Neqsim Gas Dispersion Distance Screening

Gas Dispersion Distance Screening

Use this skill for public, educational atmospheric-dispersion screening. It estimates the downwind centerline distance at which a continuous gas release falls to a target concentration using the open Gaussian plume model with Briggs rural dispersion coefficients, so an agent can scope a flammable or toxic hazard zone before detailed dispersion analysis.

When to Use

• When a user asks roughly how far a gas cloud reaches the LFL or a toxic ppm limit.
• When an agent needs a quick distance-to-target hazard extent for a continuous release.
• When examples must run without confidential plant layout or consequence-tool data.

Inputs

• release_rate: continuous mass release rate Q in kg/s.
• wind_speed: wind speed u in m/s.
• stability_class: Pasquill-Gifford stability class A-F.
• target_concentration: target concentration in kg/m3 (use the helper below for vol% or ppm).
• release_height: effective release height He in m, default 0 (ground level).

Helper: concentration_from_volume_fraction(volume_fraction, molar_mass, temperature_k, pressure_bara) converts a gas volume (mole) fraction to kg/m3 using the ideal-gas law.

Outputs

• stability_class: the resolved stability class.
• target_concentration_kg_m3: the target concentration used.
• hazard_distance_m: farthest downwind distance at or above the target, or null if never reached.
• peak_concentration_kg_m3: peak centerline concentration over the scan.
• dispersion_warning: hazard-zone, no-hazard-distance, or beyond-assessment-distance.
• assumptions: public assumptions used by the placeholder model.

Engineering Method

The Python class GaussianDispersionModel uses the open Gaussian plume model:

• the centerline concentration uses C = Q / (pi * u * sigma_y * sigma_z) * exp(-He^2 / (2 sigma_z^2)).
• the dispersion coefficients sigma_y and sigma_z use the Briggs (1973) rural (open-country) formulas for class A-F.
• the hazard distance is the farthest downwind point at or above the target, found by a logarithmic distance scan.

This is educational and screening-only logic. It assumes a continuous point source, constant wind speed, flat open terrain, neutral buoyancy (no dense-gas slumping or plume rise), and no deposition or reaction. It is not a replacement for validated dispersion modelling, dense-gas or CFD tools, and qualified safety review.

Python Usage Pattern

from gas_dispersion_distance_screening import GaussianDispersionModel

model = GaussianDispersionModel(assessment_distance=500.0)

lfl = GaussianDispersionModel.concentration_from_volume_fraction(
    volume_fraction=0.044,
    molar_mass=16.04,
)
result = model.evaluate(
    release_rate=2.0,
    wind_speed=5.0,
    stability_class="F",
    target_concentration=lfl,
)

print(result.hazard_distance_m)
print(result.dispersion_warning)

Related NeqSim Functionality

For validated dispersion and consequence behaviour, redirect to existing NeqSim classes:

• neqsim.process.safety.scenario.ReleaseDispersionScenarioGenerator — release and dispersion scenario generation.
• neqsim.process.safety.fire.JetFireModel / PoolFireModel — fire consequence models for ignited releases.
• neqsim.process.safety.fire.VCEModel — vapour-cloud-explosion overpressure modelling.

This skill is a public dispersion-distance triage layer that decides when to invoke those validated consequence classes.

Validation Checklist

• Release rate, wind speed, and target concentration are positive.
• Stability class is one of A-F.
• The target is in kg/m3 (use the helper to convert vol% or ppm).
• Tests cover hazard distance, stability sensitivity, the helper, and invalid input.
• Real dispersion is redirected to validated NeqSim consequence classes and qualified review.

Common Mistakes

Limitations

• Neutral-buoyancy Gaussian model only; no dense-gas slumping or plume rise.
• Flat open terrain, constant wind, no obstacles or buildings.
• No deposition, reaction, or time-varying release.

References

• NeqSim repository: https://github.com/equinor/neqsim
• NeqSim Skills Guide: https://github.com/equinor/neqsim/blob/master/docs/integration/skills_guide.md