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:
| 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)
- Run
scripts/preflight_checker.py --config simulation.json - BLOCK status: Stop immediately, fix all blocker issues
- WARN status: Review warnings, document accepted risks
- 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)
- Run
scripts/runtime_monitor.py --log simulation.logperiodically - Configure alert thresholds based on problem type
- 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)
- Run
scripts/result_validator.py --metrics results.json - All checks PASS: Results are valid for analysis
- 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:
- First, check the log for obvious errors:
python3 scripts/failure_diagnoser.py --log simulation.log --json - If diagnosis suggests numerical blow-up, check runtime stats:
python3 scripts/runtime_monitor.py --log simulation.log --json - 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
| 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 |
Security
Input Validation
- Config file paths are validated for existence before parsing; non-existent paths produce clear errors
--requiredparameter names are validated against a safe-character allowlist--rangesentries are parsed asname:min:maxwith finite numeric bounds enforced--min-free-gbis validated as a finite positive number--residual-growthand--dt-dropthresholds are validated as finite positive numbers--bound-min,--bound-max, and--mass-tolare validated as finite numbers withbound-max > bound-min
File Access
preflight_checker.pyreads a single user-specified config file (JSON/YAML) and checks disk space on the output directoryruntime_monitor.pyreads a single log file specified by--log; log files are size-limited (500 MB max) before parsingresult_validator.pyreads a single metrics file (JSON) specified by--metricsfailure_diagnoser.pyreads a single log file specified by--log- No scripts write to the filesystem; all output goes to stdout
Tool Restrictions
- Read: Used to inspect script source, references, config files, and simulation logs
- Bash: Used to execute the four Python validation scripts (
preflight_checker.py,runtime_monitor.py,result_validator.py,failure_diagnoser.py) with explicit argument lists - Write: Used to save validation reports; writes are scoped to the user's working directory
- Grep/Glob: Used to locate log files, config files, and search references
Safety Measures
- No
eval(),exec(), or dynamic code generation - All subprocess calls use explicit argument lists (no
shell=True) - Log parsing uses pre-compiled regex patterns; user-supplied patterns are not accepted (patterns are hardcoded)
- Phase names and diagnostic strings extracted from logs are sanitized (truncated, control characters stripped) before inclusion in output
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 criteriareferences/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