JP2003196574A - Method and system for predicting diffusion state of diffused substance - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To predict the diffusion state of a diffused substance emitted to the atmospheric air. <P>SOLUTION: The diffused substance is replaced with a particle, the moving position of the particle generated in an emission source is found by computation, and recorded while correlating the moving position with elapsed time after the emission. An intensity data is set to indicate intensity of the particles along the elapsed time after the emission. The intensity of the particles in a time point when the particles are generated is found thereafter based on the elapsed time after the emission, referring to the intensity data, and the moving position, the elapsed time after the emission and the intensity are recorded for every particle to be correlated each other. A concentration at a prescribed time in a prescribed area is calculation-found by integrating the intensities of the particles existing in the prescribed area. <P>COPYRIGHT: (C)2003,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for predicting the diffusion status of diffusing substances. The present invention predicts how a substance (for example, radioactive substance or smoke) emitted into the atmosphere from a diffusion source (for example, a facility using radioactive substances or a chimney) will diffuse into the atmosphere, It is designed to predict the concentration of a substance that changes from moment to moment.

[0002]

2. Description of the Related Art When a radioactive substance is discharged to the outside from an facility that handles radioactive substances, the diffusion range of the radioactive substance and the concentration of the radioactive substance at each point are predicted, and there is a risk of radioactive substances. Diffusion status forecasting methods are being developed to forecast areas of concern.

This diffusion state prediction method is not only for predicting the diffusion state of radioactive materials, but also for example when the gas body (smoke) discharged from the chimney of a factory diffuses in the atmosphere, It can also be applied when calculating the concentration or when analyzing the diffusion status of diffusible substances in the analysis of environmental assessment.

In order to predict the diffusion status of substances discharged into the atmosphere by calculation, it is necessary to perform the following two calculations. (1) Gas situation prediction calculation (2) Diffusion situation prediction calculation

The gas condition prediction calculation of the above (1) is an event by calculating a partial differential equation for analyzing atmospheric phenomena based on meteorological GPV (Grid Point Value) data and meteorological observation data such as AMEDAS. From the time of generation (for example, external emission of radioactive material) to the time point after a predetermined time, the wind direction and wind speed at a large number of evaluation points (grid point positions) are calculated by calculation at fixed time intervals, that is, at fixed time intervals. This is a calculation for obtaining the gas condition that expresses the wind velocity field data.

Further, the diffusion state prediction calculation of the above (2) is performed by substituting the concentration and properties of the released diffusion substance and the wind velocity field data into a diffusion equation for calculating the diffusion state of the substance (particle). , Calculation for obtaining the concentration of the diffusing substance at each grid point position at each time step.

<Explanation of Gas Condition Prediction Calculation> First, an outline of the gas condition prediction calculation will be described. Meteorological observation data, such as meteorological GPV data, is delivered from the meteorological service support center every 12 hours. This meteorological GPV data extends along the north-south direction on the surface of the earth and a plurality of imaginary latitude lines where the distance between the east-west directions is a specified distance (2 km) and the surface of the earth along the east-west direction. Meteorological data (wind speed vector (wind direction, wind speed, wind speed, wind speed, wind speed, wind speed, wind speed, wind speed) ), Atmospheric pressure, temperature, water content). Moreover, the meteorological GPV data is the meteorological data at each parent grid point position at the time of distribution, 3 hours ahead of the time of distribution,
Data for 51 hours at intervals of 3 hours, such as 6 hours ahead and 9 hours ahead, are collectively delivered.

In the meteorological data at the parent grid point position of the meteorological GPV data described above, the distance between the parent grid point positions is as wide as 2 Km spatially and the time is as long as 3 hours. It is not possible to calculate the diffusion concentration of the diffusing substance only with the gas condition (wind direction, wind velocity) data, that is, the wind velocity field data, which is indicated by the meteorological data at the grid point positions.

For this reason, partial differentiation for analyzing atmospheric phenomena from the spatially and temporally coarse meteorological observation data to analyze the spatially and temporally dense gas conditions (wind direction, wind speed, etc.) It is necessary to obtain it by calculating an equation.

Therefore, the child lattice point position is set between the parent lattice point positions set in the calculation region to be calculated (specific region preset in the surface of the earth). The sub-lattice points extend along the north-south direction on the surface of the earth, and a plurality of imaginary latitude lines that have a constant distance (50m) in the east-west direction and extend along the east-west direction on the surface of the earth. The distance between the north and south directions is constant (50m)
Is arranged at a point where a plurality of virtual imaginary longitude lines intersect.

Then, the meteorological data of the child lattice point position and the parent lattice point position at every fixed time interval (for example, every 20 seconds) from the start of the calculation is obtained by the differential analysis calculation of the partial differential equation for analyzing the atmospheric phenomenon. . As a partial differential equation for analyzing atmospheric phenomena, Colorado State University and Mission Rese
RAMS (Regional Atmospheric Mo) developed by arch
You can use the basic equations for wind field analysis, which are represented by the deling System) code.

The basic equations of wind velocity field analysis represented by the RAMS code are the kinetic equation, the thermal energy equation,
It is composed of the diffusion equation of water and the equation of continuity, and is represented by the following equations (1) to (6).

[0013]

[Equation 1]

As described above, RAMS (Regional Atmospher)
ic Modeling System) The basic equations for wind field analysis are calculated, and the meteorological data at each parent grid point position and each sub-grid at a fixed time interval (for example, every 20 seconds) from the start of the calculation. Wind direction vector data (wind velocity field data) indicating meteorological data at point positions can be obtained.

<Outline of Spreading State Prediction Calculation> Next, the spreading state prediction calculation will be described. HYPACT (Hybrid Particle Concentration) developed by Colorado State University and Mission Research
Transport Model) code, RAMS (Regional Atm)
The wind velocity field data for each parent grid point position and each child grid point position for each 20-second interval obtained by the Ospheric Modeling System) code is successively substituted, and the diffusion state prediction calculation is performed. The Lagrangian particle diffusion model is used as a concrete example of the diffusion state prediction calculation.

In this Lagrangian particle diffusion model, the particle diffusion rate (u ',
v ', w') is calculated, and each particle is moved.

[0017]

[Equation 2]

Here, HYPACT (Hybrid Particle
Concentration Transport Model) code, RAMS
A specific example will be described in which the wind speed field data of each parent grid point position and each child grid point position for each 20-second interval obtained by the (Regional Atmospheric Modeling System) code is successively substituted to perform prediction calculation of the diffusion state.

In order to perform this calculation, the substance discharged from the emission source into the atmosphere is replaced with a large number of particles P, and N is calculated from the position of the emission source every calculation cycle Δt (here Δt = 20 seconds).
It is set that the number (here, 20) of particles P is generated.

That is, 20 particles P are generated at the start of calculation, 20 particles are generated 20 seconds after the start of calculation, and 20 particles are generated 40 seconds after the start of calculation. , 20 particles are generated every calculation cycle Δt (20 seconds). And the calculation cycle Δt
The position (spatial coordinate) of each particle P is obtained by calculation every (20 seconds).

At the start of calculation (time 0 seconds)
The generated 20 particles P are₀₀ ⁰¹, P₀₀ ⁰²，
P₀₀ ⁰³, P₀₀ ⁰⁴, P₀₀ ⁰⁵, P₀₀ ⁰⁶, P₀₀ ⁰⁷, P₀₀ ⁰⁸, P
₀₀ ⁰⁹, P₀₀ ^Ten, P₀₀ ¹¹, P₀₀ ¹², P₀₀ ¹³, P₀₀ ¹⁴, P₀₀
¹⁵, P₀₀ ¹⁶, P₀₀ ¹⁷, P₀₀ ¹⁸, P₀₀ ¹⁹, P₀₀ ²⁰Shown as
Then, 20 seconds after the start of calculation,
Individual particles P, P₂₀ ⁰¹, P ₂₀ ⁰², P₂₀ ⁰³, P₂₀ ⁰⁴, P₂₀
⁰⁵, P₂₀ ⁰⁶, P₂₀ ⁰⁷, P₂₀ ⁰⁸, P₂₀ ⁰⁹, P₂₀ ^Ten，
P ₂₀ ¹¹, P₂₀ ¹², P₂₀ ¹³, P₂₀ ¹⁴, P₂₀ ¹⁵, P₂₀ ¹⁶, P
₂₀ ¹⁷, P₂₀ ¹⁸, P₂₀ ¹⁹, P ₂₀ ²⁰Is shown at the start of calculation
20 particles P generated 40 seconds after the point,
P₄₀ ⁰¹, P ₄₀ ⁰², P₄₀ ⁰³, P₄₀ ⁰⁴, P₄₀ ⁰⁵, P₄₀ ⁰⁶, P
₄₀ ⁰⁷, P₄₀ ⁰⁸, P₄₀ ⁰⁹, P₄₀ ^Ten, P ₄₀ ¹¹, P₄₀ ¹², P₄₀
¹³, P₄₀ ¹⁴, P₄₀ ¹⁵, P₄₀ ¹⁶, P₄₀ ¹⁷, P₄₀ ¹⁸，
P₄₀ ¹⁹, P ₄₀ ²⁰Show as. That is, after the code "P"
The number shown in the lower row is the time from the start of calculation,
The number shown in the upper row after the code "P" is the
The 20 particles generated by the above are distinguished. other
Particles generated at the time point are also expressed in the same manner.

First, at the start of calculation, the emission source S
From 20 particles P ₀₀ ⁰¹ , P ₀₀ ⁰² , P ₀₀ ⁰³ , P ₀₀ ⁰⁴ , P
₀₀ ⁰⁵ , P ₀₀ ⁰⁶ , P ₀₀ ⁰⁷ , P ₀₀ ⁰⁸ , P ₀₀ ⁰⁹ , P ₀₀ ¹⁰ , P ₀₀
¹¹ , P ₀₀ ¹² , P ₀₀ ¹³ , P ₀₀ ¹⁴ , P ₀₀ ¹⁵ , P ₀₀ ¹⁶ ,
^{_{P 00 17, P 00 18,}} P 00 19, P 00 20 occurs.

