- Email: [email protected]
User Interface of Atmospheric Dispersion Simulations for Nuclear Emergency Countermeasures
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5th International Symposium on Innovative Nuclear Energy Systems, INES-5, 31 October – 2 November, 2016, Ookayama Campus, Tokyo Institute of Technology, JAPAN The 15th International Symposium on District Heating and Cooling
User Interface of Atmospheric Dispersion Simulations for Nuclear Assessing the Emergency feasibility ofCountermeasures using the heat demand-outdoor temperature function for a,a long-term district heat demand forecast b a Hamza El-Asaad *, Haruyasu Nagai , Hiroshi Sagara a a b c I. AndrićTokyo *, A. Pina , P. Ferrão , J.Ookayama, Fournier ., B. Lacarrière , O. Le Correc Institute of Technology 2-12-1-N1-17, Meguro-ku, Tokyo, Japan 152-8550 a
b
a,b,c
Research Group for Environmental Science, Japan Atomic Energy Agency, 2-4 Shirane Shirakata, Tokaimura, Naka-gun, Ibaraki, Japan a IN+ Center for Innovation, Technology and Policy Research -319-1195 Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France
Abstract InAbstract the event of a nuclear emergency, evacuation experts will have very limited time to make life saving decisions. Therefore, it is very important to provide these experts with knowledge of plume characteristics which are generated by an intuitive user District heating networks are commonly addressed in thetoliterature as one of the most effective solutions decreasing interface; backed by simulations of radionuclide dispersions better assist experts in evacuation planning. This for study aims to the greenhouse gas emissions from buildingthat sector. These systems require high investments which are returned through the heat verify the effectiveness of the userthe interface can provide a one year meteorological and dispersion data based on WSPEEDIDue to athe conditions building renovation policies, heat demand the future could decrease, IIsales. library. Such userchanged interfaceclimate might be beneficialand to risk and crisis management planning in case ofina radioactive dispersion. prolonging the investment return period. main of this paper isby to Elsevier assess theLtd. feasibility of using the heat demand – outdoor temperature function for heat demand ©The 2017 Thescope Authors. Published forecast. The district of Alvalade, in Lisbon (Portugal), wasInternational used as a case study. The district is Nuclear consisted of 665 Peer-review under responsibility of thelocated organizing committee of the 5th Symposium on Innovative Energy buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district Systems. renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were comparedWSPEEDI-II; with resultsnuclear from aemergency; dynamic heat demand model,radioactive previouslydispersion; developed and analysis; validatedaccident; by the authors. Keywords: evacuation planning; plume risk management; crisis The results user showed that when only weather change is considered, the margin of error could be acceptable for some applications management; interface (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the 1.The Introduction decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the After the accident at the Fukushima Daiichi Nuclear Power Plant (hereinafter referred to as FNPP1) there have coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and been a lot of studies focusing on emergency preparedness regarding radionuclide dispersion resulting from a nuclear improve the accuracy of heat demand estimations. © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +81-3-5734-2379. Cooling. E-mail address: [email protected]
Keywords: Heat demand; Forecast; Climate change 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the organizing committee of the 5th International Symposium on Innovative Nuclear Energy Systems.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the organizing committee of the 5th International Symposium on Innovative Nuclear Energy Systems. 10.1016/j.egypro.2017.09.429
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Hamza El-Asaad et al. / Energy Procedia 131 (2017) 279–284 Hamza El-Asaad/ Energy Procedia 00 (2017) 000–000
