Event Date
Biography
Ajinkya S Desai is a Lawrence Postdoctoral Fellow at Lawrence Livermore National Laboratory (LLNL) researching fire behavior and smoke plume dispersion in flat as well as complex terrain, both with and without forest cover. His career arc has been quite interdisciplinary. Ajinkya obtained his Ph.D. in Civil and Environmental Engineering from the Boundary Layers and Turbulence Laboratory at University of California, Irvine. After graduating with his Bachelor's in Aerospace Engineering from the Indian Institute of Technology (IIT), Kanpur, where he worked in the field of computational fluid dynamics, he moved to the USA for his Master’s at UC San Diego where his research investigated oceanographic field data. To explore his passion for the arts and their role in social reformation, he then pursued an MFA in the Dramatic Arts at the Old Globe Theatre in San Diego, following which he performed at correctional facilities and homeless shelters. At LLNL, Ajinkya’s research is primarily focused on field experiments, designed and implemented in collaboration with local Prescribed Burn Associations, US Forest Service stations, and universities. Moreover, he is also interested in exploring the utility of experimental data in model development and simulating underexplored fire behavior using existing models for improved physical underpinnings. He is also a member of the California Fire Science Seminar Series Student Committee, part of the California Fire Science Consortium, and assists in selecting and hosting speakers from diverse backgrounds in fire research and management across the country and internationally.
Abstract
Complex turbulence patterns emerge from the interaction of a wildland fire-front with its surrounding atmosphere in a variety of terrain and ambient conditions. This interaction, referred to as fire-atmosphere interaction, frequently begets unexpected fire behavior that is difficult to control and threatens communities residing at the boundaries of wilderness. Fire–atmosphere interactions also inform ember-driven ignitions and smoke dispersion patterns that affect respiratory health and visibility downwind. Despite the progress made in recent decades and the operational utility of several fire models, a lot still needs to be understood about fundamental fire behavior to improve model predictive capabilities and expand their range of application.
This work begins with the examination of wind velocity and temperature data collected during burn experiments ranging from small scales to operational scales (prescribed burns) for the turbulence processes characteristic of the presence of a fire in grassland and forested (canopy) environments. Given the spatial restraints on field measurements, we further attempt to investigate flow structures characteristic of buoyant-plume–canopy interaction under crosswind forcing through large-eddy simulations (LES) using a low-complexity, ‘no-flame’ setup. By varying ambient wind speeds and heat-source strength, we attempt to construct scaling laws informing plume deflection in canopy environments.
Comprehensive knowledge of these processes can help develop improved parameterizations for the process-level phenomena in coarser-resolution, fast-running, predictive fire-behavior and plume-dispersion models. Improved models can be utilized for careful planning of prescribed burns intended to reduce hazardous fuels and forewarning fire managers regarding conditions conducive to unexpected fire behavior, leading to efficient wildland fire management practices.