Numerical Investigation of a Concrete Material Model for Ultra-High Performance Concrete


Elzaıny A., Girgin S. C., Yalçınkaya Ç.

3rd International Civil Engineering and Architecture Conference (ICEARC'23), Trabzon, Turkey, 12 - 14 October 2023, pp.1-10

  • Publication Type: Conference Paper / Full Text
  • City: Trabzon
  • Country: Turkey
  • Page Numbers: pp.1-10
  • Dokuz Eylül University Affiliated: Yes

Abstract

Purpose: A finite element model consisting of a single element is used to calibrate and validate the Karagozian & Case material model in LS-Dyna for Ultra-High Performance Concrete (UHPC) and compare it to the results from the literature to determine the accuracy of the material model to be used for more complex finite element models.

Study design/methodology/approach: a partially fixed single solid hexahedra element is used to capture and validate the behavior of the Karagozian & Case (KCC) material model in LS-Dyna under monotonic compression. The results will be validated using experimental data to determine the accuracy of the material model in question. Furthermore, further validation of the calibrated KCC model is carried out through a case study conducted on a single concrete column.

Findings: The parameters auto-generation capability of the KCC material model can produce acceptable results for normal-strength concrete. However, this model needs to be calibrated to provide reliable results for UHPC. The calibration procedure is carried out by using an empirical stress-strain model specifically proposed for UHPC and Ultra-High Performance Fiber Reinforced Concrete (UHPFRC). Based on the analysis results, the calibrated material model is proven to capture the actual behavior of UHPC with acceptable accuracy.

Originality/value: Finite element results rely on numerous parameters. The calibration and validation of the KCC material model in this study is an important step before commencing more complex finite element models. The same calibration procedure present in this study can be followed in more complex models to predict UHPC behavior.