Inversion method, system and medium for thermophysical parameters of porous media

Abstract

The application discloses a kind of inversion measurement method, system and medium for the thermal physical parameters of porous medium, belong to material thermal physical parameter measurement technical field, method is: obtaining temperature measurement data;Obtain heat transfer model, wherein, heat transfer model is used to dynamically correct apparent specific heat and target thermal conductivity according to the temperature value of porous medium at current time, to calculate the temperature value of next time, target thermal conductivity is determined according to first model parameter and second model parameter, first model parameter is used to characterize solid heat conduction, and second model parameter is used to characterize pore thermal radiation, heat transfer model is one-dimensional heat transfer model determined according to energy conservation equation in target heat transfer direction;According to temperature measurement data, the first model parameter and the second model parameter in heat transfer model are inverted, to obtain first target parameter and second target parameter, therefore, by implementing the application, it can realize to improve measurement accuracy.

Description

Technical Field

[0001] This invention relates to the field of material thermophysical parameter measurement technology, and in particular to a method, system and medium for inverting the measurement of thermophysical parameters of porous media. Background Technology

[0002] In engineering fields such as island and reef construction in the South China Sea, high-temperature underground energy storage, and ground source heat pumps, accurately grasping the thermophysical parameters of typical porous media such as calcareous sand under extreme high-temperature conditions (such as fire) is the core basis for structural safety design, energy storage efficiency assessment, and heat pump system optimization. However, such media are often in a water-containing state at high temperatures and may undergo significant physical phase changes and chemical reactions. Their heat transfer process involves a complex coupling of multiple mechanisms, including solid heat conduction, pore heat radiation, and latent heat of phase change.

[0003] Currently, the thermal probe transient method is mainly used to measure the high-temperature thermal properties of porous media. This method is based on the transient heat transfer theory of a linear heat source in an infinite medium. A heating probe is inserted into the medium to be tested, its temperature rise response is recorded, and then the equivalent thermal conductivity of the medium is deduced.

[0004] However, this method is based on a theoretical model that is purely thermally conductive, without an internal heat source, and ignores the contribution of high-temperature radiation. When it is actually used to measure high-temperature, water-containing reactive porous media, the heat absorption of water vaporization and other chemical reactions inside the medium will seriously interfere with the temperature rise curve of the probe. At the same time, the significantly enhanced pore thermal radiation effect at high temperatures will also be coupled into the single equivalent thermal conductivity and cannot be separated, resulting in extremely low accuracy of the measurement results in the phase transition temperature range. Summary of the Invention

[0005] This invention provides a method, system, and medium for inverting the measurement of thermal properties of porous media, which can solve the problem of low accuracy of measurement results in the phase transition temperature range.

[0006] This invention provides a method for inverting and measuring the thermal properties of porous media, comprising: Acquire temperature measurement data of porous media at different depths along the target heat transfer direction during the heating process; A heat transfer model is obtained, wherein the heat transfer model is used to dynamically correct the apparent specific heat capacity and target thermal conductivity based on the temperature value of the porous medium at the current moment, so as to calculate the temperature value at the next moment. The target thermal conductivity is determined according to a first model parameter and a second model parameter. The first model parameter is used to characterize the heat conduction of the solid, and the second model parameter is used to characterize the heat radiation of the pores. The heat transfer model is a one-dimensional heat transfer model determined according to the energy conservation equation in the target heat transfer direction. Based on the temperature measurement data, the first model parameters and the second model parameters in the heat transfer model are inverted to obtain the first target parameters and the second target parameters.

[0007] This invention provides realistic, multi-dimensional temperature constraint data for parameter inversion of heat transfer models, avoiding deviations in inversion results caused by single-depth temperature data and improving the accuracy and reliability of parameter inversion. Simultaneously, temperature data along the target heat transfer direction can directly match the computational dimension of the one-dimensional heat transfer model, reducing errors caused by model dimensionality reduction. The one-dimensional heat transfer model constructed based on the energy conservation equation simplifies the computational complexity of complex three-dimensional heat transfer problems, reduces the computational power requirements for model solving, and ensures the physical consistency of the heat transfer process, avoiding distortion of calculation results caused by non-conservation models. Dynamic correction of apparent specific heat capacity and target thermal conductivity breaks through... The limitation of fixed constants for specific heat capacity and thermal conductivity in traditional heat transfer models is overcome by making model parameters dynamically change with temperature. This allows for accurate reflection of the changes in the thermophysical properties of porous media at different temperatures, improving the model's fitting accuracy to the actual heat transfer process. By decomposing the target thermal conductivity into two independent components—solid heat conduction (first parameter) and pore heat radiation (second parameter)—a refined characterization of the heat transfer mechanism of porous media is achieved, providing a clear optimization target for subsequent parameter inversion. The inversion algorithm matches the measured temperature data with the model calculation data, directly obtaining model parameters that match the actual operating conditions, thus improving the accuracy and relevance of parameter measurements.

