Steel and Composite Structures
Volume 52, Number 6, 2024, pages 647-656
DOI: 10.12989/scs.2024.52.6.647
Enhancing mechanical performance of steel-tube-encased HSC composite walls: Experimental investigation and analytical modeling
ZY Chen, Ruei-Yuan Wang, Yahui Meng, Huakun Wu, Lai and Timothy Chen
Abstract
This paper discusses the study of concrete composite walls of algorithmic modeling, in which steel tubes are
embedded. The load-bearing capacity of STHC composite walls increases with the increase of axial load coefficient, but its
ductility decreases. The load-bearing capacity can be improved by increasing the strength of the steel pipes; however, the
elasticity of STHC composite walls was found to be slightly reduced. As the shear stress coefficient increases, the load-bearing
capacity of STHC composite walls decreases significantly, while the deformation resistance increases. By analyzing actual
cases, we demonstrate the effectiveness of the research results in real situations and enhance the persuasiveness of the
conclusions. The research results can provide a basis for future research, inspire more explorations on seismic design and
construction, and further advance the development of this field. Emphasize the importance of research results, promote
interdisciplinary cooperation in the fields of structural engineering, earthquake engineering, and materials science, and improve
overall seismic resistance. The emphasis on these aspects will help highlight the practical impact of the research results, further
strengthen the conclusions, and promote progress in the design and construction of earthquake-resistant structures. The goals of
this work are access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable
urbanization and participation, implementation of sustainable and disaster-resilient architecture, sustainable planning and
management of human settlements. Simulation results of linear and nonlinear structures show that this method can detect
structural parameters and their changes due to damage and unknown disturbances. Therefore, it is believed that with the further
development of fuzzy neural network artificial intelligence theory, this goal will be achieved in the near future.
Key Words
AI computer aided intelligent; composite walls; FEM analysis; fuzzy model; high-strength concrete; mechanical behavior; resilient and sustainable
Address
ZY Chen:School of Science, Guangdong University of Petrochemical Technology, Maoming, Guangdong, China
Ruei-Yuan Wang:School of Science, Guangdong University of Petrochemical Technology, Maoming, Guangdong, China
Yahui Meng:School of Science, Guangdong University of Petrochemical Technology, Maoming, Guangdong, China
Huakun Wu:School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, Guangdong, China
Lai:School of Science, Guangdong University of Petrochemical Technology, Maoming, Guangdong, China
Timothy Chen:Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125, USA