JP5613708B2 - Airflow status prediction device, airflow status prediction method, diffusion status prediction device, and diffusion status prediction method - Google Patents

Description

  The present invention relates to an airflow state prediction device, an airflow state prediction method, a diffusion state prediction device, and a diffusion state prediction method.

  When harmful diffusing materials are released into the atmosphere, it is important to quickly and accurately predict the diffusion behavior of diffusing materials in order to properly evacuate from diffusing materials and to carry out threat removal activities for diffusing materials. .

  As an example of a technique for quickly and accurately predicting the diffusion behavior of a diffusing material, for example, a plurality of airflow field databases (hereinafter abbreviated as “DB”) having different wind directions and atmospheric stability are provided. A system that predicts the airflow field when a diffusion event occurs by interpolating the meteorological data of the date and time when the event occurred and data under conditions where the atmospheric stability is close, and predicts the diffusion situation based on this airflow field Is proposed in Patent Document 1 (Japanese Patent No. 4209354).

  The technique described in Patent Document 1 inputs weather data at the time of occurrence of a diffusion event, calculates atmospheric stability based on the input weather data, and selects “wind direction” from the built airflow field DB. The airflow field data with the closest "and atmospheric stability" is selected, and the diffusion behavior is obtained by performing diffusion calculation based on the airflow field data.

  The airflow field DB is constructed by taking out a narrow area (several kilometers) from a wide area (several tens km to several hundred kilometers) weather data such as weather GPV (grid point value) by nesting method. After extracting the vertical distribution by wind direction (16 directions) and atmospheric stability (7 levels), these extracted data are taken in as initial conditions and uniform boundary conditions for meteorological models such as RAMS (Regional Atmospheric Modeling Systems), This is done by obtaining a plurality of three-dimensional airflow fields.

  According to the technique described in Patent Document 1, GPV data is provided every 10 minutes, so that the time-series data can be processed in the same manner as described above to predict the diffusion situation over time.

  In addition, as another technique, initial conditions are determined every 10 minutes determined by performing time interpolation and spatial interpolation using weather data such as GPV as in the technique described in Patent Document 1. The meteorological model is calculated using RAMS, etc., and the weather elements (wind speed, wind direction, turbulent energy, humidity, temperature, etc.) are sequentially determined by the nesting method. Patent Document 2 (Japanese Patent No. 4404220) discloses a technique for obtaining a final airflow field by correcting the calculated weather data based on the difference from the meteorological data in the observation point data in the region of interest after calculation as the stepped weather data. ) Is proposed.

  In the technique described in Patent Document 2, the diffusion calculation is performed based on the finally obtained airflow field data, and the diffusion behavior is obtained. In this method, the meteorological data calculated by the nesting method is corrected by using the meteorological element at the observation point, so that it is possible to provide more accurate airflow field data.

  Furthermore, as a technique for predicting more quickly than the technique described in Patent Document 2, as in Patent Document 2, it is determined by performing temporal interpolation and spatial interpolation using weather data such as GPV. Meteorological model calculation by RAMS etc. is performed giving initial conditions for every minute, and meteorological elements (wind speed, wind direction, turbulent energy, humidity, temperature, etc.) are sequentially obtained by nesting method and finally about 250m interval Japanese Patent Application Laid-Open No. 2003-26883 discloses a technique for obtaining a final airflow field by calculating a degree of meteorological element as meteorological data in units of 10 minutes and then interpolating these data in a region of interest at a distance interval of 5 m. 2008-89418). In the technique described in Patent Document 3, diffusion calculation is performed based on the finally obtained airflow field data to determine the diffusion behavior.

Japanese Patent No. 4209354 Japanese Patent No. 4404220 JP 2008-89418 A

  However, all of the techniques described in Patent Documents 1 to 3 require that the emission point of the diffusing material be specified, and must process a large amount of wide area data before constructing the database. There is a problem. On the other hand, in recent years, the occurrence of harmful substances in urban areas has been confirmed, and it is desired to construct a diffusion behavior prediction system for diffusing substances with higher versatility.

  The present invention has been made in view of such a situation, and accurately predicts an airflow state and a diffusion state accurately (at intervals of several meters) for a narrow area of interest (for example, several hundreds to several kilometers). An object is to provide an airflow state prediction device, an airflow state prediction method, a diffusion state prediction device, and a diffusion state prediction method.

  In order to solve the above-described problem, an airflow condition prediction apparatus according to an embodiment of the present invention includes an airflow element including wind directions and wind speeds observed at a plurality of observation points in a region of interest set as an area for predicting an airflow condition. The observation area and the position information of the observation point are received, and the observation area of the received airflow element is held in an accessible storage means, and the region of interest is under the condition that the wind direction and the wind speed included in the airflow element are different from each other. The analysis result of the air flow element obtained by analyzing the air flow in the region of interest including information on the size and position of the structure existing in the region is associated with the position in the region of interest and the condition as air flow data. The degree of coincidence is calculated by comparing and collating with the airflow data at a location corresponding to the position information of the observation point in the airflow database. The degree of coincidence is calculated according to the calculated degree of coincidence. Characterized by including a comparison operation unit for weighted combination of each stream data in the database.

  In order to solve the above-described problem, the diffusion state prediction apparatus according to the embodiment of the present invention includes an airflow element including wind directions and wind speeds observed at a plurality of observation points in a region of interest set as a region for predicting the diffusion state. The observation result of the diffusion element including the concentration of the substance, and the position information of the observation point, and the received observation result of the air flow element and the stored wind direction and the wind direction included in the air flow element The analysis result of the air flow element obtained by analyzing the air flow in the region of interest including information on the size and position of the structure existing in the region of interest under the condition where the wind speed is different is obtained as the air flow. The airflow data at a location corresponding to the observation point in the airflow database associated with the position in the region of interest and the condition as data, and the received diffusion Information on the size and position of the structure existing in the region of interest under the condition that the observation direction of the element and the wind direction and the wind speed included in the air flow element are different from each other, and are stored in accessible storage means. In addition, the result of analysis of the diffusion element obtained by performing diffusion analysis in the attention area is used as diffusion data to compare and match the position in the attention area and the diffusion data in the diffusion database associated with the condition. And a comparison operation unit that weights and combines the respective diffusion data in the diffusion database according to the calculated degree of coincidence.

  An airflow situation prediction method according to an embodiment of the present invention is a method for predicting an airflow situation in a region of interest set as an area for predicting an airflow situation using a computer in order to solve the above-described problem. The computer receives the airflow element observation results including the wind direction and the wind speed observed at multiple observation points in the area of interest set as the area where the computer predicts the airflow situation, and the position information of the observation points, and the received airflow element observation results Including information on the size and position of the structure existing in the region of interest under conditions in which the wind direction and the wind speed included in the airflow element are different from each other. The analysis result of the airflow element obtained by analyzing the airflow in the attention area is associated with the position in the attention area and the condition as airflow data. The airflow data at a location corresponding to the position information of the observation point in the flow database is compared and collated to calculate the degree of coincidence, and the airflow data in the airflow database is weighted and combined according to the calculated degree of coincidence. It comprises a processing step.

  A diffusion situation prediction method according to an embodiment of the present invention is a method for predicting an airflow situation in a region of interest set as an area for predicting an airflow situation using a computer in order to solve the above-described problem, Observation results of air flow elements including wind direction and wind speed, observation results of diffusion elements including substance concentration, and position of observation points observed at multiple observation points in the attention area set as an area where the computer predicts the diffusion situation The information is received and the observation result of the received airflow element and the storage means accessible by the computer are stored in the attention area under different conditions of the wind direction and the wind speed included in the airflow element. The analysis result of the air flow element obtained by the air flow analysis in the region of interest including the size and position information of the structure to be analyzed The airflow data at the location corresponding to the observation point in the airflow database associated with the position in the region of interest and the condition, and the received observation result of the diffusion element, and the storage means accessible by the computer are stored. Obtained by performing diffusion analysis in the region of interest including information on the size and position of structures existing in the region of interest under conditions in which the wind direction and wind speed included in the airflow element are different. In addition, using the analysis result of the diffusion element as diffusion data, the position in the region of interest and the diffusion data in the diffusion database associated with the condition are compared and collated to calculate the degree of coincidence, and the diffusion is determined according to the calculated degree of coincidence. It is characterized by comprising processing steps for weighted combination of each spread data in the database.

  According to the present invention, it is possible to accurately and quickly predict the airflow situation and the substance diffusion situation in the region of interest.

Schematic explaining the structural example of the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on embodiment of this invention. The functional block diagram which shows the functional structure of the airflow condition prediction apparatus and diffusion state prediction apparatus which concern on embodiment of this invention. Explanatory drawing explaining the attention area set with the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on embodiment of this invention. Explanatory drawing which shows an example of the airflow database which the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on embodiment of this invention refer. Explanatory drawing which shows an example of the diffusion database which the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on embodiment of this invention refer. Explanatory drawing which shows an example of the calculation result of the coincidence of each airflow data (or diffusion data) which the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on embodiment of this invention calculated. Explanatory drawing explaining the example of a display (1st display example) which displays the result which the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on embodiment of this invention estimated on the display. Explanatory drawing explaining the example of a display (2nd display example) which displays the result which the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on embodiment of this invention estimated on the display. The functional block diagram which shows the functional structure of the 1st airflow condition prediction apparatus and the 1st spreading | diffusion condition prediction apparatus which are examples of the airflow condition prediction apparatus and diffusion state prediction apparatus which concern on embodiment of this invention. The flowchart (flowchart) which shows the process step of the 1st spreading | diffusion situation prediction procedure which a 1st spreading | diffusion situation prediction apparatus performs. Explanatory drawing explaining the observation point (P5) to add in a 1st airflow condition prediction apparatus and a 1st spreading | diffusion condition prediction apparatus. The functional block diagram which shows the functional structure of the 2nd airflow condition prediction apparatus which is an example of the airflow condition prediction apparatus which concerns on embodiment of this invention, and a 2nd diffusion condition prediction apparatus. The flowchart (flowchart) which shows the process step of the 2nd spreading | diffusion situation prediction procedure which a 2nd spreading | diffusion situation prediction apparatus performs. The functional block diagram which shows the functional structure of the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on the 3rd Embodiment of this invention. Explanatory drawing explaining narrowing of the wind direction which the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on the 3rd Embodiment of this invention perform. It is explanatory drawing explaining narrowing down of the analysis area which the airflow condition prediction apparatus and diffusion condition prediction apparatus concerning the 3rd Embodiment of this invention perform, (A) is an explanation which shows an example of the attention area before narrowing down the analysis area FIG. 4B is an explanatory diagram showing an example of the attention area after narrowing down the analysis area. The flowchart (flowchart) which shows the process step of the 4th spreading condition prediction procedure which the spreading condition prediction apparatus which concerns on the 3rd Embodiment of this invention performs. The functional block diagram which shows the functional structure of the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on the 4th Embodiment of this invention. Explanatory drawing explaining the example of the update of the airflow database which the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on the 4th Embodiment of this invention perform. The flowchart (flowchart) which shows the process step of the 5th spreading | diffusion condition prediction procedure which the spreading | diffusion condition prediction apparatus which concerns on the 4th Embodiment of this invention performs. The functional block diagram which shows the functional structure of the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on the 5th Embodiment of this invention. Explanatory drawing explaining the relationship between the reference | standard wind direction (8 directions) to set, the wind direction at the time of a diffusion event occurrence, and an attention area in the airflow condition prediction apparatus and diffusion condition prediction apparatus which concern on the 5th Embodiment of this invention. The flowchart (flowchart) which shows the process step of the 5th spreading condition prediction procedure which the spreading condition prediction apparatus which concerns on the 5th Embodiment of this invention performs. In the diffusion state prediction apparatus according to the fifth embodiment of the present invention, an example of a relationship between a reference wind direction to be set (eight directions), a wind direction at the time of occurrence of a diffusion event, a wind direction to be added as airflow data to an airflow database, and a region of interest. Explanatory drawing to explain.