[0008] Furthermore, the step of dynamically correcting the apparent specific heat capacity and target thermal conductivity based on the current temperature value of the porous medium specifically involves: The weighting factor is obtained by normalizing the liquid saturation and temperature values ​​of the porous medium at the current moment. When the porous medium is in a dry state, the first model parameters, the second model parameters, and the temperature value are input into a preset first function to calculate the linear term corresponding to the solid heat conduction and the nonlinear term corresponding to the pore heat radiation, so as to obtain the first thermal conductivity in the dry state. To obtain the thermal conductivity of water, when the porous medium is in a wet state, the thermal conductivity of the water and the linear term are calculated according to the geometric mean model to obtain the second thermal conductivity under wet conditions. The first thermal conductivity, the second thermal conductivity, and the weighting factor are input into a preset second function to obtain the target thermal conductivity.

[0009] By normalizing the liquid saturation and temperature values ​​to obtain weighting factors, a quantitative characterization of the dry and wet states of porous media is achieved. The weighting factors can dynamically reflect the influence of moisture content in the medium on heat transfer, providing a reasonable quantitative basis for the fusion of thermal conductivity in dry and wet states. The contribution ratio of the two heat transfer mechanisms in the dry state is clearly distinguished: the linear term corresponds to the linear heat transfer law of solid heat conduction, and the nonlinear term corresponds to the nonlinear heat transfer law of pore heat radiation, making the calculation of thermal conductivity more in line with the physical essence. At the same time, the first function directly correlates the parameters of the first and second models with the thermal conductivity, providing a clear mathematical mapping relationship for parameter inversion. The geometric mean model is a classic model suitable for calculating the thermal conductivity of multiphase media, which can accurately reflect the synergistic heat transfer effect of the solid skeleton and pore water in the wet state. The target thermal conductivity is obtained by fusing the first and second thermal conductivity based on the weighting factors, realizing a smooth transition of thermal conductivity in dry and wet states, and improving the model's adaptability to the dynamic changes of porous media from dry to wet (or vice versa).

[0010] Furthermore, the step of dynamically correcting the apparent specific heat capacity and target thermal conductivity based on the current temperature value of the porous medium specifically involves: The initial heat capacity of the porous medium in a dry state is obtained, and a preset first temperature range and a second temperature range are obtained. The first temperature range is used to determine whether there is a water phase change in the porous medium, and the second temperature range is used to determine whether there is skeleton decomposition in the porous medium. If the temperature value is within the first temperature range, the first equivalent heat capacity is adjusted according to the liquid saturation to obtain the apparent specific heat capacity, wherein the first equivalent heat capacity is used to characterize the latent heat of vaporization of water. If the temperature value is within the second temperature range, then a second equivalent heat capacity for characterizing the endothermic decomposition of the skeleton is determined based on the temperature value, and the apparent specific heat capacity is obtained by combining the second equivalent heat capacity and the initial heat capacity.

[0011] This provides a benchmark reference value for the dynamic correction of apparent specific heat capacity, clarifies the basic heat capacity parameters under conditions of no water phase change and no skeleton decomposition, and ensures the accuracy of model calculations under normal temperature and dry conditions. Incorporating the latent heat of water vaporization into the specific heat capacity correction scope solves the problem of temperature simulation deviation in the high-temperature range caused by the traditional model neglecting the latent heat of phase change. Simultaneously, by combining liquid saturation adjustment with equivalent heat capacity, the influence of latent heat is matched to the water content, improving the accuracy of heat transfer simulation during the phase change process. Considering the endothermic effect of porous medium skeleton decomposition at high temperatures expands the applicable temperature range of the model, avoiding the problem of overestimating temperature values ​​in the high-temperature range caused by the traditional model neglecting skeleton decomposition, and achieving phased and accurate correction of apparent specific heat capacity.

[0012] Furthermore, the adjustment of the first equivalent heat capacity based on the liquid saturation to obtain the apparent specific heat capacity specifically involves: The first equivalent heat capacity is determined based on the temperature value; The first equivalent heat capacity is adjusted according to the liquid saturation, and the apparent specific heat capacity is obtained by combining the adjusted equivalent heat capacity term with the initial heat capacity.

[0013] This further refines the correction logic for the apparent specific heat capacity during the water phase transition stage, realizing dual control where "temperature determines the baseline value of equivalent heat capacity and liquid saturation determines the adjustment range of equivalent heat capacity." This makes the correction of equivalent heat capacity more consistent with the uneven distribution of water in actual porous media, and improves the accuracy of heat capacity calculation under non-uniform saturated conditions.

[0014] Furthermore, the liquid saturation is determined based on a steady-state seepage model, specifically: The obtained water level, steady-state flux, saturated permeability coefficient, and saturated water content are input into the steady-state seepage model to obtain the volumetric water content distribution value of the porous medium in the initial state and the liquid saturation.

