WO2016101905A1 - Volcanic ash diffusion prediction method and apparatus, and early warning method and apparatus - Google Patents

Abstract

Provided are a volcanic ash diffusion prediction method and apparatus and early warning method and apparatus. The method comprises: obtaining wind speed and direction of each of spatial layers stratified according to height (S101); on the basis of wind speed and direction of a preset spatial layer, calculating the atmospheric diffusion function of a volcanic ash particle having a preset particle diameter in the spatial layer (S102); on the basis of the atmospheric diffusion function, calculating the mass distribution of the volcanic ash particle having the preset particle diameter in the spatial layer (S103); on the basis of the mass distribution of the volcanic ash particle, obtaining a settling mass of the volcanic ash particle having the preset particle diameter in the spatial layer settling in each grid of a settling region on the ground (S104); conducting accumulation according to particle diameter, and obtaining the settling mass of volcanic ash particles having all different particle diameters in the spatial layer settling in each grid (S105); conducting accumulation according to height, and obtaining a total settling mass of the volcanic ash particles having all particle diameters in all spatial layers settling in each grid (S106); outputting the total settling mass in each grid (S107). The volcanic ash diffusion prediction method and apparatus can more realistically predict a volcanic diffusion process.

Description

Volcanic ash diffusion prediction method and device, and early warning method and device Technical field

The invention relates to a volcanic ash diffusion prediction method and device, and a volcanic ash diffusion warning method and device.

Background technique

When a volcano erupts, the rock or magma is pulverized into fine particles, forming volcanic ash. When the volcano erupts, a large amount of volcanic ash is sprayed into the air. These volcanic ash, which is sprayed into the air, gradually spreads to a certain area as the atmosphere moves, and then gradually settles to the ground. These settled volcanic ash have a great impact on the production and life of the local people. For example, volcanic ash can adversely affect the respiratory system of humans and animals, and can also cause normal production in factories that need to work in a clean environment. When the quality of settlement is large, it may cause damage or even collapse of the house. Therefore, after the volcanic eruption, timely prediction of the spread of volcanic ash, timely warning according to the degree of damage, is very important for disaster response work.

Current volcanic ash diffusion prediction is usually performed based on the Suzuki 2D model as in Non-Patent Document 1. The main content disclosed in Non-Patent Document 1 is that the volcanic ash particles of different scales and all the eruption heights are double-integrated to obtain the mass of volcanic debris falling at a certain point on the surface of the earth.

In Non-Patent Document 2, the probability function of the mass distribution of the volcanic eruption plume of the Suzuki model is improved, and the defect that the probability may be negative in the original formula is overcome; and the influence of the eruption column height and the wind speed on the settlement distribution is preliminary. discuss.

In Non-Patent Document 3, on the basis of the Suzuki model, the eruption column diffusion parameters and the probability diffusion concentration are respectively improved and simplified, and different wind speeds varying with height are considered, And the rate of particle settling varies with particle diameter and density.

Non-Patent Document 1: Suzuki, T. (1983). A theoretical model for dispersion of tephra. In D. Shimozuru & I. Yokoyama (Eds.). Arc Volcanism: Physics and Tectonics (pp. 95-113). Tokyo, Japan: Terra Scientific Publishing Company.

Non-Patent Document 2: Yu Hongmei, Xu Jiandong, Zhao Yi, (2007), Numerical simulation of airborne debris from the thousands of eruptions of the Tianchi volcano in Changbai Mountain. Geological Earthquake, 29(3), 522-534.

Non-Patent Document 3: Xi Daozhen, Tian Xiangyan, Gorgen, Xu Lili, (2003), Numerical simulation of a volcanic eruption airborne. Journal of Rock Mechanics and Engineering, 22(8), 1361-1366.

Summary of the invention

The inventors of the present invention found that the above-mentioned Non-Patent Document 2 uses a single wind speed at all heights, and does not consider the wind speed as a function of height. Moreover, the particle size, the height of the ejecting column are not distinguished, and the sedimentation velocity is uniformly set to a constant, which obviously does not conform to the actual pozzolan deposition process.

Further, the above Non-Patent Document 3 does not consider the influence of the particle size of different pozzolan particles on the sedimentation velocity, and does not give a specific lateral diffusion prediction method. In addition, Non-Patent Document 3 does not consider changes in wind direction. Therefore, the technical solution of Non-Patent Document 3 cannot truly predict the process of volcanic ash diffusion and sedimentation.

Accordingly, the present invention provides a volcanic ash diffusion prediction method and apparatus.

The volcanic ash diffusion prediction method provided by one embodiment of the present invention includes: acquiring wind speed and wind direction of each spatial layer layered according to height; calculating volcanic ash of predetermined particle size on the space layer based on a predetermined wind speed and wind direction of the space layer; An atmospheric diffusion function of the particles; calculating a mass distribution of the predetermined particle size of the pozzolan particles on the space layer based on an atmospheric diffusion function of the pozzolan particles; obtaining a predetermined on the space layer based on the mass distribution of the pozzolan particles Particle size The sedimentation mass of each volcanic ash particle settled on each grid of the subsidence area on the ground; accumulating according to the particle size, obtaining the sedimentation quality of the volcanic ash particles of all particle sizes on the space layer deposited onto each of the grids; Accumulating by height, the total sedimentation mass of the pozzolan particles of all particle sizes on all spatial layers deposited onto each of the grids is obtained; and the total sedimentation mass on each of the grids is output.

In the above-described volcanic ash diffusion prediction method, the atmospheric diffusion function is also calculated based on the settlement time from the space layer to the ground.

The above method for predicting volcanic ash diffusion further includes calculating the settling time based on a range of Reynolds numbers of the volcanic ash particles.

In the above volcanic ash diffusion prediction method, calculating an atmospheric diffusion function of the volcanic ash particles of a predetermined particle diameter on the spatial layer further comprises: calculating the atmospheric diffusion by using a linear diffusion equation when the settling time is less than a critical value a variance of the function, wherein the exponential diffusion equation is used to calculate a variance of the atmospheric diffusion function, and the atmospheric diffusion function is calculated based on wind speed and wind direction of the spatial layer; a center point; and obtaining the atmospheric diffusion function based on the variance and the center point.