  Hereinafter, an airflow state prediction device, an airflow state prediction method, a diffusion state prediction device, and a diffusion state prediction method according to embodiments of the present invention will be described with reference to the accompanying drawings.

  FIG. 1 is a schematic diagram illustrating a configuration example of an airflow state prediction apparatus and a diffusion state prediction apparatus according to an embodiment of the present invention.

  The airflow state prediction device according to the embodiment of the present invention is a device that predicts the airflow state of a region of interest, which is a predetermined region including a point of interest where a diffusion event has occurred. In addition, the diffusion state prediction device according to the embodiment of the present invention is a device that predicts the diffusion state of the diffusing substance released in the attention area using the airflow state predicted by the airflow state prediction device.

  The airflow state prediction apparatus and the diffusion state prediction apparatus according to the embodiment of the present invention are, for example, a program that causes a computer 1 that is hardware, an airflow state prediction apparatus, and a diffusion state prediction apparatus including the airflow state prediction apparatus (hereinafter, referred to as a program). , Referred to as “air flow / diffusion situation prediction PG”).

  The computer 1 includes a CPU (Central Processing Unit) 2 which is an example of a processor, a main storage device 3 such as a RAM (Random Access Memory), an auxiliary storage such as a ROM (Read Only Memory) and an HDD (Hard Disk Drive). The apparatus 4 includes an input device 5 such as a keyboard and a mouse, an output device 6 such as a display and a printer, and a communication unit 7 that communicates with an external device.

  The computer 1 can be connected to a calculation server 8 as an external device on the network via the communication unit 7, and causes the calculation server 8 to execute at least a part of arithmetic processing and receive an execution result. Can do.

  The computer 1 can be connected to an external device other than the calculation server 8 via a network. For example, the computer 1 and a site terminal (observation device) that transmits location information and observation result information can be connected to a network. In this case, it is possible to receive on-site positional information and observation result information via the communication unit 7.

  The auxiliary storage device 4 accessible by the CPU 2 such as a ROM has an airflow / diffusion state prediction PG 10 and an information database such as a map necessary for executing the airflow / diffusion state prediction PG 10 (hereinafter, the database is abbreviated as “DB”). 11. Airflow DB 12 is stored, data necessary for execution of airflow / diffusion state prediction PG10 and airflow / diffusion state prediction PG10 is loaded into main storage device 3 such as RAM, and processing according to this program is executed. .

  At this time, the CPU 2 functions as means for executing the airflow state prediction processing procedure and the diffusion state prediction processing procedure by the airflow / diffusion state prediction PG10. For example, in the example shown in FIG. 2 described later, the CPU 2 functions as an airflow calculation unit 24, a DB creation update unit 25, a comparison calculation unit 26, a display processing unit 27, and a diffusion calculation unit 31. The main storage device 3 such as a RAM provides a work area for temporarily storing programs and data executed by the CPU 2.

  The map information DB 11 includes, for example, map information of an area (attention area) to be subjected to numerical analysis set in a size of several hundreds m to several km squares, sizes of buildings and the like existing in the attention area, and It has at least position information (hereinafter referred to as “building information”). The map information held in the map information DB 11 and the building information of the attention area are associated with the position information, and the map information and building information in a predetermined range including the position information can be searched using the position information as a search key. . The map information and the building information are used when generating display information for displaying the analysis result together with the map.

  The airflow DB 12 obtains airflow data obtained by performing numerical analysis (airflow analysis) using a hydrodynamic model (CFD model) a plurality of times for a set region of interest under a situation where airflow elements including wind direction and wind speed are changed. (Airflow analysis result). The airflow data held by the airflow DB 12 is associated with the situation (case: Case) in which the airflow analysis is performed, and the airflow data corresponding to the situation can be searched using this situation as a search key.

  Note that the airflow DB 12 is preferably constructed in advance. The time required for a steady fluid calculation (million elements) in an urban area is usually about several hours, although it depends on the processing capacity of the CPU 2 of the computer 1. This is because the time for calculating the steady fluid necessary for constructing the DB 12 can be saved.

  The diffusion DB 13 includes diffusion data (diffusion analysis result) of a substance obtained by performing a plurality of times under a situation corresponding to each situation where the air flow analysis of the air flow DB 12 is performed. The diffusion data held by the diffusion DB 13 is associated with the situation (case: Case) in which the airflow analysis is performed, and the diffusion data of the substance corresponding to the situation can be searched using this situation as a search key. In addition, the diffusion DB 13 is created for each substance, and a DB to be used is selected according to the substance that predicts the diffusion state.

  It should be noted that the diffusion DB 13 is an optional component that is required when performing the diffusion analysis quickly when performing not only the airflow analysis but also the diffusion analysis. More specifically, when the computer 1 is made to function as a second diffusion state prediction device to be described later, that is, when airflow calculation and diffusion calculation are performed at once, other diffusion state prediction devices and airflow state prediction are required. It is not necessary when functioning as a device. Further, it is preferable that the diffusion DB 13 is constructed in advance similarly to the airflow DB 12.

  Next, functional configurations of the airflow state prediction device and the diffusion state prediction device according to the embodiment of the present invention will be described.

  FIG. 2 is a functional block diagram showing functional configurations of the airflow state prediction device 20 and the diffusion state prediction device 50 which are examples of the airflow state prediction device according to the embodiment of the present invention.

  The airflow condition prediction apparatus 20 includes an input unit 21, an output unit 22, a communication unit 23, an airflow calculation unit 24, a DB creation update unit 25, a comparison calculation unit 26, a display processing unit 27, a storage unit 28, and a control unit 29. . The diffusion state prediction device 50 includes an input unit 21, an output unit 22, a communication unit 23, an air flow calculation unit 24, a DB creation update unit 25, a comparison calculation unit 26, a display processing unit 27, and a storage included in the air flow state prediction device 20. In addition to the unit 28 and the control unit 29, a diffusion calculation unit 31 is further provided.

  The input unit 21 is realized by, for example, an input device connected to a computer via an interface or input means such as a keyboard or a mouse provided in the computer itself. The input unit 21 receives input of information and gives the received information to the control unit 29.

  The output unit 22 is realized by, for example, a display device such as a display device connected to the computer via an interface or a display provided in the computer itself, a printing means such as a printer connected via the interface to the computer, or the like. When receiving the display request, the output unit 22 displays the content corresponding to the display request on the screen. Further, when receiving the print request, the output unit 22 prints out the content corresponding to the print request.

  The communication unit 23 has a function of transmitting / receiving data to / from an external device such as the computer server 8 shown in FIG. The communication unit 23 transmits the data received from the control unit 29 to the external device, and gives the data transmitted from the external device to the control unit 29.

  For example, as shown in FIG. 3, the airflow calculation unit 24 performs an airflow analysis on the attention area 35 in which the set numerical fluid analysis (airflow analysis) is performed, and calculates a three-dimensional flow velocity distribution in the attention area 35. It has the function to do. The airflow calculation unit 24 solves, for example, two conservation equations of fluid mass and momentum and a transport equation of turbulent energy and energy dissipation rate using, for example, a k-ε turbulence model, and after one time step The fluid flow velocity, pressure, turbulent energy, and energy dissipation rate are calculated for each analysis mesh in the region of interest 35 to derive a spatial distribution of these physical quantities.

  The analysis mesh of the attention area 35, the building information existing in the attention area 35, the initial conditions of the flow velocity and pressure of the fluid in the attention area 35, and the initial parameters when performing the airflow analysis such as the boundary conditions are, for example, user input It is given to the airflow calculation unit 24 by being input from the input unit 21 by an operation or by reading initial parameter information held in a storage area that can be read by the airflow calculation unit 24.

  FIG. 3 is an explanatory diagram for explaining an example of the attention area 35 set by the airflow situation prediction apparatus 20 and the diffusion situation prediction apparatus 50. Here, the four alphabets N, E, S, and W shown in FIG. 3 mean north, east, south, and west directions, respectively.

  The attention area 35 is set as a three-dimensional space having a plurality of divided analysis meshes, for example, in a range of about several hundred meters to several kilometers, such as about 500 m in the east and west, about 500 m in the north and south, and about 500 m in height. When the airflow calculation unit 24 performs the numerical fluid analysis, the reference wind direction (for example, eight directions) and the reference wind speed (for example, the low speed side wind speed and the high speed defined by statistically processing the wind speed measured at the representative point in the region of interest) The three-dimensional flow velocity distribution in the region of interest 35 set under the condition (two conditions of the side wind speed) is calculated.