[0015] This method of calculating liquid saturation using a steady-state seepage model ensures the physical rationality and computational accuracy of the liquid saturation parameters, avoiding errors caused by directly assuming a uniform distribution of liquid saturation. At the same time, the input parameters are all easily measurable conventional hydrological parameters, lowering the threshold for practical application of the model.

[0016] Further, the step of inverting the first model parameters and the second model parameters in the heat transfer model based on the temperature measurement data to obtain the first target parameters and the second target parameters specifically involves: Obtain an objective function with the first model parameters and the second model parameters as optimization variables, and calculate the loss value between the temperature measurement data and the simulated temperature data output by the heat transfer model based on the objective function; The heat transfer model is iteratively optimized based on the loss value until a preset stopping condition is met, at which point the iteration stops and the first target parameter and the second target parameter are obtained.

[0017] This clarifies the mathematical implementation path of parameter inversion. The deviation between measured and simulated values ​​is quantified through the objective function, and the optimization objective is to minimize the loss value, thus ensuring the optimality of the inversion parameters. The iterative optimization process can automatically correct parameter deviations, improving the efficiency and accuracy of parameter inversion and avoiding the subjectivity and tediousness of manual calculations.

[0018] Furthermore, the first function is: ; in, It is the first thermal conductivity. It is a coupled linear term of solid-state heat conduction and gas-state heat conduction. It is the thermal radiation term. The first model parameters include A and B, and C is the second model parameter. The second function is: ; ; ; in, It is solid-state conduction, approximately , It's porosity. It is the thermal conductivity of water. It is a weighting factor.

[0019] This provides a clear and directly executable mathematical formula for calculating the target thermal conductivity, avoiding calculation ambiguity caused by vague function forms. At the same time, the formula clarifies the quantitative relationship between the first model parameters (A, B), the second model parameter (C), and the thermal conductivity, giving the parameter inversion a clear mathematical basis and improving the repeatability and verifiability of the model.

[0020] Furthermore, the energy conservation equation is: ; in, These are spatial coordinates representing depth. It is time. It's temperature. It is the effective density, and , It is the apparent specific heat capacity.

[0021] This clarifies the core governing equations of the one-dimensional heat transfer model, using the product of effective density and apparent specific heat capacity as the heat capacity term. This conforms to the classical physical equations of heat conduction in porous media, ensuring the theoretical rigor of the model. At the same time, the equations are concise, facilitating numerical solutions and parameter sensitivity analysis.

[0022] Another embodiment of the present invention provides an inversion measurement system for the thermal properties of porous media, comprising: a measurement module, a fitting module, and an inversion module; The measurement module is used to acquire temperature measurement data of the porous medium at different depths in the target heat transfer direction during the heating process. The fitting module is used to obtain a heat transfer model, wherein the heat transfer model is used to dynamically correct the apparent specific heat capacity and target thermal conductivity based on the temperature value of the porous medium at the current moment, so as to calculate the temperature value at the next moment. The target thermal conductivity is determined according to a first model parameter and a second model parameter. The first model parameter is used to characterize solid heat conduction, and the second model parameter is used to characterize pore heat radiation. The heat transfer model is a one-dimensional heat transfer model determined according to the energy conservation equation in the target heat transfer direction. The inversion module is used to invert the first model parameters and the second model parameters in the heat transfer model based on the temperature measurement data to obtain the first target parameters and the second target parameters.

[0023] Another embodiment of the present invention also provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is executed, controls the device where the computer-readable storage medium is located to perform the steps of the inversion measurement method for thermal property parameters of porous media of the present invention. Attached Figure Description

[0024] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 This is a schematic flowchart of a method for inverting and measuring the thermal properties of porous media provided in an embodiment of the present invention. Figure 2 This is an axial view of an insulated barrel device provided in an embodiment of the present invention; Figure 3 This is a top view of an insulated barrel device provided in an embodiment of the present invention; Figure 4 This is a side view of an insulated barrel device provided in an embodiment of the present invention; Figure 5 This is a side view of an insulated barrel device provided in an embodiment of the present invention; Figure 6 This is a perspective view of an insulated barrel device provided in an embodiment of the present invention.

[0026] Figure 7 This is a schematic diagram of the structure of an inversion measurement system for the thermal properties of porous media provided in an embodiment of the present invention; Among them, 1 is the heating cover; 2 is the handle; 3 is the insulated barrel wall; 4 is the water level pipe; 5 is the water outlet; 6 is the moving roller; 7 is the flange; 8 is the water inlet; and 9 is the wiring port. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0029] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0030] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0031] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0032] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0033] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0034] See Figure 1 To address the problem of low accuracy of measurement results in the phase transition temperature range in existing technologies, an embodiment of the present invention provides a method for inverting and measuring the thermal properties of porous media, comprising: Step 101: Obtain temperature measurement data corresponding to different depths in the target heat transfer direction during the heating process of the porous medium.