power plant. Prefectural governments in Japan that host nuclear power plants are working on numerous ways to improve their crisis management plans and to also improve nuclear emergency countermeasures [1]. After the incident of FNPP1 it is obvious that steps need to be taken to assist evacuation experts. Experts need to make quick decisions regarding the safety of the people residing near nuclear power plants. One way of tackling this issue is by using an intuitive user interface. The interface can provide these experts with knowledge of the plume characteristics from simulations of radionuclide dispersions. The interface can also display crucial information regarding radionuclide dispersion, which then compares levels of radioactivity in the atmosphere with current policy on evacuation due to radioactive release. For example, in case of a disaster unfolding, and in the event of a plume passing, then evacuation experts would be able to assess the situation by using information retrieved from the interface to view certain characteristics of the plume. Plume characteristics are crucial because they can determine air dose rate from deposition, and total air dose rate, hence triggering an evacuation order if deemed necessary. An equally important method to be taken from this study is the minimization of uncertainty when pre-planning for any potential radionuclide dispersion accident. This user interface can help experts, in the field of mass evacuation, view predictions regarding a certain scenario, and its outcomes. This will then planned for ahead of time to help in reducing uncertainty. Pre-planning maybe done by using this user interface to view many different scenarios which could have different simulations that show different times, radionuclides, terrain and plume analysis. The main aim of this study is to verify the effectiveness of our user interface by conducting a calculation performance test based on the scenario of Fukushima Daiichi Disaster and to demonstrate ease of data access. Such data would include for example: time of radioactive release, air dose rate from deposition, total air dose rate, distance of the maximum value of the total air dose rate from the release point (FNPP1) and the direction in degrees. Being provided with this information can help in determining where and how to evacuate residents in the affected zones. 2. Methodology The method that supports the evacuation experts (the users) is based on an atmospheric dispersion simulation system, known as Worldwide version of System for Prediction of Environmental Emergency Dose Information II (WSPEEDI-II) [2] developed by Japan Atomic Energy Agency (JAEA). A library has been created by a research group in JAEA which contains data for any one year period based on simulations compiled by WSPEEDI-II. The library consists of spatiotemporal data of radioactive dispersion in the air, and deposition on the ground. Initially, a meteorological dataset has been developed using a meteorological model. The plume dispersion scenarios differ in weather or season, radionuclides, and release rates. Secondly, the dispersion is modelled using a modified Lagrangian particle dispersion (new-GEARN) of WSPEEDI-II which conducts one hour unit release periods. In these calculations, the radioactive decay for each individual radionuclide is not applied. Instead, radioactive decay is applied to the output, therefore calculation results for any type of radionuclide can be obtained for the referenced radionuclide. And these release periods will be done for every one hour segment of release within a target of any one year period. Because this calculation is done for every field of meteorological combination it therefore outputs a matrix for all calculations with regards to nuclide, deposition, release height and time. Finally, the method to reproduce spatiotemporal distributions of radionuclides for any condition of a source term is by linear combination of a matrix [3]. Essentially, this step is the most important in the case of the expert because new scenarios will emerge hence helping identify important plume characteristics. Such characteristics might include direction of the plume, size, types of radionuclide and different scenarios in different seasons. The user interface will use the data from the library to provide short summaries of various scenarios, and finally the user will then decide which of the data provided will be of interest to them. The platform of the user interface can run on any computer running a Linux operating system with the programming language of Fortran 90; hence making the interface friendly and simple to setup and use.
