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Proceedings of the 10th International Operational Modal Analysis Conference (IOMAC 2024) [electronic resource] : Volume 1 / edited by Carlo Rainieri, Carmelo Gentile, Manuel Aenlle López.

Contributor(s): Material type: TextSeries: Lecture Notes in Civil Engineering ; 514Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024Description: XVI, 742 p. 496 illus., 443 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031614217
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • TA401-492
Online resources:
In: Springer Nature eBookSummary: This volume gathers the latest advances and innovations in the field of operational modal analysis and structural health monitoring, as presented at the 10th International Operational Modal Analysis Conference (IOMAC), held in Naples, Italy on May 22-24, 2024. The contributions cover a diverse range of topics, including AI for data interpretation, automatic modal parameter estimation, Digital Twin, modal testing methods, instrumentation and case studies, model correlation and updating, modal-based SHM, modal mass estimation. Selected by means of a rigorous peer-review process, they will spur novel research directions and foster future multidisciplinary collaborations.
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
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This volume gathers the latest advances and innovations in the field of operational modal analysis and structural health monitoring, as presented at the 10th International Operational Modal Analysis Conference (IOMAC), held in Naples, Italy on May 22-24, 2024. The contributions cover a diverse range of topics, including AI for data interpretation, automatic modal parameter estimation, Digital Twin, modal testing methods, instrumentation and case studies, model correlation and updating, modal-based SHM, modal mass estimation. Selected by means of a rigorous peer-review process, they will spur novel research directions and foster future multidisciplinary collaborations.

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