After 20 seconds from the start of the calculation, 20 particles P ₂₀ ⁰¹ and P 20 are newly added from the emission source S shown in FIG.
₂₀ ⁰² , P ₂₀ ⁰³ , P ₂₀ ⁰⁴ , P ₂₀ ⁰⁵ , P ₂₀ ⁰⁶ , P ₂₀ ⁰⁷ , P ₂₀
⁰⁸ , P ₂₀ ⁰⁹ , P ₂₀ ¹⁰ , P ₂₀ ¹¹ , P ₂₀ ¹² , P ₂₀ ¹³ ,
P ₂₀ ¹⁴ , P ₂₀ ¹⁵ , P ₂₀ ¹⁶ , P ₂₀ ¹⁷ , P ₂₀ ¹⁸ , P ₂₀ ¹⁹ , P
₂₀ ²⁰ occurs. At this time, particles P ₀₀ ⁰¹ , P ₀₀ ⁰² , P ₀₀ ⁰³ , P ₀₀ ⁰⁴ , P ₀₀ ⁰⁵ , generated at the start of calculation,
P ₀₀ ⁰⁶ , P ₀₀ ⁰⁷ , P ₀₀ ⁰⁸ , P ₀₀ ⁰⁹ , P ₀₀ ¹⁰ , P ₀₀ ¹¹ , P
₀₀ ¹² , P ₀₀ ¹³ , P ₀₀ ¹⁴ , P ₀₀ ¹⁵ , P ₀₀ ¹⁶ , P ₀₀ ¹⁷ , P ₀₀
¹⁸ , P ₀₀ ¹⁹ , and P ₀₀ ²⁰ reach the position away from the emission source S and are diffused. The position of each particle P is RAM
Using the wind velocity field data every 20 seconds obtained by S (Regional Atmospheric Modeling System) code, Lagr
The diffusion velocity (u ', v', w ') of each particle P in the angian particle diffusion model is calculated, and it is obtained by moving each particle.

40 seconds after the start of calculation,
20 particles P newly from the emission source S shown in 20₄₀ ⁰¹, P
₄₀ ⁰², P₄₀ ⁰³, P₄₀ ⁰⁴, P₄₀ ⁰⁵, P₄₀ ⁰⁶, P₄₀ ⁰⁷, P₄₀
⁰⁸, P₄₀ ⁰⁹, P₄₀ ^Ten, P₄₀ ¹¹, P₄₀ ¹², P₄₀ ¹³，
P₄₀ ¹⁴, P₄₀ ¹⁵, P₄₀ ¹⁶, P₄₀ ¹⁷, P₄₀ ¹⁸, P₄₀ ¹⁹, P
₄₀ ²⁰Occurs. At this time, it occurred at the start of calculation
Particle P₀₀ ⁰¹, P₀₀ ⁰², P₀₀ ⁰³, P₀₀ ⁰⁴, P₀₀ ⁰⁵，
P₀₀ ⁰⁶, P₀₀ ⁰⁷, P₀₀ ⁰⁸, P₀₀ ⁰⁹, P₀₀ ^Ten, P₀₀ ¹¹, P
₀₀ ¹², P₀₀ ¹³, P₀₀ ¹⁴, P₀₀ ¹⁵, P₀₀ ¹⁶, P₀₀ ¹⁷, P₀₀
¹⁸, P₀₀ ¹⁹, P₀₀ ²⁰At a position further away from the emission source S
It is spreading further as it reaches. At the start of calculation
20 particles P generated 20 seconds after the point₂₀ ⁰¹，
P₂₀ ⁰², P₂₀ ⁰³, P₂₀ ⁰⁴, P₂₀ ⁰⁵, P₂₀ ⁰⁶, P₂₀ ⁰⁷, P
₂₀ ⁰⁸, P₂₀ ⁰⁹, P₂₀ ^Ten, P₂₀ ¹¹, P₂₀ ¹², P₂₀ ¹³, P₂₀
¹⁴, P₂₀ ¹⁵, P₂₀ ¹⁶, P₂₀ ¹⁷, P₂₀ ¹⁸, P₂₀ ¹⁹, P₂₀ ²⁰
Diffuses as it reaches a position away from the emission source S.
ing. The position of each particle P is RAMS (Regional Atmos
pheric Modeling System) 20 seconds increments obtained by code
The Lagrangian particle diffusion model is
The diffusion rate (u ', v', w ') of each particle P in the
It is calculated and determined by moving each particle.

60 seconds after the start of calculation,
20 particles P newly from the emission source S shown in 21₆₀ ⁰¹, P
₆₀ ⁰², P₆₀ ⁰³, P₆₀ ⁰⁴, P₆₀ ⁰⁵, P₆₀ ⁰⁶, P₆₀ ⁰⁷, P₆₀
⁰⁸, P₆₀ ⁰⁹, P₆₀ ^Ten, P₆₀ ¹¹, P₆₀ ¹², P₆₀ ¹³，
P₆₀ ¹⁴, P₆₀ ¹⁵, P₆₀ ¹⁶, P₆₀ ¹⁷, P₆₀ ¹⁸, P₆₀ ¹⁹, P
₆₀ ²⁰Occurs. At this time, it occurred at the start of calculation
Particle P₀₀ ⁰¹, P₀₀ ⁰², P₀₀ ⁰³, P₀₀ ⁰⁴, P₀₀ ⁰⁵，
P₀₀ ⁰⁶, P₀₀ ⁰⁷, P₀₀ ⁰⁸, P₀₀ ⁰⁹, P₀₀ ^Ten, P₀₀ ¹¹, P
₀₀ ¹², P₀₀ ¹³, P₀₀ ¹⁴, P₀₀ ¹⁵, P₀₀ ¹⁶, P₀₀ ¹⁷, P₀₀
¹⁸, P₀₀ ¹⁹, P₀₀ ²⁰At a position further away from the emission source S
It is spreading further as it reaches. At the start of calculation
20 particles P generated 20 seconds after the point₂₀ ⁰¹，
P₂₀ ⁰², P₂₀ ⁰³, P₂₀ ⁰⁴, P₂₀ ⁰⁵, P₂₀ ⁰⁶, P₂₀ ⁰⁷, P
₂₀ ⁰⁸, P₂₀ ⁰⁹, P₂₀ ^Ten, P₂₀ ¹¹, P₂₀ ¹², P₂₀ ¹³, P₂₀
¹⁴, P₂₀ ¹⁵, P₂₀ ¹⁶, P₂₀ ¹⁷, P₂₀ ¹⁸, P₂₀ ¹⁹, P₂₀ ²⁰
Will reach a position further away from the emission source S and
Has spread to. Also, 40 seconds after the start of calculation,
Generated 20 particles P₄₀ ⁰¹, P₄₀ ⁰², P₄₀ ⁰³, P
₄₀ ⁰⁴, P₄₀ ⁰⁵, P₄₀ ⁰⁶, P₄₀ ⁰⁷, P₄₀ ⁰⁸, P₄₀ ⁰⁹, P₄₀
^Ten, P₄₀ ¹¹, P₄₀ ¹², P₄₀ ¹³, P₄₀ ¹⁴, P₄₀ ¹⁵，
P₄₀ ¹⁶, P₄₀ ¹⁷, P₄₀ ¹⁸, P₄₀ ¹⁹, P₄₀ ²⁰Is the emission source S
It spreads as it reaches a position away from. Each particle P
The position of RAMS (Regional Atmospheric Modeling
System) code for wind speed field every 20 seconds
Each particle in the Lagrangian particle diffusion model is
The diffusion rate (u ', v', w ') of P is calculated, and each particle is
Obtain by moving.

As described above, the calculation cycle Δt (20 seconds)
20 particles are generated one after another one by one, and the position of the particle in each calculation period Δt (20 seconds), that is, the spatial coordinates (xi (t), yi (t), zi (t)) are calculated. Go.

Then, when a predetermined time has elapsed from the start of the calculation, as shown in FIG. 22, when the particles P exist in the unit space (unit volume of the predicted area) separated from the emission source S by a predetermined distance, From the number of particles, the concentration of the substance in this unit space can be calculated.

That is, in the emission source S, Q (m
Assuming that the substance of ³ ) is discharged, 20 particles P are generated in 20 seconds (one particle per 1 second when converted), so each particle P is Q / 1 (m ³ ) per particle. It has the emission source strength of. Therefore, the concentration of the substance in this unit space can be obtained by multiplying the number of particles P existing in this unit space by the emission source intensity Q / 1 (m ³ ).

The specific example described above is generally shown as follows.
become. A large number of substances such as gas discharged from the emission source
Replace with particles. And N particles per second from the emission source
To release. In this case, the calculated particle emission is N /
sec. Emissions of substances emitted from actual sources
Is Q (m³/ Sec), each particle has Q / N
(M ³) Emission source strength.

By numerically calculating the equation of motion for each particle in a non-stationary manner, that is, RAMS (Regional Atmos
HYPACT (Hybrid), which is the equation of motion of particles,
Particle Concentration Transport Model) code, calculate the diffusion velocity (u ′, v ′, w ′) of each particle P using the Lagrangian particle diffusion model, and move each particle to determine the coordinates of each particle. It can be determined non-steadily. That is, the spatial coordinates of each particle can be determined for each calculation cycle Δt. The data of each particle obtained by the Lagrangian particle model and recorded in the data recording device is the spatial coordinates (xi (t), yi) of each particle.
(T), zi (t)) only.

HYPA, which is the equation of motion of particles (substances)
The CT code expresses advection, diffusion, and gravity settling of particles. Here, the advection phenomenon of particles depends on the time average velocity of the atmosphere, the diffusion phenomenon depends on the turbulent velocity of the atmosphere, and the gravity settling depends on the mass of particles, the acceleration of gravity, the viscosity coefficient of air, etc. (See Figure 23)

When the number of particles in a unit volume of air is n, the gas concentration (substance concentration) in this space is n × Q /
It becomes N (gas m ³ / air m ³ ). That is, the number n of particles existing in this unit space is multiplied by the emission source intensity Q / N of each particle.

