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Advanced Methods for Seismic Performance Evaluation of Building Structures III

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 3975

Special Issue Editor


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Guest Editor
Department of Architectural Engineering, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea
Interests: developing seismic design and performance evaluation methodology; large scale experiment of building components
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Earthquakes are one of the most dangerous natural events, inflicting damage and causing the collapse of buildings and infrastructure. On average, 10,000 people lose their lives from earthquakes each year. Not only do earthquakes come in different sizes, they can also occur anywhere on the globe. The demand to reduce the risk associated with earthquakes has been growing every year, leading to greater research focus on seismic design and seismic performance evaluation. Recently, the performance-based seismic engineering approach has been adopted in the earthquake engineering community. In this approach, multiple seismic performance objectives are explicitly specified, which are defined with combinations of seismic hazard levels and structural and non-structural performance levels, unlike conventional prescriptive design approaches. Critical components of performance-based seismic design and evaluation procedures include state-of-art technologies related to seismic hazard analyses, robust numerical simulation frameworks, and sophisticated performance-based seismic design and assessment methodologies. Although major technologies have been developed, many challenging obstacles remain to be solved before they can be implemented in code provisions. The Special Issue of Applied Sciences on “Advanced Methods for Seismic Performance Evaluation of Building Structures III” aims to cover recent advances in the development of major components of seismic performance evaluation and design.

Prof. Dr. Sang Whan Han
Guest Editor

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Keywords

  • numerical models
  • model parameters
  • analysis algorithm
  • seismic performance evaluation
  • seismic risk
  • seismic hazards
  • seismic force-resisting systems
  • energy dissipaters
  • seismic design and mitigation
  • assessment method
  • ground motions
  • nonlinear response

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Published Papers (2 papers)

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Research

19 pages, 7981 KiB  
Article
Experimental Study on the Seismic Performance of New Energy Dissipation Connectors in an Autoclaved Aerated Concrete Panel with Assembled Steel Frame
by Kaili Wang, Kewei Ding and Tian Yang
Appl. Sci. 2022, 12(24), 13035; https://doi.org/10.3390/app122413035 - 19 Dec 2022
Cited by 3 | Viewed by 2081
Abstract
This study proposes a new energy dissipation connector (NEDC) to connect an external autoclaved aerated concrete (AAC) wall panel with an assembled steel frame. To investigate the seismic performance and working mechanism of the NEDC under seismic action, horizontal low-cyclic loading tests were [...] Read more.
This study proposes a new energy dissipation connector (NEDC) to connect an external autoclaved aerated concrete (AAC) wall panel with an assembled steel frame. To investigate the seismic performance and working mechanism of the NEDC under seismic action, horizontal low-cyclic loading tests were conducted on two sets of steel frames with different connectors using an MTS actuator. Similarly, the seismic performance and working mechanism of the AAC wall panels were elucidated using horizontal low-cyclic loading tests. Test results revealed that the NEDC increased ductility by 10.69–21.12% and energy consumption by 101.14% when compared to those obtained using hook bolt connectors. Overall, the NEDC provides good seismic performance, large deformability, and high energy consumption capacity, thereby rendering it ideal for assembled steel buildings. Furthermore, the NEDC can reduce wall panel damage during earthquake action and enhance the seismic performance of composite frames. Full article
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23 pages, 13227 KiB  
Article
A Comparative Study of Meta-Modeling for Response Estimation of Stochastic Nonlinear MDOF Systems Using MIMO-NARX Models
by Menghui Chen, Xiaoshu Gao, Cheng Chen, Tong Guo and Weijie Xu
Appl. Sci. 2022, 12(22), 11553; https://doi.org/10.3390/app122211553 - 14 Nov 2022
Cited by 3 | Viewed by 1434
Abstract
Complex dynamic behavior of nonlinear structures makes it challenging for uncertainty analysis through Monte Carlo simulations (MCS). Surrogate modeling presents an efficient and accurate computational alternative for a large number of MCS. The previous study has demonstrated that the multi-input multi-output nonlinear autoregressive [...] Read more.
Complex dynamic behavior of nonlinear structures makes it challenging for uncertainty analysis through Monte Carlo simulations (MCS). Surrogate modeling presents an efficient and accurate computational alternative for a large number of MCS. The previous study has demonstrated that the multi-input multi-output nonlinear autoregressive with exogenous input (MIMO-NARX) model provides good discrete-time representations of deterministic nonlinear multi-degree-of-freedom (MDOF) structural dynamic systems. Model order reduction (MOR) is executed to eliminate insignificant modes to reduce the computational burden due to too many degrees of freedom. In this study, the MIMO-NARX strategy is integrated with different meta-modeling techniques for uncertainty analysis. Different meta-models including Kriging, polynomial chaos expansion (PCE), and arbitrary polynomial chaos (APC) are used to surrogate the NARX coefficients for system uncertainties. A nine-DOF structure is used as an MDOF dynamic system to evaluate different meta-models for the MIMO-NARX. Good fitness of statistical responses is observed between the MCS results of the original system and all surrogated MIMO-NARX predictions. It is demonstrated that the APC-NARX model with the advantage of being data-driven is the most efficient and accurate tool for uncertainty quantification of nonlinear structural dynamics. Full article
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