Modelling of droplet evaporation in humid gas with algebraic heat and mass transfer models

The study focuses on advancing the understanding of droplet evaporation in humid gas environments through the utilization of the LibHuAir Xiw library and a constant property model. LibHuAir Xiw provides instrumental in enhancing the precision of modeling and simulation, offering a suite of tools for tasks such as heat and mass transfer calculations in humid conditions and determining thermodynamic properties. The integration of this library marks a pivotal step toward achieving the study’s objectives. The investigation begins by emphasizing the significance of studying single droplet evaporation as a foundational step for comprehending the broader evaporation process. Droplet evaporation, a fundamental phenomenon occurring when a liquid droplet is exposed to a gas environment, is explored in-depth. The study delves into the intricacies of mass transfer, vaporization, and diffusion, crucial processes governing droplet evaporation in various scientific, industrial, and natural contexts. The constant property model is introduced to simplify the understanding of droplet evaporation, incorporating key parameters such as droplet radius and Spalding mass transfer number. The model considers the dynamic equilibrium between vapor molecules diffusing outward and those from the liquid phase, contributing to a sustained and controlled evaporation rate over time. Energy exchange and its relationship with heat transfer during droplet evaporation are discussed, highlighting the absorption of latent heat of vaporization from the surroundings, resulting in a reduction in droplet temperature. The model’s evaluation involves considering factors like the droplet evaporation rate, diffusion coefficient, and Spalding mass transfer number. The study employs the constant property model to simulate droplet evaporation over time, showcasing a graphical representation of droplet radius. To validate the constant property model, comparisons are made with experimental data from Ranz and Marshall (1952), demonstrating a close match between the model’s simulation and the experimental results. The adaptation of the linear graph to a nonlinear representation facilitates a thorough understanding of the model’s performance, emphasizing its efficency.