Spatially heterogeneous shear-induced coagulation of spherical nano-particles in 2D Taylor-Green vortex using AK-iDNS framework

This study investigates the spatially heterogeneous shear-induced coagulation of nanoparticles in a decaying 2D Taylor-Green vortex (TGV) using a novel average kernel method integrated with direct numerical simulation (AK-iDNS). This framework resolves spatially distributed coagulation dynamics, addressing a critical gap in population balance modeling for aerosols. Key features of the approach include: 1) a moment method incorporating localized shear rates from instantaneous velocity gradients; 2) quantitative identification of coagulation-diffusion competition. Simulations reveal a three-stage process: initial uniformity, shear-driven heterogeneity (characterized by depletion in strain sheets and accumulation in vortex cores), and asymptotic re-homogenization driven by diffusion. The asymptotic solution demonstrates self-similar coagulation and exponential dependence on initial shear rate. This work provides a paradigm for predicting nanoparticle evolution in complex vortical flows and establishes a foundation for extending high-precision simulation tools to three-dimensional atmospheric nanoparticle evolution models.