Simulation Validator

Goal

Provide a three-stage validation protocol: pre-flight checks, runtime monitoring, and post-flight validation for materials simulations.

Requirements

• Python 3.8+
• No external dependencies (uses Python standard library only)
• Works on Linux, macOS, and Windows

Inputs to Gather

Before running validation scripts, collect from the user:

Decision Guidance

When to Run Each Stage

Is simulation about to start?
├── YES → Run Stage 1: preflight_checker.py
│         └── BLOCK status? → Fix issues, do NOT run simulation
│         └── WARN status? → Review warnings, document if accepted
│         └── PASS status? → Proceed to run simulation
│
Is simulation running?
├── YES → Run Stage 2: runtime_monitor.py (periodically)
│         └── Alerts? → Consider stopping, check parameters
│
Has simulation finished?
├── YES → Run Stage 3: result_validator.py
│         └── Failed checks? → Do NOT use results
│                            → Run failure_diagnoser.py
│         └── All passed? → Results are valid

Choosing Validation Thresholds

Script Outputs (JSON Fields)

Three-Stage Validation Protocol

Stage 1: Pre-flight (Before Simulation)

1. Run scripts/preflight_checker.py --config simulation.json
2. BLOCK status: Stop immediately, fix all blocker issues
3. WARN status: Review warnings, document accepted risks
4. PASS status: Proceed to simulation

python3 scripts/preflight_checker.py \
    --config simulation.json \
    --required dt,dx,kappa \
    --ranges "dt:1e-6:1e-2,dx:1e-4:1e-1" \
    --min-free-gb 1.0 \
    --json

Stage 2: Runtime (During Simulation)

1. Run scripts/runtime_monitor.py --log simulation.log periodically
2. Configure alert thresholds based on problem type
3. Stop simulation if critical alerts appear

python3 scripts/runtime_monitor.py \
    --log simulation.log \
    --residual-growth 10.0 \
    --dt-drop 100.0 \
    --json

Stage 3: Post-flight (After Simulation)

1. Run scripts/result_validator.py --metrics results.json
2. All checks PASS: Results are valid for analysis
3. Any check FAIL: Do NOT use results, diagnose failure

python3 scripts/result_validator.py \
    --metrics results.json \
    --bound-min 0.0 \
    --bound-max 1.0 \
    --mass-tol 1e-3 \
    --json

Failure Diagnosis

When validation fails:

python3 scripts/failure_diagnoser.py --log simulation.log --json

Conversational Workflow Example

User: My phase field simulation crashed after 1000 steps. Can you help me figure out why?

Agent workflow:

1. First, check the log for obvious errors:
   bashCopy

   python3 scripts/failure_diagnoser.py --log simulation.log --json
   

2. If diagnosis suggests numerical blow-up, check runtime stats:
   bashCopy

   python3 scripts/runtime_monitor.py --log simulation.log --json
   

3. Recommend fixes based on findings:
   • If residual grew rapidly → reduce time step
   • If dt collapsed → check stability conditions
   • If NaN detected → check initial conditions

Error Handling

Interpretation Guidance

Status Meanings

Confidence Score Interpretation

Common Failure Patterns

Limitations

• Not a real-time monitor: Scripts analyze logs after-the-fact
• Regex-based: Log parsing depends on pattern matching; may miss unusual formats
• No automatic fixes: Scripts diagnose but don't modify simulations

References

• references/validation_protocol.md - Detailed checklist and criteria
• references/log_patterns.md - Common failure signatures and regex patterns

Version History

• v1.1.0 (2024-12-24): Enhanced documentation, decision guidance, Windows compatibility
• v1.0.0: Initial release with 4 validation scripts