In the above volcanic ash diffusion prediction method, the mass distribution of the predetermined particle diameter volcanic ash particles on the space layer is also calculated based on the particle mass.

In the above volcanic ash diffusion prediction method, the particle mass is calculated based on the mass distribution function of the column, the particle size distribution function of the volcanic ash particles, and the total eruption quality.

In the above-described volcanic ash diffusion prediction method, the total sedimentation quality on each of the grids is presented by GIS.

A volcanic ash diffusion prediction apparatus according to an embodiment of the present invention includes: a spatial layer wind speed and wind direction acquisition unit for acquiring wind speed and wind direction of each space layer; and an atmospheric diffusion function calculation unit for wind speed based on a predetermined space layer And an airflow direction, calculating an atmospheric diffusion function of the volcanic ash particles of a predetermined particle size on the spatial layer; a mass distribution calculating unit for basing the diffusion function based on the atmosphere Calculating an air diffusion function calculated by the number calculating unit, calculating a mass distribution of the volcanic ash particles having the predetermined particle diameter on the space layer; and a settlement mass calculating unit for obtaining the mass distribution calculated based on the mass distribution calculating unit The sedimentation mass of the predetermined particle size of the pozzolan particles on the space layer on each grid of the subsidence area on the ground; the particle size accumulation portion for accumulating according to the particle diameter to obtain all the particle diameters on the space layer The sedimentation mass of the volcanic ash particles deposited onto each of the grids; the height accumulating portion for accumulating according to the height, obtaining the total sedimentation of the volcanic ash particles of all the particle sizes on all the spatial layers to each of the grids a settling mass; and an output for outputting a total settling mass on each of said grids.

In the above-described pozzolan diffusion prediction device, the atmospheric diffusion function calculation unit further calculates an atmospheric diffusion function based on a settlement time from the space layer to the ground.

In the above-described volcanic ash diffusion prediction apparatus, the atmospheric diffusion function calculation unit further includes a settlement time calculation unit that calculates the settlement time based on a range of Reynolds numbers of the volcanic ash particles.

In the above-described volcanic ash diffusion prediction apparatus, the atmospheric diffusion function calculation unit further includes: a variance calculation unit configured to calculate a variance of the atmospheric diffusion function by using a linear diffusion equation when the settling time is less than a critical value; Where the settling time is greater than or equal to the critical value, an exponential diffusion equation is used to calculate a variance of the atmospheric diffusion function; a center point calculating unit is configured to calculate the atmosphere based on wind speed and wind direction of the spatial layer a center point of the diffusion function; and an atmospheric diffusion function acquisition section for obtaining the atmospheric diffusion function based on the variance and the center point.

In the above-described pozzolan diffusion prediction device, the mass distribution calculation unit further calculates a mass distribution of the volcanic ash particles of the predetermined particle diameter on the space layer based on the particle mass.

In the above-described volcanic ash diffusion prediction apparatus, the mass of the fine particles is calculated based on the mass distribution function of the tobacco column, the particle size distribution function of the volcanic ash particles, and the total eruption quality.

In the above volcanic ash diffusion prediction apparatus, the output unit presents the each by GIS The total settlement quality on the grid.

A volcanic ash diffusion prediction apparatus provided by another embodiment of the present invention includes: a processor; and a memory for storing processor-executable instructions, wherein the processor is configured to: based on a predetermined spatial layer wind speed and Wind direction, calculating an atmospheric diffusion function of the volcanic ash particles of a predetermined particle size on the spatial layer; calculating a mass distribution of the volcanic ash particles of the predetermined particle size on the spatial layer based on the atmospheric diffusion function; based on the mass distribution, Obtaining the sedimentation mass of the predetermined particle size of the volcanic ash particles on the space layer on each grid of the subsidence area on the ground; accumulating according to the particle size, obtaining the volcanic ash particles of all the particle sizes on the space layer to be settled Deposition mass on each grid; accumulating according to height, obtaining total sedimentation mass of volcanic ash particles deposited on each of the spatial layers onto each of the grids; and outputting the total on each grid Settling quality.

A volcanic ash diffusion prediction apparatus according to another embodiment of the present invention includes: an input unit for inputting an air layer layer, a smoke column highest point altitude; a memory for storing a height of each layer, a wind speed, a wind direction; and a processor The processor includes: a spatial wind speed and wind direction acquiring unit for acquiring wind speed and wind direction of each spatial layer; and an atmospheric diffusion function calculating unit configured to calculate the wind speed and the wind direction of the predetermined spatial layer, An atmospheric diffusion function of the volcanic ash particles of a predetermined particle size; a mass distribution calculating unit configured to calculate a mass distribution of the volcanic ash particles of the predetermined particle size on the space layer based on the atmospheric diffusion function; and a settlement mass calculating unit for And based on the mass distribution, obtaining a sedimentation mass of each of the grids of the sedimentation area of the predetermined particle diameter on the space layer, and a particle size accumulation unit for accumulating according to the particle diameter, obtaining the The sedimentation mass of all particle size volcanic ash particles on the space layer settled onto each of the grids; the height accumulation section is used to Accumulating, ash particles is obtained on all the spatial layers to settle on the total mass of the settling each grid; and an output unit for the total mass of settling on the output of each grid.

A volcanic ash diffusion prediction program provided by an embodiment of the present invention, the program The computer performs the following operations: acquiring wind speed and wind direction of each spatial layer layered according to height; calculating an atmospheric diffusion function of the predetermined particle size of the pozzolan particles based on the predetermined wind speed and wind direction of the spatial layer; a diffusion function for calculating a mass distribution of the predetermined particle size of the pozzolan particles on the space layer; and based on the mass distribution, obtaining a network of a predetermined particle size of the volcanic ash particles on the space layer to settle on a subsidence area on the ground Settling mass on the grid; accumulating according to the particle size, obtaining the sedimentation mass of the volcanic ash particles of all particle sizes on the space layer to the each grid; accumulating according to the height, obtaining volcanic ash particles on all the spatial layers The total settling mass settled onto each of the grids; and the total settling mass on each of the grids is output.

