Stochastic properties of bond-slip parameters at fibre pull-out. (April 2020)

• Record Type: Journal Article
• Authors: Kožar, Ivica; Torić Malić, Neira; Simonetti, Danijel; Božić, Željko
• Is Part Of: Engineering failure analysis. Volume 111(2020)
• Publication Date: 2020-04
• Subjects: Fibre reinforced concrete -- Bond-slip model -- Failure mechanism/analysis -- Fracture -- Mechanical testing -- Probability -- Tensile properties -- Inverse model -- Parameter estimation; System failures (Engineering) -- Periodicals; Fracture mechanics -- Periodicals; Reliability (Engineering) -- Periodicals; Pannes -- Périodiques; Rupture, Mécanique de la -- Périodiques; Fiabilité -- Périodiques; Fracture mechanics; Reliability (Engineering); System failures (Engineering); Periodicals; Electronic journals; 620.112
• DOI: 10.1016/j.engfailanal.2020.104478
• Languages: English
• ISSNs: 1350-6307

Abstract

Highlights: Fiber reinforced concrete failure happens through fiber pull-out. Fiber-concrete bond-slip behaviour strongly influences the failure. Fibre bundle model successfully describe bond-slip in pull-out experiments. Parameter estimation from experimental data can be performed on averaged curve. Averaging of data curves could be successfully done using factor analysis. Abstract: This paper is a continuation of our work on modelling and parameter identification in fibre reinforced concrete with steel fibres. The main characteristic of this material in failure is that fibres do not break but get pulled-out of the concrete matrix and the bond between the fibre and the matrix (bond-slip law) strongly influences the behaviour in failure. We are presenting results of a series of experiments of pulling-out of a fibre from a concrete block and their comparison with Monte Carlo simulations. The model for Monte Carlo simulation is based on the fibre bundle model with stochastic and deterministic parameters that are determined from experimental results. The devised inverse procedure enables successful estimation of both stochastic and deterministic parameters simultaneously. We have demonstrated that the averaging procedure can be applied on the experimental results and the averaged data could then be used for parameter estimation. Novel application of the factor analysis on experimental results demonstrates that it is equivalent to the averaging procedure.