Fukushima from Afar: Realtime Data that Matters(blog.cloudant.com)
blog.cloudant.com
Fukushima from Afar: Realtime Data that Matters
http://blog.cloudant.com/fukushima/
5 comments
The scientific article behind this is interesting; it is at http://arxiv.org/abs/1103.4853
Quick summary: the researchers in Seattle take the building's air filters once a day, compress them into a block, stick the block in a lead vault, and use a gamma-ray analyzer on it. They can detect radioactive particles from Japan, 7 days later (at very low levels). Based on the composition, they believe the particles are from radioactive steam, not burning fuel, which is kind of interesting. Because they are analyzing the filters, rather than the air directly, they are testing particles from 114,000 cubic meters of air at a time so they get very high sensitivity.
Quick summary: the researchers in Seattle take the building's air filters once a day, compress them into a block, stick the block in a lead vault, and use a gamma-ray analyzer on it. They can detect radioactive particles from Japan, 7 days later (at very low levels). Based on the composition, they believe the particles are from radioactive steam, not burning fuel, which is kind of interesting. Because they are analyzing the filters, rather than the air directly, they are testing particles from 114,000 cubic meters of air at a time so they get very high sensitivity.
Great summary of our paper! From the amount and ratio of the different isotopes you can do a tremendous amount of nuclear forensics, which I knew nothing about before this happened. Not everything is in books (some is still deemed top secret from WW2 and beyond), but we learned a lot by consulting with a veteran of the Manhattan project.
Any chance you can outline the steps in your workflow? Or perhaps provide a snapshot of example data?
I'm asking because I'm interested in real-world examples of how someone with a lot of CouchDB experience approaches a number crunching task like this. I think seeing the steps in how the data flows from instrument to final charts and graphs would be interesting. The fact that it was done in a rush makes it doubly interesting because it means that it wasn't planned out, and was probably iterated on a bit.
I'm asking because I'm interested in real-world examples of how someone with a lot of CouchDB experience approaches a number crunching task like this. I think seeing the steps in how the data flows from instrument to final charts and graphs would be interesting. The fact that it was done in a rush makes it doubly interesting because it means that it wasn't planned out, and was probably iterated on a bit.
How do you know it's due to Fukushima?
Pretty crazy that the guy manages to juggle being a founder and a physics professor at the same time.