• Title/Summary/Keyword: resilient and sustainable infrastructures

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A novel hybrid control of M-TMD energy configuration for composite buildings

  • ZY Chen;Yahui Meng;Ruei-Yuan Wang;T. Chen
    • Steel and Composite Structures
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    • v.48 no.4
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    • pp.475-483
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    • 2023
  • In this paper, a new energy-efficient semi-active hybrid bulk damper is developed that is cost-effective for use in structural applications. In this work, the possibility of active and semi-active component configurations combined with suitable control algorithms, especially vibration control methods, is explored. The equations of motion for a container bridge equipped with an MDOF Mass Tuned Damper (M-TMD) system are established, and the combination of excitation, adhesion, and control effects are performed by a proprietary package and commercial custom submodel software. Systematic methods for the synthesis of structural components and active systems have been used in many applications because of the main interest in designing efficient devices and high-performance structural systems. A rational strategy can be established by properly controlling the master injection frequency parameter. Simulation results show that the multiscale model approach is achieved and meets accuracy with high computational efficiency. The M-TMD system can significantly improve the overall response of constrained structures by modestly reducing the critical stress amplitude of the frame. This design can be believed to build affordable, safe, environmentally friendly, resilient, sustainable infrastructure and transportation.

Apply evolved grey-prediction scheme to structural building dynamic analysis

  • Z.Y. Chen;Yahui Meng;Ruei-Yuan Wang;Timothy Chen
    • Structural Engineering and Mechanics
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    • v.90 no.1
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    • pp.19-26
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    • 2024
  • In recent years, an increasing number of experimental studies have shown that the practical application of mature active control systems requires consideration of robustness criteria in the design process, including the reduction of tracking errors, operational resistance to external disturbances, and measurement noise, as well as robustness and stability. Good uncertainty prediction is thus proposed to solve problems caused by poor parameter selection and to remove the effects of dynamic coupling between degrees of freedom (DOF) in nonlinear systems. To overcome the stability problem, this study develops an advanced adaptive predictive fuzzy controller, which not only solves the programming problem of determining system stability but also uses the law of linear matrix inequality (LMI) to modify the fuzzy problem. The following parameters are used to manipulate the fuzzy controller of the robotic system to improve its control performance. The simulations for system uncertainty in the controller design emphasized the use of acceleration feedback for practical reasons. The simulation results also show that the proposed H∞ controller has excellent performance and reliability, and the effectiveness of the LMI-based method is also recognized. Therefore, this dynamic control method is suitable for seismic protection of civil buildings. The objectives of this document are access to adequate, safe, and affordable housing and basic services, promotion of inclusive and sustainable urbanization, implementation of sustainable disaster-resilient construction, sustainable planning, and sustainable management of human settlements. Simulation results of linear and non-linear structures demonstrate the ability of this method to identify structures and their changes due to damage. Therefore, with the continuous development of artificial intelligence and fuzzy theory, it seems that this goal will be achieved in the near future.

Grey algorithmic control and identification for dynamic coupling composite structures

  • ZY Chen;Ruei-yuan Wang;Yahui Meng;Timothy Chen
    • Steel and Composite Structures
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    • v.49 no.4
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    • pp.407-417
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    • 2023
  • After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.