JP2005283202A - Diffusion state prediction method and diffusion state prediction system of diffusate - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To determine in a short time diffusion data for showing the diffusion state of a diffusate diffused into the air. <P>SOLUTION: An air current field database comprising a plurality of air current field data having different wind directions and atmospheric stabilities is stored in a storage part 10. Weather data α are inputted from a weather data input part 12 into an air current field data operation part 11. The air current field data operation part 12 takes out the air current field data d having the 'wind direction' and the 'atmospheric stability' similar to the 'wind direction and atmospheric stability' of the weather data α from the air current field database in the storage part 10. A diffusion data operation part 13 determines diffusion field data by substituting the air current field data dt(=d) for a diffusion equation. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a diffusion state prediction method and a diffusion state prediction system for a diffusion material, and calculates a diffusion state of a diffusion material discharged into the atmosphere in a short time by preparing an airflow field database and a diffusion field database in advance. It is something that can be done.

  When radioactive materials are discharged to the outside (in the atmosphere) from facilities that handle radioactive materials, the diffusion range of radioactive materials and the concentration of radioactive materials at each point are predicted, and there is a risk of danger from radioactive materials Diffusion situation prediction methods are being developed to predict certain areas.

  This diffusion status prediction method not only predicts the diffusion status of radioactive materials, but also calculates the gas concentration at each point when the gas (smoke) discharged from the factory chimney diffuses into the atmosphere. It can also be applied to the analysis of the diffusion status of diffusing substances in the analysis of environmental assessment.

  In order to predict the diffusion state of the diffused substance discharged into the atmosphere by calculation, airflow field data is obtained, and then diffusion field data is obtained based on the airflow field data.

  In emergency response systems such as nuclear accidents, it is necessary to predict and evaluate the diffusion of harmful gases in a few kilometers square centered on diffusion sources (nuclear power plants, etc.). The current system uses wide-area meteorological data to calculate steady-state airflow field data and / or unsteady airflow field data using computational fluid dynamics (CFD) using a numerical simulation model. Thereafter (or simultaneously), the CFD is used to calculate steady-state diffusion data from the steady-state airflow field data, or non-stationary diffusion data from the unsteady-state airflow field data.

  Note that CFD is a calculation method for analyzing airflow field data or diffusion field data by dividing a calculation region into a grid pattern and time-integrating the differential equations of variables for variables (wind speed, temperature, etc.) at each grid point. It is.

  In the current gas situation prediction calculation (calculation for obtaining airflow field data), CFD calculation is performed on partial differential equations for analyzing atmospheric phenomena based on meteorological observation data such as weather GPV (Grid Point Value) data and AMEDAS. From the time of the event occurrence (for example, the release of radioactive material) to the time ahead of the specified time, obtain the wind direction and wind speed at a number of evaluation points (grid point positions) at certain time intervals by calculation, that is, for a certain time Find airflow field data for each step.

  Further, in the current diffusion state prediction calculation (calculation for obtaining diffusion field data), the concentration and properties of the released diffusion substance and the airflow field data are substituted into the diffusion equation for calculating the diffusion state of the diffusion substance (particle). Thus, the concentration of diffusion material (diffusion field data) at each lattice point position for each time step is obtained.

  Various types of “diffusion equations for calculating the diffusion state of diffusive substances (particles)” have been developed. One example is HYPACT (Hybrid Particle Concentration) developed by Colorado State University and US ATMET. Transport Model) code.

JP 2002-202383 A JP2003-196574

  Conventionally, since calculation is performed using CFD to calculate airflow field data and diffusion field data, a huge amount of time is required for the calculation. In particular, calculation of airflow field data takes a long time.

  An object of the present invention is to provide a diffusion state prediction method and a diffusion state prediction system for a diffusion substance that can obtain diffusion field data (data indicating the diffusion state of a diffusion substance) in a short time in view of the above-described conventional technology. And

The configuration of the diffusion status prediction method of the present invention that solves the above problems is as follows.
In advance, an airflow field database consisting of a plurality of airflow field data having different wind directions and atmospheric stability at a target point where a diffusion source that discharges diffused substances into the atmosphere exists,
The wind direction and atmospheric stability are obtained based on the weather data of the target date and time, and the airflow field data having the wind direction and atmospheric stability similar to the wind direction and atmospheric stability of the weather data of the target date and time are extracted from the airflow field database. ,
It is characterized in that diffusion field data of a diffusing material is obtained by substituting the extracted airflow field data into a diffusion equation for calculating a diffusion state of the diffusing material.

