Actividades formativas

Seminario: Size Effect in Concrete Strength: Deterministic and Probabilistic Influences

Lugar: Salón de Grados, Escuela Técnica Superior de Ingeniería, Universidad de Sevilla.

Fecha y hora: 18 de noviembre de 2024, de 16:30 a 17:30 horas.

Organiza: Programa de Doctorado en Ingeniería Mecánica y de Organización Industrial, Universidad de Sevilla. 

Financia: 4º Plan Propio de Docencia

 
Prof. Miroslav Vorechovsky
Institute of Structural Mechanics, Faculty of Civil Engineering,
Brno University of Technology
Concrete is a heterogeneous material whose strength is significantly influenced by the size effect, reflecting how the nominal strength of a structure varies with its dimensions. This lecture will explore the energy-based deterministic size effect, which stems from stress redistribution occurring during the failure process before the peak load is reached. Identifying the characteristic length scale, related to material stiffness, small-scale strength, and fracture energy, is crucial for predicting the maximum load-carrying capacity of concrete structures. This length scale, combined with the stress state configuration, plays a dominant role in strength predictions. However, material strength also exhibits spatial randomness, introducing a probabilistic size effect. Larger structures are more likely to contain weak zones, further reducing their nominal strength. The length scale governing spatial variability, particularly the autocorrelation length of a random field modeling the material’s variability, becomes essential in this context. Both stress redistribution and spatial variability are interconnected, together influencing the statistical strength of concrete structures. This lecture will present continuous and discrete models that incorporate spatial variability, enabling probabilistic predictions of structural responses. Additionally, an analytical model for the statistical strength of heterogeneous materials will be discussed as a potential substitute for computationally expensive Monte Carlo simulations.
 
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