Generalization of the k-moment method using the maximum entropy principle. Application to the NBKM and full spectrum SLMB gas radiation models

Abstract The k-moment method is generalized by applying the maximum entropy principle to get several estimates of the k-distribution function on any kind of spectral interval as a function of the first two moments of the absorption coefficient. Corresponding formulations of the blackbody weighted band averaged transmission function of a gaseous uniform path are obtained. Different constraints involving the first and second order positive, first order negative and logarithmic moments are introduced together with a physical meaning whenever it is possible. Different sets of these constraints are considered to get maximum entropy estimates of the distributions functions: the Dirac, exponential, Gamma, inverse Gaussian and reciprocal inverse Gaussian k-distribution functions. Analytical formulas are provided for each of these distributions and for their associated transmission function, as a function of the mean and variance of the absorption coefficient. The methodology can be applied considering any spectral interval: narrow, wide, the full spectrum, continuous or not. Thus the resulting associated transmission and cumulative k-distribution functions can be utilized in the frame of a large variety of gas radiation models. Hence the k-moment method using the maximum entropy principle is assessed in the frame of the NBKM and full spectrum SLMB gas radiation models. A series of test cases implying comparisons with reference Line-by-Line results exhibits which maximum entropy k-distributions are likely to give the best estimations of narrow band or total emitted intensities, curves-of-growth of the total emission function and full spectrum cumulative k-distribution functions. In particular, the inverse Gaussian and Gamma k-distributions seem most of the time to perform very well.

[1]  G. A. Watson A treatise on the theory of Bessel functions , 1944 .

[2]  R. Vaillon,et al.  A nonuniform narrow band correlated-k approximation using the k-moment method , 2010 .

[3]  E. Jaynes Information Theory and Statistical Mechanics , 1957 .

[4]  Anouar Soufiani,et al.  Gas IR Radiative Properties: From Spectroscopic Data to Approximate Models , 1999 .

[5]  T. Kawamura,et al.  Characterizations of the Distributions of Power Inverse Gaussian and Others Based on the Entropy Maximization Principle , 2003 .

[6]  Y. Yung,et al.  Atmospheric Radiation: Theoretical Basis , 1989 .

[7]  M. Modest Radiative heat transfer , 1993 .

[8]  R. Vaillon,et al.  The spectral-line moment-based (SLMB) modeling of the wide band and global blackbody-weighted transmission function and cumulative distribution function of the absorption coefficient in uniform gaseous media , 2008 .

[9]  D. Widder Necessary and sufficient conditions for the representation of a function as a Laplace integral , 1931 .

[10]  W. Collins,et al.  Extension of the weak-line approximation and application to correlated-k methods , 2011 .

[11]  R. Vaillon,et al.  The k-moment method for modeling the blackbody weighted transmission function for narrow and wide band radiative properties of gases , 2007 .

[12]  S. Tashkun,et al.  CDSD-1000, the high-temperature carbon dioxide spectroscopic databank , 2003 .

[13]  O. Gicquel,et al.  A multi-spectral reordering technique for the full spectrum SLMB modeling of radiative heat transfer in nonuniform gaseous mixtures , 2011 .

[14]  G. S. Mudholkar,et al.  The Inverse Gaussian Models: Analogues of Symmetry, Skewness and Kurtosis , 2002 .

[15]  Irene A. Stegun,et al.  Handbook of Mathematical Functions. , 1966 .

[16]  Tinne Hoff Kjeldsen,et al.  The Early History of the Moment Problem , 1993 .

[17]  Gerassimos A. Athanassoulis,et al.  Moment information for probability distributions, without solving the moment problem, II: Main-mass, tails and shape approximation , 2009 .

[18]  R. Vaillon,et al.  A database for the SLMB modeling of the full spectrum radiative properties of CO2 , 2010 .

[19]  D. Widder The inversion of the Laplace integral and the related moment problem , 1934 .

[20]  Mikhail Alexandrov,et al.  A new three-parameter cloud/aerosol particle size distribution based on the generalized inverse Gaussian density function , 2000, Appl. Math. Comput..