The configuration of the diffusion status prediction system of the present invention is as follows.
A storage unit storing an airflow field database composed of a plurality of airflow field data having different wind directions and atmospheric stability at a target point where a diffusion source that discharges diffused substances to the atmosphere exists;
A weather data input unit for inputting the weather data of the target date and time,
The wind direction and atmospheric stability are obtained based on the weather data of the target date and time input from the weather data input unit, and the wind direction and atmospheric stability are similar to the wind direction and atmospheric stability of the weather data of the target date and time. An airflow field data calculating unit for extracting data from an airflow field database stored in the storage unit;
A diffusion field data calculation unit that obtains diffusion field data of a diffusing material by substituting the airflow field data extracted by the airflow field data calculation unit into a diffusion equation that calculates a diffusion state of the diffusing material.

The configuration of the diffusion status prediction method of the present invention is as follows.
An airflow field database consisting of multiple airflow field data with different wind directions and atmospheric stability at the target point where a diffusion source that emits diffused substances into the atmosphere exists is obtained in advance, and each airflow field data in this airflow field database is diffused. By substituting in the diffusion equation for calculating the diffusion state of the substance, a diffusion field database consisting of a plurality of diffusion field data with different wind directions and atmospheric stability is obtained in advance.
Obtain the wind direction and atmospheric stability based on the meteorological data of the target date and time, and extract from the diffusion field database the diffusion field data that has a wind direction and atmospheric stability similar to the wind direction and atmospheric stability of the meteorological data of the target date and time. It is characterized by.

The configuration of the diffusion status prediction system of the present invention is as follows.
A storage unit storing a diffusion field database composed of a plurality of diffusion field data having different wind directions and atmospheric stability at a target point where a diffusion source that discharges diffused substances to the atmosphere exists;
A weather data input unit for inputting the weather data of the target date and time,
A diffusion field having a wind direction and atmospheric stability similar to the wind direction and atmospheric stability of the weather data of the target date and time is obtained based on the weather data of the target date and time input from the weather data input unit. And a diffusion field data calculation unit that extracts data from a diffusion field database stored in the storage unit.

The configuration of the diffusion status prediction method of the present invention is as follows.
In advance, an airflow field database consisting of a plurality of airflow field data having different wind directions and atmospheric stability at a target point where a diffusion source that discharges diffused substances into the atmosphere exists,
The wind direction and atmospheric stability of each meteorological data are obtained based on the meteorological data at multiple points in time at the target date and time, and the wind direction and atmospheric stability are similar to the wind direction and atmospheric stability at multiple points in time at the target date and time. A plurality of airflow field data being extracted from the airflow field database,
By substituting the extracted plurality of airflow field data into a diffusion equation for calculating the diffusion state of the diffusing material, the plurality of diffusion field data of the diffusing material is obtained in time series.

The configuration of the diffusion status prediction system of the present invention is as follows.
A storage unit storing an airflow field database composed of a plurality of airflow field data having different wind directions and atmospheric stability at a target point where a diffusion source that discharges diffused substances to the atmosphere exists;
A weather data input unit for inputting weather data at multiple points in time and
The wind direction and the atmospheric stability are obtained based on the meteorological data at a plurality of times of the target date and time input from the weather data input unit, and the wind direction and the atmospheric stability are similar to the wind direction and the atmospheric stability of the meteorological data of the target date and time. A plurality of airflow field data that are extracted from an airflow field database stored in the storage unit,
A diffusion field data calculation unit that obtains diffusion field data of a diffusion material in time series by substituting the airflow field data extracted by the airflow field data calculation unit into a diffusion equation for calculating a diffusion state of the diffusion material. Features.

In the present invention, by preparing an airflow field database in advance, calculation of airflow field data becomes unnecessary, and the diffusion state of exhaust substances can be predicted in a short time.
Further, in the present invention, by preparing a diffusion field database in advance, calculation of airflow field data and calculation of diffusion field data become unnecessary, and it is possible to predict the diffusion state of exhaust substances in a short time.
Furthermore, in the present invention, unsteady airflow field data can be obtained from an airflow field database prepared in advance, and unsteady diffusion field data can be obtained based on the unsteady airflow field data. Can predict the diffusion situation.

