Porous media seepage effect constrains underground building thermal flow field and inversion detection method

Abstract

The present invention provides a porous medium seepage effect constrained underground building heat flow field and inversion detection method, comprising: constructing a geometric model of a mountain according to the topographic information of the mountain; constructing an underground building in the mountain; assigning corresponding porous medium geological materials to the geometric model; adding a physical field of heat transfer of the porous medium geological materials to the geometric model; considering the influence of the voids of the porous medium geological materials and the seepage effect of groundwater on heat transfer, adding a seepage effect physical field to the geometric model; coupling the porous medium geological material heat transfer physical field and the seepage effect physical field to determine the mountain geological background heat flux; determining the solar radiation energy on the mountain surface according to the elevation information of the mountain surface; filtering out the solar radiation energy on the mountain surface and the mountain geological background heat flux under different geological layers in the infrared remote sensing image of the mountain to obtain the heat flow field of the underground building, performing inversion detection on the heat flow field, and determining the location and scale information of the underground building.

Description

Technical Field

[0001] The present invention belongs to the interdisciplinary field of physical geography, thermal physics and remote sensing technology, and more specifically, relates to a porous medium seepage effect constrained underground building thermal flow field and inversion detection method. Background Art

[0002] Porous fractured rock is a complex rock mass commonly found in underground caverns, tunnels, civil air defense structures, and other man-made structures within mountains. It consists of randomly distributed porous media consisting of fractured rock blocks, with gaps between the rock and soil. These porous media are rich in flowing water, known as seepage. By simulating the heat transfer model in actual mountains using porous media and seepage effects, combined with a "layered iterative filtering of background heat flow" method, we can detect the location of underground structures and estimate their distribution range and three-dimensional location.

[0003] The distribution of the temperature field throughout the mountain is controlled by the temperature distribution and thermal state of the shallow crust, as well as by underground artificial structures and external conditions. Theoretical and experimental studies have shown that heat energy is generally transferred in three ways: conduction, convection, and radiation. The distribution of the temperature field within underground artificial structures is primarily achieved through conduction and convection. The seepage effect of the water medium within the interstices of the mountain rock strata transfers heat through convection, thus affecting the temperature field distribution of the entire porous medium. The seepage of water in the interstices of the porous medium directly affects the amplitude of rock temperature fluctuations. Therefore, the influence of the porous medium and the seepage effect on temperature is very significant.

[0004] Heat generated by artificial structures within the mountain due to a range of human activities (equipment heat dissipation, electrical energy, and daily life) is transferred to the mountain surface through seepage and porous media, thereby affecting the surface temperature distribution. Through the seepage effect and thermal convection exchange through the porous media, the water temperature approaches that of the rock mass, achieving a dynamic thermal equilibrium within a given range.

[0005] Existing thermal simulation methods for underground structures only consider the thermal field distribution of underground facilities under conduction through solid bodies such as rock and soil. They fail to account for the influence of rock fractures and the fluid media within them on the underground temperature distribution. Fluid media accelerate the thermal exchange between underground facilities and the mountain background, making it more pronounced at the surface. Previous ANSYS simulations also failed to accurately describe the seepage effect of rock pores and consider heat transfer in porous media, resulting in significant errors in the final detection results. Summary of the Invention

[0006] In response to the defects of the existing technology, the purpose of the present invention is to provide a method for constraining the thermal flow field and inversion detection of underground buildings based on the seepage effect of porous media, aiming to solve the problem that the existing thermal simulation method of underground buildings only considers the thermal field distribution of underground facilities under solid conduction such as rock and soil, but does not consider the influence of rock cracks and the fluid medium therein on the underground temperature field distribution, resulting in large errors in underground building detection.

[0007] To achieve the above objectives, in a first aspect, the present invention provides a method for detecting the thermal flow field and inversion of underground buildings constrained by the seepage effect of porous media, comprising the following steps:

[0008] Constructing a geometric model of the mountain based on the topographic information of the mountain; an underground building is constructed in the mountain;

[0009] Assigning corresponding porous medium geological materials to the geometric model with reference to the geological distribution of the mountain; the porous medium geological materials include soil and rock, and the fluid material in the pores of the porous medium geological materials includes water;

[0010] Setting the parameters of the porous medium geological material and the parameters of the fluid material in the pores to add the physical field of heat transfer of the porous medium geological material to the geometric model;

[0011] Considering the influence of voids in porous geological materials and seepage effect of groundwater on heat transfer, a seepage effect physical field is added to the geometric model;

[0012] The heat transfer physical field of the porous medium geological material and the seepage effect physical field are coupled to determine the mountain geological background heat flux under different geological layers;

[0013] Determine the solar radiation energy on the mountain surface based on the elevation information of the mountain surface;

[0014] The solar radiation energy on the mountain surface and the geological background heat flux of the mountain under different geological layers are filtered out from the infrared remote sensing image of the mountain to obtain the heat flow field of the underground building. The heat flow field of the underground building is then inverted and detected to determine the location information of the underground building.

[0015] In an optional example, the heat transfer physical field of the porous medium geological material and the seepage effect physical field are coupled to determine the mountain geological background heat flux under different geological layers, specifically:

[0016] There are pores in the porous medium geological material, and there is corresponding gaseous water and liquid water in the pores. The pores and the water medium in the pores constitute a seepage field. As the water medium evaporates, the heat absorbed and released by liquefaction will affect the heat transfer characteristics of the porous medium geological material. Taking into account the influence of the seepage field on the physical field of heat transfer of the porous medium geological material, the mountain geological background heat flux is obtained.

[0017] In an optional example, the physical field of heat transfer in the porous media geological material is:

[0018] Q d +Q v =Q1

[0019]

[0020]

[0021] Among them, Q v and Q d represent the convective heat flux and conductive heat flux of porous media geological materials respectively; Q1 is the heat flux input from the outside to the porous media geological materials; ρ and C w represents water density and constant pressure heat capacity respectively; w is the fluid velocity; k is the thermal conductivity of the medium; h is the altitude gradient of the mountain; It is the vertical gradient change of temperature in underground buildings in the mountain.

[0022] In an optional example, the percolation effect physical field is:

[0023]

[0024]

[0025] Q s =κ*A*(h2-h1) / L

[0026] Where t is time, ε p is the porosity, u is the seepage velocity, κ is the permeability, μ is the dynamic viscosity of the fluid, p is the pressure of the fluid, is the fluid pressure difference, g is the acceleration due to gravity, represents the gradient of elevation D; Q s represents the seepage rate, h2 represents the upstream head, h1 represents the downstream head, A represents the cross-sectional area perpendicular to the flow direction, L represents the seepage length; porosity ε p is the pore space volume V f Total volume V t Ratio:

[0027] In an optional example, the heat transfer physical field of the porous medium geological material and the seepage effect physical field are coupled to determine the mountain geological background heat flux under different geological layers; specifically:

[0028] The mass conservation equations of gaseous water and liquid water in the pores of the seepage field are summed to calculate the equilibrium equation for the change of water content in the pores of porous media geological materials with time:

[0029]

[0030]

[0031]

[0032] in, is the water content in the voids of porous geological materials in the seepage field; represents the change of water content in porous media with time, ρ g is the density of gaseous water in the seepage field, w v is the gas mass fraction in the seepage field, u g is the flow rate of gaseous water in porous media, g w is the binary diffusion coefficient of gaseous water in the seepage field and dry air in the gap in the gas phase, u1 is the seepage velocity in the gap in the seepage field, g 1c is the capillary transport coefficient of liquid water in the voids in the seepage field; s1 and s g is the saturation variable of the lower constraint of two-phase flow in porous media, satisfying s1+s g =1;D eff is the effective diffusivity in unsaturated medium;

