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In this study, complete (i.e., including all vibrational quantum numbers in an N2vibrational ladder) data sets of vibration-to-vibration and vibration-to-translation rate coefficients for N2–N2collisions are explicitly computed along with transport properties (shear and bulk viscosity, thermal conductivity, and self-diffusion) in the temperature range 100–9000 K. To reach this goal, we improved a mixed quantum–classical (MQC) dynamics approach by lifting the constraint of a Morse treatment of the vibrational wave function and intramolecular potential and permitting the use of more realistic and flexible representations. The new formulation has also allowed us to separately analyze the role of intra- and intermolecular potentials on the calculated rates and properties. Ab initiointramolecular potentials are indispensable for highly excited vibrational states, though the Morse potential still gives reasonable values up to v= 20. An accurate description of the long-range interaction and the van der Waals well is a requisite for the correct reproduction of qualitative and quantitative rate coefficients, particularly at low temperatures, making physically meaningful analytical representations still the best choice compared to currently available ab initiopotential energy surfaces. These settings were used to directly compute the MQC rates corresponding to a large number of initial vibrational quantum numbers, and the missing intermediate values were predicted using a machine learning technique (i.e., the Gaussian process regression approach). The obtained values are reliable in the wide temperature range employed and are therefore valuable data for many communities dealing with nonlocal thermal equilibrium conditions in different environments.

The energy transfer, dissociations, and chemical reactions between O2and N2play an important role in the re-entry process of aircraft and many atmospheric, combustion, and plasma processes. Recently, Varga et al. (J. Chem. Phys., 2016, 144, 024310) developed a full-dimensional high-precision potential energy surface (PES) of the ground triplet electronic state for the O2and N2system based on ca. 55,000 data points, whose energies were calculated by multi-state complete-active-space second-order perturbation theory/minimally augmented correlation-consistent polarized valence triple-zeta electronic structure calculations plus dynamically scaled external correlation. The fitting function adopted the many-body expansion form with the four-body interactions fitted by the permutationally invariant polynomial in terms of bond-order functions of the six interatomic distances (MB-PIP). In this work, we refit the PES of the N2O2system by two methods based on the same data set that was used by Varga et al. The first uses the permutation invariant polynomial–neural network (PIP-NN) method to fit the entire energy of the 55,000 data points. In the second approach, the PIP-NN method is used to fit only the four-body interaction component, a similar treatment in the MB-PIP method, and the resulting PES is named MB-PIP-NN. Then, the performances of these new PESs and the MB-PIP PES are comprehensively and systematically compared, such as comparisons of various scans, properties of stationary points, and dynamics simulations. Possible improvements for the PES of N2O2are suggested. A more reliable PES of the system can be constructed in terms of data sampling range, electronic structure calculation level, and fitting method for high-temperature calculation and simulation in the future.

This study proposes a quasi-one-dimensional model to predict the chemical non-equilibrium flow along the stagnation streamline of hypersonic flow past a blunt body. The model solves reduced equations along the stagnation streamline and predicts nearly identical results as the numerical solution of the full-field Navier-Stokes equations. The high efficiency of this model makes it useful to investigate the overall quantitative behavior of related physical-chemical phenomena. In this paper two important properties of hypersonic flow, shock stand-off distance and oxygen dissociation, are studied using the quasi-one-dimensional model with the ideal dissociating gas model. It is found that the shock stand-off distance is affected by both chemical and thermal non-equilibrium. The shock stand-off distance will increase when the flow conditions are changed from equilibrium to non-equilibrium, because the average density of the shock-compressed gas will decrease as a result of the increase in translational energy. For oxygen dissociation, the maximum value of its dissociation degree along the stagnation line varies with the flight altitude. It is increased at first and decreased thereafter with the altitude, which is due to the combination effect of the equilibrium shift and chemical non-equilibrium relaxation. The overall variation of the maximum dissociation is then plotted in the speed and altitude coordinates as a reference for engineering application.

Aeroheating prediction is a challenging and critical problem for the design and optimization of hypersonic vehicles. One challenge is that the solution of the Navier-Stokes equations strongly depends on the computational mesh. In this letter, the effect of mesh resolution on heat flux prediction is studied. It is found that mesh-independent solutions can be obtained using fine mesh, whose accuracy is confirmed by results from kinetic particle simulation. It is analyzed that mesh-induced numerical error comes mainly from the flux calculation in the boundary layer whereas the temperature gradient on the surface can be evaluated using a wall function. Numerical schemes having strong capability of boundary layer capture are therefore recommended for hypersonic heating prediction.