Cornaggia, A., Garbowski, T., Cocchetti, G., Ferrari, R., & Rizzi, E. (2023). Optimised structural modelling for Inverse Analysis parameter identification relying on dynamic measurements. In Eccomas Proceedia ID: 10715/Conference Proceeding ID: 20669 (pp. 4234-4248). Eccomas Proceedia.
Cornaggia, A., Garbowski, T., Cocchetti, G., Ferrari, R., & Rizzi, E. (2023). Optimised structural modelling for Inverse Analysis parameter identification relying on dynamic measurements. In Eccomas Proceedia ID: 10715/Conference Proceeding ID: 20669 (pp. 4234-4248). Eccomas Proceedia.
Cornaggia, A., Garbowski, T., Cocchetti, G., Ferrari, R., & Rizzi, E. (2023). Optimised structural modelling for Inverse Analysis parameter identification relying on dynamic measurements. In Eccomas Proceedia ID: 10715/Conference Proceeding ID: 20669 (pp. 4234-4248). Eccomas Proceedia.
Cornaggia, A., Garbowski, T., Cocchetti, G., Ferrari, R., & Rizzi, E. (2023). Optimised structural modelling for Inverse Analysis parameter identification relying on dynamic measurements. In Eccomas Proceedia ID: 10715/Conference Proceeding ID: 20669 (pp. 4234-4248). Eccomas Proceedia.
Abstract
In the context of Inverse Analysis in Civil Engineering, parameter identification and model calibration, of a structural system, relying on dynamic measurements, are subjects of a growing research interest. In the present contribution, the topic is tackled with reference both to simplified structural numerical examples and to a specific case study, namely a historical road three-span reinforced concrete arched bridge, with vibrational data previously acquired by standard wired accelerometers on the deck, under operational traffic conditions. In particular, the present work aims at focussing on the identification issues, concerning the definition of a maximum allowable threshold number of sought material parameters (e.g., Young’s moduli and mass densities of different structural components), with respect to the amount of available measurement data, and the investigation of the inverse analysis discrepancy function to be optimised, in order to set the intrinsic issue of multiple “realizations”, in case of a plain use of modal properties, and in view of forming a well–posed optimisation problem. Structural modelling, sensitivity analysis and numerical optimisation approaches are herein combined toward a robust and efficient identification strategy, to be effectively employed in structural assessment and diagnosis, also with respect to originally available or enriched sets of experimental data. The proposed methodology, and collected results, shall outline an efficient identification procedure, in view of automated inverse analysis, practically oriented to the dynamic assessment and structural diagnosis in the Civil Engineering context, as applied e.g. to strategic bridge infrastructures.
Copyright:
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