Thermal and wind environment information generating device, thermal and wind environment information generating method, disaster prevention and mitigation information generating device, and disaster prevention and mitigation information generating method

Abstract

To provide a hyperthermia-wind environment information generating device, hyperthermia-wind environment information generating method, disaster prevention-disaster mitigation information generating device and disaster prevention-disaster mitigation information generating method that can grasp prediction information on a hyperthermia-wind environment of a local location real time and highly accurately.SOLUTION: A hyperthermia-wind environment information generating device 200 comprises: a weather information acquisition unit 201; an object area setting unit 202; and a hyperthermia-wind environment forecast unit 211. The weather information acquisition unit 201 is configured to acquire window direction information, wind velocity information and ambient temperature information, which are obtained by analyzing broad-range weather observation data as weather information on an object location, on a location within a prescribed range from the object location. The object area setting unit 202 is configured to set an area including the object location as an object area. The hyperthermia-wind environment forecast unit 211 is configured to implement thermal fluid analysis processing about the object area on the basis of the information acquired in the weather information acquisition unit, and thereby generate forecast information on the hyperthermia-window environment every location within the object area as of an object date and time.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a thermal and wind environment information generating device, a thermal and wind environment information generating method, a disaster prevention and mitigation information generating device, and a disaster prevention and mitigation information generating method. [Background technology]

[0002] In recent years, the number of natural disasters occurring not only in Japan but all over the world has been increasing, and the economic losses caused by these disasters are also on the rise. Major natural disasters in Japan include the Great Hanshin-Awaji Earthquake and the Great East Japan Earthquake, but in recent years, damage caused by heavy rains and typhoons has also been increasing. For this reason, even if natural disasters cannot be prevented, there is a need for disaster prevention measures to eliminate damage to human beings and social infrastructure when disasters occur, and for disaster mitigation measures to reduce damage. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-296362 [Patent Document 2] Japanese Patent Application Laid-Open No. 2001-325555 Summary of the Invention [Problem to be solved by the invention]

[0004] Meanwhile, with the recent advancement of DX (digital transformation) and digital twins, efforts are underway to apply various data and simulations collected from the real world to operational and business transformation, including data necessary for disaster prevention and mitigation (e.g., Patent Document 1).

[0005] However, even with this data, the current situation is that observation and simulation technologies have not yet been established to grasp meteorological information such as wind direction, wind speed, and temperature in real time for localized areas, for example, areas of a few meters to a few tens of meters. For example, with observation technology, it is difficult to obtain localized data over a wide area due to limitations on the installation of observation equipment, and with simulation technology, the weather forecast analysis carried out by the Japan Meteorological Agency can only predict meteorological data for areas of a few kilometers at most.

[0006] Furthermore, it is possible to grasp local weather data by using computational thermal fluid dynamics (CFD) technology, which can analyze air flow, etc. (for example, Patent Document 2), but this method has the problem of taking time to analyze and losing real-time capabilities.

[0007] Furthermore, because numerical thermal fluid analysis technology imposes a high analytical load, it is difficult to set a wide analysis area, and it is not possible to take into account wide-area natural environmental information, such as the effects of typhoons, etc., making it difficult to obtain accurate data necessary for disaster prevention and mitigation in real time.

[0008] The present disclosure has been made in consideration of the above circumstances, and aims to provide a thermal and wind environment information generating device, a thermal and wind environment information generating method, a disaster prevention and mitigation information generating device, and a disaster prevention and mitigation information generating method that are capable of accurately grasping predicted information on the thermal and wind environment of a local location in real time, taking into account wide-area weather information. [Means for solving the problem]

[0009] The thermal and wind environment information generating device according to the present disclosure includes a weather information acquisition unit that acquires, as weather information for a target location, wind direction information, wind speed information, and temperature information for positions within a predetermined range from the target location, obtained by analyzing wide-area meteorological observation data; a target area setting unit that sets a predetermined area including the target location as a target area; and a thermal and wind environment prediction unit that generates predicted information for the thermal and wind environment at a predetermined date and time, including at least one of information on wind speed, wind direction, temperature, and wind pressure for each position within the target area, by performing a thermal fluid analysis process for the target area based on the information acquired by the weather information acquisition unit.

[0010] The target area setting unit may set the target area based on wind direction information acquired by the weather information acquisition unit so that the target area includes the target position and has a larger area upwind of the target position.

[0011] The weather information acquisition unit may acquire, as the weather information for the target position, weather information for any one of a plurality of positions within a predetermined range from the target position.

[0012] The weather information acquisition unit may select the closest position upwind of the target position from among a plurality of positions within a predetermined range from the target position, and acquire the weather information of the selected position as the weather information for the target position.

[0013] The weather information acquisition unit may acquire, as the wind speed information, a plurality of pieces of wind speed information for each height from the ground, and may acquire, as the temperature information, a plurality of pieces of temperature information for each height from the ground.

