Improving Monte Carlo simulations for an accurate modeling of soot aggregation

International audienceThe aggregation of soot particles is probably the most important mechanism of growth. In this context, particles naturally evolve into polydisperse sizes [1]. These particles experience a movement characterized by very different momentum relaxation times (i.e. the ratio between the particle mass and friction coefficient). Thus, accurate numerical methods, such as Langevin Dynamics become computationally expensive to simulate the coagulation of a large population of particles [2]. On the other hand, the Monte Carlo (MC) method (simply consisting in iteratively selecting a particle at time, moving it in a random orientation and checking for collisions), is a very computationally efficient alternative to overcome this issue. However, it is usually regarded as a technique that relies on an artificial description of time making it difficult to study aggregation process [3]. Despite this, some efforts have been made to obtain a more physical description of time [4, 5]. Unfortunately, as we will show, they usually lead to incoherent time progress for the ensemble of polydisperse particles and/or they are restricted to specific flow regimes (continuum or free molecular). Also, in different studies based on the MC method, the probability of moving a particle is adapted to the specific flow regimes with some rules whose expressions lack of justification [6]. Moreover, in such studies, particles are usually displaced along a constant distance in the order of the monomer’s diameters, regardless of their sizes. A few studies have considered size-dependent displacements [7]. In this study, we propose a new MC method with justified probabilities of particles movement, considering size-dependent displacement and able to bring a validated and consistent physical time evolution for individual as well as for the ensemble of polydisperse particles.The method is firstly presented and compared with previous methods found in the literature to finally validate it by comparison with Langevin Dynamics simulations. The evolution of calculated mean squared displacements for different-sized particles is compared with theoretical values. The method is able to efficiently simulate the dynamics of coagulation. For the first time, consistent and coherent residence times of particles are obtained. The proposed MC method could be used to study more complex dynamic processes such as aggregates sintering, surface growth or breakage