Hamza El-Asaad et al. / Energy Procedia 131 (2017) 279–284 Hamza El-Asaad/ Energy Procedia 00 (2017) 000–000
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2.1. Procedure to acquire spatiotemporal distribution Radioactivity of air concentration qa,i(x, y, t) [Bq/m3] of nuclide i at each grid point (x, y) and time (t) is obtained by:
q x, y , t a ,i
j
Q q x, y , t exp t t Q j ,i
a ,1, j
0
i
(1)
1
Where the release rate for each radionuclide (i), Qj,i [Bq/h] at the j-th release segment in the selected release period, and its radioactive decay (decay constant: λi) are applied to air concentration, qa,1,j(x, y, t) [Bq/m3], of reference radionuclide with unit release (Q1 =1 Bq/h) in the library. In which the release rate Qj,i is set as decaycorrected value to a specific time, t0 (for example, shutdown time), for every time segment. Radioactivity of deposited radionuclide i at each grid point and time, qd,i(x, y, t) [Bq/m2] is calculated as:
q x, y , t d ,i
j
Q q x, y , t exp t t Q j ,i
d ,1, j
0
i
(2)
1
Where qd,1,j(x, y, t) [Bq/m2] is deposition of reference radionuclide with unit release and release period at each grid point (x, y) and time (t). After obtaining the air concentration and deposition of nuclide i, it is possible now to calculate air dose rates from all radionuclides in the plume and deposition, Da,total(x, y, t) and Dd,total(x, y, t) [Gy/h], respectively, as:
a ,total
x , y , t C a ,i q a ,i x , y , t
(3)
d ,total
x , y , t C d ,i q d ,i x , y , t
(4)
D D
i
i
Where Ca,i and Cd,i are conversion coefficients from air concentration and deposition of the summation of every selected i radionuclide to air dose rate, respectively. 2.2. Setting up and calculating scenarios For a user to reach conclusions, four steps need to be taken: Step 1- Input- magnitude of accident In the first step the user can decide the magnitude of the accident by inputting information such as: 1) types of radionuclides released, 2) the release rate, 3) start time, and 4) duration of release. This step allows the user to adjust the accident scenario according to their desire. Step 2- Applying spatiotemporal distribution into WSPEEDI-II library The user interface in this step applies the spatiotemporal distribution to the whole data in WSPEEDI- II library by changing release start time to every hour of the days in the target year.
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Step 3- Generating a short summary After the user interface generates a wide range of scenarios from step 3 it will then create a short summary of all the scenarios. This short summary may include simple textual information describing characteristics of dispersion conditions such as maximum value of the total air dose rate and location, direction of plume movement, and areas where the total air dose rate exceeds acceptable radiation levels. Thus, as a result, the user may view all the possible scenarios easily. Step 4- Review and refer Finally, after the user views the short summary of all possible scenarios then they can personally identify the scenario of interest to them and once they do they can then refer to the WSPEEDI-II library for the full details of that scenario for further analysis. 3. Performance test To demonstrate the efficiency of the user interface, a test calculation was conducted. However, this study uses WSPEEDI-II library for the 20-day release period starting from the FNPP1 disaster on March 11, 2011. A simple input by the user into the user interface will calculate in a matter of seconds and generate quick yet crucial information to evacuation experts. 3.1. Test conditions The assumption of the input is as follows: Radionuclides includes, Cs-137, I-131, Te-132 and Xe-133, the release rate (Bq/h) is 3.0x1014, 3.0x1015, 3.0x1015 and 1.2x1016, respectively, the release start time is 2011-03-13, 00:00, and the release duration is one hour. The release rates were taken from the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) 2013 report [4] as a reference to the actual release rates in the FNPP1 accident. 3.2. Results and Discussion The results of this study demonstrate the efficiency of the user interface created to summarize one year worth of output to the user. Results provided below shows how a pre-planned assumption of release rate set by the author of this paper, assumed the user, provides us with total air dose rate. For simplicity, we ran the calculation for the first 20 hours of total air dose rate, however, we only show up to hour eight. From hour eight to hour 24 the maximum air dose rate stabilizes, hence also stabilizing the position of maximum air dose rate. Table 1: The maximum value and point of total air dose rate from deposition and concentration with respect to year, month, day and time (1-hour release rate), distance and direction from FNPP1. Year‐Month‐Day, Hours
