[Eoas-seminar] [Seminar-announce] Scientific Computing Colloquium with Saurabh Saxena

[eoas-seminar at lists.fsu.edu]

"Water and Energy Balance-Based Model for Predicting Diurnal Ignition Potential of Complex Fuels"

Saurabh Saxena
PhD student in Mechanical Engineering
Florida State University

NOTE: Please feel free to forward/share this invitation with other groups/disciplines that might be interested in this talk/topic. All are welcome to attend.

https://fsu.zoom.us/j/94273595552

Meeting # 942 7359 5552


Wednesday, October 19, 2022, Schedule:

* 3:00 to 3:30 PM Eastern Time (US and Canada)
Nespresso & Teatime (in 417 DSL Commons)

* 3:30 to 4:30 PM Eastern Time (US and Canada)
Colloquium - Attend F2F (in 499 DSL) or Virtually (via Zoom)

Abstract:

Fuel ignition potential is one of the primary drivers influencing the extent of damage in wildland and wildland-urban interface fires. Determining fire and ember exposure of fuels that vary spatially and temporally will aid in recognizing necessary defensive actions and mitigating damages. This study develops a novel coupled water-energy balance model that predicts diurnal temperature and moisture content evolution of multi-material objects/fuels of complex shapes. The simulations are done in high spatial and temporal resolutions under changing environmental conditions. Examples of complex fuel scenarios are interface or intermix communities composed of natural and manmade random-shaped objects. The fuel ignition potential is determined by predicting the transient temperature and dryness of fuel, which depends on several parameters, including terrain, geographical location, local weather conditions, fuel material, and proximity to flame (if any exists). The model can be used in various fuel condition problems and due to its high spatiotemporal resolution, can also be coupled with computational fluid dynamics simulations when coupled physics is desired. This presentation focuses on the model theory and demonstrates that the model performs well against several existing analytical and measured data.


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