  Here, whether the speed is low or high is determined based on whether it is slower or faster than a threshold value to be set. As for the threshold value to be set, for example, a numerical value obtained by statistically estimating the wind speed generated in the attention area 35 from weather data such as AMEDAS at neighboring points is used.

  In addition, the numerical fluid analysis (airflow analysis) executed by the airflow calculation unit 24 can be performed including information on a building existing in the attention area 35. Since the building information inside the attention area 35 can be obtained separately by three-dimensional data based on the aerial survey point information, etc., the information on the buildings existing inside the attention area 35 is included by giving the obtained building information. Airflow analysis can be performed.

  The DB creation update unit 25 has a DB creation function for creating a new DB, and can use this DB creation function to newly create the airflow DB 12 and the diffusion DB 13. The DB creation / updating unit 25 has a DB update function for updating an existing DB, and the already created airflow DB 12 and diffusion DB 13 can be updated using this DB update function.

  4 and 5 are explanatory diagrams illustrating examples of the airflow DB 12 and the diffusion DB 13 that are referred to by the airflow state prediction device 20 and the diffusion state prediction device 50, respectively.

  The airflow DB 12 and the diffusion DB 13 are shown in FIGS. 4 and 5, respectively, when the airflow analysis and the diffusion analysis are performed in a plurality of cases such as 16 cases (wind direction: 8 directions × wind speed: 2 stages = 16 ways), for example. As described above, the airflow data and the diffusion data in each analysis mesh corresponding to the place in the attention area 35 are stored in association with each other for the 16 cases in which the airflow analysis and the diffusion analysis are performed.

  Here, the airflow data is information on airflow elements at a certain place in the attention area 35. For example, if it demonstrates by airflow DB12 shown by FIG. 4, the wind direction 1-1 and the wind speed 1-1 are airflow data in Case1 in the place P1. The diffusion data is information on diffusion elements at a certain location in the attention area 35. For example, in the case of the diffusion DB 13 shown in FIG. 5, the concentration 1-1 is diffusion data in Case 1 at the location P1.

  The DB update performed by the DB creation / updating unit 25 includes not only a change in data stored therein but also a change in the DB configuration such as an extension of the DB. For example, in the case of the airflow DB 12 shown in FIG. 4, for example, not only when the information in the cell such as the wind speed 1-1 is changed, but the number of rows (locations) and the number of columns (Case) are increased or decreased. If the DB configuration is changed, the DB is updated.

  The comparison calculation unit 26 has a function (DB collation function) for acquiring observation data of an observation point acquired from the input unit 21 or the communication unit 23 and airflow data including information on wind direction and wind speed at the observation point from the airflow DB 12, observation A function for calculating the degree of coincidence between the observation data at the point and the airflow data at the observation point of the airflow DB 12 (a degree of coincidence calculation function), and a weighted combination (weighting calculation averaging process) according to the degree of coincidence between the observation data and the airflow data ) (Weighting arithmetic averaging processing function).

  FIG. 6 is an explanatory diagram illustrating an example of a calculation result of the degree of coincidence of each airflow data (or diffusion data) calculated by the airflow state prediction device 20 and the diffusion state prediction device 50.

  When the airflow data at the observation point is extracted using the observation point information as a search key, the comparison calculation unit 26 calculates the degree of coincidence between the extracted airflow data and the observation data. For example, the calculation result of the degree of coincidence as shown in FIG. 6 can be obtained by calculating using the following equation (1) when there are k natural factors.

  As a factor of the above formula (1), for example, when the wind direction and the wind speed of the airflow element are acquired and compared, the following formulas (2) and (3) derived from the above formula (1) are used. The degree of coincidence between the observation data at the observation point and the airflow data at the observation point of the airflow DB 12 can be calculated.

  When the comparison calculation unit 26 calculates the degree of coincidence between the observation data at the observation point and the airflow data at the observation point of the airflow DB 12, the weighting combination (weighting calculation averaging) is performed according to the degree of coincidence between the observation data and the airflow data. Process) to calculate the predicted value of the wind velocity field in the region of interest 35. The predicted value of the wind speed field can be calculated using the following equation (6).

  Note that the description of the comparison calculation unit 26 described the case where the comparison calculation unit 26 calculates the airflow situation (predicted value of the wind velocity field) in the region of interest 35, but the diffusion situation (predicted value of the concentration field). The same applies to).

  That is, as in a second embodiment to be described later, the degree of coincidence between the observation data at the observation point and the diffusion data at the observation point of the diffusion DB 13 is calculated, and weighted combination (weighting calculation) is performed according to the calculated degree of coincidence. In the case of performing the averaging process), if a formula that takes diffusion factors into account as a factor is applied as in the above formula (3) and the wind velocity field in the above formula (6) is applied as a concentration field, the concentration field Can be calculated using the above equation (6).

  The display processing unit 27 has a function of generating display information for displaying information on display means such as a display. The display processing unit 27 displays, for example, information on the airflow calculation result performed by the airflow calculation unit 24, information on the diffusion calculation result performed by the diffusion calculation unit 31, and information on the result of coincidence calculation performed by the comparison operation unit 26. When received, display information for displaying the received content is generated, and the generated display information is given to the control unit 29. The display method may be initially set or may be set from the input unit 21 each time.

  7 and 8 are explanatory diagrams for explaining a display example in which the results predicted by the airflow state prediction device 20 and the diffusion state prediction device 50 are displayed on a display (display means) as the output unit 22.

  For example, as shown in FIG. 7, the display displays an airflow calculation result or a diffusion calculation result (hereinafter referred to as “airflow / diffusion calculation result”) 36 together with the observation point P on a map in the region of interest. Alternatively, as shown in FIG. 8, the coincidence calculation result 37 can be displayed together with the airflow / diffusion calculation result 36. Note that the display format of the information displayed on the display is not limited to that shown in FIGS. For example, the coincidence degree calculation result 37 can be displayed as a table as shown in FIG.

  The storage unit 28 includes a storage area where data can be read (read) and written (write), and has a function of holding data in the storage area. The airflow calculation unit 24, the DB creation update unit 25, the comparison calculation unit 26, the display processing unit 27, the control unit 29, and the diffusion calculation unit 31 access to read and write data.

  The storage unit 28 holds at least a map information DB 11 and an airflow DB 12 as data accessed by the airflow state prediction device 20 and the diffusion state prediction device 50. In addition, about the spreading | diffusion condition prediction apparatus 50, when performing the 2nd spreading | diffusion condition prediction procedure mentioned later, spreading | diffusion DB13 is further hold | maintained.

  The control unit 29 is a means for controlling the overall processing of the airflow state prediction device 20 or the diffusion state prediction device 50, and includes an input unit 21, an output unit 22, a communication unit 23, an airflow calculation unit 24, and a DB creation update unit 25. The comparison operation unit 26, the display processing unit 27, the storage unit 28, and the diffusion calculation unit 31 exchange data with each other and have a function of controlling them.

  When the control unit 29 receives information from the input unit 21, the output unit 22, the communication unit 23, the airflow calculation unit 24, the DB creation update unit 25, and the comparison calculation unit 26 according to the type of information received by the input unit 21. Then, a request is given to any one of the display processing unit 27, the storage unit 28, and the diffusion calculation unit 31 based on the received information.

  When receiving information from the communication unit 23, the control unit 29 outputs the output unit 22, the airflow calculation unit 24, the DB creation update unit 25, the comparison calculation unit 26, and the display processing unit 27 according to the type of information received from the communication unit 23. The received information is given to either the storage unit 28 or the diffusion calculation unit 31.

  When the air flow calculation result is received from the air flow calculation unit 24, the control unit 29 gives the received air flow calculation result to a processing unit to be used next such as the DB creation update unit 25, the comparison operation unit 26, or the diffusion calculation unit 31, for example. .

  Upon receiving the calculation result from the comparison calculation unit 26, the control unit 29 gives the calculation result to the display processing unit 27 to generate display information for displaying the calculation result when displaying the calculation result. In addition, when the diffusion calculation is further performed, the control unit 29 gives the calculation result to the diffusion calculation unit 31 and causes the diffusion calculation unit 31 to execute the diffusion calculation.

  Upon receiving the display information generated by the display processing unit 27, the control unit 29 gives the received display information to the output unit 22 as a display unit together with a display request. The output unit 22 displays display contents based on the given display information.

  Upon receiving the result of the diffusion calculation from the diffusion calculation unit 31, the control unit 29 gives the result of the diffusion calculation to the display processing unit 27, and generates display information for displaying the result of the diffusion calculation on the display processing unit 27. Let Further, when creating or updating the diffusion DB 13, the received diffusion calculation result is given to the DB creation updating unit 25.

  The diffusion calculation unit 31 included in the diffusion state prediction device 50 starts from at least one specified diffusion event occurrence point in the attention region 35 based on the airflow state prediction result of the attention region 35 calculated by the airflow state prediction device 20. It has a function of calculating the diffusion state (diffusion data) such as the concentration of the substance to be diffused and the concentration fluctuation, and predicting the diffusion state. Various diffusion event occurrence points can be envisaged depending on the event, and an example of such an event is a power plant exhaust port.

  Here, a diffusion analysis method applicable when the diffusion calculation unit 31 predicts the diffusion state of a substance may be appropriately selected from methods applicable for a person skilled in the art to calculate a concentration field from an airflow field. it can. Examples of diffusion analysis methods that can be applied in the diffusion calculation unit 31 include a method of obtaining spatial concentration information of a substance to be diffused by solving a scalar transport equation, and a spatial concentration information using a particle tracking method. There is a technique to seek.

  According to the airflow state prediction device 20 and the diffusion state prediction device 50 configured as described above, for example, intervals of several hundred meters to several kilometers, etc., compared to the conventional (the weather GPV wide-area weather data is several tens km to several hundred km intervals). Since the airflow DB 12 is created for the attention area 35 set in a relatively narrow area, the DB can be created in a much shorter time than in the past.

  Further, according to the airflow condition prediction apparatus 20, information on airflow elements such as wind speed and wind direction and diffusion elements such as the concentration of diffusing substances observed at a plurality of observation points in the region of interest 35, and position information on the observation points are displayed on the site. By providing as data, the field data is compared and compared with the airflow DB 12 using the given field data as a search key, and further, weighted arithmetic averaging processing is performed to obtain the airflow status (predicted value) at the time of the occurrence of the diffusion event The air flow status can be predicted accurately (with a few m intervals) quickly.