2011‐03‐13, 00:00‐01:00 2011‐03‐13, 00:00‐02:00 2011‐03‐13, 00:00‐03:00 2011‐03‐13, 00:00‐04:00 2011‐03‐13, 00:00‐05:00 2011‐03‐13, 00:00‐06:00 2011‐03‐13, 00:00‐07:00 2011‐03‐13, 00:00‐08:00
Maximum air dose rate (µGy/h) 17.1 16.5 5.3 4.4 0.8 0.3 0.3 0.3
Position of maximum air dose rate Distance from FNPP1 (km) 11 16.27 39.29 64 52 15.3 15.3 15.3
Direction from FNPP (deg.) 0 11 15 4 7 11 11 11
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Table 1 demonstrates how the plume is passing by the area of interest (outside the 10-km exclusion zone from FDNPP1), in the first hour the total air dose rate is at the peak. However, in the second hour it starts to drop and after the sixth hour the air dose starts to stabilize to 0.3 µGy/h, showing that the plume has already passed leaving only air dose rate from deposition. Along with the total air dose rate table a horizontal distribution concentration diagrams will also be displayed in the short summary. However, since the total air dose rate has stabilized after the fourth hour we will only provide the first four hours of the diagrams. a
b
c
d
Figure 1. Horizontal distribution patterns of total air dose rate at (a) one hour, (b) two hour, (c) three hour, and (d) four hour after the release start time
Figure 1. (a) - (d) show how the plume is dispersed immediately after the release until four hours after the event. In Figure 1. (a) the plume is developing in and around the FDNPP1, so it is still highly concentrated in that area, hence a high total air dose rate. However, in Figure 1. (b) – (d) the plume is moving upwards (Northeast) into the Pacific Ocean consequently, resulting in a lower total air dose, in fact even stabilizing. These plume conditions can be easily pictured from the short summary in Table 1 and Figure 1. Therefore, the user can easily identify the scenario of interest to them from the huge data set, and they can refer to the WSPEEDI-II library for the full details of that scenario for further analysis. Along with the short summary it is also very important that experts access this information in a timely manner, so an example comparison is made between manually calculating on WSPEEDI-II the first 24 hours of dispersion after the FDNPP1 and using the interface to make the same calculation (table 2). Table 2: Calculation time on user interface versus calculation time on WSPEEDI-II. Mode Time (Seconds)
WSPEEDI-II 680
User Interface 24
The difference in time is considerably higher, especially if the situation is dire and requires immediate attention. Therefore, it is very important that this user interface demonstrates to the user the time saved when planning for an emergency. Other implications of the user interface, in contrast to WSPEEDI-II, is the type of information that will presented. The user interface will show specific and important data about the characteristics of the plume, such as: maximum air dose rate, position of the plume and direction. On the other hand, WSPEEDI-II provides a much more in depth look into not only plume characteristics but also meteorological field generation time and dispersion calculations. Since the library of data is massive then reviewing in depth details of each and every scenario would be a very time consuming task, therefore the user interface minimizes data analysis in that sense as well. Conclusion The study of plume analysis is very important regarding evacuation planning because it relies on total deposition that is left after a plume passage in a certain area, and the effects of the deposition on human health. The user interface in this study can assist evacuation experts in pre-planning for a crisis or assist during a crisis to decrease uncertainty. The method used is dependent on a large already existing library and can provide a vast amount of
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different scenarios to assist the user. The user interface has demonstrated how input from the user can produce an output of short summaries in a very quick amount of time. Comparing the time difference between WSPEEDI-II and the user interface results in 96% reduced calculation time, a huge number considering a situation where time is very limited. Also, experts want to see many scenarios when pre-planning for a disaster. Consequently, having a user interface that can help them generate scenarios in a very short amount of time can be very helpful. Finally, because the user interface, unlike WSPEEDI-II, provides only some important data the user can simply browse easily through all generated scenarios. This will not only save time but, will help the user truly identify which scenarios are worth analyzing.
