Application of optimal experiment design method to detect the ideal sensor positions: A case study of Milan metro line 5. (December 2022)

• Record Type: Journal Article
• Authors: Schoen, Maximilian; Hölter, Raoul; Boldini, Daniela; Alimardani Lavasan, Arash
• Is Part Of: Tunnelling and underground space technology. Volume 130(2022)
• Publication Date: 2022-12
• Subjects: Mechanized tunneling -- Sensitivity analysis -- Optimization -- Milan metro line 5 -- Numerical Simulation -- Optimal experimental design -- Metamodeling; Tunneling -- Periodicals; Underground construction -- Periodicals; Tunnels -- Periodicals; Underground areas -- Periodicals; 624.193
• DOI: 10.1016/j.tust.2022.104723
• Languages: English
• ISSNs: 0886-7798

Abstract

Highlights: Monitoring design for efficient parameter identification via inverse analysis. Spatial and temporal sensitivity analysis for soil-structure interaction. Uncertainty reduction in parameters identification without expert knowledge. Abstract: This paper proposes a concept of optimal experimental design (OED) to enable an efficient parameter identification through an inverse analysis and to design an optimized monitoring set up. This method intends to provide a systematic and reproducible approach for parameter determination in mechanized tunnel modelling from field measurements during excavation. In this concept, identification of most relevant parameters is followed by a secondary spatial and temporal global sensitivity analyses in various time scales to find the most relevant positions in the existing monitoring set-up for parameter identification. To afford the computational costs, metamodeling approach was employed to substitute the FE model with a response surface function. To validate the numerical model and to justify the applicability of this concept for a real case, the measured tunnel-induced settlements in a shallow founded nine-storey building, undercrossed by the new double tube Milan metro line 5, are adopted. Results indicated that the OED-assisted design of sensor arrangements enables adequate identification of the model parameters with least uncertainty and less monitoring effort (e.g. fewer sensors), while no expert decision is required in the process. Finally, comparison of results from standard and OED-designed monitoring setups indicates a significant enhancement in the reliability of numerical results considering the measurement tolerances.