[0035] It should be noted that the porous media targeted by this invention are mainly granular porous media, such as calcareous sand.

[0036] In the above steps, the porous medium, taking calcareous sand as an example, is placed in a pre-set one-dimensional insulated barrel device. This device is equipped with a high-temperature heater (simulating fire heat) and connected to a constant-pressure water tank for precise water level control. The barrel body is also insulated to ensure one-dimensional heat transfer. Different depths (e.g., along the central axis of the device, i.e., the target heat transfer direction) are considered. By embedding multiple ordinary thermocouples, the expensive and heat-sensitive TDR moisture sensor can be avoided, allowing data measurement to be achieved using only inexpensive and durable thermocouples. The device is heated at the top while maintaining bottom water level control, and the temperature response curves of all thermocouples over time are recorded simultaneously. Temperature measurement data were obtained, including highly characteristic 100°C isothermal plateau (reflecting latent heat of moisture), 880°C isothermal plateau (reflecting latent heat of decomposition), and the propagation delay of heat waves at different depths (reflecting thermal conductivity).

[0037] Step 102: Obtain the heat transfer model, wherein the heat transfer model is used to dynamically correct the apparent specific heat capacity and target thermal conductivity based on the temperature value of the porous medium at the current moment, so as to calculate the temperature value at the next moment. The target thermal conductivity is determined according to the first model parameter and the second model parameter. The first model parameter is used to characterize the heat conduction of the solid, and the second model parameter is used to characterize the heat radiation of the pores. The heat transfer model is a one-dimensional heat transfer model determined according to the energy conservation equation in the target heat transfer direction.

[0038] The apparent specific heat capacity is used to reflect the additional endothermic effect caused by physical phase changes (such as water vaporization) or chemical reactions (such as calcium carbonate decomposition) occurring inside the porous medium; the target thermal conductivity is used to reflect the influence of temperature changes and the state of the medium (especially dry / wet state) on the heat transfer capacity.

[0039] In the above steps, a one-dimensional transient mathematical model is constructed to accurately describe the heat from a fire passing through a water-containing, reactive porous medium. This model includes four modules: the energy conservation governing equation (physical framework), a dynamic moisture field module, an apparent heat capacity module (for handling heat sinks), and a thermal conductivity parameterization module (i.e., the core unknown to be inverted). The sample to be tested is spatially meshed along the heat transfer direction (height) to obtain multiple consecutive spatial mesh locations. Simultaneously, the total heating time is divided into many small time steps. In the calculation of each time step, the following operations are performed sequentially on all spatial mesh locations to deduce the temperature of the next time step from the current temperature.

[0040] Specifically, a mathematical model is obtained to characterize the unsteady (transient) transfer of heat along a single direction (one-dimensional). This model is based on the governing equations constructed according to the law of conservation of energy, and can be a one-dimensional transient partial differential equation of heat conduction that includes thermophysical parameters. The model dynamically links the three physical sub-modules with the main governing equations through a closed-loop logic of temperature feedback, parameter update, and equation solving: at each computational node of the model's time step, based on the instantaneous temperature at the current moment... As a state criterion, the dynamic moisture field module is triggered to determine whether moisture has evaporated, thereby correcting the effective density. This triggers the apparent heat capacity module to match the apparent specific heat capacity that includes latent heat peak characteristics. And trigger the thermal conductivity module to calculate the target thermal conductivity, including high-temperature radiation nonlinear terms. The model parameterizes the target thermal conductivity, resulting in two independent undetermined model parameters with different physical meanings: a first model parameter characterizing the heat conduction mechanism of the solid skeleton, and a second model parameter characterizing or primarily related to the high-temperature-excited enhanced thermal radiation heat transfer mechanism within the medium's pores. By adjusting these two parameters, the model can simulate different effective thermal conductivityes, thereby fitting the material properties of different porous media.

[0041] As an example of an embodiment of the present invention, the energy conservation equation is: ; in, These are spatial coordinates representing depth. It is time. It's temperature. It is the effective density, and , It is the apparent specific heat capacity.

[0042] Step 103: Based on the temperature measurement data, invert the first model parameters and the second model parameters in the heat transfer model to obtain the first target parameters and the second target parameters.

[0043] As an example of an embodiment of the present invention, the step of inverting the first model parameters and the second model parameters in the heat transfer model based on the temperature measurement data to obtain the first target parameters and the second target parameters specifically involves: obtaining an objective function with the first model parameters and the second model parameters as optimization variables; calculating the loss value between the temperature measurement data and the simulated temperature data output by the heat transfer model based on the objective function; iteratively optimizing the heat transfer model based on the loss value until a preset stopping condition is met, at which point the iteration stops, and the first target parameters and the second target parameters are obtained.

