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Advanced Seismic Design and Performance Evaluation of Building Structures
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Advanced Seismic Design and Performance Evaluation of Building Structures

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

Deadline for manuscript submissions: closed (22 October 2022) | Viewed by 10798

Special Issue Editor

Prof. Dr. Sang Whan Han

E-Mail Website
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 can cause catastrophic losses both economic and in terms of human lives. To reduce the losses associated with earthquakes, buildings should be constructed using reliable seimic design methodologies. In addition, the pontetial danger in existing structures should be evaluated with accurate seismic performance evaluation methods and the structures should be retrofitted properly. Many advanced seismic design and performance evaluation methods have been developed. This Special Issue of Applied Sciences, entitled Advanced Seismic Design and Performance Evaluation of Building Structures, aims to cover cutting edge seismic design and performance evaluation methods and their applications, including seismic hazard analyses, numerical simulation, performance-based seismic design and assessment, and seismic loss estimation.

Prof. Dr. Sang Whan Han
Guest Editor

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Keywords

  • seimic design
  • seismic performance evaluation
  • seismic hazard
  • numerical simulation
  • performance-based seismic design and assessment
  • seismic loss estimation

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Published Papers (4 papers)

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Research

19 pages, 8064 KiB  
Article
Structural Health Monitoring of Underground Metro Tunnel by Identifying Damage Using ANN Deep Learning Auto-Encoder
by Nadeem Abbas, Tariq Umar, Rania Salih, Muhammad Akbar, Zahoor Hussain and Xiong Haibei
Appl. Sci. 2023, 13(3), 1332; https://doi.org/10.3390/app13031332 - 19 Jan 2023
Cited by 14 | Viewed by 3313
Abstract
Due to the complexity of underground environmental conditions and operational incidents, advanced and accurate monitoring of the underground metro shield tunnel structures is crucial for maintenance and the prevention of mishaps. In the past few decades, numerous deep learning-based damage identification studies have [...] Read more.
Due to the complexity of underground environmental conditions and operational incidents, advanced and accurate monitoring of the underground metro shield tunnel structures is crucial for maintenance and the prevention of mishaps. In the past few decades, numerous deep learning-based damage identification studies have been conducted on aboveground civil infrastructure. However, a few studies have been conducted for underground metro shield tunnels. This paper presents a deep learning-based damage identification study for underground metro shield tunnels. Based on previous experimental studies, a numerical model of a metro tunnel was utilized, and the vibration data obtained from the model under a moving load analysis was used for the evaluation. An existing deep auto-encoder (DAE) that can support deep neural networks was utilized to detect structural damage accurately by incorporating raw vibration signals. The dynamic analysis of a metro tunnel FEM model was conducted with different severity levels of the damage at different locations and elements on the structure. In addition, root mean square (RMS) was used to locate the damage at the different locations in the model. The results were compared under different schemes of white noise, varying levels of damage, and an intact state. To test the applicability of the proposed framework on a small dataset, the approach was also utilized to investigate the damage in a simply supported beam and compared with two deep learning-based methods (SVM and LSTM). The results show that the proposed DAE-based framework is feasible and efficient for the damage identification, damage size evaluation, and damage localization of the underground metro shield tunnel and a simply supported beam with comparison of two deep models. Full article
(This article belongs to the Special Issue Advanced Seismic Design and Performance Evaluation of Building Structures)
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15 pages, 2455 KiB  
Article
Prediction of the Yield Strength of RC Columns Using a PSO-LSSVM Model
by Bochen Wang, Weiming Gong, Yang Wang, Zele Li and Hongyuan Liu
Appl. Sci. 2022, 12(21), 10911; https://doi.org/10.3390/app122110911 - 27 Oct 2022
Cited by 5 | Viewed by 1531
Abstract
Accuracy prediction of the yield strength and displacement of reinforced concrete (RC) columns for evaluating the seismic performance of structure plays an important role in engineering the structural design of RC columns. A new hybrid machine learning technique based on the least squares [...] Read more.
