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The present study reports an updated detailed chemical kinetic model for soot formation.
In this work, a new statistical model for soot formation and growth is developed and presented.
A sectional approach for the description of Polycyclic Aromatic Hydrocarbons (PAHs) and a two-equation model for soot particle dynamics are introduced.
Significant improvements in the prediction of soot volume fraction are obtained using the PAH inception model for soot inception compared to the conventional acetylene approach.
A subgrid model for soot dynamics is developed for large-eddy simulation (LES) that uses a method of moments approach with Lagrangian interpolative closure (MOMIC) so that no a priori knowledge of the particles' distribution is required.
The chemical kinetic mechanism has been coupled to a sectional aerosol dynamics model for soot growth, considering PAH-based inception and surface condensation, surface chemistry (growth and oxidation), coagulation, and fragmentation.
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Using this unified sooting tendency database, we have developed a predictive model for sooting behavior applicable to a broad range of hydrocarbons and oxygenated hydrocarbons.
Morel and Keribar [40] and Wahiduzzaman et al. [41] suggested models for soot formation and their oxidation in diesel engines.
This could be attributed to the large distribution in the measurements or the chemical/physical models for soot formation.
New bivariate models for soot particle structure are introduced to qualitatively replicate observed particle shapes and are found to offer quantitative improvements over older single-variable models.
Experimental results suggest that the agreement among the three individual temperatures obtained from three-color pyrometry depends on which of the above models for soot radiation is used.
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