[0033] In porous media heat transfer, the average thermal property (ρC p ) eff and effective permeability k eff for:

[0034] (ρC p ) eff =ε p (s g ρ g C p,g +s1ρ1C p,1 )+θ s ρ s C p,s

[0035] k eff =ε p (s g k g +s1k1)+θ s k s

[0036] Among them, ρ s is the density of the porous medium matrix, C p,g is the constant-pressure heat capacity of the gaseous water medium in the pores of the porous medium, Cp,1 is the constant-pressure heat capacity of liquid water in porous mesopores, C p,s is the constant pressure heat capacity of the porous medium matrix, θ s is the pore influence factor of the porous medium matrix, C p,g is the constant pressure heat capacity of gaseous water in the pores of porous media, k g is the permeability of gaseous water medium in porous media, k1 is the permeability of liquid water medium in porous mesopores, and k s is the permeability of the liquid phase in the porous medium matrix;

[0037] The average velocity of gaseous and liquid water in porous media u eff for:

[0038] (ρC p ) eff u eff =u g ρ g C p,g +u1ρ1C p,1

[0039] The mountain geological background heat flux Q2 under different geological layers is:

[0040] Q2=-[(C p,v -C p,a )g w +C p,1 g 1c ]

[0041]

[0042] Among them, C p,v is the enthalpy diffusion heat flux generated by the diffusion of gaseous water in porous media, C p,a is the capillary heat flux caused by the presence of liquid water in the pores; (ρC) eq is the water density ρ and the constant pressure heat capacity C ρ The equivalent value of k eq is the effective thermal conductivity and T is the temperature.

[0043] In an optional example, the solar radiation energy on the mountain surface is determined based on the elevation information of the mountain surface; specifically:

[0044] The total solar radiation energy on the mountain surface is obtained by adding the direct solar radiation and the diffuse solar radiation:

[0045] E total =E dir +E dif

[0046] Among them, E total is the total solar radiation energy, Edir and E dif are direct radiation energy and scattered radiation energy respectively;

[0047] The direct solar radiation energy is the sum of the direct radiation in all sun map sectors; the diffuse radiation energy is the sum of the diffuse radiation in all sky map sectors;

[0048] E dir =∑E dir (θ,α)

[0049] E dif =∑E dif (θ,α)

[0050] Among them, E dir (θ,α) and E dif (θ, α) are the direct radiation and diffuse radiation when the centroid is located at the zenith angle θ and azimuth angle α, respectively.

[0051] In an optional example, solar radiation energy on the mountain surface and the geological background heat flux of the mountain under different geological layers are filtered out from the infrared remote sensing image of the mountain to obtain the heat flow field of the underground building, and the heat flow field of the underground building is inverted and detected to determine the location information of the underground building;

[0052] By filtering out the background heat flux of each layer of the mountain and the solar radiation energy on the mountain surface in the infrared remote sensing image of the mountain, the disturbance energy contained in each layer of the mountain is detected and analyzed to determine the disturbance signal distribution image constructed by the heat flow field energy of underground buildings in each layer of the mountain, and to obtain the optimal altitude of underground buildings in the mountain;

[0053] The disturbance signal distribution images of underground buildings in each layer of the mountain are inverted and detected, and the energy contained in the mountain background of different thicknesses is calculated as follows:

[0054]

[0055] Where E(x,y,t) is the energy from the z2(x,y) coordinate to the z1(x,y) coordinate, and HF(x,y,z,t) is the heat flux per unit area; A(z) and ε(z) are the cross-sectional area and heat flux attenuation coefficient at a certain altitude inside the mountain, respectively; z1(x,y) and z2(x,y) are the height coordinates of the mountain surface and the height coordinates of a certain depth from the surface, respectively. By adjusting z2(x,y), the heat flux field energy contained in the mountain background of different thicknesses can be calculated.

[0056] When filtering out the background heat flux of each layer of the mountain and the solar radiation energy on the mountain surface from the infrared remote sensing image of the mountain, when the heat flow field energy of a certain height layer no longer changes, the height at this time is the optimal altitude of the underground building.

[0057] In a second aspect, the present invention provides a porous medium seepage effect constrained underground building thermal flow field and inversion detection system, comprising:

[0058] A mountain model construction unit is configured to construct a geometric model of a mountain based on its topographic information; the mountain includes underground buildings; and to assign corresponding porous media geological materials to the geometric model with reference to the geological distribution of the mountain; the porous media geological materials include soil and rock, and the fluid material in the pores of the porous media geological materials includes water;

[0059] a heat transfer physical field determination unit, configured to set the porous medium geological material parameters and the fluid material parameters in the pores, so as to add the physical field of heat transfer of the porous medium geological material to the geometric model;

[0060] A seepage physical field determination unit is used to consider the influence of the voids in porous geological materials and the seepage effect of groundwater on heat transfer, and to add a seepage effect physical field to the geometric model;

[0061] A background heat flux determination unit is used to couple the heat transfer physical field of the porous medium geological material and the seepage effect physical field to determine the mountain geological background heat flux under different geological layers;

[0062] The building heat flow field determination and inversion unit is used to determine the solar radiation energy on the mountain surface based on the elevation information of the mountain surface; and to filter out the solar radiation energy on the mountain surface and the mountain geological background heat flux under different geological layers in the infrared remote sensing image of the mountain to obtain the heat flow field of the underground building, and to inversely detect the heat flow field of the underground building to determine the location information of the underground building.

[0063] In an optional example, there are pores in the porous medium geological material, and there is corresponding gaseous water and liquid water in the pores. The pores and the water medium in the pores constitute a seepage field. As the water medium evaporates, the heat absorbed and released by the liquefaction will affect the heat transfer characteristics of the porous medium geological material. The background heat flux determination unit takes into account the influence of the seepage field on the physical field of heat transfer of the porous medium geological material to obtain the mountain geological background heat flux.

[0064] In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:

[0065] This paper proposes a method for detecting underground building thermal flow fields and inversion based on the constraints of porous media heat transfer and seepage effects. Water is added to the pores of a porous rock mass, acting as "capillaries" within the mountain. The temperature field of the mountain containing underground structures under the influence of the seepage field is simulated to calculate the background heat flux of the mountain. A thermal radiation model between the mountain and the air layer, combined with DSM data, is used to calculate the energy of solar radiation passing through the atmosphere. Solar radiation interference is filtered out from the raw infrared data. Using an underground target inversion model, the background heat flow field energy of each layer of the mountain is filtered out from infrared remote sensing images. The optimized elevation of underground artificial structures within the mountain is obtained, along with a disturbance signal distribution image constructed from the heat flow field energy of the underground targets within each layer, thereby detecting the location of the underground structures. Compared to previous simulations using solid heat transfer modeling, this method for detecting and locating underground targets constrained by porous media heat transfer and seepage effects reduces the relative error from 13.68% to 8.9%. This method demonstrates significant effectiveness. At present, there are no reports at home or abroad on underground target detection and positioning methods that consider the constraints of heat transfer and seepage effects in porous media. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 This is a flow chart of a method for constraining the thermal flow field and inversion detection of underground buildings using porous media seepage effects, provided by an embodiment of the present invention;

[0067] Figure 2 is a three-dimensional geometric map of the Yujiashan area provided by an embodiment of the present invention;