[0014] The thermal and wind environment information generating device may further include a ground object information acquisition unit that acquires information on the type, position, shape, size, and material of ground objects within the target area, and the thermal and wind environment prediction unit may generate prediction information for the thermal and wind environment using the information acquired by the ground object information acquisition unit.

[0015] In addition, the thermal and wind environment information generation method disclosed herein acquires wind direction information, wind speed information, and temperature information for positions within a predetermined range from the target position, obtained by analyzing wide-area meteorological observation data, as weather information for the target position, sets a predetermined area including the target position as the target area, and performs thermal fluid analysis processing for the target area based on the acquired information, thereby generating predicted information for the thermal and wind environment at a specified date and time, including at least one of information on wind speed, wind direction, temperature, and wind pressure for each position within the target area.

[0016] In addition, the disaster prevention / mitigation information generation device of the present disclosure is communicatively connected to one of the thermal / wind environment information generation devices and includes a disaster prevention / mitigation information generation unit that uses predicted information on the thermal / wind environment generated by the thermal / wind environment prediction unit to generate information for disaster prevention or mitigation for each location within the target area.

[0017] In addition, the disaster prevention and mitigation information generation method disclosed herein involves a disaster prevention and mitigation information generation device that is communicatively connected to one of the thermal and wind environment information generation devices, using predicted information on the thermal and wind environment generated by the thermal and wind environment information generation device to generate information for disaster prevention or mitigation for each location within the target area. [Effects of the Invention]

[0018] According to the thermal and wind environment information generating device, thermal and wind environment information generating method, disaster prevention and mitigation information generating device, and disaster prevention and mitigation information generating method disclosed herein, predicted information on the thermal and wind environment at a local location can be obtained accurately in real time, taking into account wide-area weather information. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a block diagram showing the configuration of a PC using a thermal and wind environment information generating device and a disaster prevention and mitigation information generating device according to one embodiment. FIG. [Figure 2] 3 is a flowchart showing the operation of the thermal and wind environment information generating device and the disaster prevention and mitigation information generating device according to one embodiment. [Figure 3]FIG. 1 is an explanatory diagram showing the objective analysis coordinate position, which is the position to be analyzed by the thermal and wind environment information generating device and the disaster prevention and mitigation information generating device according to one embodiment, and the position from which the weather information used for the analysis is obtained. [Figure 4] 1 is an explanatory diagram showing the location of an area to be analyzed by a thermal and wind environment information generating device and a disaster prevention and mitigation information generating device according to one embodiment. FIG. [Figure 5] 1 is an explanatory diagram showing a state in which a target area to be analyzed by a thermal and wind environment information generating device and a disaster prevention and mitigation information generating device according to an embodiment is rotated by a predetermined angle. FIG. [Figure 6] This is a graph showing wind speed information at multiple altitudes in a target area acquired by a thermal and wind environment information generating device and a disaster prevention and mitigation information generating device according to one embodiment, an approximate curve calculated from the wind speed information, and wind speed values at each altitude of the wind inflow surface in the target area. [Figure 7] 1 is an explanatory diagram showing a state in which the area of the wind inflow plane of a target area to be analyzed by a thermal and wind environment information generating device and a disaster prevention and mitigation information generating device according to one embodiment is divided. FIG. [Figure 8] (a) is predicted information of velocity distribution in the target area R0 generated by a disaster prevention and mitigation information generation device according to one embodiment using local objective analysis data at the objective analysis coordinate position Q1, and (b) is predicted information of velocity distribution in the target area R1 generated using local objective analysis data at the objective analysis coordinate position Q1. [Figure 9] (a) is predicted information of wall pressure distribution in target area R0 generated by a disaster prevention and mitigation information generation device of one embodiment using local objective analysis data at objective analysis coordinate position Q1, and (b) is predicted information of wall pressure distribution in target area R1 generated using local objective analysis data at objective analysis coordinate position Q1. [Figure 10] (a) is predicted information of velocity distribution generated by a disaster prevention and mitigation information generation device according to one embodiment for a target area R1 rotated to match wind direction D using local objective analysis data at objective analysis coordinate position Q3, and (b) is predicted information of wall pressure distribution generated for a target area R1 rotated to match wind direction D using local objective analysis data at objective analysis coordinate position Q3. DETAILED DESCRIPTION OF THE INVENTION

[0020] Below, we will explain the case where a thermal and wind environment information generating device installed in a PC (personal computer) generates thermal and wind environment information for a specified date and time regarding a specified outdoor area, and then a disaster prevention and mitigation information generating device uses the generated information to generate information regarding disaster prevention and mitigation.