References [1]. Shimane prefecture emergency countermeasures [Personal interview]. (2016, July 11). [2]. TERADA, H., & CHINO, M. (2008, May 16). Development of an Atmospheric Dispersion Model for Accidental Discharge of Radionuclides with the Function of Simultaneous Prediction for Multiple Domains and its Evaluation by Application to the Chernobyl Nuclear Accident. Journal of Nuclear Science and Technology,45(9), 920-931. http://dx.doi.org/10.1080/18811248.2008.9711493 [3]. Nagai, H. (n.d.). Updating source term and atmospheric dispersion simulations for the dose reconstruction in Fukushima Daiichi Nuclear Power Station Accident. European Physics Journal – Web of Conferences (EPJ – WoC) (submitted). [4]. UNSCEAR (United Nations Scientific Committee on the Effects of Atomic Radiation), UNSCEAR 2013 Report: Sources, Effects and Risks of Ionizing Radiation, Vol. I, United Nations, New York, USA (2014). [5]. The Fukushima Nuclear Accident Independent Investigation Commission (p. 36, Rep.). (2012). The National Diet of Japan. [6]. Katata, G. (2015, January 30). Detailed source term estimation of the atmospheric release for the Fukushima Daiichi Nuclear Power Station accident by coupling simulations of an atmospheric dispersion model with an improved deposition scheme and oceanic dispersion model. Atmospheric Physics and Chemistry, 1029-1070. Retrieved October 20, 2016, from www.atmos-chem-phys.net/15/1029/2015 [7]. Committee on Lessons Learned from the Fukushima Nuclear Accident for Improving Safety and Security of U.S. Nuclear Plants; Nuclear and Radiation Studies Board; Division on Earth and Life Studies; National Research Council. Washington (DC): National Academies Press (US); 2014 Oct 29.
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5th International Symposium on Innovative Nuclear Energy Systems, INES-5, 31 October – 2 November, 2016, Ookayama Campus, Tokyo Institute of Technology, JAPAN The 15th International Symposium on District Heating and Cooling
User Interface of Atmospheric Dispersion Simulations for Nuclear Assessing the Emergency feasibility ofCountermeasures using the heat demand-outdoor temperature function for a,a long-term district heat demand forecast b a Hamza El-Asaad *, Haruyasu Nagai , Hiroshi Sagara a a b c I. AndrićTokyo *, A. Pina , P. Ferrão , J.Ookayama, Fournier ., B. Lacarrière , O. Le Correc Institute of Technology 2-12-1-N1-17, Meguro-ku, Tokyo, Japan 152-8550 a
b
a,b,c
Research Group for Environmental Science, Japan Atomic Energy Agency, 2-4 Shirane Shirakata, Tokaimura, Naka-gun, Ibaraki, Japan a IN+ Center for Innovation, Technology and Policy Research -319-1195 Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France
Abstract InAbstract the event of a nuclear emergency, evacuation experts will have very limited time to make life saving decisions. Therefore, it is very important to provide these experts with knowledge of plume characteristics which are generated by an intuitive user District heating networks are commonly addressed in thetoliterature as one of the most effective solutions decreasing interface; backed by simulations of radionuclide dispersions better assist experts in evacuation planning. This for study aims to the greenhouse gas emissions from buildingthat sector. These systems require high investments which are returned through the heat verify the effectiveness of the userthe interface can provide a one year meteorological and dispersion data based on WSPEEDIDue to athe conditions building renovation policies, heat demand the future could decrease, IIsales. library. Such userchanged interfaceclimate might be beneficialand to risk and crisis management planning in case ofina radioactive dispersion. prolonging the investment return period. main of this paper isby to Elsevier assess theLtd. feasibility of using the heat demand – outdoor temperature function for heat demand ©The 2017 Thescope Authors. Published forecast. The district of Alvalade, in Lisbon (Portugal), wasInternational used as a case study. The district is Nuclear consisted of 665 Peer-review under responsibility of thelocated organizing committee of the 5th Symposium on Innovative Energy buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district Systems. renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were comparedWSPEEDI-II; with resultsnuclear from aemergency; dynamic heat demand model,radioactive previouslydispersion; developed and analysis; validatedaccident; by the authors. Keywords: evacuation planning; plume risk management; crisis The results user showed that when only weather change is considered, the margin of error could be acceptable for some applications management; interface (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the 1.The Introduction decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the After the accident at the Fukushima Daiichi Nuclear Power Plant (hereinafter referred to as FNPP1) there have coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and been a lot of studies focusing on emergency preparedness regarding radionuclide dispersion resulting from a nuclear improve the accuracy of heat demand estimations. © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +81-3-5734-2379. Cooling. E-mail address: [email protected]
