A Spatio-Temporal Dynamic Visualization Method of Time-Varying Wind Fields Based on Particle System

Abstract

The particle system is widely used in vector field feature visualization due to its dynamics and simulation. However, there are some defects of the vector field visualization method based on the Euler fields, such as unclear feature expression and discontinuous temporal expression, so the method cannot effectively express the characteristics of wind field on the temporal scale. We propose a Lagrangian visualization method based on spatio-temporal interpolation to solve these problems, which realizes the fusion and expression of the particle system and the time-varying wind data based on the WebGL shader. Firstly, the linear interpolation algorithm is used to interpolate to obtain continuous and dense wind field data according to the wind field data at adjacent moments. Then, we introduce the Lagrangian analysis method to study the structure of the wind field and optimize the visualization effect of the particle system based on Runge–Kutta algorithms. Finally, we adopt the nonlinear color mapping method with double standard deviation (2SD) to improve the expression effect of wind field features. The experimental results indicate that the wind visualization achieves a comprehensive visual effect and the rendering frame rate is greater than 45. The methods can render the particles smoothly with stable and outstanding uniformity when expressing continuous spatio-temporal dynamic visualization characteristics of the wind field.

A Vector Field Visualization Method for Trajectory Big Data

“…Work relevant to this paper primarily focuses on particle-based visualization methods. Particle systems simulate fuzzy and abstract objects by modeling many particles' motion and attribute changes, offering new perspectives for vector field visualization [34]. Hin and Post [35] decomposed turbulence into convective motion and turbulent motion through Reynolds decomposition, establishing a physical relationship between perturbation and eddy diffusion coefficients, and achieved excellent flow visualization results through the collective behavior of numerous particles.…”