Events Calendar

AME Seminar

Speaker: Tirtha Banerjee, UC Irvine

Talk Title: TBD

Abstract: The traditional motivation behind studying the dynamics of turbulent wind flow in vegetation canopies has been to understand the nature of mass, momentum and energy exchange between the land surface and the atmosphere. The nature of this interaction determines the microclimate in a forest environment where plants exchange carbon and water and its understanding is relevant for a plethora of applications ranging from ecology, hydrology, agriculture and the modeling of weather and climate. However, the fundamental nature of turbulence in a vegetation canopy is significantly different from the atmospheric surface layer lying above, which means that scaling laws and exchange coefficients from traditional wall bounded flows are not applicable. In a forest canopy, momentum absorption happens not only at the ground surface but throughout the depth of the canopy, resulting in a unique roughness sub layer. Instead of a log-layer, the mean velocity profile is inflected, second order moments are variable with height and skewnesses are large. Large scale coherent structures impart significant impact on the turbulence dynamics. Sweeping motions arising out of downdraft motions of counter-rotating vortices dominate eddy fluxes. A mixing layer model is found to be a better model for describing canopy flows. High frequency measurements and computational fluid dynamics modeling, especially Large Eddy Simulations (LES) has been instrumental in revealing the nature of canopy turbulence in the last few decades. Now this knowledge is being used to push the frontiers of our limited understanding of how wildland fires behave. The main controls on wildland fire behavior -“ fuel (canopy and grasslands), weather and topography are strongly influenced by fine scale physics of canopy turbulence. We will demonstrate that further developments in the understanding of canopy turbulence can benefit wildfire modeling tools and developing actionable management strategies.

Biography: Tirtha Banerjee is an Assistant Professor at the Department of Civil and Environmental Engineering, University of California, Irvine. He received his Bachelor of Science degree in Civil Engineering from Jadavpur University, Calcutta, India in 2011. During his undergraduate studies, he conducted research in the areas of structural dynamics and Aerospace Engineering in India and Germany as a DAAD (German Academic Exchange Service) Fellow. Upon completion of his undergraduate studies in 2011, he moved to the U.S. and joined Duke University in Durham, NC, as a Ph.D. student and conducted theoretical, numerical and experimental studies involving environmental fluid dynamics and turbulent flows. He received his Ph.D. in 2015 and joined the Karlsruhe Institute of Technology (KIT) in Germany for postdoctoral research in atmospheric boundary layer dynamics. He relocated to the U.S. in early 2017 to join the Los Alamos National Laboratory (LANL) in New Mexico and started working on wildfires, ecosystem disturbance as well as wind energy resources. At LANL he received a Chick Keller Postdoctoral Fellowship in 2017 and a Directors Fellowship in 2018. He joined UC Irvine in fall 2019. Research in the Boundary Layers and Turbulence Lab led by Banerjee studies mass, momentum and energy exchange between the land surface and the atmosphere using a range of theoretical, numerical and experimental techniques. He currently serves as an associate editor of the journal Earth Systems and Environment (Springer) and as an editorial board member of the journal Agricultural and Forest Meteorology (Elsevier).

Host: AME Department

More Info: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09

Webcast: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09

Location: Seaver Science Library (SSL) - 202

WebCast Link: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09

Audiences: Everyone Is Invited

Contact: Tessa Yao

Event Link: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09