second sc5 pilot: identifying the release location of a substance

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SECOND SC5 PILOT IDENTIFYING THE RELEASE LOCATION RELEASE LOCATION OF A SUBSTANCE NCSR Demokritos 20 December 2016

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SECOND SC5 PILOTIDENTIFYING THE RELEASE LOCATIONRELEASE LOCATION OF A SUBSTANCE

NCSR Demokritos20 December 2016

ContentContent

Environment contamination The Chernobyl plumey p The Algeciras plume Th F k hi l The Fukushima plume Problem definition Leveraging BDE Issues to be explored Issues to be explored

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Environment contaminationEnvironment contamination

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DepositionDeposition

Wet deposition

Dry deposition

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FactorsFactors

Climate and weather are important factors affecting accident consequences

In the absence of rain dry deposition takes placeo radioactive particles settle under the influence of o radioactive particles settle under the influence of

gravity, wind and turbulence

Snow and rain result Snow and rain result in wet deposition

S Source: http://www.irsn.fr/EN/publications/thematic/fukushima/Documents/IRSN_Fukushima-Environment-consequences_28022012.pdf

The Chernobyl plumeThe Chernobyl plume

At 01:23 on 26/4/1986 a severe accident took place at Chernobyl-4 nuclear power plant

Atmospheric dispersion models were applied to the 137Cs atmospheric release po The meteorological conditions in Europe following the

accident were reconstructedacc de we e eco s uc ed

Source: http://www.irsn.fr/EN/publications/thematic-safety/chernobyl/Pages/The-Chernobyl-Plume.aspxwww.big-data-europe.eu

Source: http://www.europarl.europa.eu/news/en/news-room/20140514STO47018/forsmark-how-sweden-alerted-the-world-about-the-danger-of-chernobyl-disaster

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Source: http://www.europarl.europa.eu/news/en/news-room/20140514STO47018/forsmark-how-sweden-alerted-the-world-about-the-danger-of-chernobyl-disasterwww.big-data-europe.eu

The Algeciras plumeThe Algeciras plume

HYSPLIT simulation of 137Cs dispersion between 0 and 500m altitude every 3 hours over a 3-day period.

Source: http://www-dase.cea.fr/public/dossiers_thematiques/modelisation_et_simulation_du_transport_atmospherique/description_en.html

p y y pIt is presumed that the source (red dot) emits 100 Bq between 00:00 and 03:00 on May 30, 1998.

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The Fukushima plumeThe Fukushima plume

At 14:46 on 11/3/2011 the Tohoku-Chihou-Taiheiyo-Oki earthquake rocked Fukushima Daiichi nuclear power station

An hour later a tsunami invaded the site Hydrogen explosions

E l ti di th F k hi D ii hi Explanations regarding the Fukushima Daiichi accident consequences on the environment appear

h // i f /EN/ bli i / h iat: http://www.irsn.fr/EN/publications/thematic-safety/fukushima/Pages/2-fukushima-understanding-environment.aspx

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Issue at handIssue at hand

Release of a hazardous substance in the atmosphere

Support the decision making process for countermeasure takingg

Estimation of consequences on:h manso humans

o environment

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Problem statementProblem statement

Identify the release location of a substance Available information:

o Measurements of the substance level at certain locations

o Current weather conditionso Past weather conditionso Past weather conditions

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Current approachesCurrent approaches

Computational approach:o work backwards – inverse modelling – from the current

atmospheric conditions to estimate source location

Long computation times required, especially for g p q , p ycomplex caseso complicated topography o complicated topography o weather conditions

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Leveraging BDELeveraging BDE

Use BDE to manage:o A large number of pre-computed dispersion datao Historical atmospheric conditions

In this manner: In this manner:o The computationally hardest part is pre-computed

M t hi t t h i diti t th o Matching current atmospheric conditions to the pre-computed cases formulates a smaller problem

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The computational essenceThe computational essence

Match current weather against a database of historical atmospheric conditions by:o Building upon the NetCDF data management and

searching tools created during the first SC5 piloto Encoding weather patterns onto mapsWeather similarity map/image similarity

o Developing operators that search consecutive hourly slices for similar weather

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Open issuesOpen issues

Open issues to be investigated during the pilot implementation:o What exactly does “similar enough weather” mean for

this pilot purposes?o What volumes need to be pre-computed to always

have in the database “similar enough weather”?o Are these volumes manageable and searchable?

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Questions?Questions?

BigDataEurope Web site:https://www.big-data-europe.eu

Thank you for your attention!

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