[0044] In this embodiment, the measured temperature data obtained in step 101 is used as the target or reference, and the heat transfer model defined in step 102 is used as a simulator. Any applicable parameter optimization or fitting algorithm is employed, and the first and second model parameters in the heat transfer model are iteratively adjusted to generate the corresponding simulated temperature data. Specifically, under the current model parameter conditions, the effective density is... Apparent specific heat capacity and target thermal conductivity These three physical property parameters, which are corrected for real-time temperature, are substituted into the master equation to calculate the temperature distribution at the next moment. Through time-step recursive calculation, the equation set is used to calculate the simulated temperature curve for each spatial location corresponding to the current model parameters, thereby obtaining the simulated temperature data.

[0045] The simulated temperature curve corresponding to each spatial grid location is compared with the actual temperature curve measured by the adiabatic barrel device to construct an error function. If the error does not reach the convergence criterion, the optimization algorithm adjusts the model parameter values ​​according to the error gradient and enters the next round of calculation until a specific set of first and second model parameter values ​​is found, so that the simulated temperature data calculated by the model and the measured temperature data achieve the best overall match (i.e., the error between the two is minimized, satisfying the preset convergence criterion), and the iteration terminates. The optimal set of model parameter values ​​is used as the final measurement result output, i.e., the first target parameter and the second target parameter. The corresponding parameter values ​​at this time are identified as the true thermophysical parameters of the material under extreme high temperatures.

[0046] Furthermore, the present invention proposes a method such as Figure 2-6The one-dimensional insulated barrel device shown includes an insulated main unit, a top radiant heating unit, a bottom hydraulic boundary monitoring unit, and a multi-depth data acquisition unit. This device aims to construct a rigorous one-dimensional heat flow field and a controllable moisture distribution field, providing temperature response data for subsequent parameter inversion.

[0047] A. Insulation core unit (constructing a one-dimensional heat transfer boundary): High-temperature resistant cylinder: The core container is a cylindrical cylinder open at both ends; Material: High-temperature resistant ceramic or thin-walled heat-resistant stainless steel is used to withstand temperatures above 1000°C without chemical reaction.

[0048] Radial insulation layer: The outer wall of the cylinder is wrapped with multiple layers of composite insulation material; The inner layer is made of nano-aerogel felt or polycrystalline mullite fiber, which is resistant to temperature up to 1200°C and is tightly attached to the cylinder wall to prevent radial heat loss. The outer layer is made of fiberglass wool or rock wool to further insulate against residual heat. Objective: To ensure that heat is transferred perpendicularly only along the axial direction (Z-axis) to satisfy the requirements of the mathematical model. The one-dimensional assumption.

[0049] B. Top radiant heating unit (simulating fire boundary): Radiant heater: Located directly above the cylinder, using silicon carbide (SiC) heating elements; Function: Maintains a constant surface high temperature (e.g., 800°C - 1000°C) to simulate the thermal shock of a real fire; Heat spreader (optional): A high-temperature resistant thin plate (such as silicon carbide plate) is placed between the heater and the soil sample surface to ensure uniform heating of the top surface of the soil column; Temperature control system: Equipped with a PID temperature controller, which can be set to heat according to a specific temperature rise curve or maintain a constant high temperature; C. Bottom hydraulic boundary monitoring unit (determines the initial water level boundary): Functional Overview: Used to visually monitor and determine the specific height (z=0) of the groundwater level inside the soil column before and during the experiment, providing accurate geometric boundary parameter input for the mathematical model in step 102; The specific structure includes a permeable base: a porous permeable stone or a high-temperature resistant sintered metal plate is installed at the bottom of the cylinder to support the sand and connect the water passage. External liquid level observation tube (i.e., water level tube): A transparent vertical connecting tube is led out from the side or bottom of the base and connected to the inside of the cylinder; Principle and Application: Based on the principle of communicating vessels, regardless of the distribution of sand inside the cylinder, the liquid level in the external observation tube always remains horizontal and consistent with the height of the free water level (saturation level) inside the soil column; Scale markings: A height scale is provided next to the observation tube for directly reading the vertical distance of the water level line relative to the bottom of the tube; Operation and Model Correlation: In the experimental preparation stage, water is injected into the device through the inlet to establish the initial water level; the physical location of parameter z=0 is determined by reading the liquid level height in the observation tube; this observation value is used as a known boundary condition and input into the initial water field model in step one, thereby calculating the water content distribution based on this water level line.

[0050] D. Multi-depth data acquisition unit: Sensor array: A temperature sensor is horizontally inserted at regular intervals (e.g., 2cm, 5cm, 10cm, 15cm...) along the central axis of the cylinder from top to bottom; Sensor selection: Use type K or type N armored thermocouples; Armor: High-temperature resistant metal or ceramic sheaths must be used to prevent the sensor from being damaged at 800°C or from chemically corroding with salt. Data acquisition instrument: High-frequency multi-channel data logger, synchronously recording temperature change curves over time at all depths. .

