Students, faculty, researchers and engineers from fire safety programs around the world are invited to join the "burning behavior prediction" competition - of a Balsam Fir Christmas Tree. The highest individual and highest group scores - i.e., the average scores of all submissions from a single research team or program (min. 3 team members) - will be announced to all competition participants and the research team (from a University or research institution) with the highest average group score will also earn the coveted Golden Pinecone Award.

The competition burn will be livestreamed for all participants. Our current reigning champions are the members of University of Queensland Fire Safety Science and Engineering Program. Hopefully someone new can dethrone them and earn the Golden Pinecone this year!

COMPETITION TREE INFORMATION:Holiday trees for FPE burn demo 2021

Species: Balsam Fir (3x, pictured right)
Weight: 11.92kg +/- 0.90 kg
Height: 188 cm +/- 6 cm
Storage: Trees will be kept, unwatered, for 15 days in laboratory storage at approximately 50% relative humidity and 18°C.
Ignition: 6 cm diameter pool of heptane (40 mL) placed approximately 10 cm below the lowest branches and 30 cm away from the trunk of the tree (Note: this procedure moves the ignition source farther away from the center of the tree as compared to previous competitions).

Uncertainties represent one standard deviation of height and weight measurements of each of the three individual competition trees.

HOW TO PARTICIPATE: Generating and submitting your predictions

This year, the submission (and generation of) predicted heat release rate (HRR) curves will once again be made

possible by visiting Here, you can use a custom-made app that allows you to ‘build’ (and submit) your own fire by adjusting just four parameters that define:

  • Fire Growth Rate
  • Peak Heat Release Rate (Peak HRR)
  • Duration of Steady Burning
  • Fire Decay

In this app, after you click submit, an email will be generated that contains the four parameters defining your HRR curve. In this email, please remember to add your name, email and lab affiliation if you wish to receive credit (and final competition results) and CLICK SEND so that we receive your submission.

If you prefer the old system – submitting HRR predictions in massive spreadsheets or .txt files – you may submit those files directly to These prediction files should be formatted in two columns with a 1 Hz resolution in the format: [time (s) | HRR (kW)].

Data table from 2019 Christmas tree fire burn.

The burn tests will be repeated in triplicate and your predictions will be scored with respect to the average and standard deviations (with explicit considerations for measurement uncertainty) of experimentally measured burning behavior (i.e., peak HRR, time to peak, fire growth time and duration, and total energy release).

Points (100 possible) will be awarded in 5 categories as listed below. Our scoring system will give up to 20 points for each category so long as the predicted values are within two standard deviations considering the calculated uncertainties. 


Uncertainty calculated as:

Peak Heat Release Rate

Propagation of error includinguncertainty in time-resolved balance reading and
heat of combustion

Total Energy Release

Propagation of error includinguncertainty in time-resolved balance reading and
heat of combustion  

Time to Peak Heat Release Rate

Standard deviation of time to
peak HRR values measured in each
of the 3 repeated tests

Duration in which HRR exceeds 80% of peak HRR

In each test, a lower and upper estimate of the duration of burning in which HRR exceeds 80% of peak HRR can be made based on the uncertainty in measured HRR. These two values are shown graphically in Fig. 1.

Uncertainty in 80% duration is thus calculated as the standard deviation of all 6 of these values measured from each of the 3 repeated tests.

Duration in which HRR exceeds 50% of peak HRR

Calculated identically as the
uncertainty in 80% duration


QUESTIONS?  Please contact demo leaders,  Dr. Isaac Leventon ( or Dr. Fernando Raffan-Montoya (

Dr. Leventon would like to thank Dr. Anthony  Hamins of NIST for his thoughtful comments and helpful suggestions in conversations leading up to this year's event.