[0068] Figure 3 This is a three-dimensional geometric model grid map of the Yujiashan area provided by an embodiment of the present invention;

[0069] Figure 4 This is a hierarchical structure design diagram of the Yujiashan three-dimensional geometric model provided by an embodiment of the present invention;

[0070] Figure 5 Schematic diagram of material properties of the Yujiashan porous rock layer medium provided by an embodiment of the present invention;

[0071] Figure 6 Schematic diagram of Wuhan temperature conditions (China Weather Network) provided by an embodiment of the present invention;

[0072] Figure 7 This is a schematic diagram of the three-dimensional thermal field of Yujiashan Mountain provided by an embodiment of the present invention;

[0073] Figure 8 This is a direct solar radiation distribution map of Yujiashan provided by an embodiment of the present invention;

[0074] Figure 9 This is a schematic diagram of direct solar radiation calculation for Yujiashan provided by an embodiment of the present invention;

[0075] Figure 10 A hemispherical view map of the center point of a DSM image provided by an embodiment of the present invention;

[0076] Figure 11 This is a hemispherical view map corresponding to the Yujiashan observation point provided by an embodiment of the present invention (gray indicates visible, black indicates invisible);

[0077] Figure 12 The scattered radiation distribution map of the hemispherical viewing area corresponding to the observation point provided by the embodiment of the present invention;

[0078] Figure 13 This is a scattered radiation distribution diagram of Yujiashan provided by an embodiment of the present invention;

[0079] Figure 14 This is a distribution diagram of total solar radiation energy received by the surface of the Yujiashan area provided by an embodiment of the present invention;

[0080] FIG15( a ) is an image showing the result of filtering out the thermal flow field energy contained in a mountain with a thickness of 10 m, provided by an embodiment of the present invention;

[0081] FIG15( b ) is an image showing the result of filtering out the thermal flow field energy contained in a mountain with a thickness of 20 m, provided by an embodiment of the present invention;

[0082] FIG15( c ) is an image showing the result of filtering out the thermal flow field energy contained in a mountain with a thickness of 30 m, provided by an embodiment of the present invention;

[0083] FIG15( d ) is an image showing the result of filtering out the thermal flow field energy contained in a mountain with a thickness of 40 m, provided by an embodiment of the present invention;

[0084] FIG15( e ) is an image showing the result of filtering out the thermal flow field energy contained in a mountain with a thickness of 50 m, provided by an embodiment of the present invention;

[0085] FIG15( f ) is an image showing the result of filtering out the thermal flow field energy contained in a 60 m thick mountain, provided by an embodiment of the present invention.

[0086] FIG15( g ) is an image showing the result of filtering out the thermal flow field energy contained in a mountain with a thickness of 80 m, provided by an embodiment of the present invention;

[0087] Figure 16 The comparison between the detection result and the actual location of Yujiashan provided by the embodiment of the present invention is shown in the figure;

[0088] Figure 17 1 is a schematic diagram of the target position result of the final inversion result provided by an embodiment of the present invention (after binarization processing);

[0089] Figure 18 is a schematic diagram of target positions on a visible light image provided by an embodiment of the present invention;

[0090] Figure 19 This is an architecture diagram of a porous medium seepage effect constrained underground building thermal flow field and inversion detection system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0091] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is in no way intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0092] The present invention proposes a detection and positioning method for a simulation model of the thermal flow field of artificial buildings in a mountain under the constraints of the heat transfer and seepage effects of porous media. Water medium is added to the voids of the porous medium rock mass and is equivalent to a "capillary" in the mountain. The thermal flow field of the mountain containing underground building facilities under the influence of the seepage field is simulated to calculate the background heat flow of the mountain; the thermal radiation model between the mountain and the air layer is used in combination with DSM data to calculate the solar radiation energy. The interference of solar radiation is filtered out in the original infrared data. The underground target inversion model is used to filter out the background thermal flow field energy of each layer of the mountain in the infrared remote sensing image, and the optimal altitude of the underground artificial building in the mountain and the disturbance signal distribution image constructed by the underground target thermal flow field energy in each layer of the mountain are obtained, thereby detecting the location information of the underground building.

[0093] Figure 1 : is a flow chart of a method for constraining underground building thermal flow field and inversion detection by porous medium seepage effect provided by an embodiment of the present invention; Figure 1 As shown, the following steps are included:

[0094] S101, constructing a geometric model of a mountain based on topographic information of the mountain; wherein the mountain has underground buildings;

[0095] S102, assigning corresponding porous medium geological materials to the geometric model with reference to the geological distribution of the mountain; the porous medium geological materials include: soil and rock, and the fluid material in the pores of the porous medium geological materials includes water;

[0096] S103, setting the parameters of the porous medium geological material and the parameters of the fluid material in the pores, so as to add the physical field of heat transfer of the porous medium geological material to the geometric model;

[0097] S104, considering the influence of the voids of the porous medium geological material and the seepage effect of the groundwater body on heat transfer, adding the seepage effect physical field to the geometric model;

[0098] S105, coupling the heat transfer physical field of the porous medium geological material and the seepage effect physical field to determine the mountain geological background heat flux under different geological layers;

[0099] S106, determining the solar radiation energy on the mountain surface based on the elevation information of the mountain surface;

[0100] S107, filtering out the solar radiation energy on the mountain surface and the mountain geological background heat flux under different geological layers in the infrared remote sensing image of the mountain to obtain the heat flow field of the underground building, and performing inversion detection on the heat flow field of the underground building to determine the location information of the underground building.

[0101] In a specific embodiment, the present invention provides a method for constraining the temperature field and detecting and locating an underground building by using the porous medium heat transfer and seepage effect, and uses the Yujiashan underground air-raid shelter in Wuhan as a research example. The method includes the following steps:

[0102] (1) Based on the DEM / DSM elevation information, a geometric model of the entire target area mountain is constructed in COMSOL multi-physics simulation software. Figure 2 As shown in the figure, the three-dimensional geometric model grid diagram of Yujiashan area is as follows Figure 3 shown.

[0103] (2) The geometric model is designed in layers according to the local geological conditions. The corresponding porous media geological materials (soil, rock, water, etc.) are assigned to the entire geometric model, and the material properties (constant pressure heat capacity, porosity, permeability, thermal conductivity, density, etc.) are set. It is added to the mountain background temperature simulation model. The hierarchical structure design diagram of the Yujiashan 3D geometric model is shown in the figure below. Figure 4 shown.

[0104] Porosity ε p Defined as the pore space volume V f Total volume V t Ratio:

[0105]

[0106] The permeability κ is calculated using the following relationship:

[0107]

[0108] pressure gradient The pressure between the inlet and outlet of the gap, L is the seepage length, u is the velocity vector of the fluid, and it is replaced by the velocity of the outlet in the flow direction.

[0109] In the entire model, the surface 0.9 meters thick is assigned as soil layer medium, and the lower part is rock material. The porous medium used in the entire model construction has different properties, as follows: porous medium rock material, constant pressure heat capacity 750J / (kg*K), density 2600kg / m^3, porosity 5%, etc. The material properties of the porous rock layer medium in Yujiashan are as follows: Figure 5 shown.

[0110] (3) Add the physical field of porous media heat transfer to the model and set the porous media properties, heat flux, temperature and other properties. According to the imaging time of the original infrared data, simulate the weather conditions of the day in the model to make the results more consistent with the actual situation. The imaging time of the infrared data we used was 14:47 on October 8, 2014. After checking the weather conditions of the day, the ambient temperature in the entire model was set to 27℃ and the bottom surface temperature of the model was set to 12℃. Wuhan temperature conditions (China Weather Network) are as follows Figure 6 shown.

