Mr Eric Victor Mueller

Research Associate/Postgraduate

Email: 

Telephone: 

+44(0)131 6507241

Location: 

John Muir

Research Institute: 

  • Infrastructure and Environment
Mr Eric Mueller
Mr Eric Mueller

Academic Qualifications: 

  • BS - Engineering Physics, Summa Cum Laude, Tufts University (2010)
  • MS - Fire Protection Engineering, Worcester Polytechnic University (2012)

Research Interests: 

Field-scale studies of wildand fire behavior

  • Despite the growing risks associated with increasingly severe fire seasons and expanding development of the wildland-urban interface, significant gaps exist in our fundamental understanding of wildland fire behavior. Wildland fires are highly complex events, driven by phenomena that occur at a wide range of scales - from microscale combustion to mesoscale atmospheric interactions, and everything in between. In order to develop strategies, both for suppression in the short term and management in the long term, a more complete understanding of these phenomena is required. Otherwise, we run the risk of becoming overly reliant on heuristic approaches that leave more room for unforeseen and undesirable outcomes.
  • Experimental measurements of fire behavior at the field scale are a key part of understanding the driving processes behind wildland fire behavior. These studies allow us to get close to conditions which are representative of a real wildland fire, and can be indicative of a prescribed fire. However, due to limitations imposed by the cost, labor, and safety concerns of such experiments, along with the inability to completely prescribe or control conditions during the test, experiments cannot provide the whole solution. They must be supplemented by numerical modeling.
  • In particular, computational fluid dynamics (CFD) models have shown promise in recent years. This is owing to their approach of attempting to accurately model, if not directly solve, all of the relevant physical phenomena (by solving the conservation equations). By taking this physical rather than empirical approach, the goal is to develop a flexible tool which can be used to model fire behavior in a wide range of conditions and scenarios. Such models can even be used to obtain correlations that feed into the more straightforward (and computationally faster) empirical models. However, due to the level of complexity inherent in such models, they require extensive development and testing. This stage is ongoing, and necessitates detailed experimental measurements for comparison. The connection between these two aspects is the main focal point of this work.