Keywords: Heat demand; Forecast; Climate change 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the organizing committee of the 5th International Symposium on Innovative Nuclear Energy Systems.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the organizing committee of the 5th International Symposium on Innovative Nuclear Energy Systems. 10.1016/j.egypro.2017.09.429
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Hamza El-Asaad et al. / Energy Procedia 131 (2017) 279–284 Hamza El-Asaad/ Energy Procedia 00 (2017) 000–000
power plant. Prefectural governments in Japan that host nuclear power plants are working on numerous ways to improve their crisis management plans and to also improve nuclear emergency countermeasures [1]. After the incident of FNPP1 it is obvious that steps need to be taken to assist evacuation experts. Experts need to make quick decisions regarding the safety of the people residing near nuclear power plants. One way of tackling this issue is by using an intuitive user interface. The interface can provide these experts with knowledge of the plume characteristics from simulations of radionuclide dispersions. The interface can also display crucial information regarding radionuclide dispersion, which then compares levels of radioactivity in the atmosphere with current policy on evacuation due to radioactive release. For example, in case of a disaster unfolding, and in the event of a plume passing, then evacuation experts would be able to assess the situation by using information retrieved from the interface to view certain characteristics of the plume. Plume characteristics are crucial because they can determine air dose rate from deposition, and total air dose rate, hence triggering an evacuation order if deemed necessary. An equally important method to be taken from this study is the minimization of uncertainty when pre-planning for any potential radionuclide dispersion accident. This user interface can help experts, in the field of mass evacuation, view predictions regarding a certain scenario, and its outcomes. This will then planned for ahead of time to help in reducing uncertainty. Pre-planning maybe done by using this user interface to view many different scenarios which could have different simulations that show different times, radionuclides, terrain and plume analysis. The main aim of this study is to verify the effectiveness of our user interface by conducting a calculation performance test based on the scenario of Fukushima Daiichi Disaster and to demonstrate ease of data access. Such data would include for example: time of radioactive release, air dose rate from deposition, total air dose rate, distance of the maximum value of the total air dose rate from the release point (FNPP1) and the direction in degrees. Being provided with this information can help in determining where and how to evacuate residents in the affected zones. 2. Methodology The method that supports the evacuation experts (the users) is based on an atmospheric dispersion simulation system, known as Worldwide version of System for Prediction of Environmental Emergency Dose Information II (WSPEEDI-II) [2] developed by Japan Atomic Energy Agency (JAEA). A library has been created by a research group in JAEA which contains data for any one year period based on simulations compiled by WSPEEDI-II. The library consists of spatiotemporal data of radioactive dispersion in the air, and deposition on the ground. Initially, a meteorological dataset has been developed using a meteorological model. The plume dispersion scenarios differ in weather or season, radionuclides, and release rates. Secondly, the dispersion is modelled using a modified Lagrangian particle dispersion (new-GEARN) of WSPEEDI-II which conducts one hour unit release periods. In these calculations, the radioactive decay for each individual radionuclide is not applied. Instead, radioactive decay is applied to the output, therefore calculation results for any type of radionuclide can be obtained for the referenced radionuclide. And these release periods will be done for every one hour segment of release within a target of any one year period. Because this calculation is done for every field of meteorological combination it therefore outputs a matrix for all calculations with regards to nuclide, deposition, release height and time. Finally, the method to reproduce spatiotemporal distributions of radionuclides for any condition of a source term is by linear combination of a matrix [3]. Essentially, this step is the most important in the case of the expert because new scenarios will emerge hence helping identify important plume characteristics. Such characteristics might include direction of the plume, size, types of radionuclide and different scenarios in different seasons. The user interface will use the data from the library to provide short summaries of various scenarios, and finally the user will then decide which of the data provided will be of interest to them. The platform of the user interface can run on any computer running a Linux operating system with the programming language of Fortran 90; hence making the interface friendly and simple to setup and use.
