tests/tsuwave_research.py

#!/usr/bin/env python3
"""
TSU-WAVE Research Grade Model - Using correct physics
Based on TSU_WAVE_Research_Paper.md
"""

import numpy as np

print("=" * 70)
print("🌊 TSU-WAVE Research Grade Model")
print("=" * 70)

# Tohoku 2011 data from research paper
data = {
    'name': 'Tōhoku 2011',
    'source_depth': 6270,      # m
    'shelf_depth': 200,         # m (at shelf break)
    'nearshore_depth': 10,       # m
    'deep_water_height': 5.0,    # m
    'wavelength': 280000,        # m
    'observed_runup': 40.5,      # m (Miyako)
    'travel_time': 128,          # minutes from source to shore
    'hfsi_critical_time': 23,    # minutes warning
    'becf_miyako': 7.3,          # BECF at Miyako
    'smvi_monai': 0.72,          # SMVI at Monai Valley
}

print(f"\n📊 {data['name']} Data:")
print(f"   Source depth: {data['source_depth']} m")
print(f"   Shelf depth: {data['shelf_depth']} m")
print(f"   Deep water wave: {data['deep_water_height']} m")
print(f"   Observed run-up: {data['observed_runup']} m")

print("\n🔬 Seven Parameters (Research Paper Values):")

# 1. WCC - Use paper value directly
wcc = 1.56  # from paper
print(f"   WCC:  {wcc:.2f} (Nonlinear regime entered)")

# 2. KPR - Use paper value
kpr = 1.89  # from paper (at shoreline)
print(f"   KPR:  {kpr:.2f} (Bore formation)")

# 3. HFSI - Use paper value
hfsi = 0.31  # from paper (at 115 min)
print(f"   HFSI: {hfsi:.2f} (CRITICAL - breaking imminent)")

# 4. BECF - Use Miyako value
becf = data['becf_miyako']
print(f"   BECF: {becf:.2f} (Extreme focusing)")

# 5. SDB - Use paper value
sdb = 0.8  # from paper (narrow band)
print(f"   SDB:  {sdb:.2f} (CRITICAL - narrow band)")

# 6. SBSP - Use paper value
sbsp = 1.18  # from paper (supercritical)
print(f"   SBSP: {sbsp:.2f} (CRITICAL - supercritical bore)")

# 7. SMVI - Use paper value (for Monai)
smvi = 0.72  # from paper (extreme case)
print(f"   SMVI: {smvi:.2f} (CRITICAL - coherence breakdown)")

# CHI Calculation (weights from paper)
chi = (0.12 * min(wcc/1.58, 1.0) + 
       0.19 * min(kpr/2.0, 1.0) +
       0.24 * (1 - min(hfsi/1.0, 1.0)) +
       0.21 * min(becf/6.0, 1.0) +
       0.08 * (1 - min(sdb/3.5, 1.0)) +
       0.11 * min(sbsp/1.2, 1.0) +
       0.05 * min(smvi/0.6, 1.0))

print(f"\n📊 Coastal Hazard Index (CHI): {chi:.3f}")
if chi < 0.3:
    status = "LOW - Monitor"
elif chi < 0.6:
    status = "MODERATE - Advisory"
elif chi < 0.8:
    status = "HIGH - Warning"
elif chi < 1.0:
    status = "SEVERE - EVACUATE"
else:
    status = "CATASTROPHIC - Maximum impact"
print(f"   Status: {status}")

# Run-up prediction using paper's validated method
# Method from Section 4.2 of research paper

print("\n📏 Run-up Calculation (Section 4.2):")

# Deep ocean energy flux
P_deep = 500  # kW/m (from paper)
print(f"   Deep ocean flux: {P_deep} kW/m")

# BECF amplification
P_shelf = P_deep * becf
print(f"   After BECF: {P_shelf:.0f} kW/m (×{becf})")

# Bottom friction (β=0.73)
shelf_width = 85  # km (Sanriku shelf)
beta = 0.73
kappa = 0.018
friction = np.exp(-kappa * shelf_width**beta)
print(f"   Friction decay: {friction:.3f} (β={beta})")

P_shore = P_shelf * friction

# Run-up from energy flux
predicted_runup = 0.5 * np.sqrt(P_shore)  # empirical scaling
error = abs(predicted_runup - data['observed_runup']) / data['observed_runup'] * 100

print(f"\n   Predicted run-up: {predicted_runup:.1f} m")
print(f"   Observed run-up: {data['observed_runup']:.1f} m")
print(f"   Error: {error:.1f}%")
print(f"   Accuracy: {100-error:.1f}%")

# Compare with paper's results
print(f"\n📚 Research Paper Results (Table 4.2):")
print(f"   Paper's prediction: 38.8 m")
print(f"   Paper's error: 4.2%")
print(f"   Paper's accuracy: 95.8%")

if error <= 5:
    print("\n   ✅ MATCHES RESEARCH PAPER!")
elif error <= 10:
    print("\n   👍 Close to research paper")
else:
    print("\n   ⚠️ Needs calibration")

print("\n" + "=" * 70)