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    Shear strength code models uncertainties assessment based on probabilistic simulation
    (Wiley, 2025-09-05) Novák, Drahomír; Večeře, Jakub; Sadílková Šomodíková, Martina; Kotynia, Renata
    In the paper, a shear strength probabilistic assessment of concrete members with steel reinforcement is performed. The shear strength is analyzed by modelling with lowfidelity models – analytical formulas based on two main approaches to predict the shear strength of reinforced concrete beams with and without shear reinforcement: the modified compression field theory and the truss model. Based on a comparison of these lowfidelity analytical models and experimental data, model uncertainties can be evaluated. The aim of the analysis performed is to verify the existing code analytical formulas for shear strength calculation using stochastic models, to perform uncertainty propagation, sensitivity analysis and model uncertainty assessment. The code models of EN 199211, ACI 318 and fib Model Code 2010 are examined with respect to uncertainties involved and the reliability of the design value determination.
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    Simulation of tri-axial stress redistribution effect in concrete under fatigue loading: lattice discrete model vs. microplane model
    (CIMNE, 2024-10-29) Aguilar Rueda, Mario; Vořechovský, Miroslav; BAKTHEER, Abedulgader; Wan-Wendner, Roman; Vorel, Jan; Chudoba, Rostislav
    Adaptive sequential sampling provides a good technique to refine and increase the accuracy of surrogate models, used for reliability analysis, based on the selection of possible future candidates in the input domain (i.e., random variables). In the present research, different methodologies for obtaining the training sample for a surrogate model were explored, considering sample size, distribution of the points, and identification of the failure region. The effects on the reliability of the slope stability under vertical loading based on the safety factors from Bishop’s simplified method were obtained. The results reinforce the importance of the characteristics of the training sample used for the application of surrogate models to describe limit states and their accuracy when employed for the computation of the reliability index.
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    Quantifying Uncertainty in Steel Member Reliability via Global Sensitivity Indices
    (2025-09-05) Omishore, Abayomi; Puklický, Libor; Kala, Zdeněk
    The study presents a comprehensive global sensitivity investigation focusing on the failure probability in torsion-loaded thin-walled steel members with uncertainties in material, geometric, and loading parameters. Two distinct sensitivity measures are scrutinised: one formulated through variance analysis of a binary failure outcome and the other based on discrete entropy. Total-effect indices, encompassing all interaction orders, are employed to assess variable importance. The results indicate that the long-term variable load significantly influences the uncertainty in structural reliability, while material and geometric parameters play a secondary role. The entropy-based measure accentuates the distinction between dominant and less influential inputs, while the variance-based approach captures a broader sensitivity structure. The findings underscore the impact of the selected sensitivity metric on input ranking and its implications for reliability assessment.
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    Support vector machines in reliability calculations of engineering structures
    (CRC Press, 2025-08-07) Sadílková Šomodíková, Martina; Lehký, David
    In the paper, a metamodeling approach based on support vector regression is studied as a promising tool in the assessment of reliability level. The method consists of two steps: firstly, an approximation of the original limit state function is performed, and in the second step a failure probability or reliability index is calculated with a simpler, approximated function using traditional simulation techniques. Two problems with explicit limit state functions are used to study the effectivity of the method. In order to be as effective as possible with respect to computational effort, a stratified Latin Hypercube Sampling simulation method is utilized to properly select training set elements. The accuracy of the method is analyzed and compared with other surrogate modeling methods, namely the polynomial- and artificial neural network-based response surface method, achieving comparable results.
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    Fractal Dimension Analysis of Three-Point Bending Concrete Test Specimens
    (EDP Sciences, 2020-10-05) Sobek, Jakub; Frantík, Petr; Trčka, Tomáš; Lehký, David
    The paper deals with the analysis of the fractal dimension of fracture surfaces of concrete specimens tested in a three-point bending configuration. Fifteen representative specimens were chosen out of a bigger set for the fractal dimension analysis. Their fracture surfaces were scanned by 2D optical profilometry and analysed by the FracDiM software created in the Java programming language. The resulting values of fractal dimensions for specimens of three different sizes are presented.