[0021] <Configuration of a PC equipped with a thermal and wind environment information generating device and a disaster prevention and mitigation information generating device according to the first embodiment> The configuration of a PC equipped with a thermal and wind environment information generating device and a disaster prevention and mitigation information generating device according to the first embodiment will be described with reference to Fig. 1. The PC 1 according to this embodiment includes an input unit 10, a CPU 20, a communication unit 30, and an output unit 40. The communication unit 30 is connected to an external wide area communication network 100.

[0022] The input unit 10 inputs information about the location (hereinafter referred to as the "target location") for which thermal and wind environment information is to be generated, as specified by the user, and information about the date and time (hereinafter referred to as the "target date and time") for which thermal and wind environment information is to be generated.

[0023] The CPU 20 incorporates a GPU 21. The CPU 20 has a function as a thermal and wind environment information generation device 200 and a function as a disaster prevention and mitigation information generation device 210, and has a weather information acquisition unit 201, a target area setting unit 202, a ground object information acquisition unit 203, a shade information calculation unit 204, a heat quantity information calculation unit 205, a surface temperature information calculation unit 206, an analysis condition setting unit 207, a thermal and wind environment prediction unit 211 and a disaster prevention and mitigation information generation unit 212 that execute calculation processing within the GPU 21.

[0024] The thermal and wind environment information generating device 200 is composed of a weather information acquiring unit 201, a target area setting unit 202, a ground object information acquiring unit 203, a shade information calculating unit 204, a heat quantity information calculating unit 205, a surface temperature information calculating unit 206, an analysis condition setting unit 207, and a thermal and wind environment predicting unit 211. The disaster prevention and mitigation information generating device 210 is composed of the thermal and wind environment information generating device 200 and a disaster prevention and mitigation information generating unit 212.

[0025] The weather information acquisition unit 201 acquires wind direction information, wind speed information, and temperature information for positions within a specified range from a specified predetermined position, obtained by analyzing wide-area meteorological observation data, from an external web server (not shown) or the like via the wide-area communication network 100.

[0026] The target area setting unit 202 sets a target area based on the wind direction information acquired by the weather information acquisition unit 201 so that the target area includes the designated target position and has a larger area upwind of the target position.

[0027] The ground object information acquisition unit 203 acquires information about ground objects within the set target area, specifically, information about the types of objects within the target area, such as buildings, roads, waterside areas such as ponds, green spaces such as parks, etc., as well as information about the position, shape, size, and material of the objects.

[0028] The shade information calculation unit 204 calculates shade information indicating the position, shape, and size of the shaded area within the target area. The heat quantity information calculation unit 205 calculates the amount of solar radiation, reflection, atmospheric radiation, terrestrial radiation, sensible heat transport, latent heat transport, and underground heat transfer for each surface material within the target area at the target date and time as heat quantity information within the target area at the target date and time.

[0029] The surface temperature information calculation unit 206 analyzes the heat balance state based on the various heat quantity information calculated by the heat quantity information calculation unit 205, and calculates the surface temperature for each material and for sunny / shaded areas at the target date and time within the target area. The surface temperature information calculation unit 206 also determines the object and its surface material for each position within the target area based on the information acquired by the ground object information acquisition unit 203. Furthermore, the surface temperature information calculation unit 206 calculates surface temperature information for each position within the target area at the target date and time based on the determined information on the material for each position, the calculated surface temperature information for each material, and shade information.

[0030] The analysis condition setting unit 207 sets the information on the wind direction, wind speed, and temperature of the air flowing into the target area acquired by the weather information acquisition unit 201, and the surface temperature for each position acquired by the surface temperature information calculation unit 206, as conditions for analyzing the thermal and wind environment of the target area.

[0031] The thermal and wind environment prediction unit 211 executes a thermal fluid analysis process for the target area based on the set conditions, thereby predicting the thermal and wind environment including at least one of information on wind speed, wind direction, temperature, and wind pressure for each local position within the target area at a specified date and time.

[0032] The disaster prevention / mitigation information generation unit 212 generates disaster prevention / mitigation information consisting of image information or video information that can be viewed by the user, based on the predicted information of the thermal and wind environment for each local location in the target area analyzed by the thermal and wind environment prediction unit 211.

[0033] The output unit 40 is configured with a display device, and displays the disaster prevention / mitigation information generated by the disaster prevention / mitigation information generation unit 212 .

[0034] <Operations of the thermal and wind environment information generating device and the disaster prevention and mitigation information generating device according to the first embodiment> Next, the operation of the thermal and wind environment information generating device 200 and the disaster prevention and mitigation information generating device 210 according to this embodiment will be described. In this embodiment, as an example of the operation of these devices, the operation when the thermal and wind environment information generating device 200 generates forecast information on the wind environment at the expected date and time of a typhoon's passage for a location specified by a user will be described. Also, the operation when the disaster prevention and mitigation information generating device 210 generates, based on the information generated by the thermal and wind environment information generating device 200, a distribution map of wind speeds for an area including the corresponding location and a distribution map of wind pressures on the wall surfaces of a building as disaster prevention and mitigation information will be described.