[0051] As an example of an embodiment of the present invention, the step of dynamically correcting the apparent specific heat capacity and target thermal conductivity based on the temperature value of the porous medium at the current moment specifically involves: normalizing the liquid saturation and temperature value of the porous medium at the current moment to obtain a weighting factor; when the porous medium is in a dry state, inputting the first model parameters, the second model parameters, and the temperature value into a preset first function to calculate the linear term corresponding to the solid heat conduction and the nonlinear term corresponding to the pore heat radiation, thereby obtaining the first thermal conductivity under dry conditions; obtaining the thermal conductivity of water; when the porous medium is in a wet state, calculating the thermal conductivity of water and the linear term according to the geometric mean model to obtain the second thermal conductivity under wet conditions; and inputting the first thermal conductivity, the second thermal conductivity, and the weighting factor into a preset second function to obtain the target thermal conductivity.

[0052] As an example of an embodiment of the present invention, the first function is: ; in, It is the first thermal conductivity. It is a coupled linear term of solid-state heat conduction and gas-state heat conduction. It is the thermal radiation term. The first model parameters include A and B, and C is the second model parameter. The second function is: ; ; ; in, It is solid-state conduction, approximately , It's porosity. It is the thermal conductivity of water. It is a weighting factor.

[0053] In this embodiment, a normalization function is used to determine the liquid saturation at the current moment. After normalization, for example, the classic form of [Côté and Konrad (2005)] is represented as follows: ; in, It is an unknown parameter. It is the instantaneous liquid saturation, and its value range is... This parameter is controlled by the dynamic moisture field module: when the local temperature When, its value is the calculated actual water saturation; when At that time, its value is forcibly set to 0.

[0054] When it is determined to be in a dry state (e.g.) = 0 or T is higher than the temperature at which water completely evaporates), call the first function. (Dry sand), considering that the heat transfer of high-temperature dry sand is a coupling of "conduction + radiation", the first function is expressed as: ; in, This term, dominated by the first set of model parameters, characterizes the coupling effect of solid thermal conduction and its pore gas. In a preferred example, this term is modeled as a linear function of temperature (e.g., A+BT), where both A and B belong to the first set of model parameters. This term, dominated by the second model parameters, is used to independently characterize pore thermal radiation. In a preferred example, this term is modeled as a high-order function of temperature, for example... This is the Roslan approximation, used to reflect the characteristic that thermal radiation intensity increases sharply with temperature, where C is the second model parameter.

[0055] When the condition is determined to be wet / saturated, the geometric mean model is used to calculate the second thermal conductivity of the saturated sand. The calculation formula is expressed as: ; in, It is pure solid-state conduction, approximated by the aforementioned linear conduction term. A+BT represents the conduction when the pores are completely filled with solid. It is porosity; It is the thermal conductivity of water.

[0056] Based on the first thermal conductivity obtained above in the dry state The second thermal conductivity in the saturated state and weighting factors The second function is input, which uses the Côté-Konrad / Johansen normalization model framework to calculate the target thermal conductivity. The second function is expressed as: .

[0057] As an example of an embodiment of the present invention, the step of dynamically correcting the apparent specific heat capacity and target thermal conductivity based on the temperature value of the porous medium at the current moment specifically involves: obtaining the initial heat capacity of the porous medium in a dry state, and obtaining a preset first temperature range and a second temperature range, wherein the first temperature range is used to determine whether there is a water phase change in the porous medium, and the second temperature range is used to determine whether there is skeleton decomposition in the porous medium; if the temperature value is within the first temperature range, the first equivalent heat capacity is adjusted according to the liquid saturation to obtain the apparent specific heat capacity, wherein the first equivalent heat capacity is used to characterize the latent heat of vaporization of water; if the temperature value is within the second temperature range, a second equivalent heat capacity is determined based on the temperature value to characterize the heat absorption of skeleton decomposition, and the apparent specific heat capacity is obtained by combining the second equivalent heat capacity and the initial heat capacity.

[0058] As an example of an embodiment of the present invention, the step of adjusting the first equivalent heat capacity according to the liquid saturation to obtain the apparent specific heat capacity specifically involves: determining the first equivalent heat capacity according to the temperature value; adjusting the first equivalent heat capacity according to the liquid saturation; and combining the adjusted equivalent heat capacity term with the initial heat capacity to obtain the apparent specific heat capacity.

