Towards a Digital Twin Approach for Structural Stiffness Assessment: A Case Study on the Cho’ponota L1 Bridge


OKUR F. Y.

Applied Sciences (Switzerland), cilt.15, sa.12, 2025 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 15 Sayı: 12
  • Basım Tarihi: 2025
  • Doi Numarası: 10.3390/app15126854
  • Dergi Adı: Applied Sciences (Switzerland)
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Agricultural & Environmental Science Database, Applied Science & Technology Source, Communication Abstracts, INSPEC, Metadex, Directory of Open Access Journals, Civil Engineering Abstracts
  • Anahtar Kelimeler: digital twin, dynamic amplification factor, dynamic characteristics, operational modal analysis, static-dynamic vehicle load test
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

In this study, a series of comprehensive experimental tests were conducted to assess the impact of permanent displacements observed during the construction of the Cho’ponota L1 Bridge in Uzbekistan and to evaluate the bridge’s structural suitability for service. The investigation included Operational Modal Analysis and static and dynamic vehicular load tests, conducted using two trucks with different weights under varying loading scenarios and speeds. A total of 28 static and 24 dynamic load cases were tested across the bridge’s four spans. Displacement measurements were acquired using geodetic instruments during the static tests, while acceleration data were recorded during dynamic tests using high-sensitivity accelerometers, from which Dynamic Amplification Factors were calculated. The results indicated that all displacement values remained within permissible safety limits, and no visible damage or cracking was detected. Beyond conventional analysis, the study proposed a test-assisted digital twin framework in which high-fidelity field data were integrated into a finite-element model. The initial numerical model was calibrated using modal properties obtained from OMA, and discrepancies were minimized through iterative updates to material parameters, especially concrete stiffness. The resulting validated digital twin accurately reflects the bridge’s current structural condition and can be used for future predictive simulations and performance-based evaluations. The findings underscore the effectiveness of combining non-destructive testing with digital twin methodology in diagnosing structural behavior and offer a replicable model for assessing bridges experiencing construction-related anomalies.