Precise predictions of H 2 O line shapes over a wide pressure range using simulations corrected by a single measurement - Sorbonne Université
Article Dans Une Revue Journal of Quantitative Spectroscopy and Radiative Transfer Année : 2018

Precise predictions of H 2 O line shapes over a wide pressure range using simulations corrected by a single measurement

Résumé

In this work, we show that precise predictions of the shapes of H2O rovibrational lines broadened by N2, over a wide pressure range, can be made using simulations corrected by a single measurement. For that, we use the partially-correlated speed-dependent Keilson-Storer (pcsdKS) model whose parameters are deduced from molecular dynamics simulations and semi-classical calculations. This model takes into account the collision-induced velocity-changes effects, the speed dependences of the collisional line width and shift as well as the correlation between velocity and internal-state changes. For each considered transition, the model is corrected by using a parameter deduced from its broadening coefficient measured for a single pressure. The corrected-pcsdKS model is then used to simulate spectra for a wide pressure range. Direct comparisons of the corrected-pcsdKS calculated and measured spectra of 5 rovibrational lines of H2O for various pressures, from 0.1 to 1.2 atm, show very good agreements. Their maximum differences are in most cases well below 1%, much smaller than residuals obtained when fitting the measurements with the Voigt line shape. This shows that the present procedure can be used to predict H2O line shapes for various pressure conditions and thus the simulated spectra can be used to deduce the refined line-shape parameters to complete spectroscopic databases, in the absence of relevant experimental values.
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Dates et versions

hal-01730803 , version 1 (13-03-2018)

Identifiants

Citer

N. H. Ngo, H. T. Nguyen, H. Tran. Precise predictions of H 2 O line shapes over a wide pressure range using simulations corrected by a single measurement. Journal of Quantitative Spectroscopy and Radiative Transfer, 2018, 207, pp.16-22. ⟨10.1016/j.jqsrt.2017.12.014⟩. ⟨hal-01730803⟩
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