• Mapeo de Fuego y Gas

    El diseño auxiliado por computadora de estudios de mapeo de Fuego y Gas para aumentar la seguridad y reducir los costos. Los sistemas de detección de fuego y gas deben...

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  • Capacitación

    El entrenamiento de MICROPACK en Detección de Fuego y Gas brinda a los delegados un entendimiento exhaustivo de todos los aspectos...

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  • Análisis de Deficiencias

    MICROPACK lleva a cabo exhaustivos estudios de análisis de deficiencias, en los que evalúa sistemas de detección de fuego y gas instalados actualmente y se asegura de que estas instalaciones cumplan...

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Gas Dispersion Analysis And Consequence Modelling

Gas Dispersion Analysis & Consequence Modelling

DNV GL Phast

Where the cost of CFD modelling is not possible or appropriate, Micropack carry out gas dispersion or consequence modelling using DNV GL Phast software. Scenarios are selected based upon common leaks, worst case leaks and any other scenarios which may be specified by our client. This modelling reviews the dispersion of flammable gas with respect to possible explosive accumulations and aids in safety reviews as well as validating any Fire and Gas detection and protection measures proposed or already in place.

Many scenario based models can be misleading and dangerous if applied alongside F&G detection mapping without a broad knowledge of the principals behind both consequence analysis and Fire and Gas detection design. This is where Micropack’s professionally certified consultancy team can use the scenarios in a safe and robust way to ensure the design is optimised but not at the expense of safety.

Phast is one of the most comprehensive process industry hazard analysis software tools for all stages of design and operation. The software examines the progress of a potential incident from the initial release to far-field dispersion including modelling of pool spreading and evaporation, and flammable and toxic effects.
Although the modelling is done computationally, all outputs are cross-checked by Micropack’s fire safety professionals’ calculations which give a estimated figure for each individual output. This gives reassurance that the semi-quantitative model is accurate and reflective of the input data.

 

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