COUPLED 2025

Stochastic Finite Element Analysis of a Multiphysics Model for Heated Concrete

  • Apostolopoulos, Panagiotis (The University of Sheffield)
  • Guadagnini, Maurizio (The University of Sheffield)
  • Huang, Shan-Shan (The University of Sheffield)
  • Dal Pont, Stefano (Université Grenoble Alpes)
  • Baroth, Julien (Université Grenoble Alpes)
  • Torelli, Giacomo (The University of Sheffield)

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The behaviour of concrete at elevated temperatures has garnered significant research attention, driven by the grave risks that fire poses to the integrity of concrete structures. Among these concerns, heat-induced spalling stands out as a critical phenomenon, wherein fragments of varying sizes are violently expelled from the surface of structural elements during rapid heating. This alarming issue underscores the urgent need for a more profound understanding of spalling and its ramifications for structural stability. Despite extensive experimental studies and the advancement of numerical models aimed at simulating concrete's response to high temperatures, a comprehensive grasp of the subject remains elusive. This challenge stems from the complex interplay of coupled thermal, hygral, chemical, and mechanical processes that unfold simultaneously during intense heating. Adding to this complexity is the inherently stochastic nature of concrete as a material and the multifaceted nature of spalling, which is influenced by both internal material properties and external factors. These factors collectively amplify the uncertainties associated with predicting spalling behaviour. To address these challenges, a coupled thermo-hygral finite element numerical model was developed to simulate heat transfer and mass transport in heated concrete. This model enables the prediction of temperature and pore pressure distributions. To validate these predictions, complementary high-temperature experiments were conducted, capturing these variables at various specimen locations. A stochastic analysis further evaluated the model's reliability and accuracy for both spalled and non-spalled specimens under identical heating conditions. Results revealed that permeability is the most critical parameter, accounting for a significant proportion of the total variance in pore pressure predictions. Thus, precise characterization of permeability in numerical models is paramount to reducing uncertainties in pore pressure estimation. This research contributes valuable insights into the high-temperature behaviour of concrete, offering enhanced spalling predictions and fostering improved structural safety in fire scenarios.