[0059] In this embodiment, the baseline heat capacity of the porous medium in a completely dry, chemically unreacted state is pre-measured using differential scanning calorimetry (DSC) or thermogravimetry (TG). And the apparent heat capacity curve including multiple characteristic peaks. For example, it includes the latent heat of vaporization peak at 100°C and the endothermic peak of decomposition at 880°C. The apparent specific heat capacity is defined as a function of spatial location z. For each spatial location, the corresponding apparent heat capacity ratio is determined based on the instantaneous state of the porous medium (including temperature and temperature-determined liquid saturation). The formula for calculating the apparent specific heat capacity is expressed as: ; in, It is the apparent specific heat capacity; It is the baseline heat capacity of the dry skeleton, used to reflect the heat absorption characteristics of the material itself when heated; It is the instantaneous liquid saturation. It is the peak of the equivalent heat capacity of the latent heat of vaporization of water, which is based on the latent heat of vaporization of water. The converted distribution is in The nearby bell-shaped function (peak center is) Distribution range coverage It represents the heat absorption capacity of pure water during a phase change. It is the equivalent heat capacity peak of the skeletal decomposition endothermic effect, which is directly measured by the DSC / TG experiment and distributed in... The nearby endothermic peak represents the decomposition reaction of calcium carbonate. The resulting huge chemical endothermic sink.

[0060] Set the temperature trigger range: The first temperature range is set according to the phase change characteristics of water, for example, set to [T v1 ,T v2 The temperature range [95°C, 105°C] is used to determine and trigger the phase transition process of water evaporation. When the temperature of a point in the medium enters this range, it is determined that the point begins to absorb the latent heat of vaporization. The second temperature range is set based on the combined thermogravimetric (TG) and DSC analysis results of the material. For example, for the decomposition of calcium carbonate, it is set to [T...]. d1 [Td2] = [870°C, 890°C], this temperature range is used to determine and trigger the endothermic chemical reaction process of skeletal decomposition. Within this temperature range, based on the initial moisture field mentioned above, the amplitude of the latent heat of vaporization peak of water at 100°C is spatially linearly scaled to reflect the influence of water content at different depths on the heat of phase change.

[0061] Check if the current temperature T at the current spatial location z satisfies T v1 ≤T≤T v2 If so, then the latent heat of vaporization of water is determined to exist, based on the current liquid saturation. For an equivalent heat capacity peak representing the latent heat of complete vaporization of pure water Amplitude scaling is performed, and If the value is 0, the scaled equivalent heat capacity term is added to the reference heat capacity to obtain the apparent specific heat capacity.

[0062] Check if the current local temperature T meets the T standard. d1 ≤T≤T d2 If so, it is determined that a skeletal decomposition reaction has occurred, and an equivalent heat capacity term representing the heat of decomposition reaction is directly superimposed on the baseline heat capacity. At that temperature, the liquid saturation It has been forcibly locked to 0, therefore the moisture item... The value is always equal to 0, thus yielding the apparent specific heat capacity.

[0063] If there is no phase change / reaction (T is not in any of the above ranges), then the apparent specific heat capacity is directly equal to the reference heat capacity.

[0064] It is important to note that using instantaneous liquid saturation Linear scaling of the 100°C latent heat peak means that the peak value is huge below the water level (total heat absorption), the peak value is small above the water level (less heat absorption), and the peak value disappears after drying (no heat absorption).

[0065] As an example of an embodiment of the present invention, the liquid saturation is determined according to a steady-state seepage model. Specifically, the obtained water level, steady-state flux, saturated permeability coefficient and saturated water content are input into the steady-state seepage model to obtain the volumetric water content distribution value of the porous medium in the initial state and the liquid saturation.

[0066] In this embodiment, to realistically simulate the process of moisture evaporating from uneven distribution to complete evaporation under fire, a dynamic calculation strategy combining the steady-state flow initial field and the temperature phase transition criterion is adopted: using the Gardner model based on steady-state flow, the initial volumetric water content distribution of the soil column before heating is calculated. and initial liquid saturation distribution , represented as: ; ; in, It is the vertical height (m) from the groundwater level, where z=0 at the water level, with upward as the positive direction, meaning the larger z is, the closer to the ground surface; It is the steady-state flux (m / s) (q=0 for still water, q<0 for rainfall infiltration, q>0 for evaporation). These are the saturated permeability coefficient and the saturated water content, respectively. It is a decay parameter, characterizing how quickly permeability decreases with altitude; It is a shape parameter that characterizes the steepness of the moisture content curve; It is the saturated permeability coefficient (a larger value should be taken for calcareous sand). It is the saturated water content (approximately equal to porosity). and These are empirical constants describing the water-holding properties of the porous medium under test. Classic literature values ​​for this type of material (such as calcareous sand) can be referenced (e.g., ), or pre-determined through conventional geotechnical tests (such as the suspended water column method).

[0067] It should be noted that q is a boundary condition parameter set in the experiment. Its value is determined by the water supply / drainage rate (for example, in this invention, to maintain a static water level, q=0, and the formula can be simplified to...). When evaporation begins, q > 0; if simulated rainfall infiltration occurs, the specific value of q is controlled by the injection rate.