[0033]

This environmental concentration (concentration of the substance in a unit volume) depends on the change over time of the amount of the substance discharged. Therefore, under the condition that the emission amount changes with time, the diffusion calculation needs to be performed for each emission condition. Therefore, if there are many expected emission conditions, it is necessary to carry out diffusion calculations for emission cases, and as a result, a huge amount of calculation time is required.

That is, as shown in FIG. 24, for example, when the gas (substance) is being discharged from the emission source S (eg, a chimney), the temporal change of the gas concentration at a certain point F on the leeward side is from the emission source S. It changes according to the change over time of the substance discharged.

That is, when the discharge amount of the substance changes with time as shown in FIG. 25A, the concentration of the substance at the point F changes with time as shown in FIG. When the discharge amount of the substance is constant as shown in a), the concentration of the substance at the point F rises to a constant value as shown in FIG. )
In the case where the substance is instantaneously discharged as shown in, the concentration of the substance at the point F temporarily rises as shown in FIG. 27B and then becomes zero.

As described above, when the discharged amount of the substance changes with time, it is necessary to change the generated number of particles with time according to the discharged amount of the substance. Then, the moving position of the particle whose number of generated particles is changed with the passage of time in this way is obtained, and the concentration of the substance is calculated from the moving position of the particle. Therefore, diffusion calculation must be performed for each case where the change in emission amount is different, and a huge amount of calculation results is required.

For example, when an accident occurs in which a radioactive substance is discharged to the outside in a facility that handles radioactive substances, an extremely large number of substances (for example, about 100 types of substances) are discharged. Moreover, the emission amount of each substance differs depending on the time. Therefore, for each substance, the number of particles generated is changed with time according to the amount of substance discharged,
In this way, the moving position of the particle whose number of generated particles is changed is obtained, and the concentration of the substance is calculated from the moving position of the particle. Therefore, in this case, it is necessary to perform 100 kinds of diffusion calculations corresponding to, for example, 100 kinds of substances.

In view of the above-mentioned conventional technique, the present invention predicts and calculates the diffusion state of a substance in a short time even when many kinds of substances are discharged and the discharge amount of each substance changes with time. An object of the present invention is to provide a diffusion state prediction method of a diffusion substance and a diffusion state prediction system of a diffusion substance that can be used.

[0039]

In order to predict the situation in which a substance discharged from an emission source into the atmosphere is diffused in the atmosphere, the method for predicting the diffusion state of a diffused material according to the present invention which solves the above-mentioned problems, The substance is replaced with a large number of particles, and it is set that a preset number of particles are generated from the position of the emission source in each calculation cycle, and the passage of time at a large number of points in the region including the position of the emission source. By substituting the wind velocity field data indicating the wind direction and wind speed that change along the direction of the particle into the diffusion equation that calculates the diffusion state of the particle, the diffusion velocity of each particle is obtained, and the spatial position where each particle exists is determined from this diffusion velocity. The spatial coordinates shown are calculated for each calculation cycle, and the elapsed time after discharge, which is the elapsed time from the time when the particles are first generated, is measured, and the spatial coordinates of each particle in each calculation cycle and after discharge of each particle are measured. Progress Corresponding intervals are recorded in the data recording device, and the emission source for the particles along the elapsed time after the discharge is proportional to the change in the discharged amount with the elapsed time after the discharge of the discharged substance. The intensity data is set, and the spatial coordinates of each particle and the elapsed time after ejection of each particle, which are recorded in the data recording device, are read out, and the readout elapsed time after ejection is referred to. The time at which each particle was generated was calculated, and the emission source intensity of each particle at this time was obtained from the emission source intensity data, and the data recording device recorded the spatial coordinates of each particle in each calculation cycle and the progress after the emission of each particle. Corresponding time and emission source intensity are recorded again, and the concentration of the substance in a predetermined area in a predetermined calculation cycle is the product of emission source intensities of all particles existing in the predetermined area in the predetermined calculation cycle. And obtaining by.

Further, the method for predicting the diffusion state of a diffused substance according to the present invention replaces the substance with a large number of particles in order to predict the state in which the substance discharged into the atmosphere from a plurality of emission sources diffuses in the atmosphere. Then, it is set that a preset number of particles are generated from the position of each emission source for each calculation cycle, and at a number of points in the region including the position of the emission source,
By substituting the wind velocity field data showing the wind direction and wind speed that change over time into the diffusion equation that calculates the diffusion state of particles, the diffusion velocity of each particle is obtained, and each particle exists from this diffusion velocity. The spatial coordinates indicating the spatial position are obtained for each calculation cycle, and the elapsed time after discharge, which is the elapsed time from the time when the particles are first generated, is measured, and the spatial coordinates of each particle and each particle in each calculation cycle. Of the emission amount of a substance emitted from each emission source with the passage of time after emission and the emission source identification information for identifying the emission source in association with each other. Emission source intensity data for particles along the elapsed time after ejection is set in proportion to the change, for each emission source, and each particle for each operation cycle was recorded in the data recording device. sky of Reads the coordinates and time elapsed after the emission of each particle and emission source identification information of each particle, calculated the time at which each particle by referring to the elapsed time after the discharge of the read occurs,
By referring to the read emission source identification information, the emission source intensity of each particle at the time when the particle is generated is obtained from the emission source intensity data corresponding to the emission source where the particle is generated, and is calculated in the data recording device in each calculation cycle. The spatial coordinates of each particle, the elapsed time after discharge of each particle, and the emission source intensity are recorded again, and the concentration of the substance in a predetermined region in a predetermined calculation cycle is the predetermined value in the predetermined calculation cycle. The feature is that it is obtained by integrating the emission source intensities of all particles existing in the region.

In the method of predicting the diffusion state of a diffused substance according to the present invention, the emission source intensity data is set by being obtained by actually measuring the concentration of the substance actually emitted from the emission source, or the emission source intensity. The data is characterized in that it is set based on the time change of the concentration of the substance measured at the observation points around the emission source.

Further, the diffusion status prediction system for diffusing substances according to the present invention is a method for measuring the concentration of diffusing substances and transmitting data indicating the amount of diffusing substances when the diffusing substances are discharged into the atmosphere. , A meteorological data distribution facility that distributes meteorological observation data, a supervisory agency that notifies evacuation advisories to the business operator and residents in the vicinity of the business operator, and a substance in a predetermined area by performing diffusion state prediction calculation processing of diffused matter A safety analysis center for calculating the concentration of the
Meteorological observation data is transmitted from the meteorological data distribution facility by the information transmission means, the concentration of the substance is transmitted from the safety analysis center to the supervisory agency by the information transmission means, and the supervisory agency is transmitted. The feature is that the evacuation recommendation is notified according to the concentration of the substance.

[0043]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described in detail below with reference to the drawings.

<First Embodiment (When There is One Emission Source)> A method of predicting the diffusion state of a diffusing substance according to the first embodiment of the present invention will be described with reference to FIGS. 1 to 10. .

In the first step (see FIG. 1, which is a calculation flow chart) in the first embodiment, the following processing is performed.
That is, even if the amount of substance actually discharged from the emission source S (see FIGS. 2 to 4 showing the diffusion state of particles) is constant, even when the amount of emission changes over time. ,
First, the discharge amount Q (m ³ / sec) of the substance is a constant value (= 1.
As 0), the behavior of particles is numerically calculated using the conventional Lagrangian particle diffusion model. Furthermore, the spatial coordinates (xi (t), yi (t), zi) that are the information that each particle has
In addition to (t)), the post-discharge elapsed time Ti (t), which is the elapsed time from the time when the particles are first generated, is recorded in the data recording device 1 for each calculation cycle Δt.

The process of the first step will be specifically described as follows. In this calculation, the calculation cycle Δt
Twenty particles are generated every (here, Δt = 20 seconds), and the position (spatial coordinate) of the particle P is calculated every calculation cycle Δt (20 seconds).

First, at the start of calculation, the emission source S
From 20 particles P ₀₀ ⁰¹ , P ₀₀ ⁰² , P ₀₀ ⁰³ , P ₀₀ ⁰⁴ , P
₀₀ ⁰⁵ , P ₀₀ ⁰⁶ , P ₀₀ ⁰⁷ , P ₀₀ ⁰⁸ , P ₀₀ ⁰⁹ , P ₀₀ ¹⁰ , P ₀₀
¹¹ , P ₀₀ ¹² , P ₀₀ ¹³ , P ₀₀ ¹⁴ , P ₀₀ ¹⁵ , P ₀₀ ¹⁶ ,
^{_{P 00 17, P 00 18,}} P 00 19, P 00 20 occurs.

20 seconds after the start of calculation,
20 particles P newly from the emission source S shown in 2₂₀ ⁰¹, P₂₀
⁰², P₂₀ ⁰³, P₂₀ ⁰⁴, P₂₀ ⁰⁵, P₂₀ ⁰⁶, P₂₀ ⁰⁷，
P₂₀ ⁰⁸, P ₂₀ ⁰⁹, P₂₀ ^Ten, P₂₀ ¹¹, P₂₀ ¹², P₂₀ ¹³, P
₂₀ ¹⁴, P₂₀ ¹⁵, P₂₀ ¹⁶, P₂₀ ¹⁷, P ₂₀ ¹⁸, P₂₀ ¹⁹, P₂₀
²⁰Occurs. At this time, the grains generated at the start of calculation
Child P₀₀ ⁰¹, P₀₀ ⁰², P₀₀ ⁰³, P₀₀ ⁰⁴, P₀₀ ⁰⁵, P₀₀ ⁰⁶，
P₀₀ ⁰⁷, P₀₀ ⁰⁸, P₀₀ ⁰⁹, P₀₀ ^Ten, P₀₀ ¹¹, P₀₀ ¹², P
₀₀ ¹³, P₀₀ ¹⁴, P₀₀ ¹⁵, P₀₀ ¹⁶, P₀₀ ¹⁷, P₀₀ ¹⁸, P₀₀
¹⁹, P₀₀ ²⁰Reaches a position away from the emission source S
They are spreading together. Each particle P₀₀ ⁰¹~ P₀₀ ²⁰Position is R
AMS (Regional Atmospheric Modeling System)
Using the wind speed field data for every 20 seconds obtained from the
Each particle P in Lagrangian particle diffusion model₀₀ ⁰¹~ P₀₀
²⁰The diffusion rate (u ', v', w ') of
Obtain by moving.

