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    Enhanced thermo-fluid dynamic modelling methodologies for convective boiling

    Access Status
    Fulltext not available
    Authors
    Chandratilleke, Tilak
    Nadim, Nima
    Date
    2018
    Type
    Book Chapter
    
    Metadata
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    Citation
    Chandratilleke, T. and Nadim, N. 2018. Enhanced thermo-fluid dynamic modelling methodologies for convective boiling. In Green Energy and Technology, 173-202.
    Source Title
    Green Energy and Technology
    DOI
    10.1007/978-981-10-0697-5_8
    School
    Department of Mechanical Engineering
    URI
    http://hdl.handle.net/20.500.11937/57959
    Collection
    • Curtin Research Publications
    Abstract

    © Springer Nature Singapore Pte Ltd. 2018. Analytical tools embedded in current thermal design practice for convective boiling systems are traditionally built upon correlated empirical data, which are constrained by the thermo-fluid dynamical complexities associated with stochastic and interactive behaviour of boiling fluid mixtures. These methodologies typically overlook or under-represent key characterising aspects of bubble growth dynamics, vapour/liquid momentum exchange, boiling fluid composition and local phase drag effects in boiling processes, making them inherently an imprecise science. Resulting predictive uncertainties in parametric estimations compromise the optimal design potential for convective boiling systems and contribute to operational instabilities, poor thermal effectiveness and resource wastage in these technologies. This book chapter first discusses the scientific evolution of current boiling analytical practice and predictive methodologies, with an overview of their technical limitations. Forming a foundation for advanced boiling design methodology, it then presents novel thermal and fluid dynamical enhancement strategies that improve modelling precision and realistic processes description. Supported by experimental validations, the applicability of the proposed strategies is ascertained for the entire convective boiling flow regime, which is currently not possible with existing methods. The energy-saving potential and thermal effectiveness underpinned by these modelling enhancements are appraised for their possible contributions towards a sustainable energy future.

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