[0035] 2 is a flowchart showing the operation of the thermal and wind environment information generating device 200 and the disaster prevention and mitigation information generating device 210. First, a user inputs, from the input unit 10, target location information for which wind environment information and disaster and mitigation information are to be generated, and date and time information when the wind speed due to a typhoon is predicted to increase at the corresponding location.

[0036] The user inputs the target location information by, for example, specifying a location on the map information displayed on the output unit 40. Furthermore, when a typhoon is approaching, the wind speed is strongest, for example, about one hour before the center of the typhoon arrives, so the user inputs one hour before the estimated time the center of the typhoon will arrive at the target location as the target date and time information.

[0037] When the user inputs the target location information and the target date and time information ("YES" in S1), the weather information acquisition unit 201 of the thermal and wind environment information generating device 200 acquires weather information for the input target location. In this embodiment, the weather information acquisition unit 201 acquires local objective analysis data (LA) provided by the Japan Meteorological Agency as weather information for the corresponding location via the wide area communication network 100 (S2).

[0038] Local objective analysis data (LA) is meteorological information at objective analysis coordinate positions, which are positions of grid points with regular intervals of about 5 km, calculated by analyzing meteorological observation data from multiple locations irregularly distributed over a wide area around the world. In other words, local objective analysis data (LA) is meteorological information at objective analysis coordinate positions calculated by assimilating wide-area observation data into meteorological analysis. Local objective analysis data (LA) includes wind direction information, wind speed information, temperature information, etc. as meteorological information for the corresponding objective analysis coordinate positions.

[0039] The weather information acquisition unit 201 acquires one piece of local objective analysis data (LA) from among a plurality of objective analysis coordinate positions within a predetermined range from the target position designated by the user as described above.

[0040] 3 is a diagram showing, on map information, a target position P designated by a user and four objective analysis coordinate positions Q1 to Q4 within a predetermined range from the target position P. Based on wind direction information for the objective analysis coordinate positions Q1 to Q4, the weather information acquisition unit 201 selects from among the objective analysis coordinate positions Q1 to Q4 the objective analysis coordinate position closest to the upwind side of the target position P. Of the objective analysis coordinate positions Q1 to Q4, Q1 and Q2 are positions on land, and Q3 and Q4 are positions on the sea.

[0041] Here, the weather information acquisition unit 201 determines that the wind direction at the target position P is the direction indicated by arrow D based on wind direction information for the objective analysis coordinate positions Q1 to Q4. Then, the weather information acquisition unit 201 selects the objective analysis coordinate position Q3 that is closest to the target position P on the upwind side from among the objective analysis coordinate positions Q1 to Q4. The weather information acquisition unit 201 acquires the local objective analysis data (LA) for the selected objective analysis coordinate position Q3 as the weather information for the target position P. The weather information acquisition unit 201 may correct the local objective analysis data (LA) for the objective analysis coordinate position Q3 based on the distance between the objective analysis coordinate position Q3 and the target position P, etc., and use this corrected value as the weather information for the target position P.

[0042] In this way, by using the local objective analysis data (LA) of the nearest objective analysis coordinate position Q3 on the upwind side of the target position P as weather information for the target position P, highly accurate thermal and wind environment information according to the state of the wind flowing into the target position P can be generated by the processing described below.

[0043] Next, the target area setting unit 202 sets a target area of a predetermined size including the specified target position P based on the wind direction information of the local objective analysis data (LA) of the objective analysis coordinate position Q3 acquired by the weather information acquisition unit 201 (S3). Here, the target area setting unit 202 sets, as the target area, an area R1 whose area upwind of the target position P is wider than an area R0 centered on the target position P, as shown in Fig. 4. In this embodiment, the size of the target area R1 is 2 km square on the ground surface, and an altitude of 0 m to 350 m.

[0044] In order to set the wind direction toward the target area R1 to a direction perpendicular to one side surface r1 of the target area R1, the target area setting unit 202 may rotate the target area R1 as shown in Fig. 5. In the example of Fig. 5, the target area R1 is rotated by an angle θ, for example, 10 degrees, in a clockwise direction parallel to the ground surface, with the center ra in the width direction of the side surface r1 as the base point.

[0045] Next, the ground object information acquisition unit 203 acquires ground object information within the set target region R1, specifically, information on the types of objects within the target region, such as buildings, roads, waterside areas such as ponds, green spaces such as parks, etc., as well as information on the positions, shapes, sizes, and materials of the objects (S4). Information on the material of objects is, for example, information such as concrete for buildings, asphalt for roads, waterside areas such as ponds, and plants (trees) for green spaces such as parks.

