engineering

Fire Engineering & Life Safety

The science of fire protection — buoyant plume modeling, smoke layer descent, flashover prediction, evacuation egress timing, and automatic sprinkler activation response.

fire engineeringfire safetysmoke dynamicsflashoveregresssprinkler systemsfire plumelife safety

Fire engineering combines fluid dynamics, heat transfer, and human behavior science to protect buildings and their occupants. Understanding how fire plumes rise, how hot smoke layers descend, and when flashover occurs is critical to designing safe structures. Performance-based fire design relies on quantitative models that predict fire growth, smoke movement, and required evacuation time.

These simulations let you model axisymmetric fire plumes, track smoke layer descent in compartments, predict flashover conditions, calculate required safe egress time, and determine sprinkler activation delay — all with real-time interactive controls grounded in established fire science correlations.

5 interactive simulations

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Evacuation Egress Time Calculator

Simulate building evacuation — explore how occupant load, exit width, travel distance, and pre-movement delay determine Required Safe Egress Time (RSET)

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Axisymmetric Fire Plume Model

Simulate buoyant fire plumes — explore how heat release rate, fire diameter, and ceiling height determine plume temperature, velocity, and entrainment using Heskestad correlations

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Flashover Prediction Model

Simulate flashover conditions in a compartment — explore how ventilation, fuel load, and room geometry determine the critical heat release rate for flashover using Thomas and Babrauskas correlations

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Smoke Layer Descent Model

Simulate smoke filling in a compartment — explore how fire size, room geometry, and ventilation determine the rate of hot smoke layer descent and available safe egress time

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Sprinkler Activation Response Model

Simulate automatic sprinkler activation — explore how RTI, ceiling jet temperature, sprinkler spacing, and fire growth rate determine activation time using the lumped-mass thermal model