  Therefore, in order to perform the diffusion calculation based on the airflow situation predicted accurately and quickly by the airflow condition prediction device 20, the diffusion state prediction device 50 appropriately performs the evacuation from the diffusion material and the threat removal activity of the diffusion material. It is possible to accurately and quickly predict information on the concentration field of the diffusing substance that is effective for the purpose.

  Furthermore, according to the airflow state prediction device 20 and the diffusion state prediction device 50, the degree of coincidence with the input data can be visualized and displayed as shown in FIG. The user can be provided with materials for determining the necessity for selection or addition. In addition, according to the airflow situation prediction device 20 and the diffusion state prediction device 50, as shown in the above formulas (4), (5), etc., a separate and independent weighting formula can be adopted depending on the elements. In addition, it is possible to calculate a predicted value in consideration of the degree of influence of each element on the airflow state and the diffusion state, and the calculation accuracy can be further improved.

  Note that the airflow state prediction device 20 and the diffusion state prediction device 50 shown in FIG. 2 are merely examples, and are not limited to those as they are. The non-essential components may be deleted, or new components may be added as appropriate.

  Next, the airflow state prediction devices 20A to 20E and the diffusion state prediction devices 50A to 50E, which are examples of the airflow state prediction device 20 and the diffusion state prediction device 50, will be described. In the following description, components that are substantially the same as the components of the airflow state prediction device 20 and the diffusion state prediction device 50 are assigned the same reference numerals, and descriptions thereof are omitted.

(First embodiment)
FIG. 9 is a functional block diagram showing functional configurations of the first airflow situation prediction apparatus 20A and the first diffusion situation prediction apparatus 50A.

  20 A of 1st airflow condition prediction apparatuses are provided with the input part 21, the output part 22, the communication part 23, the comparison calculating part 26A, the display process part 27, and the control part 29, for example. In addition, the first diffusion state prediction device 50A further includes, for example, a diffusion calculation unit 31 with respect to the first airflow state prediction device 20A. The comparison operation unit 26A is an example of the comparison operation unit 26 having the above-described DB collation function, coincidence calculation function, and weighting operation averaging processing function.

  In addition, the first airflow condition prediction device 20A and the first diffusion state prediction device 50A described above are the airflow DB12 and the map information information DB11 that are the results of calculating the airflow data taking into account the influence of the building information in the region of interest. Is stored in a readable storage area.

  Such a first airflow condition prediction apparatus 20A executes, for example, a first airflow condition prediction procedure including processing steps as shown in FIG. 10 described later as an example of an airflow condition prediction method. In addition, the first diffusion state prediction device 50A including the first airflow state prediction device 20A includes, as an example of the diffusion state prediction method, for example, a first diffusion including processing steps as illustrated in FIG. Perform situation prediction procedures.

  FIG. 10 is a flowchart (flow chart) showing the processing steps of the first diffusion status prediction procedure executed by the first diffusion status prediction device 50A.

  In addition, since step S1-step S3 overlap with a 1st airflow condition prediction procedure among 1st spreading | diffusion condition prediction procedures (step S1-step S5), about description of a 1st airflow condition prediction procedure, The description of the diffusion status prediction procedure 1 is omitted.

  In the first diffusion state prediction procedure (step S1 to step S5), an execution command for diffusion state prediction is given from the input unit 21 to the control unit 29. Based on the execution command, the control unit 29 at least performs a comparison operation. A processing step is started by controlling the unit 26A, the display processing unit 27, and the diffusion calculation unit 31 (START).

  Location information of multiple observation points in the region of interest at the time of the event, information on the observation results of air flow elements such as wind speed and direction, and information on observation results of diffusion elements such as concentration (observation data) ) Is received by the comparison calculation unit 26A (step S1).

  The number of observation points is given to the input unit 21 when the user arbitrarily designates (inputs) some or all of the plurality of observation points observed at the site, for example. Further, the position information and observation data of the designated observation point are given to the input unit 21 by inputting the position information and observation data of the observation point designated by the user, for example. Information given to the input unit 21 is given to the control unit 29 and further given to the comparison operation unit 26A.

  When the comparison calculation unit 26A receives the position information of the plurality of observation points and the observation data of the observation points given from the input unit 21, following the step S1, the comparison calculation unit 26A, the observation data and airflow DB12 at the observation point. The airflow data at the observation point is compared (step S2).

  Subsequent to step S2, the comparison calculation unit 26A calculates the degree of coincidence between the observation data compared in step S2 and the airflow data, performs weighted combination processing according to the degree of coincidence, and determines the airflow state (wind velocity field). (Predicted value) is obtained (step S3).

  Subsequent to step S3, the diffusion calculation unit 31 calculates and predicts the diffusion state of the substance in the region of interest using the airflow state obtained by executing steps S1 to S3 (step S4). When the calculation result of the diffusion state of the substance is obtained, the display information relating to the calculation result is generated by the display processing unit and given to the display as the output unit (step S5). When step S5 is completed, the first diffusion status prediction procedure ends (END).

  In the first diffusion state prediction procedure described above, data is input from the input unit 21 and given to the control unit 29 in step S1, but the data given to the control unit 29 is externally transmitted via the communication unit 23. It may be input to the first airflow situation prediction device 20A and the first diffusion state prediction device 50A.

  For example, a function (position acquisition function) for acquiring observation point position (absolute position) information using GPS or the like, and a function for acquiring observation data by observing a desired airflow element and diffusion element (observation data acquisition function) ) And a data communication function with the first airflow state prediction device 20A and the first diffusion state prediction device 50A, the observation device and the first airflow state prediction device 20A Alternatively, the first diffusion state prediction device 50A may be connected via a network so that the communication unit 23 directly receives observation point position (absolute position) information and observation data from the observation device.

  In the first diffusion state prediction procedure described above, it has been described that the diffusion calculation (step S4) is executed by the diffusion calculation unit 31, but part or all of the diffusion calculation (step S4) is performed on the network as necessary. You may perform using the calculation server for the large-scale fluid calculation installed in.

  Furthermore, it is desirable that the airflow DB 12 is created by performing calculations in advance in consideration of a calculation load of a computer that functions as the first airflow state prediction device 20A or the first diffusion state prediction device 50A. If the computing processing capability of the computer permits, it may be created at the execution stage of the airflow state prediction procedure or the diffusion state prediction procedure.

  Furthermore, in the first diffusion state prediction procedure, when the calculation result of the diffusion state of the substance is displayed (step S5), the degree of coincidence between the observation data compared in step S2 and the airflow data may be displayed together. However, if there is a possibility that there is a problem with the location and the number of the selected observation points, such as the displayed degree of coincidence is low, the first diffusion state prediction procedure can be executed by selecting the observation points again. .

  FIG. 11 is an explanatory diagram for explaining an observation point (P5) to be added in the first airflow situation prediction device 20A and the first diffusion state prediction device 50A.

  In executing the first diffusion state prediction procedure, the airflow data stored in the airflow DB 12 used in step S2 is the wind direction in each analysis mesh set by dividing the region of interest into a mesh shape during the airflow analysis. Since it is information on the air current element, the location and the number of observation points can be arbitrarily set within the range of the location and the number of points of the analysis mesh associated with the information on the air current element.

  For example, the first diffusion state prediction procedure is executed using the observation data observed at the observation points P1 to P4 displayed in the airflow / diffusion calculation result 36 shown in FIG. If you want to execute the first diffusion status prediction procedure by adding observation data at the observation point where the observation was performed, for example, the observation you want to add from the observation points that were observed in the region of interest such as the observation point P5 The first diffusion state prediction procedure can be executed by giving the position information of the point and the observation data observed at the observation point.

  If it is desired to change the observation point used for airflow prediction or diffusion prediction, the observation point may be changed in step S1 to provide observation point position information and observation data observed at the observation point.

  According to the first airflow state prediction device 20A, the first diffusion state prediction device 50A, the first airflow state prediction procedure, and the first diffusion state prediction procedure, it is created in advance using given field data as a search key. Compared with the airflow DB 12 that has been stored, and further weighted arithmetic averaging processing is performed to obtain the airflow situation (predicted value) at the time of the occurrence of the diffusion event. Can be predicted.

  In addition, according to the first diffusion state prediction device 50A and the first diffusion state prediction procedure, the diffusion calculation is performed on the basis of the airflow state predicted by the first airflow state prediction device 20A accurately and quickly. It is possible to accurately and quickly predict information on the concentration field of the diffusing material, which is effective for appropriately evacuating from the material and removing the threat of the diffusing material.

  Furthermore, an observation apparatus (site terminal) having a position acquisition function, an observation data acquisition function, and a data communication function with the first airflow condition prediction apparatus 20A and the first diffusion state prediction apparatus 50A is applied, and this observation is performed. If the communication unit 23 is configured to receive the position information and observation data of the observation point directly from the device, the designated observation point can be specified by designating the observation point that the user wants to use from the observation points actually observed. The first airflow condition prediction procedure and the first diffusion condition prediction procedure can be executed by acquiring the position information and the observation data.

  Further, in the first airflow situation prediction device 20A, the first diffusion state prediction device 50A, the first airflow situation prediction procedure, and the first diffusion state prediction procedure, the user can select from the observation points actually observed. Since the observation point used for prediction of the air current situation or the diffusion situation can be specified, there is a building (obstacle) with a difference in elevation, such as an urban area, and the area of interest 35 is affected by the obstacle. Even in areas where the airflow and diffusion conditions change in a complex manner, it is possible to select appropriate observation points and provide observation data, so the overall results are not affected by local flow. It is possible to avoid a decrease in the prediction accuracy of the air current situation and the diffusion situation.

(Second embodiment)
FIG. 12 is a functional block diagram showing functional configurations of the second airflow situation prediction device 20B and the second diffusion situation prediction device 50B.

  The second airflow situation prediction device 20B has substantially the same configuration as the first airflow situation prediction device 20A, while the second diffusion state prediction device 50B is different from the first diffusion state prediction device 50A. Thus, it differs from the first diffusion status prediction device 50A in that the diffusion DB 13 is further held and the diffusion calculation unit 31 is not provided.