  In the present invention, an airflow field database at a target point where a diffusion source exists is prepared in advance. When the diffusing material is discharged into the atmosphere from the diffusion source at the target point, airflow field data similar to the weather conditions at the time of discharging the diffusing material is extracted from the airflow field database. By using this airflow field data and calculating the diffusion state using the CFD, the diffusion state of the discharged substance can be predicted quickly and in a short time.

  Moreover, in this invention, the airflow field database in the target point where a diffusion source exists is prepared beforehand, and also the diffusion field database for each weather condition is prepared beforehand based on this airflow field database. When the diffusing material is discharged into the atmosphere from the diffusion source at the target point, the diffusion field data having a weather condition similar to the weather condition at the time of diffusing material discharge is taken out from the diffusion field database. Since this diffusion field data indicates the diffusion state of the emission material, the diffusion state of the emission material can be predicted quickly and in a short time.

<First construction method of airflow field database>
From the wide-area meteorological data, the vertical distribution of wind speed, temperature, atmospheric pressure, humidity, etc. at the target point is extracted by wind direction (16 directions) and by atmospheric stability (see FIG. 1A).
That is, from a region of wide-area meteorological data (interval (scale) of one grid is several tens to several hundreds km), a region of a narrow numerical model (scale of several kilometers: mesoscale is obtained by a nesting method using interpolation or the like. (Methoscale)), and the vertical distribution (see Fig. 1 (b)) of wind speed, temperature, atmospheric pressure, humidity, etc. at the target point (for example, the position of the nuclear power plant), by wind direction (16 directions), and atmospheric stability Extract separately.
In FIG. 1B, U is the wind speed, T is the temperature, P is the atmospheric pressure, RH is the relative humidity, and Z is the vertical distance.

For example, GPV (Grid Point Value), which is weather forecast data distributed from the Japan Meteorological Agency, is used as the above-mentioned wide-area weather data. In this GPV, values of elements (wind speed, temperature, humidity, etc.) on grid points when the whole of Japan is divided into grids are shown.
Further, the stability is determined based on the atmospheric stability classification of Pathil. In Paskir's atmospheric stability classification, the stability is determined from the wind speed and the amount of solar radiation in the daytime, and from the wind speed and the cloudiness at night, and is classified into seven stages from unstable (A) to stable (G). Yes.

  Next, the data of vertical distribution (see Fig. 1 (b)) such as wind speed, temperature, atmospheric pressure, humidity, etc., extracted by wind direction (16 directions) and atmospheric stability, are used to determine the initial conditions and uniformity of the mesoscale weather model. Incorporating as boundary conditions, airflow calculation is performed by the CFD method, and an airflow field database composed of a plurality of three-dimensional airflow field data is constructed (see FIGS. 1C and 2).

  Mesoscale meteorological models include RAMS (Regional Atmospheric Modeling System: meteorological analysis model developed at Colorado State University, USA) and MM5 (National Center for Atmospheric Science (NCAR) and Pennsylvania State University). ) Is used.

  FIG. 2 shows the constructed airflow field database DB1. The airflow field database DB1 includes 112 (7 × 16) airflow field data (d-A1, to d-G16) having different stability (A to G) and wind directions (wind directions 1 to 16). Each airflow field data (e.g., d-A1) is data having wind direction, wind speed, temperature, pressure, and humidity as data elements at a specific wind direction and a specific stability (e.g., wind direction is 1 and stability is A). is there.

<Second construction method of airflow field database>
In the second construction method of the airflow field database, based on the local meteorological observation data of the target point where the diffusion source is located, the same target point (for example, the position of the nuclear power plant) as shown in FIG. The vertical distribution of wind speed, temperature, atmospheric pressure, humidity, etc. (see FIG. 1B) is obtained for each wind direction (16 directions) and for atmospheric stability.

  Next, data on vertical distributions (see Fig. 1 (b)) such as wind speed, temperature, atmospheric pressure, and humidity obtained by wind direction (16 azimuths) and atmospheric stability were used to determine the initial conditions and uniformity of the mesoscale meteorological model. Incorporating as boundary conditions, airflow calculation is performed by the CFD method, and an airflow field database composed of a plurality of three-dimensional airflow field data is constructed (see FIGS. 1C and 2). In the following description, the airflow field database obtained in this way is indicated by a symbol “DB2”.

