INTEGRITY CODE SERIES

Vibration-Accelerated Corrosion: Coupled Mechano-Electrochemical Simulation

ZIP name: integrity_code_series_week4_vibrocorrosion.zip

Part of an ongoing series of physics-first integrity simulators by Felipe Rocha:

#	Repo	Domain
Week 3	Integrity-code-series-3	F1 lap simulation (six coupled ODEs)
Week 6	Integrity-code-series-week6-smartphone-galvanic	Smartphone galvanic corrosion (Laplace + Butler-Volmer)
Week 7	integrity_code_series_week7_h2_lferw	LF-ERW H2 conversion (B31.12 + NACE TM0316)
Week 8	integrity-code-series-week8-creep-fatigue-heater	Creep-fatigue 9Cr-1Mo (Norton/Omega + Coffin-Manson)
Week 9	integrity-code-series-week9-cui	CUI thermohygro-electrochemical (3 PDEs, Strang)
Week 10	integrity-code-series-week-10_nnph_scc	NNpHSCC full-physics (Chen-Sutherby-Xing + BS 7910)
Bonus	Vibration-Accelerated-Corrosion-Coupled-Mechano-Electrochemical-Simulation	Vibration-accelerated corrosion (SDOF + Butler-Volmer + Archard)
Bonus	synthetic-integrity-digital-twin-piml	Physics-informed neural-network surrogate
Bonus	integrity-data-foundation	Engineering data validation baseline

WHAT THIS IS

A physics-first engineering simulation of vibration-accelerated corrosion in X65 carbon steel pipe under CO2-saturated brine. The system couples:

Damped single-degree-of-freedom structural vibration (SDOF)
Stress-modified Butler-Volmer electrochemical kinetics
Faraday mass loss rate (Corrosion)
Archard fretting wear at pipe supports

An ML surrogate (GBR) is trained on 50,000+ physics-generated data points for real-time deployment. All governing equations, boundary conditions, and assumptions are explicit in source code.

EXPLICIT LIMITATIONS

beta_stress (stress-activation coefficient) is phenomenological. Calibration against coupon tests required before production use.
Fretting-corrosion synergy term is NOT modeled. Total material loss may be underestimated by 20-50% in severe fretting contact.
No external experimental dataset was used for validation. Internal consistency only.
pH model uses Nernst approximation only.
Stress model assumes spring-force / contact-area approximation. FEA required for real geometry.

GOVERNING PHYSICS

1. SDOF Vibration

m*x'' + c*x' + k*x = F0*sin(omega*t)
c = 2*zeta*sqrt(k*m)
BC: x(0) = 0, x'(0) = 0

2. Stress-Modified Butler-Volmer

i0_eff = i0_ref * exp(beta_stress * sigma / (R*T))
i_anodic = i0_eff * exp(alpha_a * F * |eta| / (R*T))

3. Faraday Mass Loss

dm/dt [g/(cm²·s)] = (i [A/cm²] * M [g/mol]) / (n * F [C/mol])
CR [mm/yr] = (dm/dt / rho) * 10 * 3.156e7

4. Archard Fretting Wear

V_wear = K_wear * W * s * N
thickness_loss = V_wear / contact_area

REPOSITORY STRUCTURE

integrity_code_series_week4_vibrocorrosion/
├── run_pipeline.py              # Master orchestrator (start here)
├── requirements.txt
├── README.md
├── src/
│   ├── simulation/
│   │   ├── vibrocorrosion_engine.py    # Core physics engine
│   │   └── parametric_sweep.py        # 50,000-point dataset generator
│   ├── ml/
│   │   └── gbr_surrogate.py           # ML surrogate training and prediction
│   ├── validation/
│   │   └── validation_suite.py        # Physics consistency checks
│   ├── visualization/
│   │   └── viz_suite.py               # All visuals + GIF
│   └── cybersecurity/
│       └── sensor_security.py         # Threat model + sensor integrity
├── tests/
│   └── test_all.py                    # Unit test suite
├── assets/                            # Generated outputs (created at runtime)
│   ├── parametric_sweep.csv
│   ├── models/
│   │   ├── gbr_model.pkl
│   │   ├── scaler.pkl
│   │   └── model_manifest.json
│   ├── hero_3d_cr_surface.png
│   ├── secondary_time_domain.png
│   ├── secondary_residuals.png
│   ├── secondary_isorisk_map.png
│   ├── secondary_sensitivity.png
│   ├── vibrocorrosion_sweep.gif
│   ├── validation_report.json
│   └── audit_log.jsonl
├── notebooks/                         # Optional Jupyter exploration

EXECUTION ORDER

# 1. Install dependencies
pip install -r requirements.txt

# 2. Run full pipeline (tests -> simulation -> sweep -> ML -> validation -> visuals)
python run_pipeline.py

# 3. OR run steps individually:
python tests/test_all.py
python src/simulation/vibrocorrosion_engine.py
python src/simulation/parametric_sweep.py
python src/ml/gbr_surrogate.py
python src/validation/validation_suite.py
python src/visualization/viz_suite.py
python src/cybersecurity/sensor_security.py

# 4. Skip slow steps if assets already exist:
python run_pipeline.py --skip-tests --skip-sweep --skip-ml

OUTPUT FILE NAMING CONVENTIONS

File	Description
`assets/parametric_sweep.csv`	50,000+ row physics dataset
`assets/models/gbr_model.pkl`	Trained GBR model
`assets/models/scaler.pkl`	Feature scaler
`assets/hero_3d_cr_surface.png`	Primary hero visualization
`assets/secondary_*.png`	Secondary analysis charts
`assets/vibrocorrosion_sweep.gif`	Animated resonance sweep
`assets/validation_report.json`	Validation check results
`assets/audit_log.jsonl`	Hash-chained audit log

EXPECTED RUNTIMES (approximate, hardware-dependent)

Step	Estimated Time
Unit tests	< 30s
Physics simulation (100s, dt=1e-4)	30-90s
Parametric sweep (50k points)	2-5 min
ML training (GBR, 400 trees)	30-120s
Validation suite	1-3 min
Visual generation	2-5 min
GIF generation	1-2 min

CYBERSECURITY ARCHITECTURE

Threats addressed: sensor spoofing, ML model tampering, data poisoning, audit log deletion, pipeline DoS.
See src/cybersecurity/sensor_security.py for full threat model and mitigation code.
Production deployment requires IEC 62443 zone/conduit model and HSM for model hash storage.

STANDARDS REFERENCED (without specific clause citation)

API 571: Damage Mechanisms Affecting Fixed Equipment (vibration-induced fatigue/corrosion listed)
API 580/581: Risk-Based Inspection methodology (probability of failure framework)
IEC 62443: Industrial Automation and Control Systems cybersecurity

NOTE: No specific clause numbers are cited as these require license access for verification.

REPRODUCIBILITY

Fixed seeds: random_state=42 in all sklearn calls.
ODE solver: SciPy RK45 with rtol=1e-8, atol=1e-10.
All parameters defined in MaterialParams, EnvironmentParams, VibrationParams dataclasses.
Sweep grid explicitly defined in parametric_sweep.py.