Further, particles P ₀₀ generated at the start of calculation
⁰¹ to P ₀₀ ²⁰ is 20 seconds from the operation start time (the time the particles were first to generate) has elapsed. Therefore, each particle P ₀₀
⁰¹ to P ₀₀ ²⁰ each spatial coordinates (xi (t = 20), yi (t
= 20), zi (t = 20)), and the elapsed time after discharge Ti
(T) = 20 seconds corresponding to each other, the data recording device 1
(See FIG. 1 and FIG. 2).

40 seconds after the start of calculation,
20 particles P newly from the emission source S shown in FIG.₄₀ ⁰¹, P₄₀
⁰², P₄₀ ⁰³, P₄₀ ⁰⁴, P₄₀ ⁰⁵, P₄₀ ⁰⁶, P₄₀ ⁰⁷，
P₄₀ ⁰⁸, P ₄₀ ⁰⁹, P₄₀ ^Ten, P₄₀ ¹¹, P₄₀ ¹², P₄₀ ¹³, P
₄₀ ¹⁴, P₄₀ ¹⁵, P₄₀ ¹⁶, P₄₀ ¹⁷, P ₄₀ ¹⁸, P₄₀ ¹⁹, P₄₀
²⁰Occurs. At this time, the grains generated at the start of calculation
Child P₀₀ ⁰¹, P₀₀ ⁰², P₀₀ ⁰³, P₀₀ ⁰⁴, P₀₀ ⁰⁵, P₀₀ ⁰⁶，
P₀₀ ⁰⁷, P₀₀ ⁰⁸, P₀₀ ⁰⁹, P₀₀ ^Ten, P₀₀ ¹¹, P₀₀ ¹², P
₀₀ ¹³, P₀₀ ¹⁴, P₀₀ ¹⁵, P₀₀ ¹⁶, P₀₀ ¹⁷, P₀₀ ¹⁸, P₀₀
¹⁹, P₀₀ ²⁰Reaches a position further away from the emission source S
It is spreading further as well. In addition, 2 from the start of calculation
20 particles P generated after 0 seconds₂₀ ⁰¹, P₂₀ ⁰²，
P₂₀ ⁰³, P₂₀ ⁰⁴, P₂₀ ⁰⁵, P₂₀ ⁰⁶, P₂₀ ⁰⁷, P₂₀ ⁰⁸, P
₂₀ ⁰⁹, P₂₀ ^Ten, P₂₀ ¹¹, P₂₀ ¹², P₂₀ ¹³, P₂₀ ¹⁴, P₂₀
¹⁵, P₂₀ ¹⁶, P₂₀ ¹⁷, P₂₀ ¹⁸, P₂₀ ¹⁹, P₂₀ ²⁰Is discharged
It spreads as it reaches a position away from the source S.
Each particle P₀₀ ⁰¹~ P₀₀ ²⁰, P₂₀ ⁰¹~ P₂₀ ²⁰The position of RA
MS (Regional Atmospheric Modeling System) code
Using the wind speed field data obtained every 20 seconds,
Each particle P in the grangian particle diffusion model₀₀ ⁰¹~
P₀₀ ²⁰, P₂₀ ⁰¹~ P₂₀ ²⁰Diffusion rate (u ', v',
w ') is calculated and calculated by moving each particle.
It

Further, particles P ₀₀ generated at the start of calculation
⁰¹ to P ₀₀ ²⁰ is 40 seconds from the operation start time (the time the particles were first to generate) has elapsed. Therefore, each particle P ₀₀
⁰¹ to P ₀₀ ²⁰ each spatial coordinates (xi (t = 40), yi (t
= 40), zi (t = 40)), and the elapsed time after discharge Ti
(T) = 40 seconds corresponding to each other, the data recording device 1
(See FIG. 1 and FIG. 3). The calculation start time from 20 seconds after the particles P ₂₀ ⁰¹ to P ₂₀ ²⁰ The generated 20 seconds from the operation start time (the time the particles were first to generate) has elapsed. Therefore, the spatial coordinates of each particle ^{_{P 20 01 ~P 20 20 (xi}} (t = 40), yi (t = 40), zi (t = 4
0)) and the elapsed time after discharge Ti (t) = 20 seconds are respectively recorded in the data recording device 1 (FIGS. 1 and 3).
reference).

60 seconds after the start of calculation,
20 particles P newly from the emission source S shown in FIG.₆₀ ⁰¹, P₆₀
⁰², P₆₀ ⁰³, P₆₀ ⁰⁴, P₆₀ ⁰⁵, P₆₀ ⁰⁶, P₆₀ ⁰⁷，
P₆₀ ⁰⁸, P ₆₀ ⁰⁹, P₆₀ ^Ten, P₆₀ ¹¹, P₆₀ ¹², P₆₀ ¹³, P
₆₀ ¹⁴, P₆₀ ¹⁵, P₆₀ ¹⁶, P₆₀ ¹⁷, P ₆₀ ¹⁸, P₆₀ ¹⁹, P₆₀
²⁰Occurs. At this time, the grains generated at the start of calculation
Child P₀₀ ⁰¹, P₀₀ ⁰², P₀₀ ⁰³, P₀₀ ⁰⁴, P₀₀ ⁰⁵, P₀₀ ⁰⁶，
P₀₀ ⁰⁷, P₀₀ ⁰⁸, P₀₀ ⁰⁹, P₀₀ ^Ten, P₀₀ ¹¹, P₀₀ ¹², P
₀₀ ¹³, P₀₀ ¹⁴, P₀₀ ¹⁵, P₀₀ ¹⁶, P₀₀ ¹⁷, P₀₀ ¹⁸, P₀₀
¹⁹, P₀₀ ²⁰Reaches a position further away from the emission source S
It is spreading further as well. In addition, 2 from the start of calculation
20 particles P generated after 0 seconds₂₀ ⁰¹, P₂₀ ⁰²，
P₂₀ ⁰³, P₂₀ ⁰⁴, P₂₀ ⁰⁵, P₂₀ ⁰⁶, P₂₀ ⁰⁷, P₂₀ ⁰⁸, P
₂₀ ⁰⁹, P₂₀ ^Ten, P₂₀ ¹¹, P₂₀ ¹², P₂₀ ¹³, P₂₀ ¹⁴, P₂₀
¹⁵, P₂₀ ¹⁶, P₂₀ ¹⁷, P₂₀ ¹⁸, P₂₀ ¹⁹, P₂₀ ²⁰Is discharged
As it reaches further away from the source S, it diffuses further
ing. Also, it occurs 40 seconds after the start of calculation
20 particles P₄₀ ⁰¹, P₄₀ ⁰², P₄₀ ⁰³, P₄₀ ⁰⁴, P
₄₀ ⁰⁵, P₄₀ ⁰⁶, P₄₀ ⁰⁷, P₄₀ ⁰⁸, P₄₀ ⁰⁹, P₄₀ ^Ten, P₄₀
¹¹, P₄₀ ¹², P₄₀ ¹³, P₄₀ ¹⁴, P₄₀ ¹⁵, P₄₀ ¹⁶，
P₄₀ ¹⁷, P₄₀ ¹⁸, P₄₀ ¹⁹, P₄₀ ²⁰Away from the source S
It spreads as it reaches a certain position. Each particle P₀₀ ⁰¹~ P
₀₀ ²⁰, P₂₀ ⁰¹~ P₂₀ ²⁰, P₄₀ ⁰¹~ P₄₀ ²⁰The position of RA
MS (Regional Atmospheric Modeling System) code
Using the wind speed field data obtained every 20 seconds,
Each particle P in the grangian particle diffusion model₀₀ ⁰¹~
P₀₀ ²⁰, P₂₀ ⁰¹~ P₂₀ ²⁰, P₄₀ ⁰¹~ P₄₀ ²⁰Diffusion rate
Calculate (u ', v', w ') and move each particle.
And ask.

Furthermore, particles P ₀₀ generated at the start of calculation
⁰¹ to P ₀₀ ²⁰ is 60 seconds from the operation start time (the time the particles were first to generate) has elapsed. Therefore, each particle P ₀₀
Each spatial coordinate of ^{01 to} P ₀₀ ²⁰ (xi (t = 60), yi (t
= 60), zi (t = 60)), and the elapsed time after discharge Ti
(T) = 60 seconds corresponding to each other, the data recording device 1
(See FIG. 1 and FIG. 4). The calculation start time from 20 seconds after the particles P ₂₀ ⁰¹ to P ₂₀ ²⁰ The generated 40 seconds from the operation start time (the time the particles were first to generate) has elapsed. Therefore, the spatial coordinates of each particle ^{_{P 20 01 ~P 20 20 (xi}} (t = 60), yi (t = 60), zi (t = 6
0)) and the elapsed time after discharge Ti (t) = 40 seconds are associated with each other and recorded in the data recording device 1 (FIGS. 1 and 4).
reference). The calculation starting point particles P ₄₀ ⁰¹ that occurred after 40 seconds to P ₄₀ ²⁰ is 20 seconds from the operation start time (the time the particles were first to generate) has elapsed. Therefore, the respective spatial coordinates (xi (t = 60), y of each particle P ₄₀ ^{01 to} P ₄₀ ²⁰
i (t = 60) and zi (t = 60)) are associated with the elapsed time after ejection Ti (t) = 20 seconds and recorded in the data recording device 1 (see FIGS. 1 and 4).

As described above, the calculation cycle Δt (20 seconds)
20 particles are generated one after another one by one, and the position of the particle in each calculation period Δt (20 seconds), that is, the spatial coordinates (xi (t), yi (t), zi (t)) are calculated. Go. In addition, the elapsed time after discharge T in each calculation cycle Δt
i (t) is measured and recorded in the data recording device 1 one after another in correspondence with the spatial coordinates of each particle in each calculation cycle and the elapsed time after discharge of each particle.