<Method to obtain steady-state airflow field data using airflow field database and perform diffusion calculation by CFD>
A third embodiment of the present invention will be described with reference to FIG. 3 showing a calculation procedure and FIG. 4 which is a calculation block diagram.

  The storage unit 10 stores a previously obtained airflow field database DB1. This airflow field database DB1 is obtained by the method of the first embodiment described above. Specifically, as shown in FIG. 2, 112 airflow field data (d-A1 to d1) having different stability and wind direction. d-G16).

  Meteorological data α of the target date and time is input from the weather data input unit 12 to the airflow field data calculation unit 11. The target date and time refers to the date and time when a diffused material (for example, radioactive material) is discharged from the diffusion source (for example, a nuclear power plant) to the atmosphere. The weather data α has 16 directions of wind direction, wind speed, temperature, pressure, and humidity as data elements.

The airflow field data calculation unit 11 sequentially performs the following calculations.
(1) First, the atmospheric stability of the meteorological data α is calculated from each data element of the input meteorological data α.

(2-1) Next, “wind direction and atmospheric stability” which is very close to “wind direction and atmospheric stability” of the weather data α from the airflow field database DB1 stored in the storage unit 10 and having different stability and wind direction. The airflow field data is extracted. Here, the extracted airflow field data is indicated by a symbol “d”. The extracted airflow field data is sent to the diffusion field data calculation unit 13 as airflow field data dt.
(2-2) If there is no airflow field data with “wind direction and atmospheric stability” that is very close to “wind direction and atmospheric stability” of weather data α, “wind direction and atmospheric stability” of weather data α A plurality of airflow field data having “wind direction and atmospheric stability” as close as possible to “degree” are extracted. Then, by interpolating the extracted airflow field data, new airflow field data that has the same “wind direction and atmospheric stability” as the “wind direction and atmospheric stability” of the weather data α is calculated. The new airflow field data is sent to the diffusion field data calculation unit 13 as airflow field data dt.

  The diffusion field data calculation unit 13 obtains diffusion field data by substituting the airflow field data dt into a diffusion equation for calculating the diffusion state of the diffusion substance (particle). This diffusion field data indicates the diffusion state (diffusion region, diffusion concentration) of the diffusion material, and the diffusion state can be predicted from this diffusion field data.

  Various types of “diffusion equations for calculating the diffusion state of the diffusive material (particle)” have been developed. For example, HYPACT (Hybrid Particle Concentration Transport Model) developed by Colorado State University and US ATMET. Use a code.

  In the present embodiment, when obtaining the airflow field data dt, the “wind direction and atmospheric stability” of the meteorological data α of the target date and time is extremely determined from the airflow field database DB1 prepared in advance without performing CFD calculation. Since only the airflow field data having the similar “wind direction and atmospheric stability” is extracted, the airflow field data dt can be obtained in a short time, and consequently, the diffusion field data can be obtained in a short time.

<Modification of Example 3>
In the third embodiment described above, the airflow field database DB1 obtained by the method of the first embodiment is used as the airflow field database stored in the storage unit 10, but the airflow field database DB2 obtained by the method of the second embodiment is used. It may be.

<Method of predicting diffusion situation using diffusion field database>
A fourth embodiment of the present invention will be described with reference to FIG. 5 showing a diffusion field database DBK, FIG. 6 showing a calculation procedure, and FIG. 7 which is a calculation block diagram. In the fourth embodiment, it is assumed that the position of the emission source is fixed and the intensity of the emission material discharged from the emission source is fixed. For example, it is a prediction system constructed assuming that a diffused material (radioactive material) leaks from a nuclear power plant.

  In Example 4, first, an airflow field database D1 (or an airflow field database D2 obtained by the method of Example 2) as shown in FIG. 2 is constructed. In addition, since it will be in the same operation | movement calculation state even if it uses any of airflow field database D1, D2 below, it demonstrates using airflow database D1.

  Furthermore, 112 kinds of airflow field data (d-A1 to d-G16) included in the airflow field database D1 and having different stability and wind direction with the discharge source position fixed and the discharge source intensity fixed, The 112 diffusion field data (dK-A1 to dK-G16) having different stability and wind direction are obtained by substituting into the diffusion equation for calculating the diffusion state of the diffusion substance (particle). Thus, the diffusion field database DBK shown in FIG. 5 is a collection of 112 diffusion field data (dK-A1 to dK-G16) having different stability and wind direction.