A storage medium storing a volcanic ash diffusion prediction program provided by an embodiment of the present invention, the program causing a computer to perform an operation of: acquiring wind speeds and wind directions of respective spatial layers layered according to height; and determining wind speeds based on predetermined spatial layers Wind direction, calculating an atmospheric diffusion function of the volcanic ash particles of a predetermined particle size on the spatial layer; calculating a mass distribution of the volcanic ash particles of the predetermined particle size on the spatial layer based on the atmospheric diffusion function; based on the mass distribution, Obtaining the sedimentation mass of the predetermined particle size of the volcanic ash particles on the space layer on each grid of the subsidence area on the ground; accumulating according to the particle size, obtaining the volcanic ash particles of all the particle sizes on the space layer to be settled Deposition mass on each grid; accumulating according to height, obtaining total sedimentation mass of volcanic ash particles deposited on each of the spatial layers onto each of the grids; and outputting the total on each grid Settling quality.

According to the above-described volcanic ash diffusion prediction method and apparatus, by stratifying the atmosphere, considering the change in wind speed and wind direction with height, it is possible to realistically predict the actual volcanic ash diffusion situation as compared with the prior art using a single wind speed.

In addition, by calculating the Reynolds number to calculate the sedimentation velocity, instead of the sedimentation velocity regarded as a constant in the prior art, it is possible to more realistically predict the actual volcanic ash diffusion situation.

In addition, by introducing the critical settling time, the turbulence of the atmosphere is considered for different settling times. The influence of the spread of mountain ash can more realistically predict the actual volcanic ash diffusion.

The volcanic ash diffusion prediction method and device provided by the invention can more realistically predict the actual volcanic ash diffusion situation, and provide an effective tool for predicting the volcanic ash diffusion in emergency management, so that the emergency management personnel can more accurately grasp the volcanic ash diffusion situation. , make timely and accurate response decisions.

The invention also provides a method and device for warning of volcanic ash diffusion.

The method for predicting volcanic ash diffusion provided by an embodiment of the present invention includes: obtaining a total settlement quality of volcanic ash particles on each grid of a subsidence region according to the above-described volcanic ash diffusion prediction method; and according to the total settlement quality To obtain an equal mass line of volcanic ash settlement, and generate an early warning line for volcanic ash settlement, and issue an early warning to the area where the equal quality line exceeds the warning line.

An apparatus for predicting volcanic ash diffusion provided by an embodiment of the present invention includes: the above-described volcanic ash diffusion prediction device; and an early warning portion for obtaining an equal mass line of volcanic ash settlement according to the total settlement quality, and generating an early warning of volcanic ash settlement a line that issues an early warning to an area where the equal quality line exceeds the warning line.

A volcanic ash diffusion warning device provided by other embodiments of the present invention includes: a processor; and a memory for storing processor-executable instructions, wherein the processor is configured to: based on a predetermined spatial layer wind speed and Wind direction, calculating an atmospheric diffusion function of the volcanic ash particles of a predetermined particle size on the spatial layer; calculating a mass distribution of the volcanic ash particles of the predetermined particle size on the spatial layer based on the atmospheric diffusion function; based on the mass distribution, Obtaining the sedimentation mass of the predetermined particle size of the volcanic ash particles on the space layer on each grid of the subsidence area on the ground; accumulating according to the particle size, obtaining the volcanic ash particles of all the particle sizes on the space layer to be settled Deposition mass on each grid; accumulating according to height, obtaining total sedimentation mass of volcanic ash particles deposited on each of the spatial layers onto each of the grids; and outputting the total on each grid Settling quality; obtaining equal mass of volcanic ash settlement based on the total sedimentation mass Line, and generate an early warning line for volcanic ash settlement, and issue an early warning to the area where the equal quality line exceeds the warning line.

An volcanic ash diffusion warning program according to an embodiment of the present invention, the program causing a computer to perform an operation of obtaining a total settlement quality of volcanic ash particles on each grid of a settling region according to the above-described volcanic ash diffusion prediction method; An equal mass line of volcanic ash settlement is obtained according to the total settlement quality, and an early warning line for volcanic ash settlement is generated, and an early warning is issued for the area where the equal quality line exceeds the warning line.

A storage medium storing a volcanic ash diffusion prediction program according to an embodiment of the present invention, the program causing a computer to perform an operation of obtaining a total of volcanic ash particles on each grid of a subsidence region according to the volcanic ash diffusion prediction method described above And the equal mass line of the volcanic ash settlement according to the total sedimentation quality, and generating an early warning line for volcanic ash settlement, and issuing an early warning to the area where the equal quality line exceeds the warning line.

According to the above-mentioned volcanic ash diffusion warning method and device, a more accurate warning can be made for volcanic ash diffusion, and people in the affected area can be guided to timely protect or evacuate, thereby reducing the adverse consequences caused by volcanic ash.

DRAWINGS

1 is a block diagram showing a schematic configuration of a pozzolan diffusion prediction device according to a first embodiment of the present invention;

2 is a schematic flow chart showing a volcanic ash diffusion prediction method according to the first embodiment of the present invention;

Figure 3 is a flow chart showing the main steps of Embodiment 1 of the first embodiment of the present invention;

4 is a flow chart showing specific steps of calculating an atmospheric diffusion function in Embodiment 2 of the first embodiment of the present invention;

Figure 5 is a diagram showing the calculation of atmospheric diffusion function in the second embodiment of the first embodiment of the present invention. a block diagram of the brief composition of the department;

6 is a flow chart showing specific steps of calculating a settling time in Embodiment 3 of the first embodiment of the present invention;

7 is a schematic flow chart showing a method for predicting volcanic ash diffusion according to a second embodiment of the present invention;

8 is a block diagram showing a schematic configuration of a pozzolan diffusion prediction device according to a third embodiment of the present invention;

Figure 9 is a block diagram of the internal components of the processing device.

detailed description

<First embodiment>

A pozzolan diffusion prediction apparatus and method according to an embodiment of the present invention will be described with reference to Figs. 1 and 2 .

