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    A Stochastic Model for Nanoparticle Deposits Growth

    Source: Journal of Engineering for Gas Turbines and Power:;2021:;volume( 144 ):;issue: 001::page 11022-1
    Author:
    Suman, Alessio
    ,
    Vulpio, Alessandro
    ,
    Casari, Nicola
    ,
    Pinelli, Michele
    DOI: 10.1115/1.4051988
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Natural events and human activities are responsible for the generation and transport of large amounts of microsized particles, which could contaminate several engineering devices like solar panels, wind turbines, and aero-engines. In industrial processes, systems as heat exchangers, fans, and dust collectors are continuously affected by nanoparticles' interaction. For several applications, the adhesion of such nanoparticles is detrimental, generating safety and performance issues. Particle-to-particle and particle-to-surface interactions are well known, even if a general explanation of nanoparticle deposit growth is still unknown. In this paper, an interpretation of deposit growth due to nanoparticle deposition can predict particle adhesion, and layer accretion is proposed. A statistical model and a set of coefficients are used to generalize nanoparticle deposits' growth by an S-shaped function. In particular, the nanoparticle deposits grow analogously to a typical autonomous population settlement in a virgin area following statistical rule, which includes the initial growth, the successive stable condition (development), and catastrophic events able to destroy the layer. This approach generalizes nanoparticle adhesion/deposition behavior, overpassing the constraints reported in common deposition models, mainly focused on the mechanical aspect of the nanoparticle impact event. The catastrophic events, such as layer detachment, are modeled with a Poisson's distribution, related to material characteristics and impact conditions. This innovative approach, analogies, and coefficients applied to common engineering applications may be the starting point for improving the prediction capability of nanoparticle deposition.
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      A Stochastic Model for Nanoparticle Deposits Growth

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    contributor authorSuman, Alessio
    contributor authorVulpio, Alessandro
    contributor authorCasari, Nicola
    contributor authorPinelli, Michele
    date accessioned2022-05-08T09:15:46Z
    date available2022-05-08T09:15:46Z
    date copyright10/20/2021 12:00:00 AM
    date issued2021
    identifier issn0742-4795
    identifier othergtp_144_01_011022.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4284917
    description abstractNatural events and human activities are responsible for the generation and transport of large amounts of microsized particles, which could contaminate several engineering devices like solar panels, wind turbines, and aero-engines. In industrial processes, systems as heat exchangers, fans, and dust collectors are continuously affected by nanoparticles' interaction. For several applications, the adhesion of such nanoparticles is detrimental, generating safety and performance issues. Particle-to-particle and particle-to-surface interactions are well known, even if a general explanation of nanoparticle deposit growth is still unknown. In this paper, an interpretation of deposit growth due to nanoparticle deposition can predict particle adhesion, and layer accretion is proposed. A statistical model and a set of coefficients are used to generalize nanoparticle deposits' growth by an S-shaped function. In particular, the nanoparticle deposits grow analogously to a typical autonomous population settlement in a virgin area following statistical rule, which includes the initial growth, the successive stable condition (development), and catastrophic events able to destroy the layer. This approach generalizes nanoparticle adhesion/deposition behavior, overpassing the constraints reported in common deposition models, mainly focused on the mechanical aspect of the nanoparticle impact event. The catastrophic events, such as layer detachment, are modeled with a Poisson's distribution, related to material characteristics and impact conditions. This innovative approach, analogies, and coefficients applied to common engineering applications may be the starting point for improving the prediction capability of nanoparticle deposition.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Stochastic Model for Nanoparticle Deposits Growth
    typeJournal Paper
    journal volume144
    journal issue1
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.4051988
    journal fristpage11022-1
    journal lastpage11022-9
    page9
    treeJournal of Engineering for Gas Turbines and Power:;2021:;volume( 144 ):;issue: 001
    contenttypeFulltext
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