[0046] Methods by which the ground object information acquisition unit 203 acquires information on the position, shape, and size of objects in the target area include, for example, acquiring the information by on-site measurements, acquiring the information by modeling 3D information from aerial surveys, etc. The ground object information acquisition unit 203 may also acquire information on the shape and size of buildings in the target area using a 3D city model made public by the G-Spatial Information Center (Project PLATEAU) of the Ministry of Land, Infrastructure, Transport and Tourism.

[0047] Information previously input into the map information is used as information on the material of objects in the target area acquired by the ground object information acquisition unit 203. Information on the material of objects is, for example, information such as concrete for buildings, asphalt for roads, water for waterside areas such as ponds, and plants (trees) for green spaces such as parks.

[0048] Next, the shadow information calculation unit 204 calculates shadow information indicating the position, shape, and size of the shadow area within the target region R1 at the target date and time (S5). For example, the shadow information calculation unit 204 calculates the shadow information by using the ground object information of the target region R1 acquired by the ground object information acquisition unit 203 to translate the ceiling surface of the building on the ground surface along a vector indicating the direction in which sunlight shines.

[0049] Next, the heat quantity information calculation unit 205 calculates the amount of solar radiation, reflection, atmospheric radiation, terrestrial radiation, sensible heat transport, latent heat transport, and underground heat transfer for each surface material at the target date and time within the target region R1 as heat quantity information at the target date and time (S6). The heat quantity information calculation unit 205 calculates this information based on weather forecast information provided by, for example, the Japan Meteorological Agency.

[0050] Solar radiation is the amount of heat that reaches the ground from the sun. This amount of solar radiation also includes the amount of heat that is scattered into the atmosphere, so the amount of solar radiation is never "0" even in shaded areas. Reflection is the amount of heat that is reflected when solar radiation reaches the ground. Atmospheric radiation is the amount of heat transported from the atmosphere to the ground by radiative heat transfer. Terrestrial radiation is the amount of heat transported from the earth's surface to space by radiative heat transfer. Sensible heat transport is the amount of heat that moves from the ground to the atmosphere. Latent heat transport is the amount of heat required for water to evaporate. Subterranean heat transfer is the amount of heat that moves into the ground.

[0051] Next, the surface temperature information calculation unit 206 calculates the surface temperature for each position within the target region R1 at the target date and time based on the determined information on the material for each position and the calculated information on the surface temperature for each material. At this time, since the amount of solar radiation is significantly reduced in regions recognized as being in the shade by the shade information calculation unit 204, the surface temperature information calculation unit 206 calculates the surface temperature of the shaded region to be lower than that of the sunny region. Furthermore, the surface temperature information calculation unit 206 determines that water surfaces and green spaces have a high amount of latent heat transport and performs calculations to calculate the surface temperatures of water surfaces and green spaces to be lower than those of concrete and asphalt regions.

[0052] Here, when calculating the surface temperature for each position at the target date and time within the target region, the surface temperature information calculation unit 206 may calculate the temperature of the exterior wall surface of the building as the same temperature as the ground surface temperature calculated for the corresponding material, for example, concrete. By performing the calculation process in this manner, it is possible to reduce the calculation load without reducing the accuracy as much as possible in the thermal fluid analysis process described below.

[0053] Next, the analysis condition setting unit 207 sets the wind direction to the target area R1 at the target date and time, and the wind speed and temperature at each altitude as analysis conditions for the thermal fluid analysis based on the information of the local objective analysis data (LA) of the objective analysis coordinate position Q3 acquired by the weather information acquisition unit 201 (S8).

[0054] In this embodiment, in order to reduce the computational load in the thermal fluid analysis process, the boundary conditions of the target region R1 are set as follows: the wind direction on the inflow surface, which is the inflow boundary, is set to one direction perpendicular to the inflow surface, and the wind speed is set to a constant flow velocity. Also, the upper boundary surface of the target region R1 is set as the target boundary, and the other boundary surfaces are set as pressure outlet boundaries.

[0055] Here, the local objective analysis data (LA) contains only scattered wind speed information for each objective analysis coordinate position between 0 m and 350 m, which is the altitude of the target area R1. Therefore, the analysis condition setting unit 207 calculates and interpolates wind speed information for each altitude from the wind speed information for several locations in the local objective analysis data (LA) for the objective analysis coordinate position Q3.

[0056] The vertical wind speed distribution in urban areas, etc., is expressed by the following formula (1) according to the standards of the Architectural Institute of Japan.

number

[0057] In this embodiment, the analysis condition setting unit 207 calculates the α value of the target area R1 as 0.25, which is close to that of an urban area, using the least squares method with the results obtained from the local objective analysis data (LA) at the objective analysis coordinate position Q3.

[0058] 6, points E1 to E3 represent wind speed information at multiple altitudes in target region R1 obtained from local objective analysis data (LA) at objective analysis coordinate position Q3, and thick solid line L1 represents an approximation curve calculated from the wind speed information at points E1 to E3 using the least squares method based on the above formula (1). Based on this approximation curve, the analysis condition setting unit 207 calculates the wind speed value for each altitude between 0 m and 350 m that will flow into target region R1 on the target date and time, and sets it as the analysis condition for the thermal fluid analysis.