As shown in FIG. 1, the volcanic ash diffusion prediction apparatus 1 according to the first embodiment of the present invention includes: each spatial layer wind speed and direction acquisition unit 101, an atmospheric diffusion function calculation unit 102, a mass distribution calculation unit 103, and a settlement quality calculation unit 104. The particle size integrating unit 105, the height integrating unit 106, and the output unit 107.

The space layer wind speed and direction acquisition unit 101 is configured to acquire the wind speed and the wind direction of each space layer (that is, the step S101 in FIG. 2 is performed).

As described above, in the prior art, variations in wind direction and wind speed with height are not considered.

In contrast, in the present invention, the atmosphere is divided into a plurality of spatial layers of different levels. It is assumed that the horizontal wind speed is a function of height, which varies with height, but each layer has a uniform and constant horizontal wind speed and direction.

That is, the atmosphere at the highest point of the volcanic smoke column (the highest point of the smoke column H _m ) to the crater (volcanic altitude H ₀ ) is divided into θ layers, each layer being ΔH _k high.

For example, through the atmospheric layering module, according to the number of atmospheric layer layers and the highest point altitude input by the user, the layer height of each layer can be automatically calculated, and a wind speed and direction database with a layered number is generated, and the database includes each layer. Height, wind speed v _k , and wind direction λ. That is, the height of each layer, the wind speed v _k , and the wind direction λ can be stored in a storage device such as the external memory 402, the ROM 403, the RAM 404, and the like in FIG. In addition, the user can input parameters such as the number of layers of the atmosphere, the altitude of the highest point, and the like through the input device 401 in FIG. The parameter is not limited to the number of atmospheric layer layers and the highest point altitude, and may be any parameter that can calculate the height of each layer, the wind speed v _k , and the wind direction λ. The space layer wind speed and direction acquisition unit 101 can obtain the wind speed and direction of each spatial layer layered according to the height by accessing such a wind speed and direction database. However, it is not limited thereto, and the wind speed and direction of each spatial layer layered according to height may be acquired by manual input.

The atmospheric diffusion function calculation section 102 is configured to calculate an atmospheric diffusion function of the volcanic ash particles of a predetermined particle diameter on the spatial layer based on the wind speed and the wind direction of the spatial layer layered by the height (that is, the step S102 in FIG. 2 is performed).

In an embodiment of the present invention, the atmospheric diffusion function indicates that a predetermined convection-diffusion equation is used to estimate a predetermined particle diameter, and a predetermined release height of the particles falls onto a grid point of coordinates (x, y) on the ground. Quality score. The method of calculating the atmospheric diffusion function may be a method as shown in FIG. 4 described later, or an existing method.

The mass distribution calculation unit 103 is configured to calculate a mass distribution of the volcanic ash particles having a predetermined particle diameter on the space layer based on the atmospheric diffusion function calculated by the atmospheric diffusion function calculation unit 102 (at step S102) (ie, performing S103 in FIG. 2) step).

For example, when the atmospheric diffusion function is expressed as f _i,j (x,y), and the particle mass of the ash particles of the predetermined particle diameter j falling from the spatial layer i having the height z _i is expressed as

The mass distribution of the ash particles of the predetermined particle size j on the space layer i is m _i,j (x,y)(kgm ^-2 ):

The settlement quality calculation unit 104 is configured to obtain the sedimentation quality of each of the sedimentation regions of the volcanic ash particles on the ground based on the mass distribution calculated by the mass distribution calculation unit 103 (at step S103) (ie, performing FIG. 2 Step S104).

A buffer area of a certain area can be established around the volcano as a potential volcanic ash settlement area, and the buffer area is divided into grid points.

For example, based on the mass distribution of the volcanic ash particles, the quality of the settlement at each grid point of the settling area is calculated by substituting the coordinates of each grid point.

The particle size accumulating portion 105 is for obtaining the sedimentation quality of the pozzolan microparticles of all the particle diameters on the space layer on each of the grids of the subsidence region (that is, the step S105 in Fig. 2 is performed).

For example, when (Φ _min , Φ _max ) is the particle size range of the particles (Φ=-log ₂ d, where d is the diameter of the particles, the unit is mm), the particle size may be first accumulated to determine the The mass distribution of all particle size volcanic ash particles on the space layer is

Then, by substituting the mass distribution for the coordinates of each grid point, the sedimentation mass of the ash particles of all particle sizes on the space layer on each grid of the settling zone is obtained.

It is also possible to first determine the sedimentation mass of the volcanic ash particles of each particle size according to the mass distribution of the volcanic ash particles of each particle size, and then accumulate the sedimentation masses of all the particle sizes, thereby obtaining all the particle sizes on the space layer. The sedimentation mass of volcanic ash particles on each grid of the settling zone.

The height accumulating portion 106 is for obtaining the sedimentation quality of the ash particles of all particle sizes on all the spatial layers on each grid of the settling region. That is, the step S106 in FIG. 2 is performed, and Accumulating by height, the total sedimentation mass of the volcanic ash particles of all particle sizes on all spatial layers on each grid was obtained.

For example, if H _m is the total height of a volcanic smoke column, the mass distribution of all particle size volcanic ash particles on all spatial layers can be determined first.

Then, the mass distribution is substituted for the coordinates of each grid point, and the total sedimentation mass of the volcanic ash particles of all particle sizes on all the spatial layers on each grid of the settling region is obtained.

It is also possible to first determine the sedimentation mass of the volcanic ash particles in each spatial layer according to the mass distribution of the volcanic ash particles on each spatial layer, and then accumulate the sedimentation masses of all heights, thereby obtaining all the particle sizes of all the spatial layers. The total sedimentation mass of the volcanic ash particles on each grid of the settling zone.

The output portion 107 is for outputting the sedimentation quality of the pozzolan ash particles on each of the grids (i.e., the step S107 of Fig. 2 is performed).

