Evaporation

Measurement vs. modeling

The biggest contradiction in evaporation is that the real sprays may have a size distribution where even the largest droplets are below 50 μm, however, measurements of individual droplets are typically in the range of one mm. Therefore, the models are developed for a much larger size than it is present in real sprays. Even though the use of non-dimensional space allows some scaling, this problem gives researchers a lot of additional work to address the additional effect occurring in small scales.

The two common techniques, drop-tower, and suspended droplet methods have few biases which require correction to establish a proper evaporation model. This is an ongoing project to provide the proper correction tools for the measurement data by knowing the thermal environment.

The above-detailed problem is further entangled with the fact that real evaporating liquids may consist of several hundred components. Therefore, modeling requires surrogate mixtures to simplify the liquid to handle the problem numerically.

suspended droplet
Energy balance of an evaporating suspended droplet
radiation_in_evaporation
The share of radiative heat transfer at various conditions

Advancements in evaporation modeling

The D2-law is the basis of the recent evaporation models. With its limitations, it is still the most versatile model which requires low computational effort and provides a conservative estimation that is preferred by the industry. Nevertheless, the number of limiting constraints of this model was recently lowered through considering thermal radiation and non-unity Lewis number.

Even if we derive an excellent evaporation model, the estimation of evaporation will be burdened by the uncertainty of the material properties. If this is measured and published along with the corresponding uncertainties, a proper estimation can be performed. However, these databases are rather limited, and they only contain properties in a highly limited range for the fractions of common evaporating species. To solve this problem, chemists proposed several models for data estimation based on molecular theory. However, these approaches require tough evaluation and validation to make them a really powerful approach to substitute the missing quantities.