A novel hybrid model to design fiber-reinforced shotcrete for tunnel linings

Abstract

This article proposes a workflow to design fiber-reinforced shotcrete (FRS) for tunnel linings. The workflow is divided into two major stages: artificial neural network (ANN) development for predicting the composite toughness, and tunnel lining design through numerical modeling. First, an artificial neural network was developed to predict FRS toughness from ASTM C1550 and EN 14488–5 panels, with concrete strength and fiber characteristics as input parameters. An extensive literature review was developed to build a database gathering the relevant FRS properties for this work. The second part of this research consisted of developing an elastoplastic finite element model to design a steel fiber-reinforced tunnel lining application. Parameters from a real case study of a circular tunnel were taken from the literature to calibrate the proposed computational model. The model results are compared to analytical solutions and indicate good agreement. In this sense, the workflow is an alternative for designing fiber-reinforced shotcrete for tunnel linings.