Next, the process of the second step (see FIG. 1) is performed.
This will be specifically described. In the above-mentioned first step, numerical calculation was advanced with the discharge amount Q (m ³ / sec) of the substance being a constant value (= 1.0). However, the actual emission amount of the substance emitted from the emission source S often changes as the post-emission elapsed time Ti (t) elapses, as shown in FIG. Therefore, when the emission amount changes with time in this way,
Data indicating the emission source intensity for the particles along the elapsed time after ejection Ti (t) as shown in FIG. 6 is set in accordance with the change in the emission amount of the substance shown in FIG.

In the emission source intensity data in FIG. 6, for example, when the post-emission elapsed time Ti (t) is 0 seconds, 20 seconds, and 60 seconds, the emission source strengths are 0.3, 0.9, and 0.6, respectively. Become.

Next, the data is recorded in the data recording device 1,
The spatial coordinates of each particle and the elapsed time after discharge Ti (t) of each particle are read for each calculation cycle, and the time after the particle is generated by referring to the elapsed time after discharge Ti (t) of each particle Then, the emission source intensity of each particle at this time is obtained from the emission source intensity data shown in FIG. Furthermore, the spatial coordinates of each particle and the elapsed time after discharge T of each particle are calculated for each calculation cycle.
The i (t) and the emission source intensity are associated with each other and rerecorded in the data storage device 1.

More specifically, the elapsed time after discharge Ti
When (t) is 20 seconds (first operation cycle), the data are the spatial coordinates (xi (t = 20), yi (t = 20) of each particle P ₀₀ ^{01 to} P ₀₀ ^20. , Zi (t = 2
0)) and the post-ejection elapsed time Ti (t) = 20 seconds are recorded correspondingly in the data recording device 1 (see FIG. 2).

Therefore, each particle P₀₀ ⁰¹~ P₀₀ ²⁰Each of the sky
Inter-coordinates (xi (t = 20), yi (t = 20), zi
(T = 20)) and the elapsed time after discharge Ti (t) = 20 seconds
From the current time t = 20 seconds and the elapsed time after discharge
By subtracting Ti (t) = 20 seconds, each particle P₀₀
⁰¹~ P₀₀ ²⁰Elapsed time after discharge Ti
(T) = 0 seconds is calculated. Then, the discharge strength data shown in FIG.
Data, particle P₀₀ ⁰¹~ P ₀₀ ²⁰After discharge when occurs
Emission source intensity 0.3 when elapsed time Ti (t) = 0 seconds
Ask.

[0060] Then, each of the spatial coordinates of each particle _{^{P 00 01 ~P 00 20 (xi}} (t = 20), yi (t = 20), zi (t =
20)), the elapsed time after discharge Ti (t) = 20 seconds, and the emission source intensity 0.3 of each of the particles P ₀₀ ^{01 to} P ₀₀ ²⁰ are recorded again in the data recording device 1.

Further, when the elapsed time after discharge Ti (t) is 40 seconds (second calculation cycle), as data, the spatial coordinates of each particle P ₀₀ ^{01 to} P ₀₀ ²⁰ (xi (t = 4
0), yi (t = 40), zi (t = 40)), the elapsed time after discharge Ti (t) = 40 seconds, and each particle P ₂₀ ⁰¹
Each spatial coordinates of ^{_{~P 20 20 (xi (t =}} 40), yi (t =
40), zi (t = 40)), and the elapsed time after discharge Ti
(T) = 20 seconds is correspondingly recorded in the data recording device 1 (see FIG. 3).

Therefore, each particle P₀₀ ⁰¹~ P₀₀ ²⁰Each space seat
Marks (xi (t = 40), yi (t = 40), zi (t =
40)) and the elapsed time after discharge Ti (t) = 40 seconds
Elapsed time Ti after discharge from the present time t = 40 seconds
By subtracting (t) = 40 seconds, each particle P₀₀ ⁰¹~
P₀₀ ²⁰Elapsed time after discharge Ti (t)
= 0 seconds is calculated. And the emission intensity data shown in FIG.
, Particle P₀₀ ⁰¹~ P₀₀ ²⁰Elapsed after discharge when
Emission source intensity 0.3 when Ti (t) = 0 seconds
It Similarly, each particle P₂₀ ⁰¹~ P₂₀ ²⁰Each spatial coordinate of (xi
(T = 40), yi (t = 40), zi (t = 40))
And the elapsed time after discharge Ti (t) = 20 seconds is read out and
Elapsed time after discharge Ti (t) = 2 from current time t = 40 seconds
By subtracting 0 seconds, each particle P₂₀ ⁰¹~ P₂₀ ²⁰From
Elapsed time after discharge Ti (t) = 20 seconds
Ask. Then, from the emission intensity data shown in FIG.
P₂₀ ⁰¹~ P₂₀ ²⁰Elapsed time after discharging when Ti occurs
The emission source intensity of 0.5 when (t) = 20 seconds is obtained.

Then, each particle P₀₀ ⁰¹~ P₀₀ ²⁰Each space seat
Marks (xi (t = 40), yi (t = 40), zi (t =
40)), and the elapsed time after discharge Ti (t) = 40 seconds,
Particle P₀₀ ⁰¹~ P₀₀ ²⁰Corresponding with the emission source intensity of 0.3
Then, the data is recorded again in the data recording device 1. In addition, each particle P₂₀ ⁰¹
~ P₂₀ ²⁰Each spatial coordinate of (xi (t = 40), yi (t =
40), zi (t = 40)), and the elapsed time after discharge Ti
(T) = 20 seconds and each particle P₂₀ ⁰¹~ P₂₀ ²⁰Source strength of
Re-record in the data recording device 1 in correspondence with 0.5
It

When the elapsed time after discharge Ti (t) is 60 seconds (third calculation cycle), the data of each space coordinate of each particle P ₀₀ ^{01 to} P ₀₀ ²⁰ (xi (t = 6
0), yi (t = 60 ), and zi (t = 60)), the elapsed time after the discharge Ti (t) = 60 seconds, and each particle P ₂₀ ⁰¹ ~
Each spatial coordinate of P ₂₀ ²⁰ (xi (t = 60), yi (t = 6)
0), zi (t = 60)), and the elapsed time after discharge Ti
(T) = 40 seconds, and the spatial coordinates (xi (t = 60), yi (t = 60), zi of each of the particles P ₄₀ ^{01 to} P ₄₀ ^20.
(T = 60)) and the elapsed time after discharge Ti (t) = 20
Seconds are correspondingly recorded in the data recording device 1 (see FIG. 4).

Therefore, each particle P₀₀ ⁰¹~ P₀₀ ²⁰Each space seat
Marks (xi (t = 60), yi (t = 60), zi (t =
60)) and the elapsed time after discharge Ti (t) = 60 seconds
From the present time t = 60 seconds, and the elapsed time after discharge Ti
By subtracting (t) = 60 seconds, each particle P₀₀ ⁰¹~
P₀₀ ²⁰Elapsed time after discharge Ti (t)
= 0 seconds is calculated. And the emission intensity data shown in FIG.
, Particle P₀₀ ⁰¹~ P₀₀ ²⁰Elapsed after discharge when
Emission source intensity 0.3 when Ti (t) = 0 seconds
It Similarly, each particle P₂₀ ⁰¹~ P₂₀ ²⁰Each spatial coordinate of (xi
(T = 60), yi (t = 60), zi (t = 60))
And the elapsed time after discharge Ti (t) = 40 seconds is read out and
Elapsed time after discharge Ti (t) = 4 from current time t = 60 seconds
By subtracting 0 seconds, each particle P₂₀ ⁰¹~ P₂₀ ²⁰From
Elapsed time after discharge Ti (t) = 20 seconds
Ask. Then, from the emission intensity data shown in FIG.
P₂₀ ⁰¹~ P₂₀ ²⁰Elapsed time after discharging when Ti occurs
The emission source intensity of 0.5 when (t) = 20 seconds is obtained. same
Each particle P₄₀ ⁰¹~ P₄₀ ²⁰Each spatial coordinate of (xi (t =
60), yi (t = 60), zi (t = 60))
Elapsed time after exiting Ti (t) = 20 seconds is read out and the current time is
From the time t = 60 seconds, the elapsed time after discharge Ti (t) = 20 seconds
By subtracting, each particle P₄₀ ⁰¹~ P₄₀ ²⁰There has occurred
Calculate the elapsed time after discharge Ti (t) = 40 seconds
It Then, from the emission intensity data shown in FIG.₄₀
⁰¹~ P₄₀ ²⁰Elapsed time Ti (t) after discharge when occurs
The emission source intensity 0.9 at 40 seconds is calculated.

Then, each particle P₀₀ ⁰¹~ P₀₀ ²⁰Each space seat
Marks (xi (t = 60), yi (t = 60), zi (t =
60)) and the elapsed time after discharge Ti (t) = 60 seconds,
Particle P₀₀ ⁰¹~ P₀₀ ²⁰Corresponding with the emission source intensity of 0.3
Then, the data is recorded again in the data recording device 1. In addition, each particle P₂₀ ⁰¹
~ P₂₀ ²⁰Each spatial coordinate of (xi (t = 60), yi (t =
60), zi (t = 60)) and the elapsed time Ti after discharge
(T) = 40 seconds and each particle P₂₀ ⁰¹~ P₂₀ ²⁰Source strength of
Re-record in the data recording device 1 in correspondence with 0.5
It In addition, each particle P₄₀ ⁰¹~ P₄₀ ²⁰Each spatial coordinate of (xi (t
= 60), yi (t = 60), zi (t = 60)),
Elapsed time after discharge Ti (t) = 20 seconds and each particle P₄₀ ⁰¹~
P₄₀ ²⁰Record the data by correlating with the emission source intensity of 0.9
Rerecord on device 1.

In the subsequent calculation cycles as well, similar processing calculations are carried out, and each spatial coordinate of each particle and the elapsed time after discharge Ti
Corresponding (t) and the emission source intensity of each particle are recorded again in the data recording device.

