A simulation-based and data-augmented shear force inversion method for offshore platform connector

Tao Zhang, Selda Oterkus, Erkan Oterkus, Jiajun Hu, Xueliang Wang, Fang Wang

Research output: Contribution to journalArticlepeer-review

Abstract

This study introduces a Simulation-Based and Data-Augmented method for shear force inversion to address the challenge of directly measuring shear force on connector pins in multi-module floating platforms. Stress sensors are strategically placed in adjacent areas. Extensive Finite Element simulation scenarios lead to the identification of optimal features sensitive to both force magnitude and direction. Subsequently, an Artificial Neural Network (ANN) is developed to distill the simulation data into characteristic sensor responses. Fine-tuning with physical measurements further enhances shear force inversion accuracy. Using simulated and experimental data, the method demonstrates a shear force inversion error below 3.2% and an angular inversion error under 1.4% across test conditions. This methodology provides essential load data for connector safety assessments and crucial guidelines for the assembly of multimodule floating platforms.
Original languageEnglish
Article number103577
Number of pages20
JournalMarine Structures
Volume95
Early online date29 Jan 2024
DOIs
Publication statusPublished - May 2024

Keywords

  • offshore platform
  • connector pin
  • shear force inversion
  • ANN
  • simulation-based and data-augmented

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