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I. Bravo^1,2, A. Astiazaran^1,2, J. Nieto^1,2 and P. Ciáurriz^1,2

¹, Ceit-Basque Research and Technology Alliance (BRTA), Donostia – San Sebastián, Spain
²Tecnun, Universidad de Navarra, Donostia – San Sebastián, Spain

doi:10.4203/ccc.15.18.8

I. Bravo, A. Astiazaran, J. Nieto, P. Ciáurriz, "Iterative Finite Element Model Validation of a Railway Track System through Experimental-Numerical Modal Correlation", in J. Pombo, (Editor), "Proceedings of the Seventh International Conference on Railway Technology: Research, Development and Maintenance ", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 15, Paper 18.8, 2026, doi:10.4203/ccc.15.18.8

Keywords: railway infrastructure, experimental modal analysis, parameter identification, structural dynamics, finite element model calibration, modal assurance criterion.

Abstract

This article describes a specialized computational framework designed to automate the calibration of Finite Element Models for railway infrastructure. By integrating MATLAB's optimization tools with Abaqus software, the system iteratively adjusts stiffness parameters for ballast and rail pads to match experimental vibration data. The methodology employs the Modal Assurance Criterion and the optimization algorithms to minimize discrepancies between numerical predictions and real-world measurements. A multi-start strategy is implemented to ensure that the calibration process converges toward global rather than local minima. Detailed architectural diagrams and technical analyses illustrate a modular hierarchy of scripts that handle everything from data normalization to the automated execution of simulation macros. Ultimately, this framework provides a high-precision tool for ensuring the structural integrity and dynamic fidelity of critical rail transport models.

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Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 15 PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 18.8 Iterative Finite Element Model Validation of a Railway Track System through Experimental-Numerical Modal Correlation I. Bravo^1,2, A. Astiazaran^1,2, J. Nieto^1,2 and P. Ciáurriz^1,2 ¹, Ceit-Basque Research and Technology Alliance (BRTA), Donostia – San Sebastián, Spain ²Tecnun, Universidad de Navarra, Donostia – San Sebastián, Spain doi:10.4203/ccc.15.18.8 Full Bibliographic Reference for this paper I. Bravo, A. Astiazaran, J. Nieto, P. Ciáurriz, "Iterative Finite Element Model Validation of a Railway Track System through Experimental-Numerical Modal Correlation", in J. Pombo, (Editor), "Proceedings of the Seventh International Conference on Railway Technology: Research, Development and Maintenance ", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 15, Paper 18.8, 2026, doi:10.4203/ccc.15.18.8 Keywords: railway infrastructure, experimental modal analysis, parameter identification, structural dynamics, finite element model calibration, modal assurance criterion. Abstract This article describes a specialized computational framework designed to automate the calibration of Finite Element Models for railway infrastructure. By integrating MATLAB's optimization tools with Abaqus software, the system iteratively adjusts stiffness parameters for ballast and rail pads to match experimental vibration data. The methodology employs the Modal Assurance Criterion and the optimization algorithms to minimize discrepancies between numerical predictions and real-world measurements. A multi-start strategy is implemented to ensure that the calibration process converges toward global rather than local minima. Detailed architectural diagrams and technical analyses illustrate a modular hierarchy of scripts that handle everything from data normalization to the automated execution of simulation macros. Ultimately, this framework provides a high-precision tool for ensuring the structural integrity and dynamic fidelity of critical rail transport models. download the full-text of this paper (PDF, 13 pages, 944 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
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