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108                                            New Trends in Coal Conversion

         where P, L, and T g are the sum of the partial pressures of the participating gases, beam
         length, and gas temperature, respectively.
            The Smith et al. (1982) WSGGM has been commonly used in combustion CFD un-
         til new efforts are made recently to properly address the impacts of high-concentration
         CO 2 and H 2 O vapor under oxy-fuel conditions on the gaseous radiative properties (Yin
         et al., 2010b; Johansson et al., 2011; Kangwanpongpan et al., 2012; Krishnamoorthy,
         2013; Bordbar et al., 2014; Guo et al., 2015). In the new models, the variations in H 2 O
         and CO 2 concentrations in a flame are also considered in different ways. Most
         commonly, discrete coefficient tables are used to address the variations in gas compo-
         sitions, in the similar way of the Smith et al. (1982) WSGGM. For instance, the oxy-
         fuel WSGGM (Yin et al., 2010b) accounts for the species variations by using seven
         coefficient tables, each of which corresponds to a typical H 2 O and CO 2 condition.
         Based on the local gas composition, different tables are used to evaluate the local radi-
         ative properties. The use of discrete coefficient tables may result in discontinuity, i.e., a
         small change in gas composition may induce a sharp change in the radiative properties.
         To eliminate the discontinuity problem, smooth coefficient functions of H 2 O/CO 2
         molar ratio are proposed more recently to address the species variations in a flame
         (Johansson et al., 2011; Kangwanpongpan et al., 2012; Bordbar et al., 2014; Guo
         et al., 2015).
            Despite all the progress in refining WSGGMs, the WSGGMs still have limitations
         in practical use. For instance, all WSGGMs only account for the impacts of H 2 O and
         CO 2 under atmospheric pressure. In oxy-fuel combustion, CO concentrations can be
         10 times higher than that in conventional air-fuel combustion. Although the spectral
         absorption bands of CO and CO 2 are mostly overlapped and the absorption coefficients
         of CO 2 and H 2 O are generally higher than those of CO, zones of high CO concentra-
         tions and high CO 2 concentrations are never overlapped in a real combustor. As a
         result, excluding CO in the calculation of gaseous radiative properties, as done in
         WSGGMs, is expected to yield differences or errors in the results. This has been
         demonstrated in a CFD analysis of a 0.8 MW natural gas oxy-fuel furnace (Yin,
         2017), in which a computationally efficient exponential wide band model (E-
         EWBM) is presented and implemented into the CFD analysis. The Yin et al.
         (2010b) oxy-fuel WSGGM, which is derived using the EWBM as a reference model,
         is also implemented into CFD analysis of the same furnace. The simulation results
         based on the two gaseous radiative property models are compared to each other as
         well as to the experimental data. The E-EWBM, which can naturally account for
         H 2 O, CO 2 , CO, CH 4 , NO, and SO 2 in the evaluation of gaseous radiative properties,
         is found to make distinct difference with the oxy-fuel WSGGM in the CFD results due
         to the impacts of high-concentration CO in a relatively large zone in the furnace.
            The accuracy of the E-EWBM may be further improved by refining some of the
         model parameters based on the line-by-line calculation with the HITEMP-2010 data-
         base, as attempted in (Yan et al., 2015). Such refinements can yield about 6% differ-
         ence in the total emissivity compared with the original EWBM (Yin, 2016). It needs to
         be emphasized that the accuracy of a specific CFD-oriented gas radiative property
         model (including the E-EWBM) can only be assessed by the comparison with the
         most comprehensive and accurate approach such as the line-by-line approach
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