[0059] The analysis condition setting unit 207 may input wind speed values for each altitude in the target region R1 used in the computational fluid analysis as a function indicating the velocity distribution in the height direction. Alternatively, as shown in Fig. 7, the analysis condition setting unit 207 may divide the wind inflow surface r1 of the target region R1 into multiple regions in the height direction and set wind speed values for each region, thereby approximately reproducing the velocity distribution. In this case, the analysis condition setting unit 207 may set wind speed values at smaller altitude intervals, for example, as the altitude becomes lower.

[0060] By setting wind speed values for each altitude in this way, it is possible to perform highly accurate processing in the thermal fluid analysis processing described below.

[0061] The thick dotted line L2 in FIG. 6 indicates the wind speed values set by the analysis condition setting unit 207 for each region obtained by dividing the inflow surface r1 of the target region R1.

[0062] Next, the analysis condition setting unit 207 sets the surface temperature for each position at the target date and time within the target region, which is acquired by the surface temperature information calculation unit 206 .

[0063] Next, the thermal and wind environment prediction unit 211 predicts the thermal and wind environment by analyzing the air flow and temperature at the target date and time in the target area using a general thermal fluid analysis (CFD; Computational Fluid Dynamics) method based on the conditions set by the analysis condition setting unit 207 (S9). Specifically, the thermal and wind environment prediction unit 211 predicts the thermal and wind environment for each position at the target date and time in the target area by calculating the air flow and temperature in each cubic or rectangular space obtained by dividing the rectangular parallelepiped-shaped ground space of the target area into a three-dimensional grid. The information on the thermal and wind environment predicted by the thermal and wind environment prediction unit 211 includes at least one of information on wind speed, wind direction, temperature, and wind pressure for each position at the target date and time in the target area.

[0064] Here, in order to speed up the analysis processing, it is considered more suitable for the thermal and wind environment prediction unit 211 to adopt the lattice Boltzmann method using the Boltzmann equation rather than a method using the Navier-Stokes equation, which is a general method for thermal fluid analysis processing. The lattice Boltzmann method is a method that excels in parallelizing calculations and is compatible with GPUs, which have high parallel calculation processing capabilities. The thermal and wind environment prediction unit 211 can use, for example, Discovery Live software from ANSYS (registered trademark) as software for executing thermal fluid analysis on the GPU 21.

[0065] Next, the disaster prevention / mitigation information generation unit 212 generates disaster prevention / mitigation information consisting of image information or video information that can be viewed by the user based on the predicted information of the thermal and wind environment for the target area analyzed by the thermal and wind environment prediction unit 211, and outputs it to the output unit 40 (S10).

[0066] Examples of disaster prevention and mitigation information include streamline distribution information showing the air flow in the aboveground space of the target area, spatial wind speed distribution information showing areas in the aboveground space by color-coding each wind speed range, and wind speed distribution information on a plane at a specified height above the ground that is parallel to the ground.

[0067] As an example, Fig. 8(a) shows predicted information on the velocity distribution of a 10m high cross section at the target date and time in the target area R0, generated using the local objective analysis data (LA) of Q1, the objective analysis coordinate position closest to the target position P. Fig. 8(b) shows predicted information on the velocity distribution of a 10m high cross section at the target date and time in the target area R1, generated using the local objective analysis data (LA) of the objective analysis coordinate position Q1.

[0068] In Figures 8(a) and (b), the area surrounded by the solid line is the target position P, the arrow D indicates the wind direction, and the area surrounded by the dotted line is the upwind area F near the target position P. Comparing Figures 8(a) and (b), by shifting the target area from R0 to R1, the number of upwind buildings taken into account in the analysis process increases, and the wind speed distribution in the area including the upwind area F near the target position P differs due to the influence of the upwind buildings. As a result, it is thought that shifting the target area from R0 to R1 improved the accuracy of wind speed distribution predictions.

[0069] Fig. 9(a) shows the wall pressure distribution, i.e., the predicted information of the wind pressure acting on the building wall, at the target date and time in the target area R0, generated using the local objective analysis data (LA) at the objective analysis coordinate position Q1. Fig. 9(b) shows the predicted information of the wall pressure distribution, at the target date and time in the target area R1, generated using the local objective analysis data (LA) at the objective analysis coordinate position Q1.

[0070] In Figures 9(a) and (b), the area surrounded by the solid line is the target position P, and the arrow D indicates the wind direction D. Comparing Figures 9(a) and (b), by shifting the target area from R0 to R1, the number of upwind buildings considered in the analysis process increases, resulting in a difference in the wall pressure distribution acting on the walls of the buildings within target position P. This suggests that shifting the target area from R0 to R1 has improved the accuracy of predicting the wall pressure distribution.

