Author(s): Dongchen Wang; Marcelo H. Garcia
Linked Author(s):
Keywords: Density driven mixing layer; Remote sensing image based model
Abstract: Previous study about river mixing layer (ML) has been focused on the mixing of flows with homogenous properties. The impact of temperature, salinity, turbidity, or other properties of river water are neglected. However, under certain circumstances, the minor variance of flow densities (> 0.1\%) may cause different mixing patterns. This density-driven mixing layer (DDML) can be found in many places, such as Chicago River confluence and Rio Parana and Paraguay confluence. At these locations, salinity and turbidity difference between two branches causes a plunging mixing phenomenon which affects the mixing efficiency. Depending on flow conditions, the difference in mixing could be more than two orders of magnitude. In this work, the density-driven mixing layer (DDML) is categoried into four different types, and links to numerical model to study its dynamics. Three transition states from classic mixing layer (ML) by Best (1987) to density-driven mixing layer (DDML) are presented.
Year: 2020