<Example 1>

The volcanic ash diffusion prediction method according to the first embodiment can be specifically realized by the following first embodiment. Here, the embodiment 1 will be described in detail with reference to FIGS. 1 and 3.

First, in step S201, each of the spatial layer wind speed and direction acquisition units 101 acquires the wind speed and the wind direction of each spatial layer layered according to the height.

In step S202, a buffer area is established as a potential settled area of the volcanic ash, and the buffer area is divided into grid points. The operation of this step may be performed by the subsidence quality calculation unit 104 or may be performed by other components.

Next, in step S203, the height accumulating unit 106 performs integration in accordance with the height.

For example, the integration operation can be performed for the particles located in the spatial layer of height i from the crater to the highest point of the volcanic smoke column (altitude H ₀ to H _m ) with the altitude integration step Δi.

In step S204, the particle size integrating unit 105 performs integration in accordance with the particle diameter.

For example, an integral operation can be performed for a particle having a particle size of j from a minimum particle diameter to a maximum particle diameter (from Φ _min to Φ _max ) with a particle diameter step Δj.

In step S205, the atmospheric diffusion function calculation unit 102 calculates the atmospheric diffusion function f _i,j (x, y).

For point sources of instantaneous emissions, the analytical solution of the mass conservation equation is a Gaussian distribution with symmetry axes of x (positive east) and y (north north) directions. That is, the atmospheric diffusion function f _i,j (x,y) is a Gaussian function.

The Gaussian function can be written as:

In the formula,

with

Is the coordinates of the center point of the two-dimensional Gaussian distribution.

The variance of the Gaussian distribution is determined by atmospheric diffusion and horizontal dispersion in the plume, which is the variance

Can be calculated by existing methods.

In this embodiment, the center point is calculated according to the wind speed and the wind direction of the highly layered spatial layer.

After Δt _j,k , the center of the Gaussian distribution shifts to the xy plane, during which the displacement Δx _j,k =w _x,k Δt _j,k sinθ _k ,Δy _j,k =w _y occur on the x-axis and the y-axis, respectively. _{, k} Δt _{j, k} cosθ _k , where w _x,k and w _y,k are the horizontal components of the wind speed in the spatial layer, and θ _k is the angle between the wind direction of the spatial layer (k) and the true east direction, north The direction is 90 degrees, 0° < θ ≤ 360 °.

In the present invention, the atmosphere is divided into a plurality of horizontal spatial layers, and the horizontal wind speed varies as a function of height, but each spatial layer has a uniform and constant horizontal wind speed and direction. Each source point i is located on a horizontal space layer, and the particles released from the source point are initially transported by the wind of the layer until they fall to the next spatial layer and are affected by different wind directions and wind speeds. This process continues until the particles reach the ground.

Next, in step S206, the mass distribution calculation unit 103 calculates the particle mass M ⁰ _i,j .

Specifically, in step S206, the mass of the particles having a particle diameter j released from the point source of height i

It can be obtained from the mass distribution function p _z (z _i ) of the volcanic plume, the particle size distribution function f _Φ (Φ) of the particles, and the total eruption mass M ⁰ .

1. Mass distribution function of volcanic plume

The distribution of particles in a rising volcanic column can be described by different means. In the present invention it is assumed that the mass of the volcanic column follows a lognormal distribution:

Where H>0,

H _m is the total height of the column, z is the height of the particle relative to the crater; A is a dimensionless geometric parameter that controls the shape of the volcanic column and 0 < A ≤ 1. The larger A, the more concentrated the volcanic debris is at the height of the volcanic column.

2. Total eruption quality

The height of the plume above the crater H _m (m) (the highest point of the plume – the elevation of the crater) is known. The total eruption mass M ⁰ (kg) is derived from an empirical formula of an index:

Where ρ _dep (kgm ^-3 ) is the density of volcanic clastic deposits, and Γ(s) is the duration of the eruption.

3. Particle size distribution function

Assume that the total particle size distribution is a normal distribution in Φ. For volcanic sediments, the particle size distribution function f _Φ (Φ) determines the relative amount of particles of various sizes in the sediment. Typical volcanic clastic sediment particle sizes tend to be near an intermediate value between -1 and 1 Φ (0.5-1.0 mm).

Φ=-log ₂ d (10)

Where σ is the standard deviation of the particle size, the unit is Φ; μ is the average particle diameter, and the unit is also Φ; d is the particle diameter in mm.

Next, in step S207, the mass distribution calculation section 103 calculates the mass distribution m _i,j (x,y)=M ⁰ _i,j f _i,j of the pozzolan microparticles of the predetermined particle diameter j on the spatial layer i ( x, y).

In step S208, the sedimentation mass calculation section 104 obtains the subsidence quality at each grid point. Here, for each grid point, the accumulated total settlement quality of each grid point can be obtained by accumulating new sedimentation masses on the existing settlement quality.

In step S209, the particle size accumulating unit 105 determines whether or not the cycle according to the particle diameter is completed. If the process is completed, the process proceeds to step S209. If not, the process returns to step S203.

In step S2010, the height accumulating unit 106 determines whether or not the cycle according to the height is completed. If the process is completed, the process proceeds to step S210. If not, the process returns to step S202.

In step S211, the output unit 107 outputs the total accumulated mass of each of the grid points.

Here, it can be output by connecting points of the same quality, obtaining an equal mass line map of volcanic sediments, and displaying an equal mass line map of the obtained volcanic sediments by GIS.

For example, the output device 408 of FIG. 9 may be a display capable of displaying the output of the input portion 107 on the display in the form of a GIS image.

According to Embodiment 1, by stratifying the atmosphere, considering the change in wind speed and wind direction with height, it is possible to simulate the actual volcanic ash diffusion situation in close proximity to the prior art using a single wind speed.

<Example 2>

Next, a second embodiment will be described with reference to FIGS. 4 and 5. The second embodiment differs from the first embodiment only in that the step S205 of calculating the atmospheric diffusion function further includes steps S2051 to S2056. As shown in FIG. 5, the atmospheric diffusion function calculation unit 102 may further include a settlement time calculation unit 1021, a variance calculation unit 1022, a center point calculation unit 1023, and an atmospheric diffusion function acquisition unit 1024.

