PSI - Issue 73

Kateřina Matýsková et al. / Procedia Structural Integrity 73 (2025) 100 – 105 Kateřina Matýsková, Marie Horňáková / Structural Integrity Procedia 00 (2025) 000 – 000

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highest decrease can be observed in the case of fracture energy. This difference arises because experimental fracture energy includes all sources of energy dissipation in the specimen, while in the numerical model fracture energy is an effective material parameter in the constitutive law. In this case, it was identified by inverse analysis, so it is calibrated to reproduce the observed response rather than directly equal to the measured value. The discrepancy reflects the difference between a physical test result and the simplified constitutive representation used in the numerical model. 5. Conclusions In this article, experiments were carried out to obtain a description of the mechanical properties of a concrete mix in which the fine aggregate was replaced by waste material from the production of CETRIS boards. The measured data were used for a numerical model of three-point bending test to define more accurately the concrete’s fracture parameters by inverse analysis. The inverse analysis was performed using SARA software, which allows for a stochastic description of parameters. In this software, the tensile strength, modulus of elasticity and fracture energy were described using normal distribution (by mean value and standard deviation) and the LHS method with the mean selection of variables was used for simulations. By adjusting the input data according to the simulation results, a very similar pattern of force versus strain was achieved to the measured values. The similarity of the plots was assessed visually and by the simplified sum of squares method. Although this inverse analysis is automated using SARA software, it is still a very time-consuming process. A further possible research direction might be the use of other types of statistical distributions of input parameters or the description of multiple input parameters using histograms or random distributions, their influence could then be detected by sensitivity analysis, as well as the definition of fracture parameters for mixtures where a different percentage of raw material was replaced by this waste material. Acknowledgements This research and this paper were funded by the Ministry of Education, Youth and Sports of the Czech Republic in Student Grant Competition through VSB – Technical University of Ostrava – grant number: SGS SP2025/068. References Červenka, J., Papanikolaou, V.K., 2008. Three dimensional combined fracture – plastic material model for concrete. International Journal of Plasticity 24, 2192 – 2220. https://doi.org/10.1016/j.ijplas.2008.01.004 EN 196-1, 2016. EN 196-1. Methods of testing cement: Determination of strength. https://doi.org/10.3403/30291447 EN 12390-7:2019, 2019. EN 12390-7:2019 Testing hardened concrete – Part 7: Density of hardened concrete. https://doi.org/10.3403/30360085 ISO 1920-10, 2010. ISO 1920-10. Testing of concrete – Part 10: Determination of static modulus of elasticity in compression. Karihaloo, B.L., Nallathambi, P., 1990. Effective crack model for the determination of fracture toughness of concrete. Engineering Fracture Mechanics 35, 637 – 645. https://doi.org/10.1016/0013-7944(90)90146-8 Khalilpour, S., BaniAsad, E., Dehestani, M., 2019. A review on concrete fracture energy and effective parameters. Cement and Concrete Research 120, 294 – 321. https://doi.org/10.1016/j.cemconres.2019.03.013 Matýsková, K., Bílek, V., Horňáková, M., Bujdoš, D., n.d. Mechanical characteristics of high -performance concretes with substitution of fine aggregate by waste material from CETRIS Boards Production. 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