Next, the processing of the third step (see FIG. 1) is performed.
This will be specifically described. For example, the elapsed time after discharge Ti (t)
= 120 seconds, the emission source S as shown in FIG.
In order to calculate the concentration of the substance in a predetermined lattice area (unit space having a unit volume) I, J, K that is a predetermined distance away from the data recording device 1, the elapsed time after discharge Ti
The particles existing in this lattice region at (t) = 120 seconds are read out. When particles are present as shown in FIG. 7 when read out, the concentration of the substance in this unit space can be calculated by integrating the emission source strengths of these particles.

That is, in the lattice region shown in FIG. 7, four particles P ₀₀ ⁰¹ , P ₀₀ ⁰⁵ , whose intensity is 0.3,
P ₀₀ ^10, P ₀₀ ²⁰ and the strength of 0.5 and going on three particles ^{_{P 20 01, P 20 07,}} P 20 17 and intensity 0.9 and going on two particles P ₄₀ ^08, P ₄₀ ¹⁰ and one particle P ₆₀ ¹⁷ having an intensity of 0.6 is present. Therefore, by integrating the emission source intensity of these particles as follows,
The concentration of the substance in this unit space can be calculated as 5.1. (0.3 × 4) + (0.5 × 3) + (0.9 × 2) +
(0.6 × 1) = 5.1

The following is a general (mathematical) description of the first embodiment described above. In the first embodiment, as shown in FIG.
When gas is being discharged, the substance concentration (gas concentration) in the leeward lattice areas I, J, K of the emission source S is predicted according to the time change. Moreover, as shown in FIG. 9A, when the discharge amount Q of the substance is constant,
As shown in FIG. 10B, it is of course possible to predictively calculate the concentration time change of the lattice regions I, J, and K, and FIG.
Emission q
Even in the case of (t), as shown in FIG. 10B, it is possible to predictively calculate the change over time in the density of the lattice area.

In the first embodiment, first, even if the amount of substance actually discharged from the emission source S is constant or the amount of substance discharged changes with time, the substance Using the conventional Lagrangian particle diffusion model, with the discharge amount Q (m ³ / sec) as a constant value (= 1.0), the substance is replaced with particles, and N particles are generated from the emission source S every second. , The behavior of each particle is numerically calculated to obtain the spatial coordinates (xi (t), yi (t), zi (t)) indicating the position of the particle. Furthermore, the spatial coordinates (xi
In addition to (t), yi (t), zi (t)), the post-discharge elapsed time Ti (t), which is the elapsed time from the time when the particles are first generated, is calculated for each calculation cycle Δt. Record on the recording device. Thereby, the conventional Lagrangian particle diffusion model can be used to measure the time change of the concentration distribution corresponding to all the time-varying discharge amount q (t).

To this end, data indicating the emission source intensity for particles along the elapsed time after ejection Ti (t), which is proportional to the amount q (t) of the substance that changes with time, is set. Then, at a certain time (t), spatial coordinates (xi (t), yi (t), zi indicating the position of each particle are shown.
(T)) and the elapsed time after discharge Ti (t) are read from the data storage device.

When the discharge amount is constant (Q = 1.0), the emission source intensity of each particle is Q / N (m ³ ) = 1 / N,
When the emission amount q (t) changes with time, the emission source intensity of each particle is q (t-Ti) / N (m ³ ).

Again, in addition to the spatial coordinates (xi (t), yi (t), zi (t)), which are the information that each particle has, the elapsed time after discharge Ti (t) and the emission source intensity qi of each particle.
(T-Ti) / N (m ³ ) is re-recorded in the data recording device at each time (t).

In this embodiment using the Lagrangian particle model, the elapsed time after discharge, and the emission source intensity q (t-Ti) / N (m ³ ) corresponding to the emission amount q (t) which changes with time, Since the emission source intensity of each particle in the unit volume in the space (= air 1 m ³ ) is different, the emission source intensity qi of each particle
Σqi (t−T) obtained by integrating (t−Ti) / N (m ³ ).
i) / N (m ³ ) is the amount of gas present in this unit volume. Therefore, the gas concentration in this space is Σqi (t-
Ti) / N (m ³ ) / N (gas m ³ / air m ³ ).

<Second embodiment (when there are a plurality of emission sources)> There are a plurality of emission sources (j), and substances from different emission sources have different emission amounts (qj (t)) that change with time. Is discharged, the La used in the first embodiment
By providing each particle with emission source identification information (si) in addition to the particle information (position, elapsed time after release) of the grangian particle diffusion model, it is possible to exhibit the same function as in the first embodiment. Becomes

For example, as shown in FIG. 11, when there are two emission sources S1 and S2, the particles emitted from the emission source S1 have emission source identification information s1 and are emitted from the emission source S2. The particles have emission source identification information s2. Then, using the Lagrangian particle diffusion model, the substance is replaced with particles, N particles are generated from each of the emission sources S1 and S2 each second, and the behavior of each particle is numerically calculated to show the position of the particle. Coordinates (xi (t), yi (t), zi
(T)) is calculated. Furthermore, in addition to the spatial coordinates (xi (t), yi (t), zi (t)) that are the information that each particle has, the post-discharge elapsed time Ti that is the elapsed time from the time when the particle is first generated. (T) and the emission source identification information s1 or s2.

As shown in FIG. 12 (a), the emission sources S1,
Using the conventional Lagrangian particle diffusion model, assuming that the discharge amount Q discharged from S2 is constant (= 1), the concentration time change of the substance in the lattice regions I, J, and K as shown in FIG. Seek and record.

Next, assuming that the emission amount of the substance emitted from the emission source S1 is q1 (t) which changes with time as shown by the dotted line in FIG. 13 (a), it is emitted from this emission source S1. For the particles, the emission source intensity of the particles is set to q1 (t) by the same method as in the first embodiment. Then, for each particle, the emission source intensity q1 at the time when the particle is generated
The emission source intensity is set with reference to (t). As a result,
Emission source identification information s in the desired grid area I, J, K
By accumulating the emission source intensities of the particles having 1, it is possible to obtain the time change of the concentration of the substance discharged from the emission source S1 (the substance concentration in the lattice areas I, J, and K to be obtained).

Similarly, assuming that the emission amount of the substance emitted from the emission source S2 is q2 (t), the particles emitted from this emission source S2 can be obtained by the same method as in the first embodiment. Let the emission source intensity of particles be q2 (t). Then, for each particle, the emission source intensity is set with reference to the emission source intensity q2 (t) at the time when the particle is generated. As a result, the concentration of the substance discharged from the emission source S2 (the obtained lattice regions I, J, K is calculated by integrating the emission source intensities of the particles having the emission source identification information s2 in the obtained lattice regions I, J, K). It is possible to obtain the change over time in the substance concentration).

In this way, by adding the time change of the concentration of the substance discharged from the emission source S1 and the time change of the concentration of the substance discharged from the emission source S2, the lattice areas I, J, The concentration of the substance in K can be determined.

<Third Embodiment> In the third embodiment, for example, after a gas leakage accident occurs, the current and future concentration distributions can be obtained in a short time based on the measurement result of the gas discharge amount. It is a method of calculating.

The diffusion calculation such as the environmental assessment does not require the calculation result urgently. Therefore, after determining the gas emission amount q (t) which changes over time, the time from several days to several months can be obtained. Prediction calculation of the gas diffusion situation is carried out by multiplying. However, in an emergency such as a gas leak accident,
Since it is necessary to take urgent countermeasures against the surrounding residents, it is necessary to output the diffusion calculation result in the shortest possible time.

In such a case, based on the three-dimensional spatial wind velocity distribution at each time, as shown in FIGS. 14 (a), (b) and (c), the same Lagrangian particle diffusion model as in the first embodiment is used. Diffusion calculation with a constant release rate (Q = 1) is performed continuously for 24 hours.

After the occurrence of the gas leakage accident, the measured gas discharge amount q (t) is measured by a gas concentration measuring device or the like installed at the exit of the chimney which is the discharge source. This measured gas emission amount q
By setting the emission source intensity q (t) of each particle according to (t), the concentration-time change corresponding to this gas emission amount can be corrected and calculated by the same method as in the first embodiment. It is possible (see FIGS. 14D and 14E). That is, for each particle, the emission source intensity is set by referring to the emission source intensity q (t) at the time when the particle is generated (FIG. 14 (d)). Then, in the lattice areas I, J, and K to be obtained, the emission source intensities of particles existing in the area are integrated to obtain the concentration of the substance discharged from the emission source S (the lattice areas I, J, and
The time change of the substance concentration at K) can be obtained.

The future gas emission amount is equivalent to the current measured gas emission amount q (t), or is calculated based on a separately set prediction formula.

As a method for calculating the present and future three-dimensional spatial wind speed distribution, wide area grid (20 km) meteorological data (GPV: Grid Poi
nt Value) to use the wide area weather prediction model (RAM
There is a method of calculating the time change of the weather data (wind direction, wind speed, temperature) of the detailed grid (several kilometers to several tens of meters) using S, MM5, etc.

<Fourth Embodiment> In the fourth embodiment, for example, after the occurrence of a gas leakage accident, the current amount of gas discharged can be calculated in a short time based on the concentration measurement result around the leakage point. It is a method of calculating.

In the event of a gas leak accident, FIG.
Emission amount q from the gas leakage source S which is the emission source shown in (a)
It is often difficult to measure (t). In such a case, the concentration (ck (t)) actually measured at the leakage point peripheral observation point (xk)
Observation), the Lagrangian of the first embodiment
The emission amount q (t) can be estimated in a short time using the particle diffusion model.

Before the occurrence of the leakage accident, La of the first embodiment
Using the grangian particle diffusion model, constant emissions (Q =
1) (see FIG. 15B), a certain peripheral observation point (xk)
Concentration (Ck (t) calculation) is calculated (FIG. 15)
(See (c)).

This concentration (Ck (t) calculation) is a three-dimensional spatial volume (Δx × Δy × Δ) centered on the observation point (xk).
It is calculated by the following formula (10) from the particles (n particles) present in z).

Ck (t) calculation = n × ΣQ (t−Ti) / N / (Δx × Δy × Δz) (10) In this case, the discharge amount Q (t-Ti) is a constant value (= 1). Is.

Next, the concentration time change (C) at the observation point (xk)
When k (t) observation is measured, the equation (10) is used to obtain the equation (11).

