Simulation Validator
Goal
Provide a three-stage validation protocol: pre-flight checks, runtime monitoring, and post-flight validation for materials simulations.
Requirements
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Python 3.8+
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No external dependencies (uses Python standard library only)
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Works on Linux, macOS, and Windows
Inputs to Gather
Before running validation scripts, collect from the user:
Input Description Example
Config file Simulation configuration (JSON/YAML) simulation.json
Log file Runtime output log simulation.log
Metrics file Post-run metrics (JSON) results.json
Required params Parameters that must exist dt,dx,kappa
Valid ranges Parameter bounds dt:1e-6:1e-2
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
Metric Conservative Standard Relaxed
Mass tolerance 1e-6 1e-3 1e-2
Residual growth 2x 10x 100x
dt reduction 10x 100x 1000x
Script Outputs (JSON Fields)
Script Output Fields
scripts/preflight_checker.py
report.status , report.blockers , report.warnings
scripts/runtime_monitor.py
alerts , residual_stats , dt_stats
scripts/result_validator.py
checks , confidence_score , failed_checks
scripts/failure_diagnoser.py
probable_causes , recommended_fixes
Three-Stage Validation Protocol
Stage 1: Pre-flight (Before Simulation)
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Run scripts/preflight_checker.py --config simulation.json
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BLOCK status: Stop immediately, fix all blocker issues
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WARN status: Review warnings, document accepted risks
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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)
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Run scripts/runtime_monitor.py --log simulation.log periodically
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Configure alert thresholds based on problem type
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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)
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Run scripts/result_validator.py --metrics results.json
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All checks PASS: Results are valid for analysis
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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:
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First, check the log for obvious errors: python3 scripts/failure_diagnoser.py --log simulation.log --json
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If diagnosis suggests numerical blow-up, check runtime stats: python3 scripts/runtime_monitor.py --log simulation.log --json
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Recommend fixes based on findings:
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If residual grew rapidly → reduce time step
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If dt collapsed → check stability conditions
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If NaN detected → check initial conditions
Error Handling
Error Cause Resolution
Config not found
File path invalid Verify config path exists
Non-numeric value
Parameter is not a number Fix config file format
out of range
Parameter outside bounds Adjust parameter or bounds
Output directory not writable
Permission issue Check directory permissions
Insufficient disk space
Disk nearly full Free up space or reduce output
Interpretation Guidance
Status Meanings
Status Meaning Action
PASS All checks passed Proceed with confidence
WARN Non-critical issues found Review and document
BLOCK Critical issues found Must fix before proceeding
Confidence Score Interpretation
Score Meaning
1.0 All validation checks passed
0.75+ Most checks passed, minor issues
0.5-0.75 Significant issues, review carefully
< 0.5 Major problems, do not trust results
Common Failure Patterns
Pattern in Log Likely Cause Recommended Fix
NaN, Inf, overflow Numerical instability Reduce dt, increase damping
max iterations, did not converge Solver failure Tune preconditioner, tolerances
out of memory Memory exhaustion Reduce mesh, enable out-of-core
dt reduced Adaptive stepping triggered May be okay if controlled
Limitations
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Not a real-time monitor: Scripts analyze logs after-the-fact
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Regex-based: Log parsing depends on pattern matching; may miss unusual formats
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No automatic fixes: Scripts diagnose but don't modify simulations
References
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references/validation_protocol.md
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Detailed checklist and criteria
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references/log_patterns.md
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Common failure signatures and regex patterns
Version History
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v1.1.0 (2024-12-24): Enhanced documentation, decision guidance, Windows compatibility
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v1.0.0: Initial release with 4 validation scripts