Hamza El-Asaad et al. / Energy Procedia 131 (2017) 279–284 Hamza El-Asaad/ Energy Procedia 00 (2017) 000–000
281 3
2.1. Procedure to acquire spatiotemporal distribution Radioactivity of air concentration qa,i(x, y, t) [Bq/m3] of nuclide i at each grid point (x, y) and time (t) is obtained by:
q x, y , t a ,i
j
Q q x, y , t exp t t Q j ,i
a ,1, j
0
i
(1)
1
Where the release rate for each radionuclide (i), Qj,i [Bq/h] at the j-th release segment in the selected release period, and its radioactive decay (decay constant: λi) are applied to air concentration, qa,1,j(x, y, t) [Bq/m3], of reference radionuclide with unit release (Q1 =1 Bq/h) in the library. In which the release rate Qj,i is set as decaycorrected value to a specific time, t0 (for example, shutdown time), for every time segment. Radioactivity of deposited radionuclide i at each grid point and time, qd,i(x, y, t) [Bq/m2] is calculated as:
q x, y , t d ,i
j
Q q x, y , t exp t t Q j ,i
d ,1, j
0
i
(2)
1
Where qd,1,j(x, y, t) [Bq/m2] is deposition of reference radionuclide with unit release and release period at each grid point (x, y) and time (t). After obtaining the air concentration and deposition of nuclide i, it is possible now to calculate air dose rates from all radionuclides in the plume and deposition, Da,total(x, y, t) and Dd,total(x, y, t) [Gy/h], respectively, as:
a ,total
x , y , t C a ,i q a ,i x , y , t
(3)
d ,total
x , y , t C d ,i q d ,i x , y , t
(4)
D D
i
i
Where Ca,i and Cd,i are conversion coefficients from air concentration and deposition of the summation of every selected i radionuclide to air dose rate, respectively. 2.2. Setting up and calculating scenarios For a user to reach conclusions, four steps need to be taken: Step 1- Input- magnitude of accident In the first step the user can decide the magnitude of the accident by inputting information such as: 1) types of radionuclides released, 2) the release rate, 3) start time, and 4) duration of release. This step allows the user to adjust the accident scenario according to their desire. Step 2- Applying spatiotemporal distribution into WSPEEDI-II library The user interface in this step applies the spatiotemporal distribution to the whole data in WSPEEDI- II library by changing release start time to every hour of the days in the target year.
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Step 3- Generating a short summary After the user interface generates a wide range of scenarios from step 3 it will then create a short summary of all the scenarios. This short summary may include simple textual information describing characteristics of dispersion conditions such as maximum value of the total air dose rate and location, direction of plume movement, and areas where the total air dose rate exceeds acceptable radiation levels. Thus, as a result, the user may view all the possible scenarios easily. Step 4- Review and refer Finally, after the user views the short summary of all possible scenarios then they can personally identify the scenario of interest to them and once they do they can then refer to the WSPEEDI-II library for the full details of that scenario for further analysis. 3. Performance test To demonstrate the efficiency of the user interface, a test calculation was conducted. However, this study uses WSPEEDI-II library for the 20-day release period starting from the FNPP1 disaster on March 11, 2011. A simple input by the user into the user interface will calculate in a matter of seconds and generate quick yet crucial information to evacuation experts. 3.1. Test conditions The assumption of the input is as follows: Radionuclides includes, Cs-137, I-131, Te-132 and Xe-133, the release rate (Bq/h) is 3.0x1014, 3.0x1015, 3.0x1015 and 1.2x1016, respectively, the release start time is 2011-03-13, 00:00, and the release duration is one hour. The release rates were taken from the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) 2013 report [4] as a reference to the actual release rates in the FNPP1 accident. 3.2. Results and Discussion The results of this study demonstrate the efficiency of the user interface created to summarize one year worth of output to the user. Results provided below shows how a pre-planned assumption of release rate set by the author of this paper, assumed the user, provides us with total air dose rate. For simplicity, we ran the calculation for the first 20 hours of total air dose rate, however, we only show up to hour eight. From hour eight to hour 24 the maximum air dose rate stabilizes, hence also stabilizing the position of maximum air dose rate. Table 1: The maximum value and point of total air dose rate from deposition and concentration with respect to year, month, day and time (1-hour release rate), distance and direction from FNPP1. Year‐Month‐Day, Hours
