Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.1
3.8
Journals
Buildings
Special Issues
Performance Analysis and Assessment of Structures under Multi-Hazards
share announcement

Performance Analysis and Assessment of Structures under Multi-Hazards

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 804

Special Issue Editors

Dr. Bao Meng

E-Mail Website
Guest Editor
School of Civil Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
Interests: steel structures; steel-concrete composite structure; progressive collapse; dynamic impact analysis; seismic analysis
Dr. Shan Li

E-Mail
Guest Editor
Department of Civil and Environmental Engineering, National University of Singapore, Singapore 119077, Singapore
Interests: fire engineering; high performance concrete; steel-concrete composite structures; modular construction; artificial intelligence; codification
Dr. Xiang Zhu

E-Mail
Guest Editor
Department of Civil Engineering, Shanxi University, Taiyuan 030006, China
Interests: impact resistance of structure; composite structure; energy dissipation device; FEA; protective structure
Special Issues, Collections and Topics in MDPI journals
Dr. Deyang Kong

E-Mail
Guest Editor
Department of Civil and Environmental Engineering, National University of Singapore, Singapore 119077, Singapore
Interests: progressive collapse; steel and composite structures; impact engineering; fire engineering; ductile fracture of steel material

Special Issue Information

Dear Colleagues,

The frequency of natural disasters and the rise in global terrorist incidents underscore the urgency of enhancing the safety of building structures and critical infrastructure across their lifecycle. These entities now confront multifaceted challenges posed by a spectrum of hazards, encompassing earthquakes, explosions, fires, impacts, and more. Structures subjected to unforeseen loads often experience progressive or disproportionate collapse, characterized by the nature of "low probability, high consequence", leading to significant societal impacts. As socioeconomic progress continues, structural design has evolved from a single, overarching goal of "ensuring life safety" to specific, multifaceted performance objectives. This shift highlights the pressing need to ensure the comprehensive defensive performance of building structures under the threat of multiple hazards.

The aim of this Special Issue is to collect results and to promote discussion and developments from recent research pertaining to the performance analysis, assessment, design, and reinforcement of structures subjected to multiple hazards. This encompasses analyses for structures' resistance against progressive collapse, seismic events, fire incidents, impact scenarios, as well as enhancements in the performance of both new and existing structures. Please feel free to contact us if you require further clarifications regarding this Special Issue.

Dr. Bao Meng
Dr. Shan Li
Dr. Xiang Zhu
Dr. Deyang Kong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • steel/steel–concrete structures
  • progressive/disproportionate collapse
  • fire resistance analysis
  • seismic analysis
  • multi-hazard performance assessment
  • strengthening of new or existing structures

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

27 pages, 9173 KiB  
Article
Machine Learning Prediction Model for Boundary Transverse Reinforcement of Shear Walls
by Jiannan Ding, Jianhui Li, Congzhen Xiao and Baojuan Qiao
Buildings 2024, 14(2), 427; https://doi.org/10.3390/buildings14020427 - 04 Feb 2024
Viewed by 583
Abstract
Due to their roles as efficient lateral force-resisting systems, reinforced concrete shear walls exert a tremendous degree of influence on the overall seismic performance of buildings. The ability to predict the boundary transverse reinforcement of shear walls is critical to the seismic design [...] Read more.
Due to their roles as efficient lateral force-resisting systems, reinforced concrete shear walls exert a tremendous degree of influence on the overall seismic performance of buildings. The ability to predict the boundary transverse reinforcement of shear walls is critical to the seismic design process, as well as in the overall evaluation and retrofitting of existing buildings. Contemporary empirical models attain low predictive accuracy, with an inability to capture nonlinearity between boundary transverse reinforcement and different influencing variables. This study proposes a boundary transverse reinforcement prediction model for shear walls with boundary elements based on the demand of ductility. Using the extreme gradient boosting machine learning algorithm and 501 samples, some 52 input variables are considered, and a subset with six features is selected, monitored, and analyzed using both internal methods (gain and cover) and external methods. The results (R2=0.884) display superior predictive capacity compared with existing models. Interpretation and error analysis are performed. Safety analysis is conducted to obtain references for use in practical engineering. Overall, this study presents a more accurate tool for use in seismic design and provides references for the evaluation and retrofitting of existing buildings. Our contributions hold significant implications for enhancing the safety and resilience of reinforced concrete structures. Full article
(This article belongs to the Special Issue Performance Analysis and Assessment of Structures under Multi-Hazards)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop