Cellular automata ray tracing in two-dimensional aero-optical flow fields

Abstract

<sec>For the supersonic flow field with large density fluctuation produced by the unsteady flow and turbulent large-scale structures, an effective method to obtain the beam path is to solve the ray equation. Then the optical path difference (OPD), Strehl ratio (SR), optical transmission function (OTF), etc. can be obtained to analyze the optical distortion, and the correction of aero optics effects can be realized to improve the optical system performance. Generally, when the refractive index distribution is arbitrary, the ray equation analytic solution is difficult to obtain.</sec> <sec>Cellular automata (CA) ray tracing algorithm is proposed in this paper for aero-optical calculation in the 2D discrete flow fields. Unlike numerically solving the ray equation (NSRE), the coordinate value and the offset angle are calculated according to the position and direction transformation rules in CA algorithm. The position transformation rule is used to obtain the end point of the beam vector and determine whether the offset angle needs calculating at each iteration, the direction transformation rule is to calculate the offset angles. Then the refractive index field is integrated along the beam path to obtain the optical path length (OPL). The OPD is calculated from OPL. In this paper, aero-optical calculation is based on two types of flow fields. The supersonic shear layer including supersonic mixing layer and boundary layer 2D density distribution is measured by the nano-tracer-based planar laser scattering (NPLS) technique. The supersonic flow field surrounding the optical dome is simulated based on detached-eddy simulation (DES).</sec><sec>The OPD<sub>rms</sub> and program running time quantitatively verify the calculation accuracy and high efficiency of CA. The results show that for the 2D supersonic NPLS flow field and the 2D supersonic flow field surrounding the optical dome, the calculation accuracy of CA is approximately equal to NSRE. Moreover, we find that the program running time of NSRE is about four times that of the CA algorithm, so the efficiency of ray tracing is effectively improved. Thus, the CA algorithm provides a new scheme for aero-optical calculation in the 2D supersonic flow field. Meanwhile, it also provides a guideline for the research on the ray tracing in 3D discrete aero-optical flow field.</sec>

Accurate characterization of full-chain infrared multispectral imaging features under aerodynamic thermal environment

“…Cellular Automata (CA) typically comprise cellular space and rule functions. By defining specific computational domains, setting appropriate rule functions, and specifying initial conditions, boundary conditions, and neighborhood constraints, it is possible to simulate a wide range of complex systems [14,15]. To calculate aero-optical and aero-thermal radiation effects, a computational domain can be generated by integrating information from multiple physical fields within the same cellular space and applying specific boundary constraints.…”

“…Wang et al used ray tracing based on the fourth-order Runge-Kutta method to complete the accurate numerical calculation of aero-optical and aero-thermal radiation effects [12,13]. Luo et al established a differential ray equation solution format based on Cellular Automata to achieve efficient numerical calculation of aero-optical effects [14,15]. Ju et al studied the influence of aerooptical and aero-thermal radiation effects on the degradation of imaging quality under timevarying conditions based on the ray tracing method [16].…”

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“…Evolutionary rule: The state transfer equation required when a tuple changes its own state according to the state of its neighbors [18]. The local evolution rule is the most important component of a cellular automaton.…”