[0111] (3.1) The heat conservation in the heat transfer process of the model can be described as:

[0112] Q d +Q v =Q1

[0113]

[0114]

[0115] Among them, Q v and Q d represent the convective heat flux and conductive heat flux of porous media geological materials respectively; Q1 is the heat flux input from the outside to the porous media geological materials; ρ and C w represents water density and constant pressure heat capacity respectively; w is the fluid velocity; k is the thermal conductivity of the medium; h is the altitude gradient of the mountain; is the temperature gradient change in the vertical direction of the underground building in the mountain. The difference approximation can be used in the calculation. The medium here refers to the medium contained in the underground buildings of the mountain.

[0116] (4) Add the seepage effect physical field to the model and include influencing factors such as gravity and pressure.

[0117] The porous media heat transfer model takes into account the voids in the material, but the seepage effect of groundwater on heat transfer also needs to be considered. Therefore, the seepage effect on heat transfer in the fluid flow physics field needs to be incorporated. In the entire model, the fluid flow satisfies:

[0118]

[0119]

[0120] Here, ρ is the water density (kg / m3), t is the time (s), εp is the porosity, and u is the vector of directional permeability, also known as the Darcy velocity, which depends on the permeability κ (m2), the dynamic viscosity μ of the fluid (Pa·s), the pressure p of the fluid (Pa), and the acceleration due to gravity g (m / s2). The gradient of the elevation D (m) indicates the direction of the vertical coordinate y.

[0121] The law of seepage effect in porous media is as follows:

[0122] Q s =κ*A*(h2-h1) / L

[0123] Seepage rate Q s It is proportional to the upstream and downstream head difference h2-h1 and the cross-sectional area A perpendicular to the water flow direction, and inversely proportional to the seepage length L.

[0124] (5) The seepage field and the porous media heat transfer model are coupled to solve the heat propagation model of the mountain background. A corresponding three-dimensional temperature field model is established based on the thermal radiation model between the mountain containing underground buildings and the air layer. The heat flux of the mountain geological background is calculated from the three-dimensional temperature field model of the mountain;

[0125] (5.1) By summing the mass conservation equations for gaseous water and liquid water in the pores of the seepage field, the equilibrium equation for the change of water content in the porous medium with time is calculated:

[0126]

[0127] The water content in the porous medium for:

[0128]

[0129] in It is the water content in the voids of porous media in the seepage field. The water content in the voids in the seepage field includes gaseous water and liquid water. represents the change of water content in porous media with time, ρ1 is the density of liquid water in the seepage field, ρ g is the density of gaseous water in the seepage field, w v is the gas mass fraction in the seepage field, u gis the steam convection flow field coefficient caused by the total pressure gradient in the seepage field, g w is the binary diffusion coefficient of gaseous water in the seepage field and dry air in the gap in the gas phase, u1 is the seepage velocity in the gap in the seepage field, g 1c is the capillary transport coefficient of liquid water in the voids in the seepage field, ε p is the porosity of the porous medium, where s1 and s g is the saturation variable of the lower constraint of two-phase flow in porous media, satisfying s1+s g =1.

[0130] The binary diffusion coefficients g in the gas phase of the gaseous water in the seepage field and the dry air in the voids are w for:

[0131]

[0132] where ρ g is the pressure distribution of the seepage field, w v is the gas mass fraction in the seepage field, D eff Effective diffusivity in unsaturated media.

[0133] The condensation source term in the mass conservation equation for liquid water in porous media cancels out the evaporation source term in the mass conservation equation for gaseous water in the pores of porous media. The evaporation source can be expressed as:

[0134]

[0135] Among them, ε p is the porosity of the porous medium ρ g is the density of gaseous water in the seepage field, w v is the gas mass fraction in the seepage field, u g is the steam convection flow field coefficient caused by the total pressure gradient in the seepage field, g w is the binary diffusion coefficient of gaseous water in the seepage field and dry air in the voids in the gas phase.

[0136] (5.2) In porous media heat transfer, the total velocity field of liquid and gaseous water in the voids is expressed as a thermal convection term. By using the liquid saturation calculated from the water transport equation, the thermal convection state of liquid and gaseous water in the voids can be analyzed.

[0137] The average thermal properties (ρC) are calculated by analyzing the properties of the porous medium matrix, the properties of gaseous water in the air, and the properties of liquid water in the voids. p ) eff and effective permeability k eff :

[0138] (ρC p ) eff =ε p(s g ρ g C p,g +s1ρ1C p,1 )+θ s ρ s C p,s

[0139] k eff =ε p (s g k g +s1k1)+θ s k s

[0140] Among them, (ρC p ) eff is the average thermal property, k eff Effective permeability, ε p is the porosity of the porous medium, s1 and s g is the saturation variable of the lower constraint of two-phase flow in porous media, satisfying s1+s g =1,ρ s is the density of the porous medium matrix, C p,s is the constant pressure heat capacity of the porous medium matrix, k s is the permeability of the liquid phase in the porous medium matrix, θ s is the pore influence factor of the porous medium matrix, ρ g is the density of the gaseous water medium in the pores of the porous medium. C p,g is the constant pressure heat capacity of gaseous water in the pores of porous media, k g is the permeability of gaseous water medium in porous media, ρ1 is the density of liquid water medium in porous mesopores, C p,1 is the constant pressure heat capacity of the liquid water medium in the porous mesopores, k1 is the permeability of the liquid water medium in the porous mesopores. The total velocity can be expressed as the average value of the velocity of gaseous water and liquid water in the porous medium u eff ,Right now:

[0141] (ρC p ) eff u eff =u g ρ g C p,g +u1ρ1C p,1

[0142] where u eff is the average of the velocity of gaseous water and liquid water, u g is the flow rate of gaseous water in porous media, ρ g is the density of gaseous water medium in the pores of porous media, C p,gis the constant pressure heat capacity of the gaseous water medium in the pores of the porous medium, u1 is the flow rate of liquid water in the porous medium, ρ1 is the density of the liquid water medium in the porous medium, C p,1 is the constant-pressure heat capacity of liquid water medium in porous mesopores.

[0143] The heat source term in the model includes the enthalpy diffusion heat flux due to the diffusion of gaseous water in the porous medium and the capillary heat flux caused by the presence of liquid water in the pores:

[0144] Q2=-[(C p,v -C p,a )g w +C p,1 g 1c ]

[0145] Where Q2 is the heat flux of the mountain background, C p,v is the enthalpy diffusion heat flux generated by the diffusion of gaseous water in porous media, C p,a is the capillary heat flux caused by the presence of liquid water in the pores, g w C is the binary diffusion coefficient of gaseous water in the seepage field and dry air in the gap in the gas phase. p,1 is the constant-pressure heat capacity of liquid water medium in porous mesopores.

[0146] The heat transfer equation for the evaporation of liquid water in porous media into gaseous water is:

[0147] Q evap =L v G eavp

[0148] Q evap is the heat of evaporation, L v is the latent heat of vaporization, G eavp Evaporation source.

