Digital Twin Engine
Scenario Simulation
Fork the live process state, inject a perturbation, and propagate the modified graph forward through time. Compare outcomes across parallel scenarios — without touching real equipment. The what-if engine for first-principles digital twins.
How Scenarios Work
Four stages from live state to decision-ready comparison.
Fork
Snapshot the current live graph state — every model state variable and every connection's latest value. The fork captures the complete state vector in ~2KB per model.
Perturb
Inject a change into the forked state — trip an equipment model, modify a setpoint, add a load, change an input condition. The perturbation is a targeted mutation of one or more state variables.
Propagate
Execute the modified graph forward through time. Each model re-evaluates with the perturbation cascading downstream through connected models in topological order. Performance is scoped by graph size and deployment.
Compare
Side-by-side comparison of outcomes across all scenarios against the live baseline. Efficiency, energy cost, risk scores, and actionable recommendations — computed for every forked branch.
Scenario Types
Five perturbation categories supported by the scenario execution engine.
| Type | Perturbation | Example | Typical Horizon |
|---|---|---|---|
| Equipment Trip | Set a model output to zero/failed state | "What if Pump 2 trips?" | 1min - 4h |
| Setpoint Change | Modify an input parameter | "What if we increase VFD to 55 Hz?" | 1h - 24h |
| Load Forecast | Ramp an input over time | "What if influent doubles from a storm?" | 4h - 72h |
| Failure Cascade | Trip one model, observe downstream propagation | "What if the blower fails during peak load?" | 1min - 8h |
| Maintenance Window | Take a model offline for a period | "Can we service Clarifier 2 for 4 hours?" | 4h - 48h |
Technical Specifications
Performance characteristics are scoped by graph complexity, source cadence, scenario horizon, and edge host capacity.
Scenario throughput
Parallel what-if evaluations sized during activation
Max parallel scenarios
Concurrent forked graph instances sized by deployment
Propagation latency
Per time-step, full DAG traversal depends on graph size
State snapshot size
Per model, including all state variables
Simulation horizon
Configurable forward projection window
Time acceleration
Simulate 24h in 86 seconds
Test Your First Scenario
Fork the live process state, inject a perturbation, and see the system-wide impact propagate through your digital twin in under 100 milliseconds.