Accuracy prediction of the yield strength and displacement of reinforced concrete (RC) columns for evaluating the seismic performance of structure plays an important role in engineering the structural design of RC columns. A new hybrid machine learning technique based on the least squares support vector machine (LSSVM) and the particle swarm optimization (PSO) algorithm is proposed to predict the yield strength and displacement of RC columns. In this PSO-LSSVM model, the LSSVM is applied to discover the mapping between the influencing factors and the yield strength and displacement, and the PSO algorithm is utilized to select the optimal parameters of LSSVM to facilitate the prediction performance of the proposed model. A dataset covering the PEER database and the available experimental data in relevant literature is established for model training and testing. The PSO algorithm is then evaluated and compared with other metaheuristic algorithms based on the experiment’s database. The results indicate the effectiveness of the PSO employed for improving the prediction performance of the LSSVM model according to the evaluation criteria such as the root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). Overall, the simulation demonstrates that the developed PSO-LSSVM model has ideal prediction accuracy in the yield properties of RC columns. Full article
(This article belongs to the Special Issue Advanced Seismic Design and Performance Evaluation of Building Structures)
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18 pages, 8053 KiB  
Article
Effect of Wind Loads on Collapse Performance and Seismic Loss for Steel Ordinary Moment Frames
by Taeo Kim, Sang Whan Han and Soo Ik Cho
Appl. Sci. 2022, 12(4), 2011; https://doi.org/10.3390/app12042011 - 15 Feb 2022
Cited by 2 | Viewed by 2180
Abstract
The aim of this study is to investigate the effect of wind loads on the seismic collapse performance and seismic loss for steel ordinary moment frames (OMFs). For this purpose, 9-, 12-, 15-, and 18-story steel OMFs are repeatedly designed for (1) gravity [...] Read more.
The aim of this study is to investigate the effect of wind loads on the seismic collapse performance and seismic loss for steel ordinary moment frames (OMFs). For this purpose, 9-, 12-, 15-, and 18-story steel OMFs are repeatedly designed for (1) gravity load + seismic load, (2) gravity load + seismic load + wind load (wind speed = 44 m/s), and (3) gravity load + seismic load + wind load (wind speed = 55 m/s). The seismic collapse performance and seismic loss of OMFs are evaluated using the procedures in FEMA P695 (FEMA, 2009) and FEMA P58 (FEMA, 2018), respectively. Steel OMFs designed with consideration of wind loads have larger member sections than corresponding steel OMFs designed without consideration of wind loads as expected. Although member sections are increased when wind loads are considered, the growth in the maximum base shear force and lateral stiffness of OMFs are insignificant. Unlike our expectation, OMFs designed with consideration of wind loads have higher expected annual loss (EAL) than corresponding OMFs designed without consideration of wind loads. Full article
(This article belongs to the Special Issue Advanced Seismic Design and Performance Evaluation of Building Structures)
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38 pages, 20585 KiB  
Article
Seismic Strengthening of R/C Buildings Retrofitted by New Window-Type System Using Non-Buckling Slit Dampers Examined via Pseudo-Dynamic Testing and Nonlinear Dynamic Analysis
by Kang-Seok Lee, Bok-Gi Lee and Ju-Seong Jung
Appl. Sci. 2022, 12(3), 1220; https://doi.org/10.3390/app12031220 - 24 Jan 2022
Cited by 3 | Viewed by 2981
Abstract
In the present study, a window-type seismic control system (WSCS) using non-buckling slit dampers (NBSDs) was proposed and developed to address the disadvantages of conventional seismic control systems so that it can be effectively applied to existing reinforced concrete (RC) buildings. Materials testing [...] Read more.
In the present study, a window-type seismic control system (WSCS) using non-buckling slit dampers (NBSDs) was proposed and developed to address the disadvantages of conventional seismic control systems so that it can be effectively applied to existing reinforced concrete (RC) buildings. Materials testing was also conducted to examine the material performance and energy dissipation capacity of NBSD. A full-scale two-story test frame modeled from existing RC buildings with non-seismic details was subjected to pseudo-dynamic testing. As a result, the effect of NBSD-WSCS, when applied to existing RC frames, was examined and verified, especially as to its seismic retrofitting performance. In addition, based on material testing and pseudo-dynamic test results, a restoring force characteristics model was proposed to implement the nonlinear dynamic analysis of a test building retrofitted with NBSD-WSCS. Based on the proposed restoring force characteristics, nonlinear dynamic analysis was conducted, and the results were compared with those obtained by the pseudo-dynamic tests. Finally, in an attempt to commercialize this NBSD-based WSCS, nonlinear dynamic analysis was conducted on the entire RC building with non-seismic details retrofitted with NBSD-WSCS. The results showed that the RC frame (building) with no reinforcement applied underwent shear failure at seismic intensity of 200 cm/s2, a typical threshold applied in seismic design in Korea. In contrast, in the frame (building) retrofitted with NBSD-WSCS, only minor earthquake damage was expected, and even when the seismic intensity was set to 300 cm/s2, the maximum intensity that had been observed in Korea, only small or moderate seismic damage was expected. These results confirmed the effectiveness of the seismic retrofitting method using NBSD-WSCS developed in the present study. Full article
(This article belongs to the Special Issue Advanced Seismic Design and Performance Evaluation of Building Structures)
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