ML19093B815

RIC 2019 - TH35 Presentation - Atmospheric Transport Results for Benchmark Study of the Accident at the Fukushima Daiichi Nuclear Power Station (Bsaf) Phase Ii.

ML19093B815
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Issue date:	02/12/2019
From:	Bixler N, Clayton D Office of Nuclear Regulatory Research, Sandia, US Dept of Energy, National Nuclear Security Admin
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ML19093B814	List: ML19093B815 ML19093B816 ML19093B817
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2/12/2019 Atmospheric Transport Results for Benchmark Study of the Accident at the Fukushima Daiichi Nuclear Power Station (BSAF) Phase II Nathan E. Bixler and Daniel J. Clayton Sandia National Laboratories st Presented at the 31 Annual Regulatory Information Conference Bethesda, MD, USA, March 14, 2019 Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energys National Nuclear Security Administration under contract DE-NA-0003525.

SAND2019-0794 C 1

2/12/2019 Overview BSAF Project NRC/SNL MELCOR source term Sensitivity of deposition to meteorological data Sensitivity of deposition to source term Summary 2

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2/12/2019 OECD/NEA BSAF Phase I BSAF was initiated by the Nuclear Energy Agency (NEA) of the Organisation for Economic Cooperation and Development (OECD)

BSAF is a multiphase study with participants from multiple countries Phase I was completed in 2015 Focus was to better understand accident progression at each of the three units over the first 6 days New knowledge was to guide decommissioning NRC/SNL (Sandia National Labs) contributed by performing MELCOR analyses of each unit 3

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2/12/2019 OECD/NEA BSAF Phase II Phase II was completed in 2018 Focus was to extend investigation of accident progression, to evaluate source term, and to estimate atmospheric transport over the entire accident (3 weeks)

Research improved understanding of reactor end states for decommissioning NRC/SNL contributed by performing MELCOR, HYSPLIT, and MACCS calculations for each unit 4

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2/12/2019 Objectives of Atmospheric Transport Analysis to Support BSAF Provide guidance to sourceterm modelers by estimating ground deposition patterns Focus on Cs137 (best quantified of the released isotopes)

Deposition pattern depends critically on chronological alignment of release with weather pattern Benchmark atmospheric transport models against real data HYSPLIT particle tracking model As a standalone model Integrated with MACCS Results in this presentation use HYSPLIT in standalone mode 5

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2/12/2019 Two Major Sources of Uncertainty Uncertainty in weather was investigated using three sources of weather data, all from NOAA WRF (Weather Research and Forecasting) model, generated in 2014 4km spatial, 20 min temporal discretization No nudging GDAS (Global Data Assimilation System) 0.5 degrees spatial, 3 hour3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> temporal discretization No nudging WRF model, generated in 2017 4km spatial, 5 min temporal discretization Nudged with observations Uncertainty in source term was assessed using source terms from BSAF contributors 6

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2/12/2019 Meteorological Data for First 7 Days Weather data have similar trends but Significant variations in detail 7

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2/12/2019 Evolution of Integral Release Estimated by NRC/SNL 40 H Terada et al.

IRSN 35 Cs-137 Integral Release IRSN (update) 30 JAEA/NSC JNES/TEPCO 25 Stohl et al.

TEPCO 20 (PBq)

Winiarek et al.

15 ZAMG SNL MELCOR 7/2016 10 SNL MELCOR 1/2017 SNL MELCOR 7/2017 5

SNL MELCOR 1/2018 0 SNL MELCOR 5/2018 0 5 10 15 20 25 30 Elaspsed Time (day)

Curves indicate evolution of integral release for three units as estimated by NRC/SNL over the course of BSAF Phase II Many of the initial and boundary conditions needed to estimate accident progression were poorly understood Initial damage state was unknown Water injection may have failed, succeeded, or partially succeeded 8

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2/12/2019 Weather Data Comparison SNL MELCOR 5/2018 WRF Observations 2017 Plots use

• Consistent scale

• Consistent isopleth shading (1 additional level GDAS in SNL plots) WRF 2014 9

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2/12/2019 Predicted Ground Deposition WRF 2017 SNL MELCOR 5/2018 Source Term 10 10

2/12/2019 Contributions to Deposition Pattern from Individual Units

• Figures show final deposition patterns created by each unit based on final NRC/SNL source term using WRF 2017 weather data

• Unit 1 contributes very little to the overall pattern

• Unit 2 and, to a lesser extent, Unit 3 create much of the NW deposition pattern, mostly on 3/15 Unit 1 Unit 2 Unit 3 11 11

2/12/2019 BSAF Source Terms SNL received source terms from eight BSAF organizations Organization Country Code Units SNL USA MELCOR 1, 2, & 3 IAE Japan SAMPSON 1, 2, & 3 IRSN France ASTEC 1, 2, & 3 KAERI Korea MELCOR 1, 2, & 3 CIEMAT Spain MELCOR 1 CNL Canada MELCOR 2 CRIEPI Japan MAAP 2 PSI Switzerland MELCOR 3 Four provided a source term for all three units GRS (Germany) reconstructed a source term using data from radiation monitors in the area surrounding Fukushima (reverse method) 12 12

2/12/2019 Total Source Term Comparison 13 13

2/12/2019 Total Deposition Comparison Using WRF 2017 Weather Data NRC/SNL MELCOR GRS REVERSE METHOD IAE SAMPSON IRSN ASTEC KAERI MELCOR 14 14

2/12/2019 Summary NRC/SNL evaluated atmospheric transport with HYSPLIT and MACCS Uncertainty in meteorology makes a significant difference in the deposition pattern Uncertainty in source term makes an even larger difference in the deposition pattern Insights from atmospheric transport modeling improved the fidelity of the source terms over the course of BSAF Phase II BSAF results have provided preliminary guidance for decommissioning the Fukushima Daiichi units 15 15