The present work represents the second and final part of a twofold study aiming at the definition and validation of an integrated methodology for the analysis and modeling of road tunnel ventilation systems. A numerical approach is presented, based on the Finite Volume integration of the 1D mechanical and thermal energy conservation equations on a network of ducts, representing the ventilation system of the 11.6 km long Mont Blanc Tunnel. The set of distributed and concentrated loss coefficients, representing dissipation of mechanical energy by friction in each part of the ventilation system, is calibrated against a rich experimental dataset, collected throughout a dedicated set of in situ tests and presented in the first part of the work. The calibration of the model is carried out by means of genetic optimization algorithms. Predictions of the flow field using the calibrated parameters are in remarkable agreement with the experimental data, with an overall RMS error of ± 0.27 m/s, i.e. of the same order of the accuracy of the measurement probes. Further validation against a selection of field data recorded by the tunnel monitoring and control system is brought forward, highlighting the robustness and potential general applicability of the proposed approach.

An integrated approach for the analysis and modeling of road tunnel ventilation. Part II: Numerical model and its calibration

Cavazzuti M.;Cipollone M.
2021

Abstract

The present work represents the second and final part of a twofold study aiming at the definition and validation of an integrated methodology for the analysis and modeling of road tunnel ventilation systems. A numerical approach is presented, based on the Finite Volume integration of the 1D mechanical and thermal energy conservation equations on a network of ducts, representing the ventilation system of the 11.6 km long Mont Blanc Tunnel. The set of distributed and concentrated loss coefficients, representing dissipation of mechanical energy by friction in each part of the ventilation system, is calibrated against a rich experimental dataset, collected throughout a dedicated set of in situ tests and presented in the first part of the work. The calibration of the model is carried out by means of genetic optimization algorithms. Predictions of the flow field using the calibrated parameters are in remarkable agreement with the experimental data, with an overall RMS error of ± 0.27 m/s, i.e. of the same order of the accuracy of the measurement probes. Further validation against a selection of field data recorded by the tunnel monitoring and control system is brought forward, highlighting the robustness and potential general applicability of the proposed approach.
Cingi, P.; Angeli, D.; Cavazzuti, M.; Levoni, P.; Stalio, E.; Cipollone, M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2463118
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