• Title/Summary/Keyword: Smart Structure System

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Semi-active control on long-span reticulated steel structures using MR dampers under multi-dimensional earthquake excitations

  • Zhou, Zhen;Meng, Shao-Ping;Wu, Jing;Zhao, Yong
    • Smart Structures and Systems
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    • v.10 no.6
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    • pp.557-572
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    • 2012
  • This paper focuses on the vibration control of long-span reticulated steel structures under multi-dimensional earthquake excitation. The control system and strategy are constructed based on Magneto-Rheological (MR) dampers. The LQR and Hrovat controlling algorithm is adopted to determine optimal MR damping force, while the modified Bingham model (MBM) and inverse neural network (INN) is proposed to solve the real-time controlling current. Three typical long-span reticulated structural systems are detailedly analyzed, including the double-layer cylindrical reticulated shell, single-layer spherical reticulated shell, and cable suspended arch-truss structure. Results show that the proposed control strategy can reduce the displacement and acceleration effectively for three typical structural systems. The displacement control effect under the earthquake excitation with different PGA is similar, while for the cable suspended arch-truss, the acceleration control effect increase distinctly with the earthquake excitation intensity. Moreover, for the cable suspended arch-truss, the strand stress variation can also be effectively reduced by the MR dampers, which is very important for this kind of structure to ensure that the cable would not be destroyed or relaxed.

Modal parameters based structural damage detection using artificial neural networks - a review

  • Hakim, S.J.S.;Razak, H. Abdul
    • Smart Structures and Systems
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    • v.14 no.2
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    • pp.159-189
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    • 2014
  • One of the most important requirements in the evaluation of existing structural systems and ensuring a safe performance during their service life is damage assessment. Damage can be defined as a weakening of the structure that adversely affects its current or future performance which may cause undesirable displacements, stresses or vibrations to the structure. The mass and stiffness of a structure will change due to the damage, which in turn changes the measured dynamic response of the system. Damage detection can increase safety, reduce maintenance costs and increase serviceability of the structures. Artificial Neural Networks (ANNs) are simplified models of the human brain and evolved as one of the most useful mathematical concepts used in almost all branches of science and engineering. ANNs have been applied increasingly due to its powerful computational and excellent pattern recognition ability for detecting damage in structural engineering. This paper presents and reviews the technical literature for past two decades on structural damage detection using ANNs with modal parameters such as natural frequencies and mode shapes as inputs.

Experimental study on acoustic emission characteristics of reinforced concrete components

  • Gu, Aijun;Luo, Ying;Xu, Baiqiang
    • Smart Structures and Systems
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    • v.16 no.1
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    • pp.67-79
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    • 2015
  • Acoustic emission analysis is an effective technique for monitoring the evolution of damage in a structure. An experimental analysis on a set of reinforced concrete beams under flexural loading was carried out. A mixed AE analysis method which used both parameter-based and signal-based techniques was presented to characterize and identify different failure mechanisms of damage, where the signal-based analysis was performed by using the Hilbert-Huang transform. The maximum instantaneous energy of typical damage events and the corresponding frequency characteristics were established, which provided a quantitative assessment of reinforced concrete beam using AE technique. In the bending tests, a "pitch-catch" system was mounted on a steel bar to assess bonding state of the steel bar in concrete. To better understand the AE behavior of bond-slip damage between steel bar and concrete, a special bond-slip test called pullout test was also performed. The results provided the basis of quantitative AE to identify both failure mechanisms and level of damages of civil engineering structures.

Exploring the dynamic knowledge structure of studies on the Internet of things: Keyword analysis

  • Yoon, Young Seog;Zo, Hangjung;Choi, Munkee;Lee, Donghyun;Lee, Hyun-woo
    • ETRI Journal
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    • v.40 no.6
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    • pp.745-758
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    • 2018
  • A wide range of studies in various disciplines has focused on the Internet of Things (IoT) and cyber-physical systems (CPS). However, it is necessary to summarize the current status and to establish future directions because each study has its own individual goals independent of the completion of all IoT applications. The absence of a comprehensive understanding of IoT and CPS has disrupted an efficient resource allocation. To assess changes in the knowledge structure and emerging technologies, this study explores the dynamic research trends in IoT by analyzing bibliographic data. We retrieved 54,237 keywords in 12,600 IoT studies from the Scopus database, and conducted keyword frequency, co-occurrence, and growth-rate analyses. The analysis results reveal how IoT technologies have been developed and how they are connected to each other. We also show that such technologies have diverged and converged simultaneously, and that the emerging keywords of trust, smart home, cloud, authentication, context-aware, and big data have been extracted. We also unveil that the CPS is directly involved in network, security, management, cloud, big data, system, industry, architecture, and the Internet.

Experimental study on the effect of EC-TMD on the vibration control of plant structure of PSPPs

  • Zhong, Tengfei;Feng, Xin;Zhang, Yu;Zhou, Jing
    • Smart Structures and Systems
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    • v.29 no.3
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    • pp.457-473
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    • 2022
  • A high-frequency vibration control method is proposed in this paper for Pumped Storage Power Plants (PSPPs) using Eddy Current Tuned Mass Damper (EC-TMD), based on which a new type of EC-TMD device is designed. The eddy current damper parameters are optimized by numerical simulation. On this basis, physical simulation model tests are conducted to compare and study the effect of structural performance with and without damping, different control strategies, and different arrangement positions of TMD. The test results show that EC-TMD can effectively reduce the control effect under high-frequency vibration of the plant structure, and after the additional damping device forms EC-TMD, the energy dissipation is further realized due to the intervention of eddy current damping, and the control effect is subsequently improved. The Multi-Tuned Mass Damper (MTMD) control strategy broadens the tuning band to improve the robustness of the system, and the vibration advantage is more obvious. Also, some suggestions are made for the placement of the dampers to promote their application.

