Nonlinear Analysis of Circular Steel Tube Steel Reinforced Recycled Concrete Composite Columns Based on OpenSees

Literature Overview

This paper by Wang Defa, Meng Zexiang, Ma Hui, and Guo Tingting, published in Journal of Xi'an University of Technology (2020, Vol. 36, No. 1, pp. 88-94), presents a nonlinear finite element analysis of circular steel tube steel reinforced recycled concrete (RCRC) composite columns using the OpenSees software platform. The research was supported by the National Natural Science Foundation of China (51408485) and Shaanxi Provincial Natural Science Basic Research Plan (2019JM-193). The study numerically simulates eleven experimental specimens and conducts parametric analysis to identify key design parameters affecting axial compression performance.

Research Context and Methodology

The use of recycled aggregate concrete (RAC) in structural applications has gained significant attention due to sustainability concerns and the growing volume of construction and demolition waste. However, the mechanical properties of RAC differ from conventional concrete, necessitating careful structural design considerations. When combined with steel tube and steel reinforcement in composite columns, the resulting hybrid system offers potential advantages in terms of material efficiency and environmental performance.

The researchers employed OpenSees (Open System for Earthquake Engineering Simulation), an open-source finite element software widely used in structural engineering research. The modeling approach utilized a fiber-based section model based on the flexibility method, where the cross-section of the composite column was discretized into multiple material fibers, each assigned appropriate constitutive laws reflecting the nonlinear behavior of steel, recycled concrete, and any infill materials.

The nonlinear beam-column elements were selected from the OpenSees element library, capable of capturing geometric nonlinearity, material nonlinearity, and P-delta effects. The constitutive models for steel typically employed multilinear kinematic hardening or bilinear models, while recycled concrete was modeled using confinement-enhanced concrete models that account for the lateral confinement provided by the steel tube and stirrups.

Parametric Analysis Results

The parametric study examined four key parameters affecting the axial compression performance of the composite columns:

The diameter-to-thickness ratio (D/t) is a critical parameter governing the local buckling resistance of the steel tube. Lower D/t ratios provide greater confinement to the recycled concrete and delay local buckling, resulting in higher ultimate load capacity. The steel reinforcement ratio directly contributes to the axial load capacity and influences the ductility of the composite column.

The slenderness ratio affects the global buckling behavior of the column, with higher slenderness ratios leading to reduced load capacity due to increased susceptibility to elastic buckling. Interestingly, the recycled aggregate replacement rate had minimal influence on the overall load capacity, suggesting that the composite action between the steel tube, steel reinforcement, and recycled concrete effectively compensates for the reduced strength of recycled aggregate concrete.

The finite element results demonstrated good agreement with experimental data, with relative errors in predicted load capacity generally within 10 percent. This level of accuracy validates the modeling approach and constitutive models employed.

Modeling Considerations and Best Practices

Several important modeling considerations emerged from this study:

1. Fiber discretization: Adequate mesh refinement of the cross-section is necessary to capture the nonlinear stress-strain distribution, particularly in regions of high strain concentration.
2. Confinement modeling: The lateral confinement effect of the steel tube on recycled concrete must be accurately represented, as this significantly influences the compressive strength and ductility of the concrete core.
3. Steel-concrete interface: The bond behavior between the steel tube and recycled concrete should be considered, as slippage can affect load transfer and overall column performance.
4. Material model selection: Appropriate constitutive models for recycled concrete are essential, as the stress-strain behavior of RAC differs from conventional concrete, particularly in terms of peak strength and post-peak ductility.

Engineering Implications

The findings have significant implications for the sustainable design of composite columns:

• The minimal influence of recycled aggregate replacement rate on load capacity suggests that high replacement rates can be adopted without compromising structural performance, supporting waste reduction goals.
• The significant influence of D/t ratio, steel reinforcement ratio, and slenderness ratio highlights the importance of these parameters in design optimization.
• The validated OpenSees modeling approach provides a reliable tool for parametric studies and design exploration of RCRC composite columns.
• The results support the feasibility of using recycled aggregate concrete in composite columns, contributing to the circular economy in construction.

Study Insights and Reflections

This research demonstrates the effectiveness of OpenSees as a tool for nonlinear analysis of composite columns incorporating recycled materials. The fiber-based modeling approach, while computationally efficient, requires careful attention to material constitutive models and mesh discretization to achieve accurate results. The finding that recycled aggregate replacement rate has minimal effect on load capacity is encouraging for sustainable construction practices, as it suggests that structural performance can be maintained even with substantial use of recycled materials. For practicing engineers, this work provides validated analytical tools and parametric insights that can inform the design of composite columns utilizing recycled aggregate concrete, contributing to more sustainable structural engineering practices.