Non-parametric data processing in experimental studies of spirally reinforced concrete samples

Introduction. Statistical methods in the analysis of experimental data can be applied to identify patterns and test hypotheses, determine the quality of experimental data and draw conclusions based on objective data. In addition, experimental data after non-parametric processing can be used in numerical modeling using contemporary computing suites.Aim. To outline a methodology for non-parametric processing of experimental results using SCAD computing suite tools, certified in the territory of the Russian Federation. In the proposed methodology, experimental test data for spirally reinforced concrete samples of various strengths were used.Results. As a result of non-parametric processing of spirally reinforced concrete samples, empirical coefficients of the Prandtl bilinear diagram were determined according to the proposed method. This diagram is used in the SCAD computing suite to set the physical nonlinearity of the material behavior. A method for processing a small volume of experimental results is proposed for using the available data in SCAD CS numerical studies with an acceptable level of probability.Conclusions. The empirical coefficients, obtained in non-parametric processing for setting the Prandtl bilinear diagram, can be used to perform a numerical modeling of the sample bahavior for planning further experimental studies in order to find more general patterns, taking into account other behavioral factors of real structural elements in load-bearing systems of buildings and structures with spiral reinforcement, including high-intensity dynamic effects. According to experimental and theoretical studies, spiral reinforcement can significantly increase the deformability and energy capacity of reinforced concrete structures, which fundamentally affects the behavioral pattern of structures and supporting framework of buildings and structures as a whole. These behavioral features of spirally reinforced structures can be further taken into account for the computational justification of design solutions in the SCAD CS and other software programs using the Padé approximation of the Prandtl bilinear diagram.