Numerical simulations of experimental material testing in stone masonry arch railway bridges

• Type: Article in International Scientific Journal
• Date: 2022-09-12

Authors

Rúben Silva (Author) Other; C. Costa (Author) Other; António Arêde (Author) FEUP; Diogo Ribeiro (Author) FEUP

Journal

Title: Structure and Infrastructure Engineering

Pages: 1-20

ISSN: 1573-2479

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 0 Citations

ISI Web of Science

Scopus

Scientific classification

CORDIS: Technological sciences > Engineering > Civil engineering > Structural engineering

FOS: Engineering and technology > Civil engineering

Other information

Authenticus ID: P-00X-7XW

DOI: 10.1080/15732479.2022.2119585

Subject: Numerical simulations of experimental material testing in stone masonry arch railway bridges

Abstract (EN): This paper reports on a numerical study focused on the characterization of the masonry and infill material behaviour of stone arch railway bridges. The study is based on experimental data from testing campaigns carried out in materials of two granite stone bridges. The campaigns comprise lab tests on stone masonry samples (blocks and joints) collected from the bridge structure, as well as in-situ flat-jack testing and Menard pressuremeter tests on masonry and infill components, respectively. A strategy was developed resorting to Finite Element (FE) methodologies involving local scale numerical simulation of the joint lab tests (shear tests) and both in-situ tests (Flat-jack and Menard pressuremeter tests), aiming at the calibration and validation of the material parameters to be used in global scale numerical simulations of the bridges' structural behaviour. The joint shear behaviour is simulated using a FE discrete formulation based on contact elements whereas the Flat-jack and Menard pressuremeter testing is simulated using FE continuous homogeneous nonlinear materials based on a Drucker-Prager (D-P) model. The calibration of the D-P model input parameters is performed through a sensitivity analysis followed by an optimization strategy based on a genetic algorithm. The methodology showed the potential to calibrate the material constitutive parameters to be adopted in FE numerical models of this type of bridge.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 20