  More specifically, in the first diffusion state prediction device 50A, the result obtained by weighting and combining the respective airflow data obtained by the first airflow state prediction device 20A is given to the diffusion calculation unit 31 to obtain the diffusion calculation result. On the other hand, in the second diffusion state prediction device 50B, the comparison calculation unit 26A weights and combines the respective diffusion data obtained by comparing the data acquired by field observation with the airflow DB12 and the diffusion DB13. The difference is that the diffusion calculation result is obtained.

  Therefore, in the description of the second embodiment, differences from the first diffusion state prediction device 50A will be mainly described, and the components and processing steps that are not substantially different from the first airflow state prediction device 20A are the same. Reference numerals are omitted.

  The second diffusion status prediction device 50B and the second diffusion status prediction device 50B described above hold the map information DB 11, the airflow DB 12, and the diffusion DB 13 in a readable storage area.

  The second airflow condition prediction device 20B includes, for example, an input unit 21, an output unit 22, a communication unit 23, a comparison calculation unit 26A, a display processing unit 27, and a control unit 29. In addition, the second diffusion state prediction device 50B includes a second airflow state prediction device 20B, and the comparison calculation unit 26A of the second airflow state prediction device 20B uses the diffusion DB 13 to predict the diffusion state.

  In the second diffusion state prediction device 50B configured as described above, the diffusion calculation unit 31 performs the first diffusion state prediction device 50A without including the diffusion calculation unit 31 that predicts the diffusion state of the substance. By configuring the diffusion state prediction so that the data of the diffusion DB 13 can be acquired, the comparison operation unit 26A can predict the diffusion state.

  The comparison operation unit 26A of the second diffusion state prediction device 50B obtains the observation data of each observation point, and the diffusion data of the observation point stored in the diffusion DB 13 that obtains at least the concentration of the substance that predicts the diffusion state. The degree of coincidence is obtained by comparing the two, weighted arithmetic averaging processing is performed according to the obtained degree of coincidence, and the diffusion state is predicted.

  Next, as an example of the diffusion state prediction method, a second diffusion state prediction procedure performed by the second diffusion state prediction device 50B will be described.

  FIG. 13 is a flowchart (flow chart) showing the processing steps of the second diffusion status prediction procedure executed by the second diffusion status prediction device 50B.

  The second diffusion status prediction procedure is different from the first diffusion status prediction procedure in that it includes steps S11 and S12 instead of steps S3 and S4, but the other processing steps are substantially the same. The same as above. Therefore, in the description of the second diffusion status prediction procedure, processing steps that are not substantially different from the first diffusion status prediction procedure are denoted by the same reference numerals (processing step numbers), and description thereof is omitted. In addition, the second airflow condition prediction procedure performed by the second airflow condition prediction device 20B is substantially the same as the first airflow condition prediction procedure, and therefore the second airflow condition will be described with the description of the first airflow condition prediction procedure. Description of the situation prediction procedure is omitted.

  In the second diffusion status prediction procedure, a processing step is started (START), and the comparison operation unit 26A compares the position information of a plurality of observation points in the attention area and the observation data observed at the observation point when the event occurs. When received (step S1), the comparison calculation unit 26A compares the observation data at the observation point with the airflow data at the observation point in the airflow DB 12 (step S2).

  When step S2 is completed, the processing step of the second airflow condition prediction procedure proceeds to step S11. In step S11, the position information of the plurality of observation points received by the comparison calculation unit 26A and the observation data of the diffusion element such as the concentration of the diffusion material among the observation data at the observation point, and the diffusion DB 13 for the diffusion material The diffusion data at the observation point is compared (step S11).

Subsequent to step S11, the comparison calculation unit 26A calculates the degree of coincidence between the observation data compared in step S2 and step S11, the airflow data, and the diffusion data, and performs weighted combination processing according to the degree of coincidence. Then, the diffusion state (predicted value of the concentration field) is calculated (step S12). Matching degree calculated in step S12, for example, there are factors of the wind direction and wind velocity as a stream elements, if there is a factor of the concentration as the diffusion element, the above-mentioned formula (3) in F _t concentrations (other than wind direction and wind speed Factor).

  In the processing step of the second airflow condition prediction procedure, when step S12 is completed, display information related to the calculation result of step S12 is generated and given to the display as the output unit (step S5). When step S5 is completed, all processing steps are terminated (END).

  According to the second airflow state prediction device 20B, the second diffusion state prediction device 50B, the second airflow state prediction procedure, and the second diffusion state prediction procedure, the first airflow state prediction device 20A, the first diffusion The effect similar to that of the situation prediction device 50A, the first airflow situation prediction procedure, and the first diffusion situation prediction procedure can be obtained, and the diffusion element is also measured at the observation point, and the observation data and the diffusion DB 13 at the observation point are measured. The degree of coincidence is obtained by comparing with the diffusion data stored in, and the weighting calculation averaging process according to the degree of coincidence is performed, whereby the diffusion state (predicted value) at the time of the occurrence of the diffusion event can be obtained.

  That is, according to the second airflow state prediction device 20B, the second diffusion state prediction device 50B, the second airflow state prediction procedure, and the second diffusion state prediction procedure, the diffusion analysis is performed after the diffusion DB 13 is created. In addition, it is possible to accurately and quickly predict the diffusion state of the substance that diffuses in the event of a disaster (at intervals of several meters). Therefore, if the diffusion DB 13 is created in advance, the diffusion state can be predicted with a smaller calculation load than other diffusion state prediction devices and diffusion state prediction procedures for performing diffusion analysis.

  In the second embodiment described above, each of the diffusion data is obtained by causing the comparison operation unit 26A of the first airflow condition prediction apparatus 20A to compare the acquired observation data with the airflow DB12 and the diffusion DB13. Although it is an example of the 2nd spreading | diffusion condition prediction apparatus 50B, it comprises the comparison calculating part 26 (26A, 26B) of the 3rd airflow condition prediction apparatus 20C etc. which are mentioned later instead of the 1st airflow condition prediction apparatus 20A. Other airflow state prediction devices can also be applied.

(Third embodiment)
FIG. 14 is a functional block diagram showing functional configurations of the third airflow situation prediction device 20C and the third diffusion state prediction device 50C.

  The third airflow state prediction device 20C and the third diffusion state prediction device 50C are, for example, the other airflow state prediction devices 20 and the diffusion state such as the first airflow state prediction device 20A and the first diffusion state prediction device 50A. The prediction device 50 is different from the prediction device 50 in that a comparison calculation unit 26B is provided instead of the comparison calculation unit 26A, but the other points are not substantially different. Therefore, in the description of the third embodiment, the processing steps executed by the comparison calculation unit 26B and the comparison calculation unit 26B will be mainly described, and substantially the same as the first airflow state prediction device 20A and the first diffusion state prediction device 50A. Constituent elements and processing steps that are not different from each other are designated by the same reference numerals and are omitted.

  The third airflow condition prediction device 20C includes, for example, an input unit 21, an output unit 22, a communication unit 23, a comparison calculation unit 26B, a display processing unit 27, and a control unit 29. The third diffusion state prediction device 50C further includes a diffusion calculation unit 31 with respect to the third airflow state prediction device 20C, for example. The comparison calculation unit 26B has a function of narrowing down the wind direction and area when performing weighted combination processing according to the degree of coincidence obtained by comparing the observation data with the airflow data in the airflow DB 12 (hereinafter simply referred to as “restriction”). This is an example of the comparison operation unit 26 to which “function” is further added.

  The comparison calculation unit 26B is out of a predetermined range such that, for example, the azimuth angle with respect to the observed wind direction exceeds 45 degrees among the wind directions set in the airflow data stored in the airflow DB 12 using the narrowing function. Regarding the direction, it is determined that the relationship with the observed wind direction is low, and it can be excluded from the calculation target of the airflow state prediction procedure and the diffusion state prediction procedure. The range of narrowing down the wind direction may be set in advance, or may be set when the airflow state prediction procedure and the diffusion state prediction procedure are executed.

  FIG. 15 is an explanatory diagram for explaining the narrowing of the wind direction performed by the third airflow condition predicting device 20C and the third diffusion condition predicting device 50C (more specifically, the comparison calculation unit 26B).

  When the narrowing of the wind direction is described in the example shown in FIG. 15, if the wind direction observed at the observation point (shown by a double circle in FIG. 15) is northwest (NW), it is adjacent to the observed northwest. The north (N) and the west (W) are set within a predetermined range (shown by being circled in FIG. 15), and the other directions are directions outside the predetermined range.

  In addition, the comparison calculation unit 26B uses the narrowing-down function, and the observation selected when executing the airflow state prediction procedure and the diffusion state prediction procedure from the attention area set when the airflow data stored in the airflow DB 12 is obtained. It is possible to narrow down to a predetermined area including all the points, and to exclude the outside of the narrowed area from the execution targets of the airflow state prediction procedure and the diffusion state prediction procedure.

  FIG. 16 is an explanatory diagram for explaining the analysis area narrowing performed by the comparison calculation unit 26B. FIG. 16A is an explanatory diagram showing an example of the attention area (attention area 35A) before narrowing down the analysis area. B) is an explanatory view showing an example of an attention area (attention area 35B) after narrowing down the analysis area.

  Reference numeral 35A denotes the entire attention area set when obtaining the airflow data stored in the airflow DB 12, 35B denotes the attention area after narrowing down, and P1 to P4 denote the execution of the airflow condition prediction procedure and the diffusion condition prediction procedure, respectively. Is the selected observation point.

  If the analysis region is narrowed down in the example shown in FIG. 16A and FIG. 16B, the region to be predicted for the airflow state and the diffusion state is determined from the attention region 35A and the airflow state prediction procedure and the diffusion state prediction. The attention area 35B including all of the observation points P1 to P4 selected when the procedure is executed is narrowed down, and the outside of the attention area 35B is excluded from execution targets of the airflow condition prediction procedure and the diffusion condition prediction procedure.

  As described above, in the third airflow situation prediction device 20C and the third diffusion state prediction device 50C, the attention area 35A is set as an analysis area (analysis space), and weighted combination processing is performed on all airflow data in the analysis space. Considering that the calculation load is large, the observation area close to a plurality of observation points is set as the attention area 35B, and weighted combination processing is performed using only the airflow data in the attention area 35B, thereby reducing the calculation load. Can be achieved.

