%0 Journal Article %T Fiber-reinforced Cementitious Composite: Sensitivity Analysis and Parameter Identification  %J Advanced Materials Letters %I International Association of Advanced Materials %Z 0976-3961 %A Novák, Drahomír %A Lehký, David %A Pukl, Radomír %D 2020 %\ 03/01/2020 %V 11 %N 3 %P 1-5 %! Fiber-reinforced Cementitious Composite: Sensitivity Analysis and Parameter Identification  %K fiber %K reinforced cementitious composite %K Concrete %K nonlinear modeling %K Sensitivity analysis %R 10.5185/amlett.2020.031488 %X Methods and software tools used to identify the material parameters of high-performance cementitious composites are presented. The aim is to provide techniques for the advanced assessment of the mechanical fracture properties of these materials, and the subsequent numerical simulation of components/structures made from them. The paper describes the development of computational and material models utilized for efficient material parameter determination with regards to a studied composite. This determination is performed with the help of experimental data from four-point bending tests. The data is used in inverse analysis based on artificial neural networks. Sensitivity analysis plays an important role in the process. It is a part of a complex methodology for the statistical and reliability analysis of structures made of high-performance cementitious composites. The procedure also utilizes statistical simulation of the Monte Carlo type for the preparation of a training set for the artificial neural network utilized in the material parameter identification process. In the case of fiber-reinforced concrete, the simulation mainly includes tensile strength, modulus of elasticity and the parameters of the tensile softening model. %U https://aml.iaamonline.org/article_13969_fa91df636de09352a972676d9cac3a2e.pdf