[0094] (Ck (t) observation) = n0 × Σq0 (t−0) / N / (Δx × Δy × Δz)               + N1 × Σq1 (t−ΔT) / N / (Δx × Δy × Δz)               + N2 × Σq2 (t−2 · ΔT) / N / (Δx × Δy × Δz)               + N3 × Σq3 (t−3 · ΔT) / N / (Δx × Δy × Δz)               + N4 × Σq4 (t−4 · ΔT) / N / (Δx × Δy × Δz)               + ...               + Nl × Σql (t−t) / N / (Δx × Δy × Δz)               + C0 (t) (11)

Here, n1, n2, n3, and nl are
0 seconds before, ΔT seconds before, (ΔT × 2) seconds before,
Particles emitted (ΔT × 3) seconds before and t seconds before, and the three-dimensional spatial volume (Δx × Δy ×) centered at the observation point (xk)
The total number of particles present in Δz). Also, C0
(T) is called a background concentration, is a concentration released from sources other than the emission source to be calculated and exists regardless of the observation point, and changes with a constant value or time t. q0, q1, q2, q3, and ql are 0 seconds before the t seconds, ΔT seconds before, (ΔT × 2) seconds before, (ΔT × 3) seconds before, and t (= ΔT × 1) seconds before Is the rate.

Since the Ck (t) observation is continuously measured for 24 hours, 0 seconds after the leak start time, ΔT seconds later,
After (ΔT × 2) seconds, after (ΔT × 3) seconds and t (= ΔT)
It is possible to measure (1 + 1) or more until after x1) seconds. If there are k observation points xk, k ×
It is possible to obtain (1 + 1) observation data.

The unknowns in equation (11) are q0, q1, q2,
Since there are k × (1 + 1) or more (1 + 1) known observations of q3 and ql and Ck (t) observations, the unknown number is less than the known number. In this case, the least squares method can be used to determine the unknown numbers q0, q1, q2, q3, and ql so that the least squares error for the observed concentration Ck (t) observation is minimized. Note that FIG. 16 is a flow chart showing the calculation state of the fourth embodiment.

<Fifth Embodiment> In the fifth embodiment, for example, after the occurrence of a gas leakage accident, the current amount of gas discharged can be calculated in a short time based on the result of actual measurement of the concentration around the leakage point. This is a method of estimating and calculating the concentration distribution.

According to the fourth embodiment, the Lagrangian particle diffusion model of the first embodiment is used from the time variation of the concentration (Ck (t) observation) actually measured at the leakage point peripheral observation point (xk). The emission amount q (t) can be estimated in a short time.

As shown in FIG. 17, before a leakage accident occurs,
Using the Lagrangian particle diffusion model of the first embodiment, at a constant emission rate (Q = 1), a certain peripheral observation point (xk)
The concentration (calculation of Ck (t)) of is calculated.

This concentration (Ck (t) calculation) is a three-dimensional space volume (Δx × Δy × Δ) centered on the observation point (xk).
It is calculated by the following formula (12) from the particles (n particles) present in z). Ck (t) calculation = n × ΣQ (t−Ti) / N / (Δx × Δy × Δz) (12) In this case, the release rate Q (t-Ti) is a constant value (= 1).

Next, when the change with time of concentration ((Ck (t) observation) at the observation point (xk) is measured, the equation (13) is obtained by using the equation (12).

[0103] (Ck (t) observation) = n0 × Σq0 (t−0) / N / (Δx × Δy × Δz)               + N1 × Σq1 (t−ΔT) / N / (Δx × Δy × Δz)               + N2 × Σq2 (t−2 · ΔT) / N / (Δx × Δy × Δz)               + N3 × Σq3 (t−3 · ΔT) / N / (Δx × Δy × Δz)               + N4 × Σq4 (t−4 · ΔT) / N / (Δx × Δy × Δz)               + ...               + Nl × Σql (t−t) / N / (Δx × Δy × Δz)               + C0 (t) (13)

Here, n1, n2, n3, and nl are
0 seconds before, ΔT seconds before, (ΔT × 2) seconds before,
Particles emitted (ΔT × 3) seconds before and t seconds before, and the three-dimensional spatial volume (Δx × Δy ×) centered at the observation point (xk)
The total number of particles present in Δz). Also, C0
(T) is called a background concentration, which is a concentration that is discharged to the sky except for the emission source to be calculated and exists regardless of the observation point, and changes with a constant value or with time t.
q0, q1, q2, q3, and ql are 0 seconds before the t seconds, ΔT seconds before, (ΔT × 2) seconds before, (ΔT × 3) seconds before, and t (= ΔT × 1) seconds before Is the rate.

Since the Ck (t) observation is continuously measured for 24 hours, 0 seconds after the leak start time, ΔT seconds later,
After (ΔT × 2) seconds, after (ΔT × 3) seconds and t (= ΔT)
It is possible to measure (1 + 1) or more until after x1) seconds. If there are k observation points xk, k ×
It is possible to obtain (1 + 1) observation data.

The unknowns in equation (13) are q0, q1, q2,
Since there are k × (1 + 1) or more (1 + 1) known observations of q3 and ql and Ck (t) observations, the unknown number is less than the known number. In this case, the least squares method can be used to determine the unknown numbers q0, q1, q2, q3, and ql so that the least squares error for the observed concentration Ck (t) observation is minimized.

These estimated values q0, q1, q2, q3 and q
By using l to perform the correction calculation of the concentration time change by the method of the first embodiment, the concentration distribution for each elapsed time can be calculated.

<Sixth Embodiment> In the sixth embodiment, after the gas leakage accident, the current and future concentration distribution calculation results are provided on the Internet in a short time based on the emission amount measurement result. It is a system that does.

In the event of an emergency such as a gas leak accident, it is necessary to take emergency measures for the evacuation of residents in the surrounding area. Therefore, it is necessary to output the diffusion calculation result in the shortest possible time. However, since it is not known when such a leakage accident will occur, it is necessary to manage and operate the computer system for this purpose at the fire department, which is the supervisory agency, the police, the local government and each factory which is a business operator, for this purpose. .

Since this management operation requires a great deal of labor and cost and sophisticated computer operation technology, it is difficult to perform the management operation except for an organization that permanently installs a large-scale crisis management system.

As a method of compensating for this problem, a recent information providing system utilizing the Internet has been devised.

In the sixth embodiment, as shown in FIG. 18, safety is provided in a place different from the supervisory authorities 10 such as fire authorities, police and local governments, which are the supervisory authorities, and each factory 11 which is a business operator. The analysis center 12 is installed. The safety analysis center 12 receives the weather observation data distributed from a weather data distribution facility such as the Meteorological Agency 13 via an information transmission means such as the Internet, and normally performs calculation by using a large-sized computer. Based on the three-dimensional spatial wind velocity distribution of time, the same Lagrangian particle diffusion model as in the first embodiment is used to continuously perform diffusion calculation with a constant release rate (Q = 1) for 24 hours.

After the occurrence of the gas leakage accident, if the measured gas release amount q (t) is known from the gas concentration measuring device installed at the smoke outlet of the business operator 11, this gas release amount q (t)
Is transmitted to the safety analysis center 12 via information transmission means such as the Internet. Then, the safety analysis center 12 can correct and calculate the concentration time change corresponding to the gas release rate by the same method as in the first embodiment.

The safety analysis center 12 transmits the calculated concentration calculation result to the supervisory authorities 10 such as fire departments, police and local governments. The supervisory authority 10 gives an evacuation recommendation to the business operator 11 and the residents 14 around the factory according to the concentration.

The future gas release rate q is equivalent to the currently measured gas release rate q (t), or separately.
Calculate based on the prediction formula that is set. When there are a plurality of businesses 11, the safety analysis center 12 predicts the concentration-time change by performing the calculation shown in the second embodiment.

As a method of calculating the present and future three-dimensional spatial wind speed distribution, the meteorological observation data (GPV:
GridPoint Value) is used to create a detailed grid (several kilometers to several tens) in a wide-area weather prediction model (RAMS, MM5, etc.).
There is a method to calculate the time change of meteorological data (wind direction, wind speed, temperature) in m).

[0117]

As described above in detail with the embodiments, in the method of predicting the diffusion state of a diffusing substance according to the present invention, the situation in which the substance discharged from the emission source into the atmosphere diffuses in the atmosphere In order to predict the above, the substance is replaced with a large number of particles, and it is set that a preset number of particles are generated from the position of the emission source for each calculation cycle, and a large number of points in the region including the position of the emission source are set. In, the wind velocity field data showing the wind direction and wind speed that change with the passage of time are substituted into the diffusion equation that calculates the diffusion state of the particles, and the diffusion velocity of each particle is obtained. The spatial coordinates indicating the existing spatial position are obtained for each calculation cycle, and the elapsed time after discharge, which is the elapsed time from the time when the particles are first generated, is measured, and the spatial coordinates of each particle in each calculation cycle are Correspondingly record the elapsed time after discharge of the particles in the data recording device, and make it proportional to the change in the discharge amount with the passage of time after discharge of the discharged substance, and Emission source intensity data for particles along the line are set, and the spatial coordinates of each particle and the elapsed time after ejection of each particle, which are recorded in the data recording device, are read out, and the read progress after ejection is also read out. The time when each particle is generated is determined with reference to time, the emission source intensity of each particle at this time is obtained from the emission source intensity data, and the data recording device stores the spatial coordinates of each particle and each of the calculation cycles. The elapsed time after discharge of the particles and the emission source intensity are made to correspond to each other and re-recorded, and the concentration of the substance in the predetermined area in the predetermined calculation cycle is determined by all the particles existing in the predetermined area in the predetermined calculation cycle. It was to seek by integrating the emission source strength. Therefore, even if the amount discharged from the emission source is different, the concentration of the substance in the specific region can be calculated in a short time.

