How to choose the best simulation for a specific purpose?

A. Martilli, J. L. Santiago, T. G. Reisin, A. Baklanov, J. Bartzis, R. Buccolieri, A. M. Costa, S. Di Sabatino, G. Efthimiou, J. Franke, A. Hellsten, R. Nuterman, R. Tavares

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    The decision on the fitness for purpose of a simulation should be based on the quantity of interest. However, in general, models are used because there is no complete experimental information available on the quantity of interest, so a direct judgement is not possible. The aim of this article is to put in light this dichotomy, and propose a methodology to decide if a simulation is fit for purpose, based on the experimental data available and an ensemble of simulations. The methodology is illustrated with one example of microscale simulations.

    Original languageEnglish (US)
    Title of host publicationHARMO 2011 - Proceedings of the 14th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes
    EditorsJohn G. Bartzis, Spyros Andronopoulos, Alexandros Syrakos
    PublisherUniversity of West Macedonia
    Pages27-31
    Number of pages5
    ISBN (Electronic)9789608965065
    StatePublished - 2011
    Event14th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, HARMO 2011 - Kos Island, Greece
    Duration: Oct 2 2011Oct 6 2011

    Publication series

    NameHARMO 2011 - Proceedings of the 14th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes

    Conference

    Conference14th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, HARMO 2011
    Country/TerritoryGreece
    CityKos Island
    Period10/2/1110/6/11

    Keywords

    • Air quality
    • Fit-for-purpose
    • Modelling
    • Validation

    ASJC Scopus subject areas

    • Atmospheric Science
    • Pollution
    • Modeling and Simulation

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