This paper presents a general two-dimensional non-stationary semicausal model for the simulation of mixture fraction, which improves our previous causal model. The proposed model includes not only the pre-correlation predictors (both in time space and geometric space) as well as the cross-correlation predictors, as in the causal model, but also post-correlation predictors. The latter makes possible the consideration of interactions of a scalar, such as mixture fraction, at a physical location with that of all its adjacent locations. It has also been shown that the complicated second-and higher-order correlation predictors can be neglected in the semicausal simulation of mixture fraction. To show the validity of the model, the stochastic mean and variance of the spectral intensities at different wavelengths were predicted and compared with detailed experimental data for turbulent carbon monoxide/hydrogen/air diffusion flames having different Reynolds numbers. These comparisons showed excellent agreement with existing data and the improvement over the prior causal model.

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