  The storage unit 20 stores the diffusion field database DBK obtained as described above.

  The weather data α of the target date and time is input from the weather data input unit 22 to the diffusion field data calculation unit 21. The target date and time refers to the date and time when a diffused material (for example, radioactive material) is discharged from the diffusion source (for example, a nuclear power plant) to the atmosphere. The weather data α has 16 directions of wind direction, wind speed, temperature, pressure, and humidity as data elements.

The diffusion field data calculation unit 21 performs the following calculations in order.
(1) First, the atmospheric stability of the meteorological data α is calculated from each data element of the input meteorological data α.

(2-1) Next, “wind direction and atmospheric stability” that is very close to “wind direction and atmospheric stability” of the weather data α from the diffusion field database DBK stored in the storage unit 20 and having different stability and wind direction. Extract the diffusion field data. Here, the extracted diffusion field data is indicated by a symbol “dKt”. The extracted diffusion field data is output as diffusion field data dKt.
(2-2) If there is no diffusion field data with “wind direction and atmospheric stability” that is very close to “wind direction and atmospheric stability” of weather data α, “wind direction and atmospheric stability” of weather data α A plurality of diffusion field data having “wind direction and atmospheric stability” as close as possible to “degree” are extracted. Then, by interpolating the extracted multiple diffusion field data, new diffusion field data with the same “wind direction and atmospheric stability” as the “wind direction and atmospheric stability” of the weather data α is calculated. This new diffusion field data is output as diffusion field data dKt.

  The diffusion field data dKt output from the diffusion field data calculation unit 21 indicates the diffusion state (diffusion region, diffusion concentration) of the diffusion material, and the diffusion state can be predicted from this diffusion field data.

  In the present embodiment, when the diffusion field data dKt is obtained, the “wind direction and atmospheric stability” of the meteorological data α of the target date and time is determined from the diffusion field database DBK prepared in advance without performing the CFD calculation. Since it is only necessary to extract the diffusion field data having a similar “wind direction and atmospheric stability”, the diffusion field data dKt, that is, the diffusion state can be obtained in a short time.

<Method to obtain non-steady airflow field data using airflow field database and perform diffusion calculation by CFD>
A fifth embodiment of the present invention will be described with reference to FIG. 8 showing a calculation procedure, FIG. 9 showing a relationship between a time axis and data, and FIG. 10 which is a calculation block diagram.

  The storage unit 30 stores a previously obtained airflow field database DB1. This airflow field database DB1 is obtained by the method of the first embodiment described above. Specifically, as shown in FIG. 2, 112 airflow field data (d-A1 to d1) having different stability and wind direction. d-G16).

The airflow field data calculation unit 31 receives meteorological data α1, α2, α3, α4, α5, α6,... At a plurality of time points T1, T2, T3, T4, T5, T6. .. is input (see FIG. 9A). For example, α1 is 12:00 pm weather data, α2 is 12:10 pm weather data, α3 is 12:20 pm weather data, α4 is 12:30 pm weather data, and α5 is 12 pm The weather data at 40 minutes and α6 is the weather data at 12:50 pm.
In addition, the target day is a day when a diffusion material (for example, a radioactive material) is discharged into the atmosphere from a diffusion source (for example, a nuclear power plant). In addition, the meteorological data α1, α2, α3, α4, α5, α6... Has 16 directions of wind direction, wind speed, temperature, pressure, and humidity as data elements.

The airflow field data calculation unit 31 performs the following calculations in order.
(1) First, the atmospheric stability of the meteorological data α1 is calculated from each data element of the input meteorological data α1.

(2-1) Next, “wind direction and atmospheric stability” that is very close to “wind direction and atmospheric stability” of the weather data α1 from the airflow field database DB1 stored in the storage unit 30 and having different stability and wind direction. The airflow field data is extracted. Here, the extracted airflow field data is indicated by a symbol “d1”. The extracted airflow field data is sent to the diffusion field data calculation unit 33 as airflow field data dt1.
(2-2) If there is no airflow field data with “wind direction and atmospheric stability” that is very close to “wind direction and atmospheric stability” of weather data α1, “wind direction and atmospheric stability” of weather data α1 A plurality of airflow field data having “wind direction and atmospheric stability” as close as possible to “degree” are extracted. Then, by interpolating the extracted airflow field data, new airflow field data that has the same “wind direction and atmospheric stability” as the “wind direction and atmospheric stability” of the weather data α1 is calculated. The new airflow field data is sent to the diffusion field data calculation unit 33 as the airflow field data dt1.

