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How to Stump a Data Planner or…Learning the Hard Way

DOE/NV/25946--1468. How to Stump a Data Planner or…Learning the Hard Way. RaJah Mena FRMAC Senior Scientist Remote Sensing Laboratory Presented to NREP Annual Meeting April 23, 2012.

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How to Stump a Data Planner or…Learning the Hard Way

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  1. DOE/NV/25946--1468 How to Stump a Data Planner or…Learning the Hard Way RaJah MenaFRMAC Senior Scientist Remote Sensing Laboratory Presented to NREP Annual Meeting April 23, 2012 This work was done by National Security Technologies, LLC, under Contract No. DE‑AC52‑06NA25946 with the U.S. Department of Energy.

  2. The Review Process Lay a Good Foundation Maps Samples Gotcha’s Good data gone bad Topics

  3. Scenario package due 60 days prior to the graded exercise Contents Extent of Play Agreement Scenario Injects Data to be used to support play Who’s looking FEMA Site Specialist Scenario Evaluator (FEMA contractor) FRMAC support Review of materials Products Post review edits The Review Process

  4. Define the Extent of Play Agreement ASAP Time phases of play Affected counties Boundaries Ensure FEMA on board with plans early Identify responsible parties Utility and state need to be in constant contact Discover inconsistencies Address holes Lay a Good Foundation

  5. Visualization tools useful for meeting objectives Planning routes Discussion tools for decision makers Remove clutter Important data layers Infrastructure Boundaries Pay attention to colors Legends and other details Maps – Beyond Cigars and Keyholes…

  6. 1 2 3 4 5 8 6 7 Example

  7. Ensure you have valid assumptions NARAC model radionuclide grouping Other model radionuclide grouping Remember your time phase Allow time for physical sampling Should be somewhat realistic for the scenario Milk sample issues Transfer factors into the animals Stored feed and water vs free range Crop issues Crop availability Food vs forage Water issues SDWA calculations Procedures to support? Samples

  8. Samples Verify your ratio of Te-132/I-132 Ingrowth of materials Sr-90 before 4-days KI distribution point The Gotchas

  9. Maps Maps with no legend Insufficient map products to support objectives Samples Controller data given with samples Too few samples available in scenario package Not enough to demonstrate objectives Not enough to keep assessors busy Other Dose assessors unfamiliar with software/procedures Injects and messages that conflict with data Things we’ve seen go horribly, horribly wrong…

  10. Questions?

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