[0149] (5.3) The constant temperature inside the mountain is used as the boundary condition of the underground building surface in the mountain, which can be expressed as:

[0150] T in =f(y)=T0

[0151] (5.4) For the contact surface between the outer surface of an artificial building in a mountain and the mountain rock layer, the following thermal equilibrium relationship exists:

[0152]

[0153] Among them, T out and T in Respectively represent the surface and internal temperatures of artificial buildings in the mountain; T s represents the mountain surface temperature; c and δc Respectively represent the thickness and thermal conductivity of the concrete between the inner and outer surfaces of the artificial building in the mountain, λ g and δ g They respectively represent the thickness and thermal conductivity of the granite between the outer surface of the artificial building in the mountain and the ground surface.

[0154] (5.5)The heat transfer in porous media is described by the following equation:

[0155]

[0156] Where, (ρC) eq is the density ρ(kg / m 3 ) and the equivalent value of constant pressure heat capacity C (J / kg.k), k eq is the effective thermal conductivity, T is the temperature (K), C w is the constant pressure heat capacity of the effective fluid, and u is the flow velocity of the seepage field.

[0157] By solving the above formulas, the surface temperature field distribution of the coupled model of Yujiashan Mountain can be obtained. The present invention uses COMSOL software to perform modeling and simulation calculations in combination with relevant parameters to obtain the final three-dimensional temperature field distribution of the mountain in the Yujiashan area as shown in the figure. Figure 7 As shown:

[0158] (6) Based on the digital elevation model (DEM) and digital surface model (DSM) data, calculate the solar radiation energy on the mountain surface and filter out the solar radiation interference on the original infrared image. The solar radiation received by the surface mainly includes direct radiation, scattered radiation and reflected radiation. Since reflected radiation accounts for a small proportion and only has a significant impact on the solar radiation received by the surface under special conditions, the reflected radiation part is usually not considered in the solar radiation calculation model; therefore, when using infrared means to detect underground targets, the influence of scattered radiation and direct radiation of solar radiation must be fully considered;

[0159] This embodiment uses a hemispherical viewshed algorithm to calculate the solar radiation received by the surface. The basic idea of this algorithm is as follows: first, the hemispherical viewshed is calculated based on the DSM data (Digital Elevation Model, a terrain model expressed in absolute elevation or altitude) grid; then, the hemispherical viewshed is combined with the sun's position and sky information to determine the direct and diffuse radiation received by the grid; finally, the total solar radiation received by the surface of the area is calculated for each DSM data grid.

[0160] The total solar radiation is obtained by adding the direct solar radiation and the diffuse solar radiation:

[0161] E total =E dir +E dif

[0162] Among them, E total is the total solar radiation, E dir and E dif are the total direct radiation and the total diffuse radiation respectively;

[0163] Direct solar radiation is the sum of direct radiation in all sun map sectors; diffuse solar radiation is the sum of diffuse radiation in all sky map sectors;

[0164] E dir =∑E dir (θ,α)

[0165] E dif =∑E dif (θ,α)

[0166] Among them, E dir (θ,α) and E dif (θ, α) are the direct radiation and diffuse radiation when the centroid is at zenith angle θ and azimuth angle α, respectively;

[0167] Direct solar radiation calculation:

[0168] E dir =∑E dir (θ,α)

[0169] E dir (θ,α)=S const *τ b m(θ) *SD θ,α *SunG θ,α *cos(AngI(θ,α))

[0170]

[0171] AngI(θ,α)=arccos(cos(θ)*cos(G z )+sin(θ)*sin(G z )*cos(α-G α ))

[0172] Among them, S const is the solar constant; τ b is the atmospheric transmittance on the shortest path; m(θ) is the optical path length; SD θ,α For duration, SunG θ,α is the porosity of the sun sector; AngI(θ,α) is the incident angle between the centroid of the sky sector and the vertical line on the surface; G z and G αare the zenith angle and azimuth of the surface, θ1 and θ2 are the zenith angles at the two boundaries of the sky sector, and h is the altitude.

[0173] The direct solar radiation in each sky direction can be calculated using a sun map, which can represent the trajectory of the sun. From the perspective of the hemispherical field of view, the sun map can be divided into several discrete sectors, each with its own corresponding zenith angle and azimuth angle. The direct radiation in each sector can be considered to be the same. By calculating the direct radiation in each sector and superimposing it with the hemispherical field of view, the direct radiation distribution at the observation point can be obtained. The total direct solar radiation energy received at the observation point can then be obtained by cumulative calculation.

[0174] Calculate the sun map at the observation point from midnight to 3 pm. Combined with the calculated hemispherical view, the distribution of direct solar radiation received by the observation point can be obtained as follows: Figure 8 As shown;

[0175] By calculating the direct solar radiation received by each position in turn, the distribution of direct solar radiation energy received by the surface of Yujiashan area can be obtained, as shown in the following figure: Figure 9 As shown;

[0176] Calculation of solar diffuse radiation:

[0177] E dif =∑E dif (θ,α)

[0178] E dif (θ,α)=E glb *p*t c *SkyG θ,α *W(θ,α)*cos(AngI(θ,α))

[0179] E glb =(S const ∑(τ b m(θ) )) / (1-p)

[0180] W(θ,α)=(cosθ2-cosθ1) / Div azi

[0181] Among them, S const is the solar constant; AngI(θ,α) is the incident angle between the centroid of the sky sector and the vertical line on the surface, E glb is the normal total radiation, p is the proportion of diffuse radiation flux, SkyG θ,α is the porosity of the sky sector, h is the altitude value; θ1 and θ2 are the zenith angles at the two boundaries of the sky sector respectively; Div aziis the number of azimuth divisions of the sky map; W(θ,α) is the ratio of the scattered radiation of the sky sector to the scattered radiation of the total sector; t c is the duration; τ b is the atmospheric transmittance on the shortest path;

[0182] Taking the center point of the DSM image in Yujiashan area as an example (145m above sea level, located on the ridge), the hemispherical field of view of the center point of the DSM image is calculated, as follows: Figure 10 As shown;

[0183] When calculating the solar diffuse radiation, Figure 11 As shown, first, a hemispherical upward-looking sky field of view is established for the observation position, and the scattered radiation distribution within this hemispherical field of view is constructed; at the same time, the hemispherical field is divided into multiple sectors. When the sector division is small enough, the solar scattered radiation within the sector can be considered to be the same; the present invention selects 5° as the sector division angle, and divides each sector into 100 small areas according to the radius; the obtained field of view of the specific position point to be calculated for the scattered radiation is superimposed to obtain the scattered radiation distribution that can be received by the position, as shown in FIG. Figure 12 As shown;

[0184] By accumulating the scattered radiation within the visible range of the field of view, the total scattered radiation at the observation position can be obtained; the above operation is performed on all positions in the Yujiashan area in turn, and the scattered radiation distribution map of the Yujiashan area is obtained as follows Figure 13 As shown;

[0185] By summing the direct solar radiation energy and scattered solar radiation energy received by the surface, the total solar radiation energy distribution received by the surface in Yujiashan area can be obtained as follows: Figure 14 As shown;

[0186] (7) Filtering out the background thermal flow field energy of each layer of the mountain in the infrared remote sensing image, obtaining the optimal altitude of the underground building in the mountain and the disturbance signal distribution image constructed by the thermal flow field energy of the underground building in each layer of the mountain;

[0187] As heat from within the mountain conducts through the rock layers, a directional heat flow forms. Similar to the penetrating properties of X-rays, heat flow can "penetrate" the rock layers from the bottom of the mountain to the surface, forming a vector heat flow field. Due to differences in geological conditions, heat flow attenuates to varying degrees as it travels through different rock layers. Furthermore, the heat flow field is correlated with the temperature field within the mountain, which can be approximated as a linear relationship. The infrared radiation from the mountain surface obtained from infrared remote sensing images can be viewed as the superposition of heat flow fields from each layer of the mountain.

