@inproceedings{c54d246a095848529d8ffeb5923bce45,
title = "Density driven mixing layer in environmental flows: A high-resolution remote sensing image based, numerical simulation and field measurements aided confluence mixing 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.",
keywords = "Density driven mixing layer, Remote sensing image based model",
author = "Dongchen Wang and Garc{\'i}a, {Marcelo H.}",
note = "Publisher Copyright: {\textcopyright} 2020 Taylor & Francis Group, London; 10th Conference on Fluvial Hydraulics, River Flow 2020 ; Conference date: 07-07-2020 Through 10-07-2020",
year = "2020",
language = "English (US)",
series = "River Flow 2020 - Proceedings of the 10th Conference on Fluvial Hydraulics",
publisher = "CRC Press/Balkema",
pages = "130--136",
editor = "Wim Uijttewaal and Franca, {Mario J.} and Daniel Valero and Victor Chavarrias and Arbos, {Claudia Ylla} and Ralph Schielen and Ralph Schielen and Alessandra Crosato",
booktitle = "River Flow 2020 - Proceedings of the 10th Conference on Fluvial Hydraulics",
}