LS-DYNA: Simulating Cyclic Test for A Reinforced Concrete Column Using an Implicit Solver

Cyclic testing is an essential method for assessing the structural performance of reinforced concrete (RC) columns under repeated loading conditions, such as those encountered during earthquakes. However, simulating these tests using finite element analysis (FEM) presents significant challenges due to the complex nonlinear behavior of concrete. Even experienced professionals often find it difficult to achieve accurate representations in FEM software. This tutorial provides a detailed step-by-step guide on modeling cyclic tests for RC columns in LS-DYNA using an implicit solver. The main objective is to evaluate the column’s strength, ductility, and energy dissipation capacity. The tutorial covers crucial aspects, including constructing the geometric model of the column and reinforcement, defining nonlinear material properties for both concrete and reinforcement, setting up boundary conditions, applying cyclic loading, and exporting the final results. Furthermore, the video tutorial explains how to modularize LS-DYNA models to improve reusability and efficiency in the modeling process. It also introduces the KCC Model Input Generator, a tool developed by the author to automate the definition of the KCC model—an otherwise complex and time-consuming task due to its numerous parameters. 🔹 Download the the KCC Model Input Generator for free: https://zenodo.org/records/14877821 🔹 LS-DYNA Model : https://github.com/tranhan1405/Cyclic... For a detailed understanding of the KCC concrete model, please refer to: 👉 Wu, Y., & Crawford, J. E. (2015).Numerical modeling of concrete using a partially associative plasticity model. Journal of Engineering Mechanics, 141(12), 04015051. 👉Thai, D. K., Nguyen, D. L., & Nguyen, D. D. (2020). A calibration of the material model for FRC. Construction and Building Materials, 254, 119293. 📌 If you find this tool useful, please consider citing it: Tran, V. H. (2025). KCC Model Input Generator. Zenodo. DOI: 10.5281/zenodo.14877821