  In the airflow state prediction apparatus and the diffusion state prediction apparatus according to the embodiment of the present invention, for example, several hundreds of meters to several kilometers are assumed as the length in one direction of the attention area 35A. Therefore, in the third airflow situation prediction apparatus 20C and the third diffusion situation prediction apparatus 50C, the length in one direction of the attention area 35B after narrowing down the analysis area is shorter than the attention area 35A, for example, several tens of meters to several 100m is assumed.

  Here, the size of the attention area 35A shown in FIG. 16 is 500 m in the east-west direction, 500 m in the north-south direction, and 500 m in the height direction, and the size of the attention area 35B shown in FIG. 16 is 100 m in the east-west direction. If the distance is 100 m in the north-south direction and 100 m in the height direction, the size of the space is 1/125, so that the amount of airflow data necessary for the calculation can be reduced to the same extent. The range (size) of the attention area 35B may be set in advance, or may be set when the airflow state prediction procedure and the diffusion state prediction procedure are executed.

  In the third airflow state prediction device 20C and the third diffusion state prediction device 50C capable of excluding (omitting) the wind direction and a part of the analysis region from the execution targets of the airflow state prediction procedure and the diffusion state prediction procedure, the first diffusion The number of cases to be compared with the airflow DB 12 in the situation prediction procedure (step S2), the calculation amount of the weighted combination calculation process (step S3), and the calculation amount of the diffusion calculation (step S4) can be reduced, thereby reducing the calculation load. Can do. The reduction of the calculation load is particularly effective when the airflow state prediction device 20 and the diffusion state prediction device 50 cannot connect to the computer server via the network (in the case of stand-alone).

  Next, as an example of the diffusion state prediction method, a third diffusion state prediction procedure performed by the third diffusion state prediction device 50C will be described.

  FIG. 17 is a flowchart (flow chart) showing the processing steps of the third diffusion state prediction procedure executed by the third diffusion state prediction device 50C.

  The third diffusion state prediction procedure is different from the first diffusion state prediction procedure in that it further includes step S21 and step S22, but the other processing steps are substantially the same. Therefore, in the description of the third spreading state prediction procedure, processing steps that are not substantially different from the first spreading state prediction procedure are denoted by the same reference numerals (processing step numbers), and description thereof is omitted.

  Further, in view of the fact that the third airflow situation prediction procedure overlaps except for steps S4 and S5 of the third diffusion situation prediction procedure, the third airflow situation prediction procedure will be described with the description of the third diffusion situation prediction procedure. Description is omitted.

  In the third diffusion status prediction procedure, a processing step is started (START), and the comparison operation unit 26B compares the position information of a plurality of observation points in the attention area and the observation data observed at the observation point when the event occurs. Receive (step S1).

  Here, when narrowing down the wind direction and predicting the diffusion state, the comparison calculation unit 26B acquires information on the narrowed down range that has been set, and selects (narrows down) the wind direction (step S21). Then, the comparison calculation unit 26B compares the observation data at the observation point with the airflow data at the observation point in the airflow DB 12 (step S2). The airflow data in the airflow DB 12 used for comparison with the observation data is within the range of the narrowed wind direction, and is not used for those outside the narrowed wind direction.

  Further, when narrowing down the analysis region and predicting the diffusion state, the comparison calculation unit 26B acquires information on the narrowed down range set and selects (narrows down) the analysis region (step S22). Then, the airflow data in the analysis region narrowed down by the comparison calculation unit 26B is weighted and combined (step S3). Step S3 and subsequent steps are the same as the first diffusion status prediction procedure.

  Note that, in the example of the third diffusion state prediction procedure shown in FIG. 17, both step S21 and step S22 are included, but either one of step S21 or step S22 may be omitted. Further, in the third diffusion state prediction procedure, as long as step S21 is before step S2 and step S22 is before step S3, the order is not limited to the order shown in FIG.

  According to the third airflow state prediction device 20C, the third diffusion state prediction device 50C, the third airflow state prediction procedure, and the third diffusion state prediction procedure, the first airflow state prediction device 20A, the first diffusion The effects similar to those of the situation prediction device 50A, the first airflow situation prediction procedure, and the first diffusion situation prediction procedure can be obtained, and the calculation load can be further reduced. Therefore, the airflow state and the diffusion state are predicted more quickly than the first airflow state prediction device 20A, the first diffusion state prediction device 50A, the first airflow state prediction procedure, and the first diffusion state prediction procedure. Can do.

  In addition, although the 3rd Example mentioned above is an example which further added the narrowing-down function to the comparison calculating part 26A of 20 A of 1st airflow condition prediction apparatuses, application is limited to 20 A of 1st airflow condition prediction apparatuses. However, the present invention can be applied to other airflow state prediction devices including the comparison calculation unit 26 (26A, 26B).

(Fourth embodiment)
FIG. 18 is a functional block diagram showing a functional configuration of the fourth airflow situation prediction device 20D and the fourth diffusion state prediction device 50D.

  The fourth airflow state prediction device 20D and the fourth diffusion state prediction device 50D are different from the first airflow state prediction device 20A and the first diffusion state prediction device 50A in that a DB creation update unit 25 is further provided. Although different, other points are not substantially different. Therefore, in the description of the fourth embodiment, the processing steps executed by the DB creation / updating unit 25 and the DB creation / updating unit 25 will be mainly described, and the first airflow state prediction device 20A and the first diffusion state prediction device 50A. Components and processing steps that are not substantially different from those in FIG.

  The fourth airflow condition prediction apparatus 20D includes, for example, an input unit 21, an output unit 22, a communication unit 23, a DB creation update unit 25, a comparison calculation unit 26A, a display processing unit 27, and a control unit 29. It comprises. The fourth diffusion state prediction device 50D further includes a diffusion calculation unit 31 with respect to, for example, the fourth airflow state prediction device 20D. The DB creation update unit 25 creates and updates the airflow DB 12 read by the comparison calculation unit 26A using the DB creation function and the DB update function.

  FIG. 19 is an explanatory diagram illustrating an update example of the airflow DB 12 performed by the DB creation / updating unit 25 of the fourth airflow state prediction device 20D and the fourth diffusion state prediction device 50D. Here, reference numeral 38 shown in FIG. 19 is a diffusion event occurrence point, and MP1 and MP2 are monitor observation points.

  For example, as shown in FIG. 19, when there are monitor observation points MP1 and MP2 that are constantly observed in the region of interest, the information of the monitor observation points MP1 and MP2 can be used. That is, the observation results of the monitor observation points MP1 and MP2 can be reflected (updated) in the airflow DB 12. In this case, when the user performs a DB update operation and gives position information and observation data of the monitor observation points MP1 and MP2, the DB creation update unit 25 updates the airflow data at the monitor observation points MP1 and MP2.

  On the other hand, even when there is no monitor observation point in the attention area 35, if a weather observation station such as AMEDAS exists in the vicinity of the attention area 35, the observation data observed at the observation station is interpolated or extrapolated. Insertion (internal / external) can also be used. In this case, the DB creation / updating unit 25 has a data interpolation / extrapolation function, and the user performs the DB update operation, thereby providing the position information and observation data of the monitor observation point to be used. 25 reflects (updates) the result obtained by performing interpolation / extrapolation of data in the airflow data DB 12.

  Next, as an example of the diffusion state prediction method, a fourth diffusion state prediction procedure performed by the fourth diffusion state prediction device 50D will be described.

  FIG. 20 is a flowchart (flow chart) showing the processing steps of the fourth diffusion state prediction procedure executed by the fourth diffusion state prediction device 50D.

  The fourth diffusion state prediction procedure is different from the first diffusion state prediction procedure in that it further includes step S31 and step S32, but the other processing steps are substantially the same. Therefore, in the description of the fourth spreading state prediction procedure, processing steps that are not substantially different from the first spreading state prediction procedure are denoted by the same reference numerals (processing step numbers) and description thereof is omitted.

  Further, in view of the fact that the fourth airflow condition prediction procedure is duplicated except for steps S4 and S5 of the fourth diffusion condition prediction procedure, the fourth airflow condition prediction procedure will be described with the description of the fourth diffusion condition prediction procedure. Description is omitted.

  In the fourth diffusion status prediction procedure, a processing step is started (START), and the comparison calculation unit 26A compares the position information of a plurality of observation points in the attention area and the observation data observed at the observation point when the event occurs. Receive (step S1). On the other hand, when using observation data of monitor observation points that are constantly observed in the region of interest, create a DB of monitor observation point position information and observation data observed at the monitor observation points (monitor observation data) The updating unit 25 receives (step S31), associates the received position information of the monitor observation point with the monitor observation data of the monitor observation point, adds the airflow DB12, and updates the airflow DB12 (step S32).

  When step S32 is completed, the fourth diffusion state prediction procedure proceeds to step S2. The processing steps after step S2 are the same as those after step S2 of the first diffusion state prediction procedure except that the processing steps are executed using the airflow DB 12 updated in step S32.

  In the example of the fourth diffusion state prediction procedure shown in FIG. 20, step S31 is executed after step S1, but as long as it is before step S32, the order is not limited to that shown in FIG. May be executed at any time.

  According to the fourth airflow state prediction device 20D, the fourth diffusion state prediction device 50D, the fourth airflow state prediction procedure, and the fourth diffusion state prediction procedure, the first airflow state prediction device 20A, the first diffusion The DB creating / updating unit 25 having a DB update function can always obtain the same effects as those of the situation prediction device 50A, the first airflow situation prediction procedure, and the first diffusion situation prediction procedure. When there is a monitor observation point being observed, the observation data of the monitor observation point can be reflected (updated) in the airflow DB 12, so that the airflow state and the diffusion state can be predicted with higher accuracy.

  In addition, if the DB creation / updating unit 25 of the fourth airflow state prediction device 20D and the fourth diffusion state prediction device 50D is provided with a data extrapolation function, a weather station such as AMEDAS in the vicinity of the region of interest 35. Since the airflow data obtained by interpolating the observation data at the weather station can be reflected (updated) in the airflow DB 12 when the airflow is present, the airflow state and the diffusion state can be predicted with higher accuracy.

