Research Papers

A New Model Approach for Convective Wall Heat Losses in DQMOM-IEM Simulations for Turbulent Reactive Flows

[+] Author and Article Information
Yeshaswini Emmi, Andreas Fiolitakis, Manfred Aigner

German Aerospace Centre (DLR),
Institute of Combustion Technology,
Pfaffenwaldring 38-40,
Stuttgart D-70569, Germany

Franklin Genin, Khawar Syed

GE (Switzerland) GmbH,
Brown Boveri Strasse 7,
Baden 5400, Switzerland

Manuscript received June 26, 2018; final manuscript received September 25, 2018; published online November 20, 2018. Editor: Jerzy T. Sawicki.

J. Eng. Gas Turbines Power 141(5), 051001 (Nov 20, 2018) (10 pages) Paper No: GTP-18-1372; doi: 10.1115/1.4041726 History: Received June 26, 2018; Revised September 25, 2018

A new model approach is presented in this work for including convective wall heat losses in the direct quadrature method of moments (DQMoM) approach, which is used here to solve the transport equation of the one-point, one-time joint thermochemical probability density function (PDF). This is of particular interest in the context of designing industrial combustors, where wall heat losses play a crucial role. In the present work, the novel method is derived for the first time and validated against experimental data for the thermal entrance region of a pipe. The impact of varying model-specific boundary conditions is analyzed. It is then used to simulate the turbulent reacting flow of a confined methane jet flame. The simulations are carried out using the DLR in-house computational fluid dynamics code THETA. It is found that the DQMoM approach presented here agrees well with the experimental data and ratifies the use of the new convective wall heat losses model.

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Fig. 1

Experimental setup of the confined jet flame [12]

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Fig. 2

Temperature distribution for p1 = 0.233 and ε = 10−5

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Fig. 3

Favre-RMS of temperature with varying ε and p1 = 0.233

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Fig. 4

Favre-RMS of temperature with varying ε and p1 = 0.233. Scale zoomed in to wall.

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Fig. 5

Favre-RMS of temperature with varying p1 and ε = 1 × 10−5

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Fig. 6

Axial velocity streamlines (m/s)

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Fig. 7

Favre-average of temperature (K)

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Fig. 8

Favre-average of axial velocity

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Fig. 9

Favre-average of temperature

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Fig. 10

Favre-average of CH4 mole fraction

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Fig. 11

Favre-average of H2O mole fraction



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