DropletSMOKE++: A comprehensive multiphase CFD framework for the evaporation of multidimensional fuel droplets

This paper aims at presenting the DropletSMOKE++ solver, a comprehensive multidimensional computational framework for the evaporation of fuel droplets, under the influence of a gravity field and an external fluid flow. The Volume Of Fluid (VOF) methodology is adopted to dynamically track the interface, coupled with the solution of energy and species equations. The evaporation rate is directly evaluated based on the vapor concentration gradient at the phase boundary, with no need of semi-empirical evaporation sub-models. The strong surface tension forces often prevent to model small droplets evaporation, because of the presence of parasitic currents. In this work we by-pass the problem, eliminating surface tension and introducing a centripetal force toward the center of the droplet. This expedient represents a major novelty of this work, which allows to numerically hang a droplet on a fiber in normal gravity conditions without modeling surface tension. Parasitic currents are completely suppressed, allowing to accurately model the evaporation process whatever the droplet size. DropletSMOKE++ shows an excellent agreement with the experimental data in a wide range of operating conditions, for various fuels and initial droplet diameters, both in natural and forced convection. The comparison with the same cases modeled in microgravity conditions highlights the impact of an external fluid flow on the evaporation mechanism, especially at high pressures. Non-ideal thermodynamics for phase-equilibrium is included to correctly capture evaporation rates at high pressures, otherwise not well predicted by an ideal gas assumption. Finally, the presence of flow circulation in the liquid phase is discussed, as well as its influence on the internal temperature field. DropletSMOKE++ will be released as an open-source code, open to contributions from the scientific community

Numerical study of self-assembly of granular and colloidal particles

Self-assembly of granular materials and colloids are studied using several different computational methods such as Discrete Element Method (DEM), Smoothed Particle Hydrodynamics (SPH) method, finite volume Volume of Fluid and DEM (VOF-DEM) method and coupled VOF-Level Set and Dissipative Particle Dynamics (CVOFLS-DPD) method. A history dependent contact model is developed for the DEM and a cohesion model is introduced to study the packing of granular materials under cohesive forces. The study reveals granular size and size distribution has an important effect on the final packing structure. The study using SPH method reveals stress relaxation in a granular system subjected consecutive jamming cycles. However, above a certain initial packing fraction stress relaxation is found to be negligible. Further analysis reveals characteristics length and time scales for stress relaxation. Three-cycle basis is found to be the most preferred configuration of the particles as the granular system drives towards a more stable state. The study using VOF-DEM method reveals pattern formation by colloidal deposits as a thin film of fluid evaporates. Further analysis with CVOFLS-DPD method reveals interface forces on particles need to be carefully modeled to prevent escaping of particles during evaporation. The use of machine learning (ML) for computational study is also explored in this study. A machine-learned sub-grid scale (SGS) modeling technique is introduced for efficient and accurate prediction of reactants and products undergoing parallel competitive reactions in a bubble column. The machine-learned model replaces the iterative approach associated with the use of analytical profiles for previous sub-grid scale models for correcting concentration profiles in boundary layers.Includes bibliographical references

Data for: DropletSMOKE: a comprehensive multiphase CFD framework for the evaporation of multidimensional fuel droplets

OpenFOAM code of the DropletSMOKE solver, written in C++THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Data for: DropletSMOKE: a comprehensive multiphase CFD framework for the evaporation of multidimensional fuel droplets

OpenFOAM code of the DropletSMOKE solver, written in C+