  In addition, although the 4th Example mentioned above is an example which further comprises DB creation update part 25 with respect to 20 A of 1st airflow condition prediction apparatuses, application is limited to 20 A of 1st airflow condition prediction apparatuses. Instead of this, it is possible to construct an airflow condition prediction apparatus that further includes a DB creation update unit 25 with respect to another airflow condition prediction apparatus such as the second airflow condition prediction apparatus 20B.

(Fifth embodiment)
FIG. 21 is a functional block diagram showing functional configurations of the fifth airflow situation prediction apparatus 20E and the fifth diffusion situation prediction apparatus 50E.

  The fifth airflow state prediction device 20E and the fifth diffusion state prediction device 50E are devices that predict the airflow state and the diffusion state by reflecting observation data such as AMEDAS when the diffusion event occurs, for example, Even when the wind direction other than the direction set as the wind direction of the attention area 35 is observed, the airflow DB 12 is configured to be expandable even if the acquired observation data is data corresponding to a case where the acquired observation data is not prepared in the airflow DB 12. This enables comparison and collation with observation data, calculation of the degree of coincidence, and weighted combination.

  The fifth airflow state prediction device 20E and the fifth diffusion state prediction device 50E are different from the fourth airflow state prediction device 20D and the fourth diffusion state prediction device 50D in that an airflow calculation unit 24 is further provided. However, other points are not substantially different. Therefore, in the description of the fifth embodiment, the airflow calculation unit 24 and the processing steps executed by the airflow calculation unit 24 will be mainly described, and substantially the same as the fourth airflow state prediction device 20D and the fourth diffusion state prediction device 50D. Constituent elements and processing steps that are not different from each other are designated by the same reference numerals and are omitted.

  The fifth airflow condition prediction apparatus 20E includes, for example, an input unit 21, an output unit 22, a communication unit 23, an airflow calculation unit 24, a DB creation update unit 25, a comparison calculation unit 26A, and a display processing unit 27. And a control unit 29. The fifth diffusion state prediction device 50E further includes a diffusion calculation unit 31 with respect to, for example, the first airflow state prediction device 20A.

  In the fifth airflow state prediction device 20E and the fifth diffusion state prediction device 50E, the airflow calculation unit 24 having an airflow analysis function is newly performed using the added airflow element as a boundary condition, and the DB creation update unit 25 Uses the DB update function to add (expand) the result of the airflow analysis performed by the airflow calculation unit 24 to the airflow DB12 and update the airflow DB12. The comparison operation unit 26A uses the updated (expanded) airflow DB 12 for comparison and comparison with observation data, calculation of the degree of coincidence, and weighted combination (weighted operation averaging process).

  In the fifth embodiment described above, an example of a fifth airflow condition prediction apparatus 20E that further includes an airflow calculation unit 24 and a DB creation update unit 25 with respect to the first airflow condition prediction apparatus 20A will be described. However, it is good also as an airflow condition prediction apparatus which further provided the airflow calculation part 24 and DB creation update part 25 with respect to other airflow condition prediction apparatuses, such as the 2nd airflow condition prediction apparatus 20B.

  In the fifth embodiment described above, the fifth airflow condition prediction apparatus 20E includes the airflow calculation unit 24, but the airflow calculation unit 24 does not necessarily have to be included. If it is assumed that the additional airflow calculation calculated by the airflow calculation unit 24 is performed externally and the DB creation update unit 25 reflects the additional airflow calculation result received from the communication unit 23 in the airflow DB 12, the airflow calculation unit 24 It can also be set as the 5th airflow condition prediction apparatus 20E which does not comprise.

  FIG. 22 shows an example of the relationship between the reference wind direction (eight directions) to be set, the wind direction 39 when a diffusion event occurs, and the region of interest 35 in the fifth airflow state prediction device 20E and the fifth diffusion state prediction device 50E. It is explanatory drawing demonstrated.

  In the example shown in FIG. 22, according to the weather information of observation points such as AMEDAS in the vicinity of the attention area, the wind direction 39 of the attention area 35 was substantially north-northwest (NNW) when the diffusion event occurred. Is shown. Explaining with the example shown in FIG. 22, since the north north-northwest (NNW) wind, which is a direction other than the eight directions set as the wind direction of the region of interest 35, is observed, the airflow data of the case corresponding to the observation data Does not exist in the airflow DB 12. In other words, the observation data cannot be compared with the airflow data as it is.

  Therefore, the fifth airflow condition prediction device 20E and the fifth diffusion state prediction device 50E give boundary conditions for airflow analysis of the attention area 35 based on the weather information at the time of the occurrence of the diffusion event, and in the given conditions Performing airflow analysis and adding (expanding) the obtained results to the airflow DB 12, even if a wind other than the reference wind direction that is not initially set is observed, it is compared and matched with the observed data. The calculation of the degree and the weighted combination (weighted arithmetic averaging process) are enabled.

  Note that the fifth airflow condition prediction apparatus 20E and the fifth diffusion condition prediction apparatus 50E shown in FIG. 21 include the airflow calculation unit 24 that performs airflow analysis in the apparatus, but actually performs the airflow analysis. In this case, an external computer server connected via a network or the like may be used. By calculating the calculation required for the airflow analysis with a computer server having a high processing capability, the airflow DB 12 can be updated in a shorter time than the case where the calculation is performed in the apparatus itself (stand-alone). Moreover, the building information of the attention area 35 required when performing the airflow analysis can be given from the input unit 21, for example, but can also be read and acquired from the map information DB 11.

  Next, as an example of the diffusion state prediction method, a fifth diffusion state prediction procedure performed by the fifth diffusion state prediction device 50E will be described.

  FIG. 23 is a flowchart (flow chart) showing the processing steps of the fifth diffusion status prediction procedure executed by the fifth diffusion status prediction device 50E.

  The fifth diffusion status prediction procedure is different from the fourth diffusion status prediction procedure in that step S41 is provided instead of step S31, but the other processing steps are substantially the same. Therefore, in the description of the fifth spreading state prediction procedure, processing steps that are not substantially different from the fourth spreading state prediction procedure are denoted by the same reference numerals (processing step numbers), and description thereof is omitted.

  Note that the fifth airflow condition prediction procedure is performed on the assumption that the airflow condition and the diffusion state are reflected reflecting the weather information of observation points such as AMEDAS in the vicinity of the attention area 35. Further, in view of the fact that the fifth airflow situation prediction procedure is duplicated except for steps S4 and S5 of the fifth diffusion situation prediction procedure, the fifth airflow situation prediction procedure will be described with the description of the fifth diffusion situation prediction procedure. Description is omitted.

  In the fifth diffusion status prediction procedure, a processing step is started (START), and the comparison calculation unit 26A compares the position information of a plurality of observation points in the attention area and the observation data observed at the observation point when the event occurs. Receive (step S1). At this time, if the wind direction of the observation point is a direction other than the direction set as the wind direction of the attention area 35 as the weather information of the observation point such as AMEDAS in the vicinity of the attention area 35, additional airflow calculation is required. (Step S41).

  When the fifth airflow state prediction device 20E and the fifth diffusion state prediction device 50E execute the additional airflow calculation (step S41) using the airflow calculation unit 24 in the own device or an external computer server connected to the network. The result of the additional airflow calculation is added to the airflow DB 12, and the airflow DB 12 is updated (expanded) (step S32). The processing steps after step S32 are the same as the processing steps after step S32 in the fourth diffusion state prediction procedure.

  According to the fifth airflow state prediction device 20E, the fifth diffusion state prediction device 50E, the fifth airflow state prediction procedure, and the fifth diffusion state prediction procedure, the fourth airflow state prediction device 20D, the fourth diffusion Since the same effect as the situation prediction device 50D, the fourth airflow situation prediction procedure, and the fourth diffusion situation prediction procedure can be obtained, and a new airflow analysis (additional airflow calculation) can be performed, the obtained observations are obtained. Even if the airflow data of the case corresponding to the data is not stored in the airflow DB 12, it is possible to cope with the need to update the airflow DB12.

  That is, according to the fifth airflow situation prediction device 20E, the fifth diffusion state prediction device 50E, the fifth airflow state prediction procedure, and the fifth diffusion state prediction procedure, the airflow data of the case corresponding to the acquired observation data Is not stored in the airflow DB 12, additional airflow calculation is performed, and the obtained result is reflected (updated) in the airflow DB 12, followed by comparison with the observation data, calculation of coincidence, and weighted combination Since (weighting calculation averaging process) can be performed, the airflow state and the diffusion state can be predicted with higher accuracy.

  In addition, the example of the 5th airflow condition prediction apparatus 20E mentioned above, the 5th spreading | diffusion condition prediction apparatus 50E, the 5th airflow condition prediction procedure, and the 5th spreading | diffusion condition prediction procedure is a case corresponding to the acquired observation data. In this example, the airflow data is not stored in the airflow DB 12 and only the airflow data necessary for executing the airflow state prediction procedure and the diffusion state prediction procedure is added to the airflow DB 12. Any number is possible as long as the airflow data of the case corresponding to the data is included.

  FIG. 24 shows the reference wind direction (eight directions) to be set, the wind direction 39 when a diffusion event occurs, and the wind direction to be added to the airflow DB 12 as the airflow data in the fifth airflow state prediction device 20E and the fifth diffusion state prediction device 50E. 41 is an explanatory diagram for explaining an example of the relationship between 41 and a region of interest 35. FIG.

  In the example shown in FIG. 24, according to meteorological information of observation points such as AMEDAS in the vicinity of the attention area, the wind direction 39 of the attention area 35 was substantially north-northwest (NNW) when the diffusion event occurred. Is shown. In the example shown in FIG. 24, in addition to the north-northwest (NNW) wind direction observed in the attention area 35 as the wind direction 39 at the time of the occurrence of the diffusion event, for example, it is close to the wind direction 39 at the time of the observed diffusion event. When there are other cases of the wind direction 41 that you want to add to the airflow DB 12, such as the wind direction, perform the airflow analysis for wind directions other than north-northwest observed at the time of the diffusion event, such as west-northwest (WNW). Can be reflected (added) to the airflow DB 12.

