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    Metal Temperature Prediction of a Dry Low NOx Class Flame Tube by Computational Fluid Dynamics Conjugate Heat Transfer Approach

    Source: Journal of Engineering for Gas Turbines and Power:;2016:;volume( 138 ):;issue: 003::page 31501
    Author:
    Da Soghe, Riccardo
    ,
    Bianchini, Cosimo
    ,
    Andreini, Antonio
    ,
    Mazzei, Lorenzo
    ,
    Riccio, Giovanni
    ,
    Marini, Alessandro
    DOI: 10.1115/1.4031384
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Combustor liner of present gas turbine engines is subjected to high thermal loads as it surrounds high temperature combustion reactants and is hence facing the related radiative load. This generally produces high thermal stress levels on the liner, strongly limiting its life expectations and making it one of the most critical components of the entire engine. The reliable prediction of such thermal loads is hence a crucial aspect to increase the flame tube life span and to ensure safe operations. The present study aims at investigating the aerothermal behavior of a GE Dry Low NOx (DLN1) class flame tube and in particular at evaluating working metal temperatures of the liner in relation to the flow and heat transfer state inside and outside the combustion chamber. Three different operating conditions have been accounted for (i.e., lean–lean partial load, premixed full load, and primary load) to determine the amount of heat transfer from the gas to the liner by means of computational fluid dynamics (CFD). The numerical predictions have been compared to experimental measurements of metal temperature showing a good agreement between CFD and experiments.
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      Metal Temperature Prediction of a Dry Low NOx Class Flame Tube by Computational Fluid Dynamics Conjugate Heat Transfer Approach

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/161034
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    • Journal of Engineering for Gas Turbines and Power

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    contributor authorDa Soghe, Riccardo
    contributor authorBianchini, Cosimo
    contributor authorAndreini, Antonio
    contributor authorMazzei, Lorenzo
    contributor authorRiccio, Giovanni
    contributor authorMarini, Alessandro
    date accessioned2017-05-09T01:28:13Z
    date available2017-05-09T01:28:13Z
    date issued2016
    identifier issn1528-8919
    identifier othergtp_138_03_031501.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/161034
    description abstractCombustor liner of present gas turbine engines is subjected to high thermal loads as it surrounds high temperature combustion reactants and is hence facing the related radiative load. This generally produces high thermal stress levels on the liner, strongly limiting its life expectations and making it one of the most critical components of the entire engine. The reliable prediction of such thermal loads is hence a crucial aspect to increase the flame tube life span and to ensure safe operations. The present study aims at investigating the aerothermal behavior of a GE Dry Low NOx (DLN1) class flame tube and in particular at evaluating working metal temperatures of the liner in relation to the flow and heat transfer state inside and outside the combustion chamber. Three different operating conditions have been accounted for (i.e., lean–lean partial load, premixed full load, and primary load) to determine the amount of heat transfer from the gas to the liner by means of computational fluid dynamics (CFD). The numerical predictions have been compared to experimental measurements of metal temperature showing a good agreement between CFD and experiments.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleMetal Temperature Prediction of a Dry Low NOx Class Flame Tube by Computational Fluid Dynamics Conjugate Heat Transfer Approach
    typeJournal Paper
    journal volume138
    journal issue3
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.4031384
    journal fristpage31501
    journal lastpage31501
    identifier eissn0742-4795
    treeJournal of Engineering for Gas Turbines and Power:;2016:;volume( 138 ):;issue: 003
    contenttypeFulltext
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