You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: paper/paper.md
+4-4Lines changed: 4 additions & 4 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -100,8 +100,8 @@ ForeFire was developed as a community tool to fill the gap between highly comple
100
100
101
101
## Rapid prototyping of new models
102
102
ForeFire implements several standard fire flux and spread rate models, such as Rothermel [@andrews2018] and Balbi [@balbi2009], and makes it trivial to switch, extend, or add to this base with a single `.cpp` file using any existing model file as a template.
103
-
Internally, data is handled as *layers* that can come from a NumPy array, be read from NetCDF, or be generated on the fly by ForeFire (e.g., slope derived from the elevation layer, fuel loaded as an index map with tabulated fuel — with standards fuel tables [@Scott2005] already available).
104
-
Developing a Rate Of Spread wildfire model was the original purpose of this simulation code and helped to iterate versions of the Balbi Rate Of Spread formulation on case studies [@balbi2009;@santoni2011]. It also served to implement various heat and chemical species flux models used for volcanic eruption [@filippi2021], plume chemistry [@strada2012], or industrial fires [@baggio2022]. In addition, the code includes a generic `ANNPropagationModel` that implements a feedforward artificial neural network (ANN) and expects a pre-trained graph file.
103
+
Internally, data is handled as *layers* that can come from a NumPy array, be read from NetCDF, or be generated on the fly by ForeFire (e.g., slope derived from the elevation layer, fuel loaded as an index map with tabulated fuel — with standard fuel tables [@Scott2005] already available).
104
+
Developing a Rate Of Spread wildfire model was the original purpose of this simulation code and helped to iterate versions of the Balbi Rate Of Spread formulation on case studies [@balbi2009;@santoni2011]. It also served to implement various heat and chemical species flux models used for volcanic eruption [@filippi2021], plume chemistry [@strada2012], or industrial fires [@baggio2022]. In addition, the code includes a generic `ANNPropagationModel` that implements a feedforward artificial neural network (ANN) and expects a pre-trained graph file.
105
105
106
106
## Batch simulations with the ForeFire scripting
107
107
Custom FF language allows users to easily generate multiple scenarios, including fire-fighting strategies, model evaluation [@filippi2014], ensemble forecasts [@allaire2020], or generate a deep learning database [@allaire2021]. A FF script is a set of scheduled instructions that are interpreted in real-time, advancing the simulation clock with a `step[dt=]` or a `goTo[t=]` command.
@@ -113,11 +113,11 @@ By utilizing pre-compiled datasets over extensive regions, this approach support
113
113
114
114
115
115
### Two-way coupling with the MesoNH atmospheric model
116
-
The same scripts can be executed in coupled mode with the Open-Source atmospheric model [MesoNH](https://mesonh.cnrs.fr/)[@lac2018] with fire propagating using surface fields (wind) from MesoNH and forcing heat and other flux fields into the atmosphere. An idealized coupled simulation can be run on a laptop at field scale [@filippi2013], but also on a supercomputer to forecast fire-induced winds of large wildfires [@filippi2018], fire-induced convection [@couto2024;@campos2023], or even to estimate wildfire spotting [@alonsopinar2025].
116
+
The same scripts can be executed in coupled mode with the Open-Source atmospheric model [MesoNH](https://mesonh.cnrs.fr/)[@lac2018] with fire propagating using surface fields (wind) from MesoNH and forcing heat and other flux fields into the atmosphere. An idealized coupled simulation can be run on a laptop at field scale [@filippi2013], but also on a supercomputer to forecast fire-induced winds of large wildfires [@filippi2018], fire-induced convection [@couto2024;@campos2023], or even to estimate wildfire spotting [@alonsopinar2025].
117
117
118
118
Coupled simulations generate gigabytes of 3D data that can be converted to VTK/VTU files using Python helper scripts to visualize in the open-source tool ParaView, as shown in \autoref{fig:coupled}.
119
119
120
-
![Coupled simulation of the Pedrogao Grande wildfire [@couto2024] (Paraview rendering). On the ground, the burned area is in orange, while among atmospheric variables, downbursts are highlighted in red and pyro-cumulonimbus clouds in blue.\label{fig:coupled}](coupled.jpg)
120
+
![Coupled simulation of the Pedrogao Grande wildfire [@couto2024] (ParaView rendering). On the ground, the burned area is in orange, while among atmospheric variables, downbursts are highlighted in red and pyro-cumulonimbus clouds in blue.\label{fig:coupled}](coupled.jpg)
121
121
122
122
# Acknowledgements
123
123
This work has been supported by the Centre National de la Recherche Scientifique and French National Research Agency under grants **ANR-09-COSI-006-01 (IDEA)** and **ANR-16-CE04-0006 (FIRECASTER)**. The authors thank all contributors and collaborators who have assisted in the development and testing of the ForeFire software.
0 commit comments