Calibration of the numerical model of a freight railway vehicle based on experimental modal parameters

• Type: Article in International Scientific Journal
• Date: 2022-04

Authors

Diogo Ribeiro (Author) FEUP; Cássio Braganca (Author) Other; C. Costa (Author) Other; Pedro Jorge (Author) FEUP; Rúben Silva (Author) FEUP; António Arêde (Author) FEUP; Rui Calçada (Author) FEUP

Journal

Title: Structures

Vol. 38

Pages: 108-122

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 7 Citations

ISI Web of Science

Scopus - 8 Citations

Scientific classification

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

FOS: Engineering and technology > Civil engineering

Other information

Authenticus ID: P-00W-3XZ

DOI: 10.1016/j.istruc.2022.01.085

Subject: Calibration of the numerical model of a freight railway vehicle based on experimental modal parameters

Abstract (EN): The simulation of the dynamic behavior of the train-track system is strongly dependent on the accuracy of the numerical models of the train and track subsystems. The use of calibrated numerical models of the railway vehicles, based on experimental data, enhances their ability to correctly reproduce the dynamic responses of the train under operational conditions. In this scope, studies involving the experimental calibration of freight wagon models are still scarce. This article aims to fill this gap by presenting an efficient methodology for the calibration of a numerical model of a freight railway wagon based on experimental modal parameters. A dynamic test was performed during the unloading operation of the train, adopting a dedicated approach which does not interfere with its tight operational schedule. From data collected during the dynamic test, five natural frequencies and mode shapes associated with rigid-body and flexural movements of the wagon platform were identified through the Enhanced Frequency-Domain Decomposition (EFDD) method. A detailed 3D finite-element (FE) model of the loaded freight wagon was developed, requiring precise knowledge of the vehicle design details which, in most situations, are difficult to obtain due to confidentiality reasons of the manufacturers. The model calibration was performed through an iterative method based on a genetic algorithm and allowed to obtain optimal values for seven numerical parameters related to the suspension's stiffnesses and mass distribution. The stability of the parameters considering different initial populations demonstrated the robustness of the optimization algorithm. The average error of the natural frequencies decreased from 8.5% before calibration to 3.2% after calibration, and the average MAC values improved from 0.911 to 0.950, revealing a significant improvement of the initial numerical model.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15