[0071] Furthermore, Figure 10(a) shows the predicted velocity distribution information for a 10-meter-high cross section at the target date and time, generated for target area R1 rotated to match wind direction D using local objective analysis data (LA) at objective analysis coordinate position Q3. Comparing Figure 10(a) with Figure 8(b), changing the local objective analysis data (LA) used from data at objective analysis coordinate position Q1 to data at Q3 and rotating target area R1 to match wind direction D takes into account strong winds over the ocean, resulting in higher wind speeds overall. This suggests that changing the data used for analysis from data at objective analysis coordinate position Q1 to data at objective analysis coordinate position Q3 and rotating target area R1 to match wind direction D has improved the accuracy of the wind speed distribution prediction.

[0072] Figure 10(b) shows the predicted wall pressure distribution at the target date and time, generated for target region R1 rotated to match wind direction D using local objective analysis data (LA) at objective analysis coordinate position Q3. Comparing Figure 10(b) with Figure 9(b), it is clear that changing the local objective analysis data (LA) used from data at objective analysis coordinate position Q1 to data at Q3 and rotating target region R1 to match wind direction D takes into account the strong winds over the sea, resulting in an overall higher wind speed. This suggests that changing the data used for analysis from data at objective analysis coordinate position Q1 to data at objective analysis coordinate position Q3 has improved the accuracy of the wall pressure distribution prediction.

[0073] According to the above-described embodiment, it is possible to generate accurate, real-time forecast information on the wind environment at a local location when a typhoon passes, as well as forecast information on disaster prevention and mitigation, taking into account meteorological information over a wide area. By visually checking the generated forecast information on disaster prevention and mitigation, users can prepare for the typhoon's passage and take action to prevent and mitigate disasters.

[0074] In the above-described embodiment, the case where forecast information on the wind environment at a predetermined position when a typhoon passes and forecast information on disaster prevention and mitigation is generated has been described, but the present invention is not limited to this. For example, forecast information on disaster prevention and mitigation regarding snowstorms, dense fog, fires, etc. may also be generated.

[0075] For example, the weather information acquisition unit 201 acquires information on the snow concentration in the wind as well as the wind direction and wind speed at a target location as weather information, and the analysis condition setting unit 207 sets this information as analysis conditions. Then, the thermal and wind environment prediction unit 211 performs a thermal fluid analysis based on the set information, and the disaster prevention and mitigation information generation device 210 generates and outputs predicted information on the snow concentration distribution for each position at a target date and time in the target area as disaster prevention and mitigation information based on the analysis results.

[0076] By generating forecast information on snow concentration distribution in this way, it is possible to output disaster prevention and mitigation information, such as warnings to vehicles attempting to enter areas with high snow concentrations.

[0077] Furthermore, the weather information acquisition unit 201 acquires information on the fog concentration in the wind as well as the wind direction and wind speed at the target location as weather information, and the analysis condition setting unit 207 sets this information as analysis conditions. Then, the thermal and wind environment prediction unit 211 performs a thermal fluid analysis based on the set information, and the disaster prevention and mitigation information generation device 210 generates and outputs predicted information on the fog concentration distribution for each position at the target date and time in the target area as disaster prevention and mitigation information based on the analysis results.

[0078] By generating predicted information on fog density distribution in this way, it is possible to output disaster prevention and mitigation information, such as warnings to vehicles entering areas with high fog density.

[0079] Furthermore, the weather information acquisition unit 201 acquires information on the concentration of smoke and carbon dioxide (CO2) generated by a fire as well as wind direction and speed at a target location as weather information, and the analysis condition setting unit 207 sets this information as analysis conditions. Then, the thermal and wind environment prediction unit 211 performs thermal fluid analysis based on the set information, and the disaster prevention and mitigation information generation device 210 generates and outputs predicted information on the distribution of smoke and CO2 concentration for each position at a target date and time in the target area as disaster prevention and mitigation information based on the analysis results.

[0080] By generating predicted information on smoke and CO2 concentration distribution in this way, it is possible to output disaster prevention and mitigation information, such as information that uses sound to guide people to evacuation routes with low smoke and CO2 concentrations.

[0081] In the above-described embodiment, the local objective analysis data (LA) is used as meteorological information for acquiring wind direction and wind speed for use in the thermal fluid analysis process. However, the present invention is not limited to this. For example, other meteorological information provided by the Japan Meteorological Agency, such as information acquired from a local model, information analyzed using a WRF (Weather Research and Forecasting) model, or actual observation data may also be used.

[0082] In the above-described embodiment, the thermal and wind environment information generating device 200 generates predicted information about the wind environment, but the present invention is not limited to this, and predicted information about the thermal environment may also be generated. In this case, the weather information acquiring unit 201 acquires temperature information as weather information for the target location, the analysis condition setting unit 207 sets the temperature information together with wind direction and wind speed information as analysis conditions, and the thermal and wind environment predicting unit 211 generates predicted information about the thermal environment in accordance with the analysis conditions.