[0188] Under ideal conditions, the heat flux per unit area is as follows:

[0189]

[0190] Among them, c m is the volumetric heat capacity of the rock medium, k is the thermal conductivity of the rock medium, is the temperature gradient in the vertical direction, which can be calculated approximately by difference. The temperature gradient needs to be calculated using the temperature field. It can be seen that the two have an approximate linear relationship.

[0191] The temperature field distribution of strata at the same altitude is roughly the same. Similarly, based on the distribution of rock strata, the heat flow field can be considered to be the same. The heat flow field energy of each layer is calculated. The heat flow field energy of mountains of different thicknesses is filtered out in sequence using the real infrared radiation of the mountain surface obtained through infrared remote sensing images. This can effectively protect the target information and obtain a more accurate target disturbance signal distribution.

[0192] Since the heat transfer law of underground buildings in the mountain conforms to the mathematical model of heat conduction, the temperature field distribution of the mountain and the target can be obtained according to the heat transfer theorems and laws, and then the superimposed heat flow field distribution of the two can be calculated. Given that the thermal radiation model between the mountain and the air layer is a three-dimensional structure, the energy field distribution formula should also be expressed in a three-dimensional form. Assuming that the radiation energy at the mountain surface (x0, y0, z0) at a certain time t0 is BT(x0, y0, z0, t), according to the law of conservation of energy, the value of this radiation energy can be calculated from the heat flow field energy of the underground artificial building, the background heat flow field energy of the mountain, the radiation energy exchanged between them and the environment, and the received solar radiation energy:

[0193] BT(x0,y0,z0,t)=B(x,y,z,t)+T(x,y,z,t)+δ(x,y,z,t)+S(x0,y0,z0,t)-B m (x,y,z,t)

[0194] Among them, BT(x0,y0,z0,t) is the radiation energy of the mountain surface, B(x,y,z,t) is the background heat flow field energy of the mountain, T(x,y,z,t) is the heat flow field energy of the underground artificial building, δ(x,y,z,t) is the radiation energy of the contact surface between the mountain and the air, S(x0,y0,z0,t) is the solar radiation energy received by the mountain surface, B m (x, y, z, t) is the thermal flow field energy of the rock mass at the location corresponding to the underground artificial building;

[0195] In a real environment, the radiation energy at the interface between the mountain and the air is very small and can be basically ignored compared to the thermal flux energy between the mountain and the target. In this invention, only the relationship between the background thermal flux energy of the mountain, the thermal flux energy of the underground artificial building-like target, and the received solar radiation energy is considered.

[0196] During the detection and inversion positioning process, it is necessary to combine the energy distribution of the mountain background thermal flow field and calculate the energy contained in the mountain background of different thicknesses, as follows:

[0197]

[0198] Among them, A(z) and ε(z) are the cross-sectional area and heat flow attenuation coefficient at a certain altitude inside the mountain, respectively; z1(x, y) and z2(x, y) are the height coordinates of the mountain surface and the height coordinates of a certain depth from the surface, respectively. By adjusting z2(x, y), the heat flow field energy contained in the mountain background of different thicknesses can be calculated;

[0199] When the geological background energy of the underground target is filtered out to a certain depth, the disturbance signal of the underground structure is essentially complete. When the background energy is filtered out to a deeper depth, the change in the disturbance image is minimal, and the range of the disturbance signal area has hardly changed compared to the detection and inversion positioning results of the previous height layer. The increase in this area is mainly due to the heat flow interference of the rock mass within the two height layers. This interference is gradually weakened in this area during the layer-by-layer detection and inversion positioning process. When the energy disturbance stripped from the target area no longer changes, the optimal altitude of the underground structure in the mountain is obtained.

[0200] Yujia Mountain has a maximum altitude of 146 meters. The image was segmented at 10-meter intervals, and the background radiation field was peeled off layer by layer. By continuously slicing downward, we obtained disturbed images after filtering out the mountain background radiation field at depths of 10, 20, 30, ..., 60, 70, and 80 meters. The results are shown below:

[0201] In the detection and inversion positioning process, when the background energy is stripped to a depth of 70m, the disturbance of the underground target is basically obtained completely; when the background energy is stripped to 80m, it can be seen that the change of the disturbance image is very small at this time. Compared with the detection and inversion positioning results of the previous height layer, the range of the disturbance area has hardly changed. The increased part at this time is mainly the regional interference within the 70m~80m height layer. The above experiments have proved that this type of interference will be gradually weakened in the detection and inversion positioning process layer by layer; according to the visible light image, the interference of rocks and houses on the surface of the mountain is further filtered out; finally, the detection and inversion positioning results of the Yujiashan area are obtained, as shown in the figure. Figure 15(a)-Figure 15(g) As shown;

[0202] The final inversion depth is 80 meters, and the number of pixels in the target disturbance area after deconvolution is 207. Referring to the underground civil air defense engineering map of Yujiashan, the detection results of Yujiashan are compared with the actual location. Figure 16As shown. In previous studies, the average altitude burial depth was used to detect the burial depth of the underground civil air defense project in Yujiashan. The average altitude of Yujiashan is 100m, and the altitude of the underground facility exit is 63m, so the actual burial depth is 37m. In this detection, we used the height of the background heat flow of Yujiashan layer by layer to calculate the burial depth of the target area. The highest altitude of Yujiashan is 146m. It is divided into sections at a height interval of 10m, and the background radiation field is peeled off layer by layer downward. By continuously stratifying downward, we obtain the disturbance image after filtering out the mountain background radiation field at depths of 10m, 20m, 30m, ..., 60m, 70m, and 80m, as shown below. Figure 17 As shown in the figure, the final detection depth is 80 meters, which is more reasonable than the previous measurement standards. The overall area of the Yujiashan underground civil air defense project is 19,000 square meters. The solid heat transfer model used by previous researchers for detection covers an area of 16,400 square meters with a relative error of 13.68%. The underground target detection area under the constraints of porous medium heat transfer and seepage effects is 20,700 square meters with a relative error of only 8.9%. The detection rate has increased from 86.32% to 91.1%. The detection area is marked on the visible light image as follows Figure 18 As shown:

[0203] This method, which uses porous media heat transfer and seepage effects to constrain the calculation of underground target background heat flux, can detect underground structures in mountains. This method can obtain relatively accurate information about the depth and location of underground structures from infrared remote sensing images. Without this method, inversion detection and location of artificial structures in mountains is difficult due to strong environmental interference and weak target signals. This invention, however, enables inversion detection of underground structures in mountainous environments.

[0204] The distribution of the temperature field across the entire mountain is controlled by the temperature distribution and thermal state of the shallow crust, as well as by underground artificial construction projects and external conditions. Artificial buildings within the mountain generate heat due to a series of human activities (equipment heat dissipation, electrical energy, and daily life). This heat is transferred to the mountain surface through the seepage effect and porous media, thereby affecting the distribution of the temperature field on the mountain surface. Through the seepage effect and thermal convection exchange between the porous media, the temperature of the water flow approximates that of the rock mass, achieving a state of heat equilibrium within a given range. Water is added to the voids of the porous rock mass and is equivalent to a "capillary" in the mountain. The temperature field of the mountain containing underground construction facilities under the influence of the seepage field is simulated to calculate the background heat flux of the mountain. A thermal radiation model between the mountain and the air layer is used, combined with DSM data, to calculate solar radiation energy. Interference from solar radiation is filtered out from the raw infrared data. By adopting the underground target inversion model, the background heat flow field energy of each layer of the mountain is filtered out in the infrared remote sensing image, and the optimal altitude of the underground artificial buildings in the mountain and the disturbance signal distribution image constructed by the heat flow field energy of the underground targets in each layer of the mountain are obtained, thereby detecting the location information of the underground buildings.