  The airflow field data calculation unit 31 uses the same calculation as that for obtaining the airflow field data dt1 from the weather data α1 described above, and the airflow field data dt2, dt3 from the weather data α2, α3, α4, α5, α6. dt4, dt5, dt6,...

Further, the airflow field data calculation unit 31 obtains the airflow field data at the divided time points in the period between the time points T1, T2, T3, T4, T5, T6.
For example, as shown in FIG. 9B, the airflow field data dt11, dt12, dt13 of the divided time points T11, T12, T13, T14, T15, T16, T17, T18, T19 between the time point T1 and the time point T2, dt14, dt15, dt16, dt17, dt18, and dt19 are obtained by interpolating the airflow field data dt1 at time T1 and the airflow field data dt2 at time T2.

  The airflow field data at the time point divided between the time point T2 and the time point T3, the airflow field data at the time point divided between the time point T3 and the time point T4, and the like are similarly obtained by performing interpolation interpolation.

The diffusion field data calculation unit 33 receives the airflow field data dt (dt1, dt11, dt12, dt13, dt14, dt15, dt16, dt17, dt18, dt19, dt2,...) From the airflow field data calculation unit 31. Is entered.
The diffusion field data calculation unit 33 arranges the plurality of airflow field data dt in time series, and in order from the earliest time among the plurality of airflow field data dt, that is, each time point (T1, T11, T12, T13). , T14, T15, T16, T17, T18, T19, T2...), And the airflow field data dt1, dt11, dt12, dt13, dt14, dt15, dt16, dt17, dt18, dt19, dt2,. Diffusion field data at each time point (T1, T11, T12, T13, T14, T15, T16, T17, T18, T19, T2...) By substituting into the diffusion equation for calculating the diffusion state of the substance (particle). Ask for.

  In this way, diffusion field data at each time point (T1, T11, T12, T13, T14, T15, T16, T17, T18, T19, T2,...), That is, non-stationary diffusion field data is obtained. Such non-stationary diffusion field data indicates the diffusion state (diffusion region, diffusion concentration) of the diffusion material with time, and the diffusion state with time can be predicted from this diffusion field data.

  Various types of “diffusion equations for calculating the diffusion state of the diffusive material (particle)” have been developed. For example, HYPACT (Hybrid Particle Concentration Transport Model) developed by Colorado State University and US ATMET. Use a code.

  In the present embodiment, when obtaining the airflow field data dt, the “wind direction and atmospheric stability” of the meteorological data α of the target date and time is extremely determined from the airflow field database DB1 prepared in advance without performing CFD calculation. Since only the airflow field data having the similar “wind direction and atmospheric stability” is extracted, the airflow field data dt can be obtained in a short time, and consequently, the diffusion field data can be obtained in a short time.

  Further, in this embodiment, non-stationary (time-dependent) diffusion field data can be obtained, so that the diffusion situation over time can be predicted.

<Modification of Example 5>
In the fifth embodiment described above, the airflow field database DB1 obtained by the method of the first embodiment is used as the airflow field database stored in the storage unit 30, but the airflow field database DB2 obtained by the method of the second embodiment is used. It may be.

  The present invention can be used for grasping a diffusion state of a radioactive substance, grasping a diffusion state of a gas body, and analyzing an environmental assessment.

Explanatory drawing which shows the method of calculating | requiring narrow area weather data from wide area weather data. The table | surface which shows an airflow field database. Explanatory drawing which shows the calculation procedure of Example 3. FIG. FIG. 10 is a block diagram illustrating a calculation block according to the third embodiment. A table showing a diffusion field database. Explanatory drawing which shows the calculation procedure of Example 4. FIG. FIG. 10 is a block diagram illustrating a calculation block according to a fourth embodiment. Explanatory drawing which shows the calculation procedure of Example 5. FIG. Explanatory drawing which shows the relationship between the time-axis and data in Example 5. FIG. FIG. 10 is a block diagram illustrating a calculation block according to the fifth embodiment.