[0083] Although several embodiments have been described, the embodiments can be modified or varied based on the above disclosure. All components of the above embodiments and all features described in the claims may be individually extracted and combined, unless they contradict each other.

[0084] This disclosure can contribute, for example, to Sustainable Development Goal (SDG) Goal 11: "Make cities and human settlements inclusive, safe, resilient and sustainable." [Explanation of symbols]

[0085] 10 Input section 20 CPU 30 Communications Department 40 Output section 100 Wide Area Communication Network 200 Thermal and Wind Environment Information Generator 201 Weather Information Acquisition Department 202 Target area setting unit 203 Ground object information acquisition unit 204 Shade Information Calculation Unit 205 Calorie information calculation section 206 Surface temperature information calculation section 207 Analysis condition setting section 210 Disaster prevention / mitigation information generation device 211 Thermal and Wind Environment Prediction Department 212 Disaster Prevention and Mitigation Information Generation Department

Claims

1. a weather information acquisition unit that acquires, as weather information for a target position, wind direction information, wind speed information, and temperature information for positions within a predetermined range from the target position, which information is obtained by analyzing wide-area meteorological observation data; a target area setting unit that sets a predetermined area including the target position as a target area; a surface temperature calculation unit that calculates surface temperature information for each position within the target area using shade information that indicates the position, shape, and size of a shaded area for each date and time within the target area at a predetermined target date and time; and a thermal / wind environment prediction unit that generates predicted information on the thermal / wind environment, including at least one of information on wind speed, wind direction, temperature, and wind pressure for each position within the target area at a specified date and time, by performing a thermal fluid analysis process on the target area based on the weather information acquired by the weather information acquisition unit and the surface temperature information calculated by the surface temperature calculation unit.

2. a weather information acquisition unit that acquires, as weather information for a target position, wind direction information, wind speed information, and temperature information for positions within a predetermined range from the target position, which information is obtained by analyzing wide-area meteorological observation data; a target area setting unit that sets a predetermined area including the target position as a target area; a thermal and wind environment prediction unit that generates predicted information of a thermal and wind environment including at least one of information on wind speed, wind direction, temperature, and wind pressure for each position in the target area at a predetermined date and time by executing a thermal fluid analysis process for the target area based on the information acquired by the weather information acquisition unit; The target area setting unit sets the target area based on wind direction information acquired by the weather information acquisition unit so that the target area includes the target position and has a larger area upwind of the target position. Thermal and wind environment information generating device.

3. The thermal and wind environment information generating device according to claim 1 , wherein the weather information acquisition unit acquires, as the weather information for the target position, weather information for any one of a plurality of positions within a predetermined range from the target position.

4. The thermal and wind environment information generating device of claim 3, wherein the weather information acquisition unit selects the closest position upwind of the target position from among multiple positions within a predetermined range from the target position, and acquires the weather information of the selected position as the weather information for the target position.

5. 2. The thermal and wind environment information generating device according to claim 1, wherein the weather information acquisition unit acquires a plurality of pieces of wind speed information for each height from the ground as the wind speed information, and acquires a plurality of pieces of temperature information for each height from the ground as the temperature information.

6. a ground object information acquisition unit that acquires information on the type, position, shape, size, and material of a ground object within the target area; The thermal and wind environment information generating device according to claim 1 , wherein the thermal and wind environment prediction unit generates the predicted information of the thermal and wind environment using the information acquired by the ground object information acquisition unit.

7. As weather information for the target location, wind direction information, wind speed information, and temperature information for positions within a predetermined range from the target location are obtained by analyzing wide-area meteorological observation data; A predetermined area including the target position is set as a target area; calculating surface temperature information for each position within the target area using shade information indicating the position, shape, and size of a shaded area for each date and time within the target area at a predetermined target date and time; A thermal and wind environment information generation method that generates predicted information on the thermal and wind environment, including at least one of wind speed, wind direction, temperature, and wind pressure for each position within the target area at a specified date and time, by performing a thermal fluid analysis process on the target area based on acquired weather information and surface temperature information.

8. A device communicably connected to the thermal and wind environment information generating device according to any one of claims 1 to 6, A disaster prevention / mitigation information generation device comprising a disaster prevention / mitigation information generation unit that generates information for disaster prevention or mitigation for each location within the target area using predicted information on the thermal and wind environment generated by the thermal and wind environment prediction unit.

9. A disaster prevention and mitigation information generating device communicably connected to the thermal and wind environment information generating device according to any one of claims 1 to 6, A disaster prevention / mitigation information generation method that generates information for disaster prevention or mitigation for each location within the target area using predicted information on thermal and wind environments generated by the thermal and wind environment information generation device.

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