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Soil structure interaction effects on seismic response and resilience assessment of segmental underground tunnel joints using a physics based hybrid analytical machine learning framework
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DOI：10.1016/j.soildyn.2026.110362.png)
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Abstract
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• A hybrid analytical ML framework is proposed for SSI controlled tunnel response. • Dynamic soil impedance and wave transmission are captured in an enhanced beam model. • Segmental joints are represented to simulate slip, rotation, and localized damage. • Random Forest reproduces nonlinear SSI response patterns with high accuracy. • Joint parameter optimization reduces bending demand and displacement amplitude.
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