[0205] Figure 19 : is a diagram of the architecture of the porous medium seepage effect constrained underground building thermal flow field and inversion detection system provided by an embodiment of the present invention; Figure 19 Shown, including:

[0206] The mountain model construction unit 1910 is configured to construct a geometric model of the mountain based on its topographic information; the mountain includes underground structures; and to assign corresponding porous media geological materials to the geometric model based on the geological distribution of the mountain; the porous media geological materials include soil and rock, and the fluid material in the pores of the porous media geological materials includes water.

[0207] a heat transfer physical field determination unit 1920, configured to set the porous medium geological material parameters and the fluid material parameters in the pores, so as to add the physical field of heat transfer of the porous medium geological material to the geometric model;

[0208] A seepage physical field determination unit 1930 is configured to consider the influence of the voids in the porous geological material and the seepage effect of the groundwater on heat transfer and add a seepage effect physical field to the geometric model;

[0209] The background heat flux determination unit 1940 is used to couple the heat transfer physical field of the porous medium geological material and the seepage effect physical field to determine the mountain geological background heat flux under different geological layers;

[0210] The building heat flow field determination and inversion unit 1950 is used to determine the solar radiation energy on the mountain surface based on the elevation information of the mountain surface; and to filter out the solar radiation energy on the mountain surface and the mountain geological background heat flux under different geological layers in the infrared remote sensing image of the mountain to obtain the heat flow field of the underground building, and to inversely detect the heat flow field of the underground building to determine the location information of the underground building.

[0211] Specifically, Figure 19 The detailed functional implementation of each unit can be found in the records of the aforementioned method embodiment and will not be repeated here.

[0212] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for detecting thermal flow field and inversion of underground buildings constrained by porous medium seepage effect, characterized in that: The following steps are involved: Constructing a geometric model of the mountain based on the topographic information of the mountain; an underground building is constructed in the mountain; Assigning corresponding porous medium geological materials to the geometric model with reference to the geological distribution of the mountain; The porous medium geological material includes soil and rock, and the fluid material in the pores of the porous medium geological material includes water; Setting the parameters of the porous medium geological material and the parameters of the fluid material in the pores to add the physical field of heat transfer of the porous medium geological material to the geometric model; Considering the influence of voids in porous geological materials and seepage effect of groundwater on heat transfer, a seepage effect physical field is added to the geometric model; The heat transfer physical field of the porous medium geological material and the seepage effect physical field are coupled to determine the mountain geological background heat flux under different geological layers; Determine the solar radiation energy on the mountain surface based on the elevation information of the mountain surface; The solar radiation energy on the mountain surface and the geological background heat flux of the mountain under different geological layers are filtered out from the infrared remote sensing image of the mountain to obtain the heat flow field of the underground building. The heat flow field of the underground building is then inverted and detected to determine the location information of the underground building.

2. The method according to claim 1, characterized in that The heat transfer physical field of the porous medium geological material and the seepage effect physical field are coupled to determine the mountain geological background heat flux under different geological layers, specifically: There are pores in the porous medium geological material, and there is corresponding gaseous water and liquid water in the pores. The pores and the water medium in the pores constitute a seepage field. As the water medium evaporates, the heat absorbed and released by liquefaction will affect the heat transfer characteristics of the porous medium geological material. Taking into account the influence of the seepage field on the physical field of heat transfer of the porous medium geological material, the mountain geological background heat flux is obtained.

3. The method according to claim 1 or 2, characterized in that The physical field of heat transfer in porous media geological materials is: Q d +Q v =Q1 Among them, Q v and Q d represent the convective heat flux and conductive heat flux of porous media geological materials respectively; Q1 is the heat flux input from the outside to the porous media geological materials; ρ and C w represents water density and constant pressure heat capacity respectively; w is the fluid velocity; k is the thermal conductivity of the medium; h is the altitude gradient of the mountain; It is the vertical gradient change of temperature in underground buildings in the mountain.

4. The method according to claim 3, characterized in that The physical field of the seepage effect is: Q s =κ*A*(h2-h1) / L Where t is time, ε p is the porosity, u is the seepage velocity, κ is the permeability, μ is the dynamic viscosity of the fluid, p is the pressure of the fluid, is the fluid pressure difference, g is the acceleration due to gravity, represents the gradient of elevation D; Q s represents the seepage rate, h2 represents the upstream head, h1 represents the downstream head, A represents the cross-sectional area perpendicular to the flow direction, L represents the seepage length; porosity ε p is the pore space volume V f Total volume V t Ratio:

5. The method according to claim 4, characterized in that The heat transfer physical field of the porous medium geological material and the seepage effect physical field are coupled to determine the mountain geological background heat flux under different geological layers; specifically: The mass conservation equations of gaseous water and liquid water in the pores of the seepage field are summed to calculate the equilibrium equation for the change of water content in the pores of porous media geological materials with time: in, is the water content in the voids of porous geological materials in the seepage field; represents the change of water content in porous media with time, ρ g is the density of gaseous water in the seepage field, w v is the gas mass fraction in the seepage field, u g is the flow rate of gaseous water in porous media, g w is the binary diffusion coefficient of gaseous water in the seepage field and dry air in the gap in the gas phase, u1 is the seepage velocity in the gap in the seepage field, g 1c is the capillary transport coefficient of liquid water in the voids in the seepage field; s1 and s g is the saturation variable of the lower constraint of two-phase flow in porous media, satisfying s1+s g =1;D eff is the effective diffusivity in unsaturated medium; In porous media heat transfer, the average thermal property (ρC p ) eff and effective permeability k eff for: (ρC p ) eff =e p (s g r g C p,g +s1ρ1C p,1 )+θ s r s C p,s k eff =e p (s g k g +s1k1)+θ s k s Among them, ρ s is the density of the porous medium matrix, C p,g is the constant-pressure heat capacity of the gaseous water medium in the pores of the porous medium, C p,1 is the constant-pressure heat capacity of liquid water in porous mesopores, C p,s is the constant pressure heat capacity of the porous medium matrix, θ s is the pore influence factor of the porous medium matrix, C p,g is the constant pressure heat capacity of gaseous water in the pores of porous media, k g is the permeability of gaseous water medium in porous media, k1 is the permeability of liquid water medium in porous mesopores, and k s is the permeability of the liquid phase in the porous medium matrix; The average velocity of gaseous and liquid water in porous media u eff for: (ρC p ) eff you eff =u g r g C p,g +u1ρ1C p,1 The mountain geological background heat flux Q2 under different geological layers is: Q2=-[(C p,v -C p,a )g w +C p,1 g 1c ] Among them, C p,v is the enthalpy diffusion heat flux generated by the diffusion of gaseous water in porous media, C p,a is the capillary heat flux caused by the presence of liquid water in the pores; (ρC) eq is the water density ρ and the constant pressure heat capacity C ρ The equivalent value of k eq is the effective thermal conductivity and T is the temperature.

