Miroslav Vorechovský

Learn More
An improved form of a recently derived energetic-statistical formula for size effect on the strength of quasibrittle structures failing at crack initiation is presented and exploited to perform stochastic structural analysis without the burden of stochastic nonlinear finite-element simulations. The characteristic length for the statistical term in this(More)
SUMMARY The paper presents a model that extends the stochastic finite element method to the modelling of transitional energetic–statistical size effect in unnotched quasibrittle structures of positive geometry (i.e. failing at the start of macro-crack growth), and to the low probability tail of structural strength distribution, important for safe design.(More)
Keywords: Statistical analysis Sensitivity Reliability Monte Carlo simulation Latin Hypercube Sampling Simulated annealing Random fields Material degradation a b s t r a c t The objective of the paper is to present methods and software for the efficient statistical, sensitivity and reliability assessment of engineering problems. Attention is given to(More)
In this article, a novel method for the extension of sample size in Latin Hypercube Sampling (LHS) is suggested. The method can be applied when an initial LH design is employed for the analysis of functions g of a random vector. The article explains how the statistical , sensitivity and reliability analyses of g can be divided into a hierarchical sequence(More)
Keywords: Discrete model Lattice-particle models Energy dissipation Statistical methods Size effect Fracture testing Notch depth effect Concrete structures a b s t r a c t The paper presents a discrete meso-scale model for fracture of concrete taking into account random spatial variability of material parameters. Beams of various sizes, with notches of(More)
In this paper, we suggest principles of a novel simulation method for analyses of functions g (X) of a random vector X, suitable for the cases when the evaluation of g (X) is very expensive. The method is based on Latin Hypercube Sampling strategy. The paper explains how the statistical, sensitivity and reliability analysis of g (X) can be divided into a(More)
  • 1