Explanation of symbols

10, 20, 30 Storage unit 11, 31 Airflow field data calculation unit 12, 22, 32 Meteorological data input unit 13, 21, 33 Diffusion field data calculation unit

Claims (6)

In advance, an airflow field database consisting of a plurality of airflow field data having different wind directions and atmospheric stability at a target point where a diffusion source that discharges diffused substances into the atmosphere exists,
Wind direction and atmospheric stability are obtained based on the meteorological data of the target date and time, and airflow field data having wind direction and atmospheric stability similar to the wind direction and atmospheric stability of the meteorological data of the target date and time are extracted from the airflow field database. ,
A diffusion state prediction method for a diffusing material, wherein the extracted airflow field data is substituted into a diffusion equation for calculating a diffusion state of the diffusing material to obtain diffusion field data for the diffusing material. A storage unit storing an airflow field database composed of a plurality of airflow field data having different wind directions and atmospheric stability at a target point where a diffusion source that discharges diffused substances to the atmosphere exists;
A weather data input unit for inputting the weather data of the target date and time,
The wind direction and atmospheric stability are obtained based on the weather data of the target date and time input from the weather data input unit, and the wind direction and atmospheric stability are similar to the wind direction and atmospheric stability of the weather data of the target date and time. An airflow field data calculating unit for extracting data from an airflow field database stored in the storage unit;
A diffusion field data calculation unit for obtaining diffusion field data of a diffusion material by substituting the air flow field data extracted by the air flow field data calculation unit into a diffusion equation for calculating a diffusion state of the diffusion material Material diffusion status prediction system. An airflow field database consisting of multiple airflow field data with different wind directions and atmospheric stability at the target point where a diffusion source that emits diffused substances into the atmosphere exists is obtained in advance, and each airflow field data in this airflow field database is diffused. By substituting in the diffusion equation for calculating the diffusion state of the substance, a diffusion field database consisting of a plurality of diffusion field data with different wind directions and atmospheric stability is obtained in advance.
Obtain the wind direction and atmospheric stability based on the meteorological data of the target date and time, and extract from the diffusion field database the diffusion field data that has a wind direction and atmospheric stability similar to the wind direction and atmospheric stability of the meteorological data of the target date and time. A diffusion state prediction method for a diffusion material characterized by A storage unit storing a diffusion field database composed of a plurality of diffusion field data having different wind directions and atmospheric stability at a target point where a diffusion source that discharges diffused substances to the atmosphere exists;
A weather data input unit for inputting the weather data of the target date and time,
A diffusion field having a wind direction and atmospheric stability similar to the wind direction and atmospheric stability of the weather data of the target date and time is obtained based on the weather data of the target date and time input from the weather data input unit. A diffusion field prediction system for a diffusion material, comprising: a diffusion field data calculation unit that extracts data from a diffusion field database stored in the storage unit. In advance, an airflow field database consisting of a plurality of airflow field data having different wind directions and atmospheric stability at a target point where a diffusion source that discharges diffused substances into the atmosphere exists,
The wind direction and atmospheric stability of each meteorological data are obtained based on the meteorological data at multiple points in time at the target date and time, and the wind direction and atmospheric stability are similar to the wind direction and atmospheric stability at multiple points in time at the target date and time. A plurality of airflow field data being extracted from the airflow field database,
A method for predicting the diffusion state of a diffusing material, wherein a plurality of diffusion field data of the diffusing material is obtained in a time series by substituting the plurality of extracted airflow field data into a diffusion equation for calculating a diffusion state of the diffusing material. . A storage unit storing an airflow field database composed of a plurality of airflow field data having different wind directions and atmospheric stability at a target point where a diffusion source that discharges diffused substances to the atmosphere exists;
A weather data input unit for inputting weather data at multiple points in time and
The wind direction and the atmospheric stability are obtained based on the meteorological data at a plurality of times of the target date and time input from the weather data input unit, and the wind direction and the atmospheric stability are similar to the wind direction and the atmospheric stability of the meteorological data of the target date and time. A plurality of airflow field data, an airflow field data calculating unit for extracting from the airflow field database stored in the storage unit,
A diffusion field data calculation unit that obtains diffusion field data of a diffusion material in time series by substituting the airflow field data extracted by the airflow field data calculation unit into a diffusion equation for calculating a diffusion state of the diffusion material. A system for predicting diffusion status of characteristic diffusion materials.

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