6. The method according to any one of claims 1 to 4, characterized in that The solar radiation energy on the mountain surface is determined based on the elevation information of the mountain surface; specifically: The total solar radiation energy on the mountain surface is obtained by adding the direct solar radiation and the diffuse solar radiation: AND total =And dir +E dif Among them, E total is the total solar radiation energy, E dir and E dif are direct radiation energy and scattered radiation energy respectively; The direct solar radiation energy is the sum of the direct radiation in all sun map sectors; the diffuse radiation energy is the sum of the diffuse radiation in all sky map sectors; E dir =∑E dir (will) E dif =∑E dif (will) Among them, E dir (θ,α) and E dif (θ, α) are the direct radiation and diffuse radiation when the centroid is located at the zenith angle θ and azimuth angle α, respectively.

7. The method according to any one of claims 1 to 4, characterized in that Filtering out the solar radiation energy on the mountain surface and the geological background heat flux of the mountain under different geological layers in the infrared remote sensing image of the mountain to obtain the heat flow field of the underground building, and performing inversion detection on the heat flow field of the underground building to determine the location information of the underground building; The solar radiation energy on the mountain surface and the background heat flux of each layer of the mountain are filtered out from the infrared remote sensing image of the mountain. The disturbance energy contained in each layer of the mountain is detected and analyzed to determine the disturbance signal distribution image constructed by the heat flow field energy of underground buildings in each layer of the mountain, and to obtain the optimal altitude of underground buildings in the mountain. The disturbance signal distribution image of underground buildings in each layer of the mountain is inverted, and the energy contained in the mountain background of different thicknesses is calculated as follows: Where E(x,y,t) is the energy from the z2(x,y) coordinate to the z1(x,y) coordinate, and HF(x,y,z,t) is the heat flux per unit area; A(z) and ε(z) are the cross-sectional area and heat flux attenuation coefficient at a certain altitude inside the mountain, respectively; z1(x,y) and z2(x,y) are the height coordinates of the mountain surface and the height coordinates of a certain depth from the surface, respectively. By adjusting z2(x,y), the heat flux field energy contained in the mountain background of different thicknesses can be calculated. When filtering out the background heat flux of each layer of the mountain and the solar radiation energy on the mountain surface from the infrared remote sensing image of the mountain, when the heat flow field energy of a certain height layer no longer changes, the height at this time is the optimal altitude of the underground building.

8. A porous medium seepage effect constrained underground building thermal flow field and inversion detection system, characterized by: include: A mountain model building unit, used to build a geometric model of the mountain based on the topographic information of the mountain; There is an underground building constructed in the mountain; and assigning corresponding porous medium geological materials to the geometric model with reference to the geological distribution of the mountain; The porous medium geological material includes soil and rock, and the fluid material in the pores of the porous medium geological material includes water; a heat transfer physical field determination unit, configured to set the porous medium geological material parameters and the fluid material parameters in the pores, so as to add the physical field of heat transfer of the porous medium geological material to the geometric model; A seepage physical field determination unit is used to consider the influence of the voids in porous geological materials and the seepage effect of groundwater on heat transfer, and to add a seepage effect physical field to the geometric model; A background heat flux determination unit is used to couple the heat transfer physical field of the porous medium geological material and the seepage effect physical field to determine the mountain geological background heat flux under different geological layers; The building heat flow field determination and inversion unit is used to determine the solar radiation energy on the mountain surface based on the elevation information of the mountain surface; and to filter out the solar radiation energy on the mountain surface and the mountain geological background heat flux under different geological layers in the infrared remote sensing image of the mountain to obtain the heat flow field of the underground building, and to inversely detect the heat flow field of the underground building to determine the location information of the underground building.

9. The system according to claim 8, characterized in that There are pores in the porous medium geological material, and there is corresponding gaseous water and liquid water in the pores. The pores and the water medium in the pores constitute a seepage field. As the water medium evaporates, the heat absorbed and released by liquefaction will affect the heat transfer characteristics of the porous medium geological material. The background heat flux determination unit takes into account the influence of the seepage field on the physical field of heat transfer of the porous medium geological material to obtain the mountain geological background heat flux.

10. The system according to claim 8 or 9, characterized in that The physical field of heat transfer of porous medium geological materials determined by the heat transfer physical field determination unit is: Q d +Q v =Q1 Among them, Q v and Q d represent the convective heat flux and conductive heat flux of porous media geological materials respectively; Q1 is the heat flux input from the outside to the porous media geological materials; ρ and C w represents water density and constant pressure heat capacity respectively; w is the fluid velocity; k is the thermal conductivity of the medium; h is the altitude gradient of the mountain; It is the temperature gradient change in the vertical direction of the underground building in the mountain; The seepage effect physical field determined by the seepage physical field determination unit is: Q s =κ*A*(h2-h1) / L Where t is time, ε p is the porosity, u is the seepage velocity, κ is the permeability, μ is the dynamic viscosity of the fluid, p is the pressure of the fluid, is the fluid pressure difference, g is the acceleration due to gravity, represents the gradient of elevation D; Q s represents the seepage rate, h2 represents the upstream head, h1 represents the downstream head, A represents the cross-sectional area perpendicular to the flow direction, L represents the seepage length; porosity ε p is the pore space volume V f Total volume V t Ratio: The background heat flux determination unit couples the heat transfer physical field of the porous medium geological material and the seepage effect physical field to determine the mountain geological background heat flux under different geological layers. Specifically, the unit sums the mass conservation equations of gaseous water and liquid water in the pores of the seepage field to calculate the equilibrium equation of the water content in the porous medium geological material pores over time: in, is the water content in the voids of porous geological materials in the seepage field; represents the change of water content in porous media with time, ρ g is the density of gaseous water in the seepage field, w v is the gas mass fraction in the seepage field, u g is the flow rate of gaseous water in porous media, g w is the binary diffusion coefficient of gaseous water in the seepage field and dry air in the gap in the gas phase, u1 is the seepage velocity in the gap in the seepage field, g 1c is the capillary transport coefficient of liquid water in the voids in the seepage field; s1 and s g is the saturation variable of the lower constraint of two-phase flow in porous media, satisfying s1+s g =1;D eff is the effective diffusivity in unsaturated medium; In porous media heat transfer, the average thermal property (ρC p ) eff and effective permeability k eff for: (ρC p ) eff =e p (s g r g C p,g +s1ρ1C p,1 )+θ s r s C p,s k eff =e p (s g k g +s1k1)+θ s k s Among them, ρ s is the density of the porous medium matrix, C p,g is the constant-pressure heat capacity of the gaseous water medium in the pores of the porous medium, C p,1 is the constant-pressure heat capacity of liquid water in porous mesopores, C p,s is the constant pressure heat capacity of the porous medium matrix, θ s is the pore influence factor of the porous medium matrix, C p,g is the constant pressure heat capacity of gaseous water in the pores of porous media, k g is the permeability of gaseous water medium in porous media, k1 is the permeability of liquid water medium in porous mesopores, and k s is the permeability of the liquid phase in the porous medium matrix; The average velocity of gaseous and liquid water in porous media u eff for: (ρC p ) eff you eff =u g r g C p,g +u1ρ1C p,1 The mountain geological background heat flux Q2 under different geological layers is: Q2=-[(C p,v -C p,a )g w +C p,1 g 1c ] Among them, C p,v is the enthalpy diffusion heat flux generated by the diffusion of gaseous water in porous media, C p,a is the capillary heat flux caused by the presence of liquid water in the pores; (ρC) eq is the water density ρ and the constant pressure heat capacity C ρ The equivalent value of k eq is the effective thermal conductivity and T is the temperature.

Images