In addition, the method for predicting the diffusion state of a diffused substance of the present invention replaces the substance with a large number of particles in order to predict the state in which a substance discharged into the atmosphere from a plurality of emission sources diffuses in the atmosphere. Then, it is set that a preset number of particles are generated from the position of each emission source for each calculation cycle, and at a number of points in the region including the position of the emission source,
By substituting the wind velocity field data showing the wind direction and wind speed that change over time into the diffusion equation that calculates the diffusion state of particles, the diffusion velocity of each particle is obtained, and each particle exists from this diffusion velocity. The spatial coordinates indicating the spatial position are obtained for each calculation cycle, and the elapsed time after discharge, which is the elapsed time from the time when the particles are first generated, is measured, and the spatial coordinates of each particle and each particle in each calculation cycle. Of the emission amount of a substance emitted from each emission source with the passage of time after emission and the emission source identification information for identifying the emission source in association with each other. Emission source intensity data for particles along the elapsed time after ejection is set in proportion to the change, for each emission source, and each particle for each operation cycle was recorded in the data recording device. sky of Reads the coordinates and time elapsed after the emission of each particle and emission source identification information of each particle, calculated the time at which each particle by referring to the elapsed time after the discharge of the read occurs,
By referring to the read emission source identification information, the emission source intensity of each particle at the time when the particle is generated is obtained from the emission source intensity data corresponding to the emission source where the particle is generated, and is calculated in the data recording device in each calculation cycle. The spatial coordinates of each particle, the elapsed time after discharge of each particle, and the emission source intensity are recorded again, and the concentration of the substance in a predetermined region in a predetermined calculation cycle is the predetermined value in the predetermined calculation cycle. It was determined by integrating the emission source intensities of all the particles existing in the region. Therefore, the concentration of the substance in the specific region can be calculated in a short time even if the amount emitted from the emission source is different. Further, even if the substance is emitted from a plurality of emission sources, the concentration of the substance can be accurately calculated.

In the method for predicting the diffusion state of diffused substances according to the present invention, the emission source intensity data is set by being obtained by actually measuring the concentration of the substance actually emitted from the emission source, or the emission source intensity. The data is set based on the time change of the concentration of the substance measured at the observation points around the emission source. Therefore, even if the concentration data of the substance discharged from the emission source is not obtained in advance, the concentration can be calculated using the actually measured data.

Further, the diffusion status prediction system for diffusing substances according to the present invention is designed so that when the diffusing substance is discharged into the atmosphere, it measures the concentration of the diffusing substance and transmits data indicating the amount of the diffusing substance discharged. , A meteorological data distribution facility that distributes meteorological observation data, a supervisory agency that notifies evacuation advisories to the business operator and residents in the vicinity of the business operator, and a substance in a predetermined area by performing diffusion state prediction calculation processing of diffused matter A safety analysis center for calculating the concentration of the
Meteorological observation data is transmitted from the meteorological data distribution facility by the information transmission means, the concentration of the substance is transmitted from the safety analysis center to the supervisory agency by the information transmission means, and the supervisory agency is transmitted. The evacuation advisory is notified according to the concentration of the substance. Therefore, the supervisory authority can promptly issue evacuation advice based on the information calculated by the safety analysis center, and urgent measures can be taken for the evacuation of the surrounding residents.

[Brief description of drawings]

FIG. 1 is a flowchart showing a calculation flow in a first embodiment of the present invention.

FIG. 2 is an explanatory diagram showing a diffusion state of particles according to the first embodiment of the present invention.

FIG. 3 is an explanatory diagram showing a diffusion state of particles according to the first embodiment of the present invention.

FIG. 4 is an explanatory diagram showing a diffusion state of particles according to the first embodiment of the present invention.

FIG. 5 is a characteristic diagram showing an example of a change over time in the discharge amount of a substance.

FIG. 6 is a characteristic diagram showing an example of an emission source intensity corresponding to a time-dependent change of a substance emission amount.

FIG. 7 is an explanatory diagram showing a particle distribution in a predetermined lattice area.

FIG. 8 is an explanatory diagram showing an emission source and a lattice area.

FIG. 9 is a characteristic diagram showing the relationship between the discharge amount and the concentration when the discharge amount is constant.

FIG. 10 is a characteristic diagram showing the relationship between the discharge amount and the concentration when the discharge amount changes with time.

FIG. 11 is an explanatory diagram showing two emission sources and a lattice area.

FIG. 12 is a characteristic diagram showing the relationship between the discharge amount and the concentration when the discharge amount is constant.

FIG. 13 is a characteristic diagram showing the relationship between the discharge amount and the concentration when the discharge amount changes with time.

FIG. 14 is an explanatory diagram showing a third embodiment.

FIG. 15 is an explanatory diagram showing a fourth embodiment.

FIG. 16 is a flowchart showing a calculation flow in the fourth embodiment.

FIG. 17 is a flowchart showing a calculation flow in the fifth embodiment.

FIG. 18 is a system configuration diagram showing a system according to a sixth embodiment.

FIG. 19 is an explanatory diagram showing a diffusion state of particles in a conventional technique.

FIG. 20 is an explanatory diagram showing a diffusion state of particles in a conventional technique.

FIG. 21 is an explanatory diagram showing a diffusion state of particles in a conventional technique.

FIG. 22 is an explanatory diagram showing a particle distribution in a predetermined lattice area.

FIG. 23 is an explanatory diagram showing the function of a particle diffusion model.

FIG. 24 is an explanatory diagram showing an emission source and a lattice area.

FIG. 25 is a characteristic diagram showing the relationship between the discharge amount and the concentration when the discharge amount changes with time.

FIG. 26 is a characteristic diagram showing the relationship between the discharge amount and the concentration when the discharge amount is constant.

FIG. 27 is a characteristic diagram showing the relationship between the discharge amount and the concentration when the discharge amount is instantaneous.

[Explanation of symbols]

1 Data recording device 10 supervisory authorities 11 businesses 12 Safety Analysis Center 13 Meteorological Agency 14 Residents around the factory S, S1, S2 emission source

Claims (5)

[Claims] 1. In order to predict a situation in which a substance discharged from an emission source into the atmosphere diffuses in the atmosphere, the substance is replaced with a large number of particles, and the position of the emission source is used in advance for each calculation cycle. In addition to setting that a set number of particles will be generated, at a number of points in the region including the position of the emission source, the wind speed field data showing the wind direction and wind speed that change over time are calculated, and the diffusion state of particles is calculated. By calculating the diffusion velocity of each particle by substituting into the diffusion equation, the spatial coordinates indicating the spatial position where each particle exists from this diffusion velocity are calculated for each calculation cycle, and the point of time when the particle is first generated. The elapsed time after discharge, which is the elapsed time from, is measured and recorded in the data recording device in association with the spatial coordinates of each particle in each calculation cycle and the elapsed time after discharge of each particle. Follow-up In proportion to the change in the emission amount with the passage of time, the emission source intensity data for the particles along the passage of time after the emission is set in advance, and is recorded in the data recording device for each calculation cycle. The spatial coordinates of each particle and the elapsed time after discharge of each particle are read, and the time when each particle is generated is obtained by referring to the read elapsed time after discharge, and the emission source strength of each particle at this time is determined by the emission source. Obtained from the intensity data, the data recording device is re-recorded in association with the spatial coordinates of each particle in each calculation cycle, the elapsed time after discharge of each particle, and the emission source strength, and a predetermined area in a predetermined calculation cycle. The diffusion state prediction method of a diffusion substance, wherein the concentration of the substance is obtained by integrating emission source intensities of all particles existing in the predetermined region in the predetermined calculation cycle. 2. In order to predict a situation in which a substance discharged into the atmosphere from a plurality of emission sources diffuses in the atmosphere, the substance is replaced with a large number of particles, and the calculation cycle is calculated from the position of each emission source. Each time a preset number of particles are generated, the wind speed field data showing the wind direction and wind speed that change over time at many points in the area including the position of the emission source are collected. By substituting into the diffusion equation for computing the diffusion state, the diffusion velocity of each particle is determined, and the spatial coordinates indicating the spatial position where each particle exists from this diffusion velocity are determined for each computation cycle, and the particle is first analyzed. The elapsed time after discharge, which is the elapsed time from the time of generation, is measured, and the spatial coordinates of each particle in each calculation cycle are associated with the elapsed time after discharge of each particle and the emission source identification information for identifying the emission source. data Emission source intensity data for particles that are recorded in a recording device and are proportional to the change in the emission amount of the substance emitted from each emission source with the passage of time after the emission. Is set for each emission source, and the spatial coordinates of each particle, the elapsed time after ejection of each particle, and the emission source identification information of each particle recorded in the data recording device are read out. At the same time, the time when each particle is generated is obtained by referring to the read elapsed time after discharge, and the emission source intensity of each particle at the time when the particle is generated is referred to by referring to the read emission source identification information. It is determined from the emission source intensity data corresponding to the emission source, and the data recording device is caused to re-record the spatial coordinates of each particle for each calculation cycle, the elapsed time after emission of each particle, and the emission source intensity in a predetermined manner, In the calculation cycle The diffusion state prediction method for a diffused substance, wherein the concentration of the substance in a predetermined region in the predetermined region is obtained by integrating emission source intensities of all particles existing in the predetermined region in the predetermined calculation cycle. 3. The diffused substance according to claim 1 or 2, wherein the emission source intensity data is set by being obtained by actually measuring a concentration of a substance actually emitted from the emission source. Method for predicting the diffusion status of. 4. The diffusion according to claim 1 or 2, wherein the emission source intensity data is set based on a temporal change in the concentration of the substance measured at an observation point around the emission source. A method for predicting the diffusion status of substances. 5. When the diffusing substance is discharged into the atmosphere,
Evacuation advice to businesses that measure the concentration of diffused substances and transmit data that shows the amount of diffused substances emitted, weather data distribution facilities that distribute meteorological observation data, and the businesses and residents around them It is provided with a supervisory agency for notifying, and a safety analysis center for calculating the concentration of a substance in a predetermined area by performing the calculation process according to claim 1 or 2, wherein the safety analysis center detects a substance diffused from the operator. The data indicating the emission amount, the weather observation data from the weather data distribution facility is transmitted by the information transmission means, the concentration of the substance from the safety analysis center is transmitted to the regulatory agency by the information transmission means, The government agency notifies the evacuation recommendation according to the concentration of the transmitted substance.