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散射截面和反应速率系数是阐明分子气体态-态碰撞传能机制的重要参数，也是进行非平衡气体动力学建模的重要依据。本文采用动力学模拟中的准经典轨迹方法（ QCT）计算了90个不同初始振动态组合的N2(v)+O2(w)碰撞过程，详细讨论了各个振动激发、解离反应通道的贡献和演变趋势。研究发现，O2和N2在振动-振动能量交换（ VV）通道的贡献比较接近，振动-平动跃迁（ VT）通道主要以O2为主；总解离截面主要来自O2单解离通道，交换解离其次，N2单解离和双解离通道的贡献相对较小。基于QCT数据集，训练了性能良好的神经网络模型（相关系数R值达到0.99） ，可用于预测N2+O2态-态碰撞的总解离截面。和仅采用动力学模拟方法相比，计算成本降低了约91.94%。在5000-30000K高温范围内，给出了VV/VT速率系数的解析表达式。The scattering cross-sections and reaction rate coefficients are crucial parameters for elucidating the energy transfer mechanism of state-to-state collisions between molecular gases and also serve as a fundamental basis for modeling the non-equilibrium flow field. However, the database of kinetic processes related to nitrogen shock flows is still being developed. In this work, a detailed kinetic study of the N2+O2 collision is carried out by combining the quasi-classical trajectory method (QCT) and neural network model (NN). Firstly, QCT is used to calculate 90 N2(v)+O2(w) processes with various initial vibrational states (v,w), and the contributions of all vibrational excitation and dissociation reaction channels are discussed. The following conclusions were drawn: i) the contributions of the vibration-vibration (VV) energy exchange channel of O2 and N2 are similar, while the vibration-translational (VT) transition mainly occurs on O2; and ii) the total dissociation cross-section primarily results from the O2 single-dissociation channel, followed by the exchange-dissociation channel, with relatively minor contributions from the N2 single- and double-dissociation channels. Then, based on the QCT dataset, a high-performance NN model (R-value of 0.99) is trained to predict the total dissociation cross-section caused by N2(v)+O2(w) collisions. Compared to the method using only QCT, the computational cost is reduced by approximately 91.94%. Finally, to facilitate use in kinetic modeling, Arrhenius-type fits for the VV/VT rate coefficients are provided over the temperature range of 5000-30000K, and an exponential form related to the translational energy Et was used to fit the total dissociation cross-section.
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Keywords:
- State-to-state reaction rate coefficient /
- Vibration relaxation /
- Collision dissociation /
- Neural network model
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