Annual Numerical Simulation of the Radionuclidal Atmospheric Dispersion and Optimized Monitoring Network Design for BNPP-1

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Malakooti Hossein; mohammadiha amir; feizinejad masoud

Title

Annual Numerical Simulation of the Radionuclidal Atmospheric Dispersion and Optimized Monitoring Network Design for BNPP-1

Author(s)

Malakooti Hossein | mohammadiha amir | feizinejad masoud | Issue Writer Certificate

Keywords

Monitoring networkQ1

Design optimizationQ1

Radionuclide atmospheric dispersionQ1

ADIM1.0 modelQ1

Locating algorithmQ1

Abstract

According to the industrialization of human societies, it is obvious that knowledge of environmental pollutants, their emission, transportation, dispersion and control will play as an important factor in the survival of humanity. Monitoring and observation networks are recognized as powerful tools for detection and control of environmental pollution concentration and their applications will increase when it is combined with predictive atmospheric chemistry and physics tools and will convert to a management tool to be used in a comprehensive projects. The Monitoring networks not only detect background patterns but also must have ability to display anomaly values in critical conditions. Radiation Monitoring networks in order to observing gamma dose rate generated by natural resources and man-made artificial structures (nuclear facilities) are designed. Some of the criteria considered parameters in such projects are included environmental characteristics of the site region, the meteorological parameters responsible for transport, dispersion and transmission of pollutants and distribution of population density. The final aim of this study is to design a Monitoring network to measure the level of gamma dose radiation in the area around the nuclear power plant in Bushehr. For this purpose, it will be determined the optimize number and location of these stations in 100 km around this site. Dispersion code used in this study ADIM1. 0, is a Double Gaussian function base. In this study, is applied some interpolation approaches and approximation function of original function. The Locating algorithm is working base on recognition of the areas with the highest standard deviation (σ ) of interpolation. The reason for this selection is that in the main criterion of the interpolation methods are to minimize the interpolation error in this purpose. However, the most common method for minimizing the error values in areas with the highest error of interpolation is considering the correct value and after, conducting the new interpolation. The location of the observational station is considered to be in the area with the greatest amount of interpolation error. This method has been used in many projects in order to designing of the Monitoring network. Locating algorithms has been developed in this study, after reading the input dispersion matrix in Matlab software environment, an algorithm applies step by step to be able to determine the location of the first to the last station in the final step as follows: 1) In the beginning, the code searches maximum and minimum of the original function and after stores these values in the same location in a new matrix. 2) By taking zero values in the four corners of the new matrix and the maximum and minimum of basic matrix, the interpolation is done between these six initial guess, as the average of the interpolated matrix be equal to the original matrix. 3) The next step, the code is calculating the standard deviation of the differences between these two matrixes. The next point for the observational site will be the point with highest standard deviation. 4) The next step, the original value from basic dispersion matrix in the selective point with highest error will replaced with interpolated value in this point. 5) Now with the values for seven-point, interpolation will repeated again and the new estimate of the dispersion function will achieved. The second step will repeat and the point with the highest standard deviation will be finding in the compression with the main function, and the third step will be repeated. 6) This process will continue until when the estimate of the dispersion function for interpolation be closest to the original matrix and the last place to be find for site establishment. As mentioned earlier, the purpose of this study was to determine the optimum location of monitoring stations around Bushehr nuclear power plant to 100 km radius and for this purpose below four steps we will conduct for achieving this aim: A) In the beginning by conducting long term dispersion simulation using wind directional distributions, boundary layer stability and other input parameters to ADIM1. 0 code (Feizinejad and Khamoushi, 2003) long term radionuclide dispersion pattern will archived. For this purpose, atmospheric observations from BNPP tower and weather station and radionuclide emission data for normal operating conditions (composition and concentration) during 2011 were introduced into the code. B) By applying an interpolation method (Kriging), the ADIM1. 0 radial dispersion pattern (16 directional sectors) in the region convert to the square pattern mesh with 5 km resolution. Error variance in Kriging method is usually smaller than other conventional methods such as IDW and Spline. C) The final version of Long-term dispersion present into written Monitoring network design MATLAB code in this study as input data. D) The Locating algorithm will determine the location of observational stations. The converted long term dispersion pattern to square mesh was presented maximum, minimum and average values equal to 348×10-10, 4. 6×10-10 and 15×10-10 Bq/m3 respectively. The results was showed that the pattern of long-term dispersion of ADIM 1. 0 code is correspond to the prevailing wind and showing bigger vales in the northwest-southeast. The primary endpoint of the study was that to find areas with the highest standard deviation in the interpolation is worked perfectly valid and estimated pattern with increasing of replication process be quite similar to original dispersion pattern. Absolute error and absolute value of relative error was calculated as these quantities are expected to be diminishing rapidly with increasing the number of iterations. The iterations results were showed that the rate of decreasing absolute value of relative error level could be approximately around 283×10-10 Bq/m3 between the first to fifth iteration, after the 20th iteration could be approximately around 5×10-10 Bq/m3 between the 15th to 20th iteration, and then it is remained almost in the same level. According to this interpretation, in order to optimization of the cost of construction and maintenance of network monitoring, the number of station for Monitoring network is considered equal to 20 stations within 100 km radius area of the Bushehr nuclear power plant. The 20 monitoring stations can be represented a suitable view of dispersion pattern of radionuclide particles of the Bushehr nuclear power plant and it will be available to experts and managers for other applications and safety. The results were showed that the final interpolated pattern is obtained correctly the maximum values. It is also clearly represented spatial distribution anomaly in the South East and North West directions and background values.

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APA: Copy

Malakooti, Hossein, mohammadiha, amir, & feizinejad, masoud. (2016). Annual Numerical Simulation of the Radionuclidal Atmospheric Dispersion and Optimized Monitoring Network Design for BNPP-1. JOURNAL OF ENVIRONMENTAL STUDIES, 42(3 ), 475-487. SID. https://sid.ir/paper/2918/en

Vancouver: Copy

Malakooti Hossein, mohammadiha amir, feizinejad masoud. Annual Numerical Simulation of the Radionuclidal Atmospheric Dispersion and Optimized Monitoring Network Design for BNPP-1. JOURNAL OF ENVIRONMENTAL STUDIES[Internet]. 2016;42(3 ):475-487. Available from: https://sid.ir/paper/2918/en

IEEE: Copy

Hossein Malakooti, amir mohammadiha, and masoud feizinejad, “Annual Numerical Simulation of the Radionuclidal Atmospheric Dispersion and Optimized Monitoring Network Design for BNPP-1,” JOURNAL OF ENVIRONMENTAL STUDIES, vol. 42, no. 3 , pp. 475–487, 2016, [Online]. Available: https://sid.ir/paper/2918/en

Scientific Information Database

ISSN: 2588-4824

Journal Paper

Annual Numerical Simulation of the Radionuclidal Atmospheric Dispersion and Optimized Monitoring Network Design for BNPP-1