A new time-frequency analysis and structural instantaneous frequency extraction method based on modified spline-kernelled chirplet transform

  • Dong-Yan Xue;Ping-Ping Yuan;Zhou-Jie Zhao;Wei-Xin Ren
    • Smart Structures and Systems
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    • v.33 no.6
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    • pp.385-398
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    • 2024
  • To improve the accuracy of time-frequency analysis (TFA) and instantaneous frequency (IF) extraction of structural dynamic response signals, this paper improves the spline-kernelled chirplet transform, and a new form of modified spline-kernelled chirplet transform (MSCT) based on revised Gaussian window function and energy concentration principle is put forward. The effectiveness of the proposed method is verified by numerical examples of single-component signal, multicomponent signal, single-degree-of-freedom Duffing nonlinear system and two-layer shear frame structure model. Then, a time-varying cable test is designed to collect the acceleration response signals under linear changing tension, and the IF extraction of these signals is performed by using MSCT, which further verifies the effectiveness and accuracy of this method. Through numerical simulation and experimental verification, it is proved that the proposed method can effectively extract the IF of nonlinear structure and time-varying structure.

A computational framework for drop time assessment of a control element assembly under fuel assembly deformations with fluid-structure interaction and frictional contact

  • Dae-Guen Lim;Gil-Yong Lee;Nam-Gyu Park;Yong-Hwa Park
    • Nuclear Engineering and Technology
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    • v.56 no.8
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    • pp.3450-3462
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    • 2024
  • This paper presents a computational framework for drop time assessment of a control element assembly (CEA) under fuel assembly (FA) deformations. The proposed framework consists of three key components: 1) finite element modeling of CEA, 2) fluid-structure interaction to compute drag force, and 3) modeling of frictional contact between CEA and FA. Specially, to accommodate the large motion of CEA, beam elements based on absolute nodal coordinate formulation (ANCF) are adopted. The continuity equation is utilized to calculate the drag force, considering flow changes in the cross-sectional area during the CEA drop. Lastly, beam-inside-beam frictional contact model is employed to capture practical contact conditions between CEA and FA. The proposed framework is validated through experiments under two scenarios: free falls of CEA within FA, encompassing undeformed and deformed scenarios. The experimental validation of the framework demonstrated that the drop time of CEA can be accurately predicted under the complex coupling effects of fluid and frictional contact. The drop times of the S-shaped deformation case is longer than those of the C-shaped deformation case, affirming the time delay due to frictional force. The validation confirms the potential applicability to access the safety and reliability of nuclear power plants under extreme conditions.

I/E Selective Activation based Knowledge Reconfiguration mechanism and Reasoning

  • Shim, JeongYon
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.5
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    • pp.338-344
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    • 2014
  • As the role of information collection becomes increasingly important in the enormous data environment, there is growing demand for more intelligent information technologies for managing complex data. On the other hand, it is difficult to find a solution because of the data complexity and big scaled amount. Accordingly, there is a need for a special intelligent knowledge base frame that can be operated by itself flexibly. In this paper, by adopting switching function for signal transmission in the synapse of the human brain, I/E selective activation based knowledge reconfiguring mechanism is proposed for building more intelligent information management system. In particular, knowledge network design, a special knowledge node structure, Type definition, I/E gauge definition and I/E matching scheme are provided. Using these concepts, the proposed system makes the functions of activation by I/E Gauge, selection and reconfiguration. In a more efficient manner, the routing and reasoning process was performed based on the knowledge reconfiguration network. In the experiments, the process of selection by I/E matching, knowledge reconfiguration and routing & reasoning results are described.

Vibration Suppression of Moving Suspended Systems by Wave Absorption Control

  • Saigo, Muneharu;Nam, Dong-Ho
    • Journal of Ocean Engineering and Technology
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    • v.17 no.1
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    • pp.33-40
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    • 2003
  • 기존 대부분의 진동제어법이 모드제어에 근거한 것인데 반면, 본 연구에서는 진동억제의 또다른 방법인 파동제어기법을 다루었다. 무반사조건을 만족하면서 진동에너지를 흡수하는 파동제어는 특히 1차원 구조계에 유용하게 사용될수 있으리라고 기대되는데, 현실적으론 제어알고리즘의 실현화에 그 어려움이 있다. 본 연구에서는 근사화된 무한구조계를 계산기내에 구축하여, 진동에너지가 근사 무한구조계에 흡수되는 조건을 제어기가 실현하는 제어수법을 개발하였다. 시뮬레이션과 실험을 통하여, 본 연구에서 제안한 파동제어기법에 의해 이동하는 현수체의 진동억제가 효율적으로 이루어짐을 확인할 수가 있었다.

Experimental Performance Verification of Load Carrying Capacity Algorithm of Bridges using Ambient Vibration (상시진동을 이용한 교량 내하력 추정 알고리즘의 실험적 성능 검증)

  • Lee, Woo-Sang;Park, Ki-Tae;Han, Sung-Ho
    • Journal of the Korean Society of Safety
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    • v.25 no.3
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    • pp.83-90
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    • 2010
  • In this study, it is conducted that the performance verification of the ambient load carrying capacity algorithm using long-term measurement systems of bridges. For this purpose, a steel-box type model bridge is fabricated and the public load carrying capacity of a steel-box model bridge is estimated by conducting the numerical analysis and load test. In addition, we compare the public load carrying capacity with the estimated result of a steel-box model bridge using the ambient load carrying capacity algorithm. By the assessment result, it is shown that the estimated ambient load carrying capacity is the difference of approximately 6.0 percentages as compared with the public load carrying capacity.