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Advances on identification and animated simulations of radioactivity risk levels after Fukushima Nuclear Power Plant accident (with a data bank): A Critical Review

  • Fatih KülahcıEmail author
  • Ahmet Bilici
Article

Abstract

This review study has been based on two main foundations as advances on the attainment of the risk radioactive fallouts levels, and the applications of methods for risk assessment to actual data and visual results, which are based on a 3-year study. A risk analysis model is developed with the animated simulations including the isotope distribution based on soil activity data, 131I measured at 19 stations after the Fukushima accident. Probability distribution functions of the risk levels are obtained in addition to the probability of occurrence (risk) and the probability of non-occurrence (reliability) of the activity risks concerning 131I. The results are used for prediction of 60-day radioactive fallout subsequence and animated (.mp4) through simulations.

Graphical abstract

Keywords

Spatial modelling prediction Kriging Radionuclide migration Long-range transport Radioactive fallout Risk assessment 

List of symbols

λ

Radioactive decay constant

t1/2

Radioactive half-life

t

Time parameter

N0

Number of initial radioactive nuclei

N(t)

Number of radioactive nuclei at time t

Nr(t)

The number of nuclei at time t of rth radioactive nucleus

Nn(t)

Number of nuclide in time t of stable nuclide

A0

The initial activity

A(t)

Activity in time t

xi

ith independent parameter

f(xi)

ith dependent parameter

g(x)

Theoretical curve

εi

ith error

E

Square of the sum of errors

ai

ith coefficient

x0

Prediction point

wi(x0)

Weight value indicating the contribution from the ith station for the prediction point

G

Confidence

R

Risk

s

Sum of all cases

g

Probability/event of non-occurrence

r

Probability/event of occurrence

m

Rank

gb

Probability of non-occurrence for biggest activity value

mb

The rank for biggest activity value

n

The number of all activity events

A

Activity event

P(A)

Probability of occurrence of event A

As

Small activity value event

Ab

Great activity value event

α

Scale parameter for Weibull distribution

β

Shape parameter for Weibull distribution

µ

Location parameters for the lognormal and generalized extreme-value distributions

σ

Scale parameter for the lognormal and generalized extreme-value distributions

k

Shape parameter for generalized extreme-value distribution

f(x|k, µ, σ)

Generalized extreme-value distribution function

F(x|k, µ, σ)

Generalized extreme-value cumulative distribution function

ggev

Probability of non-occurrence for generalized extreme-value distribution

rgev

Probability of occurrence for generalized extreme-value distribution

Notes

Acknowledgements

This research was supported by Firat University (Grant Number: FF.12.25). We are grateful to the Editor-in-Chief (Prof Zsolt Revay) and two anonymous referees for their outstanding support in the investigation and development of this research.

Supplementary material

10967_2019_6559_MOESM1_ESM.docx (63 kb)
Measured and calculated activities for 19 stations (DOCX 63 kb)
10967_2019_6559_MOESM2_ESM.docx (445 kb)
Measured activity values versus time for stations and the models obtained with LSM (DOCX 445 kb)
10967_2019_6559_MOESM3_ESM.docx (43 kb)
Probabilities of occurrence (risk) and probabilities of non-occurrence (confidence) of the risks levels of 131I (DOCX 42 kb)
10967_2019_6559_MOESM4_ESM.docx (182 kb)
Probability of Occurrence and Graphics of Best Available Distributions to Data (DOCX 182 kb)
10967_2019_6559_MOESM5_ESM.docx (31 kb)
Probability of Occurrence Values According to Generalized Extreme-Value Distribution (DOCX 30 kb)
10967_2019_6559_MOESM6_ESM.docx (15.9 mb)
Iodine-131 Radioactivity Changes (DOCX 16296 kb)
10967_2019_6559_MOESM7_ESM.mp4 (5.5 mb)
Iodine131_Activity_Animated_Simulation_1.mp4 (MP4 5660 kb)
10967_2019_6559_MOESM8_ESM.pdf (1.7 mb)
Probabilities of Occurrence by Generalized Extreme-Value Distribution Corresponding to Activity Values (PDF 1703 kb)
10967_2019_6559_MOESM9_ESM.docx (5.2 mb)
Probabilities of Nonoccurrence According to Generalized Extreme-Value Distribution Corresponding to Activity Values (DOCX 5291 kb)
10967_2019_6559_MOESM10_ESM.mp4 (2.7 mb)
Probability of Occurrence.mp4 (MP4 2743 kb)
10967_2019_6559_MOESM11_ESM.mp4 (2.7 mb)
Probability of Nonoccurrence.mp4 (MP4 2748 kb)

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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2019

Authors and Affiliations

  1. 1.Science Faculty, Nuclear Physics Division, Physics DepartmentFırat UniversityElazigTurkey
  2. 2.Vocational School of Health Service, Department of OpticianryBartin UniversityBartinTurkey

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