2011‐03‐13, 00:00‐01:00 2011‐03‐13, 00:00‐02:00 2011‐03‐13, 00:00‐03:00 2011‐03‐13, 00:00‐04:00 2011‐03‐13, 00:00‐05:00 2011‐03‐13, 00:00‐06:00 2011‐03‐13, 00:00‐07:00 2011‐03‐13, 00:00‐08:00
Maximum air dose rate (µGy/h) 17.1 16.5 5.3 4.4 0.8 0.3 0.3 0.3
Position of maximum air dose rate Distance from FNPP1 (km) 11 16.27 39.29 64 52 15.3 15.3 15.3
Direction from FNPP (deg.) 0 11 15 4 7 11 11 11
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Table 1 demonstrates how the plume is passing by the area of interest (outside the 10-km exclusion zone from FDNPP1), in the first hour the total air dose rate is at the peak. However, in the second hour it starts to drop and after the sixth hour the air dose starts to stabilize to 0.3 µGy/h, showing that the plume has already passed leaving only air dose rate from deposition. Along with the total air dose rate table a horizontal distribution concentration diagrams will also be displayed in the short summary. However, since the total air dose rate has stabilized after the fourth hour we will only provide the first four hours of the diagrams. a
b
c
d
Figure 1. Horizontal distribution patterns of total air dose rate at (a) one hour, (b) two hour, (c) three hour, and (d) four hour after the release start time
Figure 1. (a) - (d) show how the plume is dispersed immediately after the release until four hours after the event. In Figure 1. (a) the plume is developing in and around the FDNPP1, so it is still highly concentrated in that area, hence a high total air dose rate. However, in Figure 1. (b) – (d) the plume is moving upwards (Northeast) into the Pacific Ocean consequently, resulting in a lower total air dose, in fact even stabilizing. These plume conditions can be easily pictured from the short summary in Table 1 and Figure 1. Therefore, the user can easily identify the scenario of interest to them from the huge data set, and they can refer to the WSPEEDI-II library for the full details of that scenario for further analysis. Along with the short summary it is also very important that experts access this information in a timely manner, so an example comparison is made between manually calculating on WSPEEDI-II the first 24 hours of dispersion after the FDNPP1 and using the interface to make the same calculation (table 2). Table 2: Calculation time on user interface versus calculation time on WSPEEDI-II. Mode Time (Seconds)
WSPEEDI-II 680
User Interface 24
The difference in time is considerably higher, especially if the situation is dire and requires immediate attention. Therefore, it is very important that this user interface demonstrates to the user the time saved when planning for an emergency. Other implications of the user interface, in contrast to WSPEEDI-II, is the type of information that will presented. The user interface will show specific and important data about the characteristics of the plume, such as: maximum air dose rate, position of the plume and direction. On the other hand, WSPEEDI-II provides a much more in depth look into not only plume characteristics but also meteorological field generation time and dispersion calculations. Since the library of data is massive then reviewing in depth details of each and every scenario would be a very time consuming task, therefore the user interface minimizes data analysis in that sense as well. Conclusion The study of plume analysis is very important regarding evacuation planning because it relies on total deposition that is left after a plume passage in a certain area, and the effects of the deposition on human health. The user interface in this study can assist evacuation experts in pre-planning for a crisis or assist during a crisis to decrease uncertainty. The method used is dependent on a large already existing library and can provide a vast amount of
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different scenarios to assist the user. The user interface has demonstrated how input from the user can produce an output of short summaries in a very quick amount of time. Comparing the time difference between WSPEEDI-II and the user interface results in 96% reduced calculation time, a huge number considering a situation where time is very limited. Also, experts want to see many scenarios when pre-planning for a disaster. Consequently, having a user interface that can help them generate scenarios in a very short amount of time can be very helpful. Finally, because the user interface, unlike WSPEEDI-II, provides only some important data the user can simply browse easily through all generated scenarios. This will not only save time but, will help the user truly identify which scenarios are worth analyzing.
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