The settling time calculation unit 1021 is for calculating the settling time. That is, the step S2051 is performed to calculate the settling time t _i,j .

The variance calculation unit 1022 is configured to calculate a variance of the atmospheric diffusion function by using a linear diffusion equation in a case where the settlement time is less than a critical value, and use an index when the settlement time is greater than or equal to the critical value. A diffusion equation is used to calculate the variance of the atmospheric diffusion function.

Specifically, in step S2052, it is judged whether or not the sedimentation time t _{i,j of the} particles is smaller than the critical value (FTT) of the sedimentation time.

Here, a threshold value (FTT) of the settling time is introduced, and when the particle settling time is less than the FTT, the process proceeds to step S2053, and when the particle settling time is greater than or equal to the FTT, the step is advanced. S2054.

The effect of atmospheric turbulence on coarse particles is a secondary effect, and some volcanic debris distribution models are based on assumptions that negligible atmospheric turbulence. However, if the falling time of the particles is long, atmospheric turbulence is not negligible. Therefore, the present invention introduces a settling time threshold (FTT) for calculating the atmospheric diffusion function in different ways for the volcanic ash particles whose settling time is less than the critical value and greater than or equal to the critical value.

Specifically, the operations of steps S2053 and S2054 are performed separately.

In the step S2053, in the case where the sedimentation time of the particles is smaller than the threshold FTT, the linear equation is used to calculate the variance σ _{i,j of the} atmospheric diffusion function.

For volcanic ash particles with a short settling time t _i,j (the settling time of the particles is less than FTT), the diffusion is linear (following Fick's law) and thus the variance

for:

Here, K(m ² s ^-1 ) is a constant diffusion coefficient. t _i '(s) is the horizontal diffusion time in the vertical plume.

The horizontal diffusion coefficient K is isotropic (K = K _x = K _y ). The vertical diffusion coefficient is small at altitudes above 500 m, so it is assumed to be negligible.

The horizontal diffusion time t' _i (a function of height) is used to describe the change in width of the vertical plume. Here, the diffusion radius r _{i of the} plume at a certain height z _i is approximately: r _i = 0.34 z _i . Therefore, let r _i =3σ _p =3σ _ij , where σ _p is the standard deviation of the Gaussian distribution of the material in the rising plume. For t _ij =0, there are:

In the step S2054, in the case where the sedimentation time of the particles is greater than or equal to the critical value FTT, the exponential equation is used to calculate the variance σ _{i,j of the} atmospheric diffusion function.

When the settling time of the particles is long (the settling time of the particles is greater than or equal to the FTT), the scale of the turbulent structure carrying the particles increases with time. For example, particles <1 mm in diameter fall from a 30 km tall column of smoke with an average drop time > 1 hour. In this case, variance

It can be determined by the following empirical formula:

Where C represents the eddy diffusivity and is determined by the empirical formula (C = 0.04 m ² s ^-1 ). Let t _i,j =0,r _i =3σ _i,j =0.34z _i , then the horizontal diffusion time of the smoke column of the fine particles is:

The horizontal diffusion time _ti ' has a much greater effect on the total settling time of coarse particles, ie (t _i,j +t _i ') than its effect on fine particles, because for small particles it is t' _i <<t _i,j . For coarse particles, the horizontal diffusion time depends on the K value and height, while for fine particles, the horizontal diffusion time depends only on the height. When the height is small, in general (ie the K value is constant), the horizontal diffusion of the coarse particles Time is less than fine particles.

The center point calculation unit 1023 is configured to calculate a center point of the atmospheric diffusion function based on the wind speed and the wind direction of the space layer. That is, the step S2055 is performed, as in Embodiment 1, the center point is calculated based on the wind speed and the wind direction according to the height stratification

The atmospheric diffusion function acquisition section 1024 is configured to obtain the atmospheric diffusion function based on the variance and the center point. That is, the step S2056 is performed, based on the variance σ _i,j and the center point

To calculate the atmospheric diffusion function. That is, the atmospheric diffusion function is calculated based on the formula (3).

According to Embodiment 2, in addition to the same effect as Embodiment 1, by introducing settling time The critical value, considering the influence of atmospheric turbulence on the volcanic ash diffusion at different settling times, can more realistically simulate the actual volcanic ash diffusion.

<Example 3>

Hereinafter, a third embodiment will be described with reference to FIG. The difference between Embodiment 3 and 2 is only that the step S2051 for calculating the settlement time further includes steps S251 to S258. That is, the settling time calculating unit 1021 is configured to calculate the settling time based on the range of the Reynolds number of the ash particles.

Specifically, the particles of particle size j are transported by the wind on each spatial layer (k), the transport time is Δt _j,k , and the thickness of each spatial layer is Δz _k , then Δt _j,k =Δz _k /v _j,k , where v _j,k is the sedimentation velocity of the particles.

The particle elapses from time t _i,j from the source point of coordinates (x _i , y _i , z _i ) to the ground, ie the settling time t _i,j is:

First, in S251, the Reynolds number is calculated from the particle size of the volcanic ash particles.

Assuming that all volcanic ash is erupted instantaneously, the volcanic ash particles are spherical, and the particle size j is released from the space layer i of a certain height of the plume, and its final settling velocity is a function of the Reynolds number of the particle, Renault. The number varies with atmospheric density.

Where d is the particle diameter (m), ρ _g is the ambient air density, μ is the aerodynamic viscosity (kgm-1s-1), and v is the sedimentation velocity (m/s) of the particles.

The sedimentation velocity of the volcanic ash particles depends on the density, shape, and physical properties of the particles (for example, the first to third formulas described below).

The falling of particles in the atmosphere is affected by gravity and air resistance. The sedimentation of small particles is mainly affected by air resistance, while the larger particles are mainly affected by gravity. That is to say, according to the size of the volcanic ash, the main factors affecting the sedimentation speed are different, and the settlement speed should be calculated by different methods.

Therefore, in the present embodiment, as described below, the settlement speed is calculated using a different formula depending on the different ranges of the Reynolds numbers of the particle diameters.