  In addition, the fifth airflow condition prediction device 20E, the fifth diffusion state prediction device 50E, the fifth airflow condition prediction procedure, and the fifth diffusion state prediction procedure are the results of newly performed airflow analysis (additional airflow calculation). Can be applied regardless of whether or not the airflow data of the case corresponding to the acquired observation data is stored in the airflow DB12.

  As described above, according to the airflow state prediction device 20, the diffusion state prediction device 50, the airflow state prediction procedure, and the diffusion state prediction procedure, the comparison verification operation with the airflow DB 12 created in advance using the given field data as a search key. Furthermore, since the weighting calculation averaging process is performed to obtain the airflow situation (predicted value) at the time of the occurrence of the diffusion event, the airflow situation can be predicted accurately (at intervals of several meters) quickly.

  Further, according to the diffusion state prediction device 50 and the diffusion state prediction procedure, the diffusion calculation is performed based on the airflow state predicted by the airflow state prediction device 20 with high accuracy and speed. It is possible to accurately and quickly predict information on the concentration field of diffusive substances that is effective for performing removal activities appropriately.

  Furthermore, an observation device (site terminal) having a position acquisition function, an observation data acquisition function, and a data communication function with the airflow state prediction device 20 and the diffusion state prediction device 50 is applied. If the communication unit 23 is configured to receive information and observation data directly, by specifying the observation point that the user wants to use from the observation points actually observed, the position information and observation data of the designated observation point Can be acquired to execute the airflow state prediction procedure and the diffusion state prediction procedure.

  In addition, in the airflow state prediction device 20, the diffusion state prediction device 50, the airflow state prediction procedure, and the diffusion state prediction procedure, the observation point used by the user for prediction of the airflow state or the diffusion state from the observation points actually observed. Since there are buildings (obstacles) with a difference in elevation, such as an urban area, the attention area 35 is affected by the obstacles, and the airflow state and the diffusion state change in a complicated manner. Even in a region, the observation data can be given by selecting an appropriate observation point, so that the accuracy of the overall airflow situation and diffusion situation can be reduced without being affected by the local flow. It can be avoided.

  The method described in the above-described embodiment is a program that can be executed by a computer, for example, written in a storage medium such as a magnetic disk, an optical disk, or a semiconductor memory and applied to various apparatuses, or transmitted through a communication medium and various types. It can also be applied to a device. A computer that implements the apparatus reads the program recorded in the storage medium, and executes the above-described processing by controlling the operation by the program.

  In addition, the present invention is not limited to the above-described embodiment as it is, and can be implemented in various forms other than the above-described examples in the implementation stage, and various modifications can be made without departing from the gist of the invention. Can be omitted, added, replaced, or changed. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

  DESCRIPTION OF SYMBOLS 1 ... Computer, 2 ... CPU, 3 ... Main memory device, 4 ... Auxiliary memory device, 5 ... Input device, 6 ... Output device, 7 ... Communication part, 8 ... Calculation server, 10 ... Airflow and diffusion condition prediction PG (program) ), 11 ... Maps and the like information DB (database), 12 ... Airflow DB (database), 13 ... Diffusion DB (database), 20 (20A-20E) ... Airflow condition prediction device, 21 ... Input unit, 22 ... Output unit, DESCRIPTION OF SYMBOLS 23 ... Communication part, 24 ... Airflow calculation part, 25 ... DB creation update part, 26 (26A, 26B) ... Comparison calculating part, 27 ... Display processing part, 28 ... Memory | storage part, 29 ... Control part, 31 ... Diffusion calculation part 35 ... 35A, 35B ... attention area, 36 ... airflow / diffusion calculation result, 37 ... coincidence calculation result, 38 ... diffusion event occurrence point, 39 ... wind direction at the time of diffusion event occurrence, 41 ... airflow DB (database) The wind you want to add to , 50 (50A~50E) ... diffusion status prediction apparatus, P1~P5 ... observation point, MP1, MP2 ... monitor the observation point.

Claims (15)

Received airflow element observation results including wind direction and wind speed and position information of the observation points observed at multiple observation points in the region of interest set as an area for predicting the airflow situation, and received airflow element observation results, Under the condition that the wind direction and the wind speed included in the airflow element are held differently and held in accessible storage means, the information on the size and position of the structure existing in the region of interest is included. The airflow data at the location corresponding to the position information of the observation point in the airflow database associated with the position in the airflow database and the position in the airflow database as the airflow data with the analysis result of the airflow element obtained by the airflow analysis A comparison operation unit is provided for calculating the degree of coincidence by comparison and collating, and weighting and combining the airflow data in the airflow database according to the calculated degree of coincidence. Airflow situation prediction apparatus according to claim. The airflow condition prediction apparatus according to claim 1, wherein when calculating the degree of coincidence, a different weighted method is adopted for each airflow element. The comparison operation unit according to claim 1 or 2 sets a region that includes all the locations of the observation points that are narrower than the region of interest, and a location corresponding to the observation result and the observation points for the set region. An airflow state prediction apparatus characterized by performing comparison and collation with the airflow data, calculating the degree of coincidence, and performing weighted combination of the airflow data in the airflow database according to the degree of coincidence. The comparison operation unit according to any one of claims 1 to 3, wherein the airflow element has an airflow direction in which an azimuth angle with respect to the wind direction observed at the observation point is within a predetermined angle among the airflow data of the airflow database. Airflow data to be extracted, and for the extracted airflow data, the comparison between the observation result and the airflow data at a location corresponding to the observation point, the calculation of the degree of coincidence, and the airflow database according to the degree of coincidence An airflow state prediction apparatus characterized by performing weighted combination of airflow data in the inside. When the comparison operation unit according to any one of claims 1 to 4 newly receives an observation result observed at an observation point other than the observation point and position information of the observation point, the comparison operation unit includes the received observation point. The airflow condition is characterized in that the degree of coincidence is calculated by comparing with the airflow data at locations corresponding to all observation points, and each airflow data in the airflow database is weighted and combined according to the calculated degree of coincidence. Prediction device. A DB having a function of creating the airflow database, a function of adding the airflow data, and a function of updating the contents of the airflow data to the airflow condition prediction apparatus according to any one of claims 1 to 5. An airflow state prediction apparatus further comprising a creation / update unit. The airflow database according to any one of claims 1 to 6, wherein the airflow database includes airflow data measured and statistically processed in the region of interest. The airflow database according to claim 1, wherein the airflow database includes airflow data obtained by airflow analysis using meteorological data at the time of occurrence of a diffusion event as a boundary condition. Prediction device. The airflow database according to any one of claims 1 to 8, wherein, in addition to the initial conditions, the wind direction and the wind speed are newly set, and the airflow data in the region of interest performed under the set conditions The airflow condition prediction apparatus characterized by including. The airflow condition prediction apparatus according to any one of claims 1 to 9, further comprising an airflow calculation unit that performs the airflow analysis. The airflow condition prediction apparatus according to any one of claims 1 to 10, further comprising a communication unit capable of transmitting information to and from an external device. A diffusion calculation unit that predicts a diffusion state of a substance in the region of interest based on the airflow state prediction result of the region of interest obtained by the airflow state prediction device according to any one of claims 1 to 11. A diffusion state prediction apparatus characterized by that. Airflow element observation results including wind direction and wind speed, observation results of diffusion elements including substance concentration, and position information of observation points observed at multiple observation points in the region of interest set as an area for predicting diffusion status The size of the structure existing in the region of interest under the condition that the received airflow element and the received observation result of the airflow element are stored in accessible storage means and the wind direction and the wind speed included in the airflow element are different. The observation point in the airflow database associated with the position in the region of interest and the condition as the airflow data using the analysis result of the airflow element obtained by analyzing the airflow in the region of interest including the information on the position and position The airflow data at the location corresponding to the data and the received observation result of the diffusing element are held in accessible storage means and included in the airflow element. Analysis of the diffusion element obtained by performing diffusion analysis in the region of interest including information on the size and position of structures existing in the region of interest under different wind directions and wind speeds. The result is used as diffusion data to compare and collate the position in the region of interest and the diffusion data in the diffusion database associated with the condition to calculate the degree of coincidence, and each diffusion data in the diffusion database according to the calculated degree of coincidence A diffusion state prediction apparatus comprising a comparison operation unit that weights and combines the two. A method of predicting an airflow situation in a region of interest set as an area for predicting an airflow situation using a computer, and a plurality of observation points in the attention area set as an area for the computer to predict an airflow situation The observation result of the airflow element including the observed wind direction and the wind speed and the position information of the observation point are received, and the observation result of the received airflow element and the storage direction accessible by the computer are stored in the airflow element. The analysis result of the air flow element obtained by analyzing the air flow in the region of interest including information on the size and position of the structure existing in the region of interest under the condition where the wind speed is different is obtained as the air flow. The airflow at a location corresponding to the position information of the observation point in the airflow database associated with the position in the region of interest and the condition as data Stream status prediction method characterized by comprising the process step of calculating the matching degree by comparing collating the chromatography data, weighting combiner for each stream data in the stream database in accordance with the calculated degree of matching. A method for predicting an airflow situation in an attention area set as an area for predicting an airflow situation using a computer, wherein the computer uses a plurality of observation points in the attention area set as an area for predicting a diffusion situation. Receives the observation results of the air flow element including the observed wind direction and wind speed, the observation results of the diffusion element including the concentration of the substance and the position information of the observation point, and the received observation results of the air flow element and the memory accessible by the computer The air flow analysis in the region of interest including the information on the size and position of the structure existing in the region of interest is performed under the condition that the wind direction and the wind speed included in the air flow element are different from each other. The analysis result of the airflow element obtained as a result is used as the airflow data for the view in the airflow database associated with the position in the region of interest and the condition. The airflow data at a location corresponding to a point, the observation result of the diffusion element received, and the storage means accessible by the computer, the wind direction and the wind speed included in the airflow element being different from each other Then, the position of the structure in the region of interest as diffusion data is the analysis result of the diffusion element obtained by performing the diffusion analysis in the region of interest including information on the size and position of the structure existing in the region of interest. And comparing and collating the diffusion data in the diffusion database associated with the condition to calculate the degree of coincidence, and weighting and combining the respective diffusion data in the diffusion database according to the calculated degree of coincidence. A characteristic diffusion state prediction method.