Yesterday, a group of visitors from the Institute of Chartered Foresters toured our lab, learned a lot about wood science and how wood properties are influenced by silviculture – with a talk by Elspeth Macdonald of Forest Research.
You can download the slides on wood properties and strength grading here.
As part of the fun, we played our “guess the strength” game. We also showed the same set of timbers to Twitter and LinkedIn before the event. Check out how well you predicted the strongest (and weakest) timbers below!
Here are the breaks in order, from worst to best:
(The codenames are not species – we think “Mint” and “Leek” were Scots pine, “Kale” and “Ivy” were spruce, and “Jasmine” was Douglas-fir)
And below you find the scores. We added some science guesses again: Dynamic modulus of elasticity was measured with an MTG timber grader and density was measured at the same time by recording mass and volume.
Username | Score* |
helpful_juniper_elk Dynamic modulus of elasticity | 2 |
gentle_larch_badger graceful_beech_robin lively_cedar_fox | 4 |
brainy_beech_finch cheerful_fir_fox courageous_juniper_finch gentle_maple_adder lively_chestnut_bear talented_maple_squirrel wandering_beech_wolf | 6 |
cheerful_rowan_elk gentle_lime_finch density expected score from random guessing | 8 |
by sound “by ear” | 10 |
This time, helpful_juniper_elk and science share the top spot. Helpful_juniper_elch did amazingly, they only switched the first two ranks and ranked all remaining timbers correctly. Chapeau! The MTG measurement too predicted the order of breaks nearly perfectly, only switching J and I. It is well expected that science cannot rank pieces of timber by strength, as the correlation between the dynamic MOE measurement and strength is far from perfect. This is why timber grading is not aiming at ranking pieces of timber, but mostly at rejecting the worst ones. If you want to learn more on how timber grading actually works, check out this post or this video (explaining grading with plums).
The order we agreed on as a group did not rank a single piece of timber correctly. Still, we were not too far off, and mostly managed to identify the better timbers (J and I) and the worse ones (L and M). LinkedIn as well identified J and I as the two favourites (each 34% of votes) and Twitter determined J as the strongest (53%) and L as the weakest (59%), which were very good guesses! The surprise winner was K – not even we expected this, only the MTG did (and a few lucky people online).
The score that we would expect to achieve with random guessing in this set is 8, which means none of us did worse than a random guess would have! The score of 10 comes from an experiment to order the timber by their sound when knocked with a hammer – just by ear – as an estimate for dynamic MOE. It seems we better keep using the machine…
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