Multi-Fidelity Trade-off Explorer

Multi-fidelity modeling combines data from simulations of different accuracy levels (fidelities) to create more accurate predictions than using high-fidelity data alone. It's like using both rough sketches and detailed blueprints to design a building!

Fidelity Levels Explained:

🔴 High-Fidelity (HF)

• Accuracy: Most accurate, closest to reality
• Cost: Most expensive (computational time/money)
• Use: Critical for final validation
• Example: Full CFD simulation with fine mesh

🟡 Medium-Fidelity (MF)

• Accuracy: Moderate accuracy
• Cost: Moderate cost
• Use: Good balance for many applications
• Example: CFD with coarser mesh

🟢 Low-Fidelity (LF)

• Accuracy: Lower accuracy but captures main trends
• Cost: Very cheap (fast computation)
• Use: Quick exploration, trend identification
• Example: Potential flow theory, empirical correlations

The Multi-Fidelity Advantage:

• 💰 Cost Efficiency: Get better accuracy per dollar spent
• ⚡ Speed: Faster than high-fidelity only
• 🎯 Smart Allocation: Use expensive simulations where they matter most
• 📊 Better Predictions: Often outperforms single-fidelity approaches

Key Concepts You'll Explore:

• Budget Allocation: How to split your computational budget
• Fidelity Selection: Which fidelity levels to use
• Cost-Benefit Analysis: When multi-fidelity pays off
• Diagnostic Metrics: How to assess multi-fidelity suitability

Advanced Settings: