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Learning loads on in‐service underground infrastructure with a trans‐dimensional Bayesian inversion method
1 INTRODUCTION Underground structures are specifically designed to withstand earth pressures, enabling the effective utilization of subsurface spaces. However, the operational environment of these structures is inherently complex, influenced by various factors, including extensive human activities (e.g., adjacent engineering activities; Gong et al., 2023; Li et al., 2023) and unforeseen geotechnical changes (e.g., ground movement; Soga et al., 2017; Zheng et al., 2024).
A Discrete Boltzmann Model for Transcritical Flows Governed by the Saint‐Venant Equations
a direction indication (−) A wetted cross-sectional area (m2) b width (m) C b friction coefficient (−) e particle velocity (m s−1) f distribution function (−) f a distribution function in a direction (−) f a eq local equilibrium function (−) F force (N) Fr Froude number (−) g gravity acceleration (m s−2) h water depth (m) h 0 reference water depth (m) n b Manning's coefficient (−) Q flow discharge (m3 s−1) R hydraulic radius (m) S 0 bed slope effect (N) S f bed and bank shear stress (N) t...
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