Risk Simulation Framework Overview

Introduction

The NeqSim Risk Simulation Framework provides comprehensive tools for analyzing equipment failures, their impact on production, and optimizing plant operation under degraded conditions. It integrates with NeqSim’s process simulation capabilities to provide physics-based risk assessment.

Key Concepts

1. Equipment Failure Modes

Equipment can fail in different ways, each with different consequences:

Failure Type	Description	Capacity Factor
TRIP	Equipment stops completely	0%
DEGRADED	Reduced capacity operation	10-90%
PARTIAL_FAILURE	Some functions lost	20-80%
FULL_FAILURE	Complete breakdown	0%
MAINTENANCE	Planned shutdown	0%
BYPASSED	Flow routed around	0% (for that unit)

2. Reliability Metrics

Standard reliability metrics from OREDA (Offshore Reliability Data):

Metric	Symbol	Description
Mean Time To Failure	MTTF	Average operating time before failure
Mean Time To Repair	MTTR	Average repair duration
Mean Time Between Failures	MTBF	MTTF + MTTR
Failure Rate	λ	Failures per time unit
Availability	A	Fraction of time operational

3. Risk Assessment

Risk is evaluated on two dimensions:

Probability (likelihood of failure)
Consequence (impact when failure occurs)

The combination determines the Risk Level:

Risk Level = f(Probability, Consequence)

4. Process Topology

Equipment connections form a directed graph:

Feed → Separator → Compressor → Cooler → Export
                 ↘ Pump → Storage

Understanding topology enables:

Cascade failure analysis
Parallel equipment identification
Critical path determination

Framework Capabilities

✅ Equipment Failure Modeling

Define failure types (trip, degraded, partial, etc.)
Capacity reduction factors
Auto-recovery behavior
OREDA-based reliability data

✅ Production Impact Analysis

Quantify production loss from failures
Compare failure scenarios
Rank equipment by criticality
Calculate revenue impact

✅ Monte Carlo Simulation

Stochastic failure simulation
P10/P50/P90 production estimates
Availability calculations
Confidence intervals

✅ Risk Matrix

5×5 probability-consequence matrix
Color-coded risk levels
Economic cost calculations
Visual ASCII/JSON export

✅ Topology Analysis

Graph extraction from ProcessSystem
Topological ordering
Parallel equipment detection
DOT format export for visualization

✅ STID Tagging

ISO 14224 compliant tag parsing
Norwegian offshore installation codes
Equipment type classification
Parallel train identification

✅ Dependency Analysis

“If X fails, what’s affected?”
Cascade failure propagation
Cross-installation dependencies
Equipment monitoring recommendations

Typical Workflow

1. Build Process Model
   └─► ProcessSystem with equipment

2. Define Failure Scenarios
   └─► EquipmentFailureMode for each critical unit

3. Assign Reliability Data
   └─► MTTF, MTTR from OREDA

4. Build Topology
   └─► ProcessTopologyAnalyzer.buildTopology()

5. Tag Equipment
   └─► STID functional locations

6. Analyze Dependencies
   └─► DependencyAnalyzer.analyzeFailure()

7. Build Risk Matrix
   └─► RiskMatrix.buildRiskMatrix()

8. Run Monte Carlo
   └─► OperationalRiskSimulator.runSimulation()

9. Optimize Degraded Operation
   └─► DegradedOperationOptimizer.optimize()

Industry Standards

This framework follows industry standards:

Standard	Application
ISO 14224	Equipment taxonomy and reliability data
OREDA	Offshore reliability data handbook
ISO 31000	Risk management principles
NORSOK Z-013	Risk and emergency preparedness
IEC 61508	Functional safety
API 580/581	Risk-based inspection

Mathematical Foundation

See Mathematical Reference for detailed formulas covering:

Failure probability distributions
Availability calculations
Monte Carlo algorithms
Risk cost functions
Production loss modeling

Next Steps

Equipment Failure Modeling - Define failure modes
Risk Matrix - Build visual risk assessment
Monte Carlo Simulation - Run stochastic analysis
Topology Analysis - Extract process structure