.

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Hydraulic Performance Characteristics of Kaplan Turbine (카프란수차의 수력학적 성능특성)

  • Lee C. H.;Park W. S.
    • 한국신재생에너지학회:학술대회논문집
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    • 2005.06a
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    • pp.443-446
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    • 2005
  • The Kaplan turbine model has been tested and analyzed. The blade angle and the guide vane opening of the turbine model were designed to be varied according to the best combination of guide vane and runner blade opening. When the changes in head and output were comparatively large, the efficiency drop were small, so the efficiency characteristics and stability of the entire operating condition were maintained in good condition. These results showed that the developed model in this study will be suitable for small hydro power stations with large changes in head and load.

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Evaluation of Pre-estimation Model to the Inprocess Surface Roughness for Grinding Operations

  • Kim, Gun-Hoi
    • International Journal of Precision Engineering and Manufacturing
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    • v.3 no.4
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    • pp.24-30
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    • 2002
  • In grinding operations, one of the most important problems is to increase efficiency of process. In order to achieve this purpose, it is necessary to administer the tool lift of grinding wheel and to optimize grinding conditions. Frequently dressing result in lowering the process efficiency remarkably and makes production cost high. On the other hand, grinding with a worn wheel causes the workpiece surface roughness to increase and often results in the occurrence of such troubles as chatter vibration and homing.

Frequency-Domain Balanced Stochastic Truncation for Continuous and Discrete Time Systems

  • Shaker, Hamid Reza
    • International Journal of Control, Automation, and Systems
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    • v.6 no.2
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    • pp.180-185
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    • 2008
  • A new method for relative error continuous and discrete time model order reduction is proposed. The reduction technique is based on two recently developed methods, namely frequency domain balanced truncation within a frequency bound and inner-outer factorization techniques. The proposed method is of interest for practical model order reduction because in this context it shows to keep the accuracy of the approximation as high as possible without sacrificing the computational efficiency. Numerical results show the accuracy and efficiency enhancement of the method.

New Learning Hybrid Model for Room Impulse Response Functions (새로운 학습 하이브리드 실내 충격 응답 모델)

  • Shin, Min-Cheol;Wang, Se-Myung
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2007.11a
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    • pp.23-27
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    • 2007
  • Many trials have been used to model room impulse responses, all attempting to provide efficient representations of room acoustics. The traditional model designs for room impulse response seem to fail in accuracy, controllability, or computational efficiency. In time domain, a room impulse response is generally considered as the combination of three parts having different acoustic characteristics, initial time delay, early reflection, and late reverberation. This paper introduces new learning hybrid model for the room impulse response. In this proposed model, those three parts are modeled using different models with learning algorithms that determine the length or boundary of each model in the hybrid model. By the simulation with measured room impulse responses, it was examined that the performance of proposed model shows the best efficiency in views of both the parameter numbers and modeling error.

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A Highly Efficient Aeroelastic Optimization Method Based on a Surrogate Model

  • Zhiqiang, Wan;Xiaozhe, Wang;Chao, Yang
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.4
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    • pp.491-500
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    • 2016
  • This paper presents a highly efficient aeroelastic optimization method based on a surrogate model; the model is verified by considering the case of a high-aspect-ratio composite wing. Optimization frameworks using the Kriging model and genetic algorithm (GA), the Kriging model and improved particle swarm optimization (IPSO), and the back propagation neural network model (BP) and IPSO are presented. The feasibility of the method is verified, as the model can improve the optimization efficiency while also satisfying the engineering requirements. Moreover, the effects of the number of design variables and number of constraints on the optimization efficiency and objective function are analysed in detail. The accuracy of two surrogate models in aeroelastic optimization is also compared. The Kriging model is constructed more conveniently, and its predictive accuracy of the aeroelastic responses also satisfies the engineering requirements. According to the case of a high-aspect-ratio composite wing, the GA is better at global optimization.