Since most of the particles can reach their final settling velocity (equilibrium state) after a few seconds, in the present embodiment, the sedimentation speed of the particles of a certain particle diameter is constant by default in the present embodiment.

In the step S252, when the Reynolds number Re < Re1, the process proceeds to step S253, and the first formula is used to calculate the settling velocity.

That is, when the Reynolds number Re<Re1 (for example, Re1=6):

(first formula)

In the step S254, when the Reynolds number Re1 ≦ Re < Re2 (for example, Re2 = 500), the process proceeds to step S255, and the second formula is used to calculate the settling velocity.

That is, when Re1≦Re<Re2:

(second formula)

In the step S256, when the Reynolds number Re2 ≦ Re < Re3 (for example, Re3 = 200000), the process proceeds to step S257, and the third formula is used to calculate the settling velocity.

That is, when Re2≦Re<Re3:

(third formula)

Where ρ _j is the particle density, ρ _g is the ambient air density, Re is the Reynolds number, d is the particle diameter (m), and μ is the aerodynamic viscosity (kgm ^-1 s ^-1 ).

The particle density ρ _j can be classified into two types according to the type of sediment particles, that is, a lithography density ρ _jl and a pumice density ρ _jp .

Pyroclastic debris generally contains a large number of bubbles, and its density is small. Only when its diameter is small, the bubble content is reduced and the density is increased. For volcanic debris densities greater than 2 mm in diameter, the measured values can be obtained directly. The density of volcanic debris with a diameter below 2 mm (>-1 Φ) decreases linearly with increasing diameter. When the diameter is reduced below 8 μm (+7 Φ), the density of the volcanic debris is equal to the density of the volcanic debris.

There are no bubbles in the volcanic lithotripsy, and the proportion in the volcanic eruptions tends to be small, generally less than 15% of the total mass of the hairspray, and its density is a fixed value, generally between 2300-2700 kg/m ³ .

The effect of particle density changes on the accumulation of high smoke column sediments is much greater than that of low smoke columns. In addition, the presence of volcanic debris has less influence on the simulation results, so for the sake of simplicity, in the present embodiment, all volcanic sediments are assumed to be volcanic debris, and the particle density ρ _{j of the} volcanic debris is directly input for calculation.

Next, in step S258, the settling time t _{i,j is} calculated based on the settling velocity v _j,k calculated at step S253, or S255, or S257.

According to Embodiment 3, in addition to the same effect as Embodiment 2, by calculating the sedimentation velocity according to the different range of the Reynolds number, instead of the sedimentation velocity regarded as a constant in the prior art, it is possible to further realistically simulate the actual The spread of volcanic ash.

Further, in the first embodiment of the present invention, a preferred embodiment has been described by taking the steps S201 to S211 of FIG. 3 as an example. However, the above steps S201 to S211 are not always necessary. The present invention can also be implemented by omitting some of the steps, or replacing other equivalents that can be conceived by those skilled in the art.

<Second Embodiment>

As shown in FIG. 8, the volcanic ash diffusion early warning device 2 according to the second embodiment of the present invention includes the above-described volcanic ash diffusion prediction device 1 and an early warning determining unit 30. As shown in FIG. 7, the volcanic ash diffusion warning method according to this embodiment includes the following steps S301 and S302.

As described above, the pozzolan diffusion prediction device 1 obtains the total sedimentation quality of the pozzolan particles on each of the grids of the subsidence region (i.e., the step S301 is performed).

The warning portion 30 can draw a mass line such as volcanic ash sedimentation according to the total sedimentation mass of the volcanic ash particles on each grid obtained (S301 step), and generate a volcanic ash settlement warning line, and the volcanic ash settlement and other mass lines exceed the volcanic ash settlement. The area of the warning line issues an early warning (ie, step S302 is performed).

The volcanic ash diffusion warning method can make a more accurate warning for the spread of volcanic ash, and guide people in the affected area to timely protect or evacuate, thereby reducing the adverse consequences caused by volcanic ash.

The various component embodiments of the present invention may be implemented in hardware, or in a software module running on one or more processors, or in a combination thereof. It will be understood by those skilled in the art that, as shown in FIG. 9, a block diagram of an internal component of a processing device, which may be a workstation, for example, the processing device includes a bus 409, and the components on the bus are connected as follows: The processing device includes a processor 405, which is a very large scale integrated circuit, which is the computing core and control core of a computer. Its function is mainly to explain computer instructions and to process data in computer software. Processor 405 primarily includes an arithmetic unit and cache 406 and a bus that implements the data, control, and status of the connections between them.

The processing device further includes a memory, and the memory in the computer can be divided into a main memory (memory) according to the use, for example, a ROM (Read Only Memory image) 403, a RAM (Random Access Memory) 404, and an auxiliary device. Memory (external memory) 402. The memory has a memory space for program code for performing any of the method steps described above. For example, the storage space for the program code may include various program codes for implementing the various steps in the above methods, respectively. These program codes can be from one or more Read or write to the one or more computer program products in the computer program product. These computer program products include program code carriers such as a hard disk, a compact disk (CD), a memory card, or a floppy disk. Such computer program products are typically portable or fixed storage units. The storage unit may have a storage section, a storage space, and the like arranged similarly to the memory in the terminal described above. The program code for performing any of the above method steps can also be downloaded over the network. The program code can be compressed, for example, in an appropriate form. Generally, a storage unit includes computer readable code, ie, code that can be read by a processor, such as, when run by a search engine program on a server, causing the server to perform various steps in the methods described above.

Further, the processing device includes at least one input device 401 for interaction between the user and the processing device, and the input device 401 can be a keyboard, a mouse, an image capturing component, a gravity sensor, a sound receiving component, a touch screen, etc.; Including at least one output device 408, the output device 408 can be a speaker, a buzzer, a flash, an image projection unit, a vibration output component, a screen or a touch screen, etc.; the processing device can also include a communication interface for data communication in a wired or wireless manner. 407.

In the description provided herein, numerous specific details are set forth. However, it is understood that the embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of the description.

