Numerical and Experimental Research on Steel-Concrete Composite Structural Systems

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

Deadline for manuscript submissions: 20 December 2024 | Viewed by 3677

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Guest Editor
School of Civil Engineering, Chongqing University, Chongqing 400045, China
Interests: steel–concrete composite structures; composite structural systems; machine learning; constitutive models; finite element
Department of Civil Engineering, Tsinghua University, Beijing 100084, China
Interests: steel–concrete composite structures; concrete constitutive models; seismic time–history analysis; slab spatial composite effect; finite element model
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Guest Editor
Department of Civil Engineering, Tsinghua University, Beijing 100084, China
Interests: steel–concrete composite structures; passive energy dissipation devices and systems; steel constitutive models; structure design

Special Issue Information

Dear Colleagues,

Compared with pre-stressed and steel-reinforced concrete structures, steel–concrete composite structures combine steel and concrete with shear connectors, providing the flexibility of steel and strength of concrete to solve the issues of large spans and heavy loads. Steel–concrete composite beams are widely used in engineering, owing to their excellent mechanical properties and economic benefits. This Special Issue, entitled “Numerical and Experimental Research on Steel-Concrete Composite Structural Systems”, aims to give an overview of the most recent innovations and advances in the field of steel–concrete composite structures and their applications. Theoretical research, experimental work, case studies and comprehensive review papers are invited for publication. Relevant topics to this Special Issue include, but are not limited to, the following subjects:

  • Composite structural systems;
  • Innovative forms of composite structures;
  • Numerical models of composite structures;
  • Intelligent analysis of composite structures;
  • Experimental research on composite structures;
  • Construction technology of composite structures;
  • Application of high-performance materials in composite structures.

Dr. Jizhi Zhao
Dr. Muxuan Tao
Dr. Liangdong Zhuang
Guest Editors

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Keywords

  • composite structures seismic performance
  • structural analysis
  • numerical simulation
  • machine learning
  • mechanical behavior
  • composite structural systems

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Published Papers (3 papers)

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Research

30 pages, 13002 KiB  
Article
Optimization of Shear Resistance in Precast Concrete Sandwich Wall Panels Using an S-Type Shear Connector
by Herman Tawil, Chee Ghuan Tan, Nor Hafizah Ramli Sulong, Fadzli Mohamed Nazri, Mohd Fazaulnizam Shamsudin and Norazura Muhamad Bunnori
Buildings 2024, 14(6), 1725; https://doi.org/10.3390/buildings14061725 - 8 Jun 2024
Viewed by 954
Abstract
Precast concrete sandwich wall panels (PCSPs) are popular for building exteriors due to their high thermal efficiency, composite performance, and low manufacturing and maintenance costs. Researchers have investigated the possibility of reducing the panel thickness while maintaining the cladding components’ thermal efficiency and [...] Read more.
Precast concrete sandwich wall panels (PCSPs) are popular for building exteriors due to their high thermal efficiency, composite performance, and low manufacturing and maintenance costs. Researchers have investigated the possibility of reducing the panel thickness while maintaining the cladding components’ thermal efficiency and strength to further improve efficiency and to reduce material consumption. However, limited research has been conducted on the shear bonding of steel plates, which is critical to ensuring durability and energy efficiency. This study investigated the shear behaviour of PCSPs with an S-type shear connector (SSC) through nine push-off tests and non-linear finite element modelling using Abaqus. Parametric studies were carried out to investigate the influence of the geometric properties of the SSC, the yield strength of the steel and the insulation thickness. The results suggest that the maximum secant stiffness for SSCs was achieved at a width of 101.4 mm and a thickness of 2 mm. Therefore, it is recommended that the width of the SSCs be limited to this value or less. Furthermore, the study found that increasing the yield strength of the steel beyond a thickness of 2 mm and a width of 101.4 mm did not improve the results and had a negative impact on the secant stiffness of the SSCs. Full article
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22 pages, 6583 KiB  
Article
Data-Driven Prediction Model for High-Strength Bolts in Composite Beams
by Haolin Li, Xinsheng Yin, Lirong Sha, Dongdong Yang and Tianyu Hu
Buildings 2023, 13(11), 2769; https://doi.org/10.3390/buildings13112769 - 1 Nov 2023
Viewed by 1089
Abstract
In recent years, the application of artificial intelligence-based methods to engineering problems has received consistent praise for their high predictive accuracy. This paper utilizes a BP neural network to predict the strength of steel–concrete composite beam shear connectors with high-strength friction-grip bolts (HSFGBs). [...] Read more.
In recent years, the application of artificial intelligence-based methods to engineering problems has received consistent praise for their high predictive accuracy. This paper utilizes a BP neural network to predict the strength of steel–concrete composite beam shear connectors with high-strength friction-grip bolts (HSFGBs). These connectors are widely used in bridge and building construction due to their superior strength and stiffness compared to traditional beams. A validated finite element model was used to predict the strength of HSFGB shear connectors. A reliable database was created by analyzing 208 models with different characteristics for machine learning modeling. Previous studies have identified issues with result variation and overestimation or underestimation of shear connection strength. Among the machine learning methods evaluated, the backpropagation neural network model performed the best. It achieved a goodness of fit of over 93% in both the training and testing sets, with a low coefficient of variation of 6.50%. Concrete strength, bolt diameter, and bolt tensile strength were found to be important variables influencing the strength of shear connectors. Other variables showed a proportional or inverse relationship with compressive strength, except for concrete strength and bolt pretension. This study presents an accurate machine learning approach for predicting the strength of HSFGB shear connectors in steel–concrete composite beams. The study offers valuable insights into the effects of various variables on the performance of shear connection strength, providing support for structural design and analysis. Full article
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19 pages, 7987 KiB  
Article
Numerical Study on the Seismic Behavior of Steel–Concrete Composite Frame with Uplift-Restricted and Slip-Permitted (URSP) Connectors
by Zhenhao Wu, Xin Nie, Jizhi Zhao, Wei Wang and Linli Duan
Buildings 2023, 13(10), 2598; https://doi.org/10.3390/buildings13102598 - 14 Oct 2023
Cited by 1 | Viewed by 1141
Abstract
Uplift-restricted and slip-permitted (URSP) connectors have been demonstrated to effectively enhance the anti-cracking performance of RC slabs in negative moment areas. While their efficacy is recognized, studies of composite frames utilizing URSP connectors remain scarce, limiting their application in construction. This research undertakes [...] Read more.
Uplift-restricted and slip-permitted (URSP) connectors have been demonstrated to effectively enhance the anti-cracking performance of RC slabs in negative moment areas. While their efficacy is recognized, studies of composite frames utilizing URSP connectors remain scarce, limiting their application in construction. This research undertakes a numerical analysis of the seismic performance of steel–concrete composite frames that employ URSP connectors. The influence of key design parameters on seismic behavior is scrutinized. Leveraging prior tests on composite frames with URSP connectors carried out by the authors’ group, a sophisticated three-dimensional FEM model is crafted. This model, built using the ABAQUS software (2016), accounts for the intricate mechanical behaviors of shear connectors. The fidelity of the FEM model is validated through a juxtaposition of numerical and test outcomes, assessing strain distribution, damage patterns, and load–displacement curves. This numerical model serves as a basis for the study, exploring the impacts of three crucial design parameters on structural seismic performance. The findings suggest that the arrangement length of URSP connectors should be constrained to less than half of the frame beam’s span to optimize mechanical performance during seismic events. Additionally, enhancing both the flange thickness and the steel beam’s height is recommended to further bolster structural integrity. Full article
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