TUNNEL-SHIELD — Benchmark Validation Results | TSII · F_tunnel

Canonical Scenarios

LPEC · FPSE · LSLC Validation Results

Severe squeezing schist, anisotropic limestone, and extreme squeezing claystone — each scenario validated against full 3D FEM benchmark analyses and historical case archives.

Case	Scenario Description	F_tunnel	TSII	LSII	δ_crown	AI Warning	Status
A	Severe squeezing schist · σ_ci=28 MPa · GSI=35 · K₀=1.8 · depth=450 m	1.41	0.931	0.22	41.3 mm	4.3 D	✅ PASS
B	Anisotropic limestone · σ_ci=65 MPa · GSI=58 · K₀=0.9 · depth=310 m	1.63	0.968	0.37	18.7 mm	5.1 D	✅ PASS
C	Extreme squeezing claystone · σ_ci=12 MPa · GSI=22 · K₀=1.2 · depth=580 m	1.38	0.927	0.18	44.8 mm	3.8 D	⚠️ LSII Margin
MEAN	— Aggregate performance across all scenarios	1.47	0.942	0.26	34.9 mm	4.4 D	🏆 CERTIFIED

D = tunnel diameters of advance warning. δ_max constraint = 45 mm. AI Warning = diameters before critical lining section.
Case C triggers LSLC Level 2: mandatory ring design review. All F_tunnel ≥ 1.38, all TSII ≥ 0.927.

AI Module Performance

PINN · XGBoost · CNN · LSLC

AI Module	Precision	Recall	Metric	Value
PINN Plastic Zone (R_p forecast)	—	—	MAE (relative)	3.4%
XGBoost Face Convergence	—	—	MAE	1.8 mm/m
CNN Distortion Classifier	0.96	0.93	AUC / FAR	0.98 / 2.8%
LSLC Governance Response	0.97	0.95	AUC / FAR	0.99 / 1.9%
PINN training corpus	847 simulations + 34 historical deep tunnel squeezing incidents
PINN loss weights	λ_data = 0.65 · λ_phys = 0.35 (Hoek-Brown + equilibrium constraints)
XGBoost features	52-dim: thrust, torque, penetration rate, grout pressure, tail gap + 12 lagged values

Governing safety constraints
R_p = R_t·[(2σ₀·(N_φ-1)+σ_ci·m_b·s^(a-1))/((1+N_φ)·(2p_i·(N_φ-1)+σ_ci·m_b·s^(a-1)))]^(1/(N_φ-1))
F_tunnel = 1 / [0.35/F_LPEC + 0.30/F_FPSE + 0.35/F_LSLC] ≥ 1.35
TSII = Φ[ min(F_LPEC, F_FPSE, F_LSLC) / 1.35 × 3.0 ] ≥ 0.90
LSII = 1 − max(UR(s)) ≥ 0.15
δ_crown(x) = −u_r(r=R_t, θ=0, x) ≤ 45 mm

Methodological Comparison

TUNNEL-SHIELD vs Conventional Practice

Feature	RMR / Q-System	Uncoupled FEM	TUNNEL-SHIELD v1.0.0
Plastic zone prediction	Empirical index only	Mesh-dependent	Closed-form + PINN correction
Face squeezing quantification	Barla CF classes only	2D approximation	3D volumetric strain + XGBoost
Lining moment-thrust analysis	Pressure diagram (static)	Ring model (static)	Full dynamic M-N + CNN monitoring
Hydrostatic asymmetry	Not addressed	Requires manual setup	Automated Biot coupling + PINN
AI augmentation	None	None	PINN + XGBoost + CNN
Advance warning	0 (post-analysis)	0 (post-analysis)	3.8–5.1 diameters (real-time)
Crown settlement control	Empirical limits	Post-analysis only	Real-time δ_max constraint
Update cycle	Design-time only	4–8 hours per run	Every advance increment (5 min)

PINN Plastic Zone Accuracy

96.6%

R_p prediction accuracy (1 − MAE)

vs closed-form baseline: 72%

XGBoost Convergence MAE

1.8 mm/m

Relative error: 4.2%

Shapley: thrust/cutter = 0.28

CNN Distortion Classification

0.96

Precision · Recall 0.93 · AUC 0.98

FAR = 2.8% · 5-class output

Governance improvement

4.4×

vs conventional monitoring

Warning lead time: 0–2h → 18–34h equivalent

Experimental Validation