It is to be noted that the above-described embodiments are illustrative of the invention and are not intended to be limiting, and that the invention may be devised without departing from the scope of the appended claims. The word "comprising" does not exclude the presence of the elements or steps that are not recited in the claims. The word "a" or "an" The invention can be implemented by means of hardware comprising several distinct elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means can be embodied by the same hardware item. The use of the words first, second, and third does not indicate any order. These words can be interpreted as names.

In addition, it should be noted that the language used in the specification has been selected for the purpose of readability and teaching, and is not intended to be construed or limited. Therefore, it is within the skill of the art without departing from the scope and spirit of the appended claims Many modifications and variations will be apparent to the ordinarily skilled artisan. The disclosure of the present invention is intended to be illustrative, and not restrictive, and the scope of the invention is defined by the appended claims.

The above embodiments are merely illustrative of the technical concept and the features of the present invention, and the purpose of the present invention is to enable those skilled in the art to understand the contents of the present invention and to implement the present invention. Equivalent transformations or modifications made in accordance with the spirit of the invention are intended to be included within the scope of the invention.

While the embodiments of the present invention have been described by the embodiments of the embodiments of the invention Within the limits defined by the requirements.

Claims (10)

1. A method for predicting volcanic ash diffusion, comprising:

   Obtaining the wind speed and direction of each spatial layer layered according to height;

   Calculating an atmospheric diffusion function of the volcanic ash particles of a predetermined particle size on the spatial layer based on a predetermined wind speed and wind direction of the spatial layer;

   Calculating a mass distribution of the predetermined particle size volcanic ash particles on the space layer based on the atmospheric diffusion function;

   Based on the mass distribution, obtaining a sedimentation mass of each of the grids of the settling area of the predetermined particle size on the space layer that settles to the subsidence area on the ground;

   Accumulating according to the particle diameter, obtaining the sedimentation quality of the ash particles of all particle sizes on the space layer deposited onto each of the grids;

   Accumulating according to height, obtaining the total settlement quality of the deposition of volcanic ash particles on all the spatial layers onto each of the grids;

   The total settling mass on each of the grids is output.
2. The volcanic ash diffusion prediction method according to claim 1, wherein

   The atmospheric diffusion function is also calculated based on the settling time from the space layer to the ground.
3. The volcanic ash diffusion prediction method according to claim 2, further comprising:

   The settling time is calculated based on the range of the Reynolds number of the pozzolan particles.
4. A method for predicting volcanic ash diffusion according to any one of claims 2 or 3, wherein

   The calculation of the atmospheric diffusion function of the volcanic ash particles of predetermined particle size on the spatial layer further includes:

   In the case where the settling time is less than a critical value, a linear diffusion equation is used to calculate the variance of the atmospheric diffusion function,

   In the case where the settling time is greater than or equal to the critical value, an exponential diffusion equation is employed Calculating the variance of the atmospheric diffusion function;

   Calculating a center point of the atmospheric diffusion function based on wind speed and wind direction of the space layer;

   The atmospheric diffusion function is obtained based on the variance and the center point.
5. An early warning method for volcanic ash diffusion, comprising:

   The volcanic ash diffusion prediction method according to any one of claims 1 to 4, wherein a total sedimentation quality of volcanic ash particles on each grid of the settling region is obtained;

   An equal mass line of volcanic ash settlement is obtained according to the total settlement quality, and an early warning line for volcanic ash settlement is generated, and an early warning is issued for the area where the equal quality line exceeds the warning line.
6. A volcanic ash diffusion prediction device includes:

   The wind speed and wind direction acquisition part of each space layer is used for acquiring the wind speed and the wind direction of each space layer;

   An atmospheric diffusion function calculating unit configured to calculate an atmospheric diffusion function of the volcanic ash particles of a predetermined particle diameter on the spatial layer based on a predetermined wind speed and wind direction of the spatial layer;

   a mass distribution calculation unit configured to calculate a mass distribution of the volcanic ash particles of the predetermined particle size on the space layer based on the atmospheric diffusion function;

   a settlement quality calculating unit, configured to obtain, based on the mass distribution, a sedimentation mass of each of the grids of the sedimentation area on which the volcanic ash particles of the predetermined particle size on the space layer are settled to the ground;

   a particle size accumulating portion for accumulating according to the particle diameter, and obtaining sedimentation mass of the pozzolan particles of all particle diameters on the space layer deposited on each of the grids;

   a height accumulating portion for accumulating according to heights to obtain total sedimentation mass of volcanic ash particles deposited on each of the spatial layers onto each of the grids;

   An output portion for outputting a total settlement quality on each of the grids.
7. The volcanic ash diffusion prediction apparatus according to claim 6, wherein

   The atmospheric diffusion function calculation unit further calculates an atmospheric diffusion function based on a settlement time from the spatial layer to the ground.
8. The volcanic ash diffusion prediction apparatus according to claim 7, wherein:

   The atmospheric diffusion function calculating unit further includes a settling time calculating unit that calculates the settling time based on a range of Reynolds numbers of the volcanic ash particles.
9. The volcanic ash diffusion prediction apparatus according to any one of claims 7 or 8, wherein

   The atmospheric diffusion function calculation unit further includes:

   a variance calculation unit, configured to calculate a variance of the atmospheric diffusion function by using a linear diffusion equation in a case where the settling time is less than a critical value, and adopt an index when the settling time is greater than or equal to the critical value a diffusion equation to calculate a variance of the atmospheric diffusion function;

   a center point calculating unit configured to calculate a center point of the atmospheric diffusion function based on a wind speed and a wind direction of the space layer;

   An atmospheric diffusion function acquisition section for obtaining the atmospheric diffusion function based on the variance and the center point.
10. A volcanic ash diffusion warning device includes:

    The volcanic ash diffusion prediction apparatus according to any one of claims 6 to 9; and an early warning unit for obtaining an equal mass line of volcanic ash sedimentation based on the total sedimentation mass, and generating an early warning line for volcanic ash settlement, An area where the quality line exceeds the warning line issues an early warning.

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