A-TEAM:

Advanced Training System
for Emergency Management

RiskWare built-in models

RiskWare has a number of built-in models for emergency simulation. They include:

SPILL: dynamic release model

    for one and two-phase releases, pool evaporation, and infiltration (stochastic, Monte Carlo framework);

    Input:

    container description, meteorology, size of a possible containment, soil permeability (infiltartion);

    Output:

    mass budget, dynamic source term (evaporation or jet release) for the atmopsheric model(s). All output available as a frequency distribution.

TIMES: dynamic 3-D Eulerian code

    that can represent building obstacles in near-field calculations; the model exists in both a near-field version (grid resolution of 1-10 meters) or a meso-sclae version (grid sizes of 10 - 1000 m).

    Input:

    Dynamic source term (automatic coupkling with SPILL, see above), dynamic meteorology, DEM, obstacle data.

    Output:

    Dynamic multi-layer concentration field.

DYNPUFF: dynamic multi-puff model

    based on INPUFF 2.4, using the diagnostic 3-D wind model DWM as a pre-processor; The model directly utilises the output of the SPILL model above.

    Input:

    Dynamic source term (automatically coupled to the SPILL model;
    2-D Wind field, auromatically computed by the embedded DWM, which in turn uses anemometric and geostrophic winds, temperature and stability class.
    Digital terrain model, surface roughness, population distribution.

    Output:

    dynamic 2-D concentration field (ground level)
    Area and population exposure above user defined threshold concentrations.

GSTM: Gaussian short-term model

    for one or more sources, steady-state with possible terrain correction, includes representation of stack effects (momentum and thermal buoancy);

    Input

    Release term (steady state), substance parameters (specific gravity), stack height, diameter, exit velocity, exit temperature.
    Meteorological parameters: wind speed and direction, air temperature, stability class, mixing height (not really needed for the near-field cases).
    Digital terrain model (optional) and population distribution.

    Output

    Steady-state 2-D concentration field. Model also computed areas above user defined threshold values and population exposure.

BLAST explosion models

    TNT equivalence and a fuel-air charge blast explosion model from the TNO Yellow Book (Third Edition 1997);

    Input:

    Substance amount and parameters, for the TNO model also ignition strength and blockage factors;
    Landuse and population distribution.

    Output:

    2-D pressure distribution, population and area exposed to pressures above a user defined threshold.

FIRE: steady-state 2-D fire model

    can describe pool and trech fires as well as BLEVE (Boiling Liquid Expanding Vapor Explosion).

    Input

    Source term (feed rate) and substance parameters (loaded automatically from the hazardous chemicals data base of Riskware); pool or trench geometry, wind direction and speed, background termperature.

    Output

    Heat flux or temperature distribution (steady state, 2-D).

SOILGW: stochastic 1-D soil/groundwater infiltration model

    estimates the arrival time of a spill at the water table, using substance viscosity, soil properties, and the groundwater level (distance from soil surface). Monte Carlo implementation.

    Input:

    substance properties, soil properties, groundwater head (vertical distance)

    Output:

    Arroival time of the contaminant (probability distribution).

MS: Metodo Speditivo

    fast empirical estimation method from Italy; uses tabultated data for substance classes, amounts and storage consitions,and weather conditions.

    Input:

    Substance class, amount, storage consitions, weather, population distribution.

    Output:

    Safety zones (radii) and their sizes, population exposure.

BLTM: dynamic river spill model

    a dynamic, Lagrangian water quality model based on the USGS BLTM model, can handle several non-interacting conservative or first order decaying substances simultaneously in complex, branched channel systems.

    The model uses a rule-based expert system as a post-processor to assess the likelyhood a fish kills, based on the LC 50 data for a number of aquatic species from the hazardous chemical data base.




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