[0068] In the time-step calculation of the model, a temperature switching mechanism is introduced to update the instantaneous liquid saturation of each grid node in real time. Specifically, when the node temperature At that time, it is determined that the moisture has not yet evaporated, the state is wet, and the setting is... At this point, the model calls the water-containing heat conduction formula, and the apparent heat capacity... It contains a large latent heat of vaporization. When the node temperature... At that time, it is determined that the moisture has completely vaporized and the state is dry, and the setting is forced. At this point, the model switches to the dry sand thermal conductivity formula, and the apparent heat capacity... The latent heat of vaporization in the structure disappears, leaving only the baseline heat capacity of the skeleton.

[0069] It should be noted that below 105℃, the liquid saturation is calculated in real time. latent heat peak Perform linear scaling. Choose 105℃ instead of 100℃ as the temperature range. The criterion for zeroing out is to ensure that the integral calculation covers the entire latent heat peak range centered at 100℃ (i.e., including the decrease to the right of the peak), thus guaranteeing the conservation of total energy. Once the temperature exceeds 105℃, the program forces... This makes the term absolutely zero in value.

[0070] like Figure 7 As shown, based on the above-described method embodiments, an embodiment of the present invention provides an inversion measurement system 700 for the thermal property parameters of porous media, comprising: a measurement module 701, a fitting module 702, and an inversion module 703; The measurement module 701 is used to acquire temperature measurement data corresponding to different depths in the target heat transfer direction during the heating process of the porous medium. The fitting module 702 is used to acquire a heat transfer model, wherein the heat transfer model is used to dynamically correct the apparent specific heat capacity and target thermal conductivity based on the temperature value of the porous medium at the current moment, so as to calculate the temperature value at the next moment. The target thermal conductivity is determined according to a first model parameter and a second model parameter. The first model parameter is used to characterize solid heat conduction, and the second model parameter is used to characterize pore heat radiation. The heat transfer model is a one-dimensional heat transfer model determined according to the energy conservation equation in the target heat transfer direction. The inversion module 703 is used to invert the first model parameters and the second model parameters in the heat transfer model based on the temperature measurement data to obtain the first target parameters and the second target parameters.

[0071] It is understood that the above system embodiments correspond to the method embodiments of the present invention, and can realize the inversion measurement method for thermal property parameters of porous media provided by any of the above method embodiments of the present invention.

[0072] It should be noted that the system embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the system embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0073] For ease of description and brevity, the embodiments of the present invention include all the implementation methods described in the above embodiments of the method for inverting and measuring the thermal property parameters of porous media, and will not be repeated here.

[0074] Based on the above embodiments of the method for inverting and measuring the thermal properties of porous media, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the method for inverting and measuring the thermal properties of porous media according to any embodiment of the present invention.

[0075] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0076] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0077] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0078] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the inversion measurement method for thermal property parameters of porous media as described in any of the above-described method embodiments of the present invention.

[0079] Based on the above-described method embodiments, this invention also provides a computer program / program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of any of the above-described method embodiments, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0080] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0081] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for inverting and measuring the thermal properties of porous media, characterized in that, include: Acquire temperature measurement data of porous media at different depths along the target heat transfer direction during the heating process; A heat transfer model is obtained, wherein the heat transfer model is used to dynamically correct the apparent specific heat capacity and target thermal conductivity based on the temperature value of the porous medium at the current moment, so as to calculate the temperature value at the next moment. The target thermal conductivity is determined according to a first model parameter and a second model parameter. The first model parameter is used to characterize the heat conduction of the solid, and the second model parameter is used to characterize the heat radiation of the pores. The heat transfer model is a one-dimensional heat transfer model determined according to the energy conservation equation in the target heat transfer direction. Based on the temperature measurement data, the first model parameters and the second model parameters in the heat transfer model are inverted to obtain the first target parameters and the second target parameters.

2. The method for inverting and measuring the thermal properties of porous media as described in claim 1, characterized in that, The step of dynamically correcting the apparent specific heat capacity and target thermal conductivity based on the current temperature value of the porous medium is specifically as follows: The weighting factor is obtained by normalizing the liquid saturation and temperature values ​​of the porous medium at the current moment. When the porous medium is in a dry state, the first model parameters, the second model parameters, and the temperature value are input into a preset first function to calculate the linear term corresponding to the solid heat conduction and the nonlinear term corresponding to the pore heat radiation, so as to obtain the first thermal conductivity in the dry state. To obtain the thermal conductivity of water, when the porous medium is in a wet state, the thermal conductivity of the water and the linear term are calculated according to the geometric mean model to obtain the second thermal conductivity under wet conditions. The first thermal conductivity, the second thermal conductivity, and the weighting factor are input into a preset second function to obtain the target thermal conductivity.

3. The method for inverting and measuring the thermal properties of porous media as described in claim 1, characterized in that, The step of dynamically correcting the apparent specific heat capacity and target thermal conductivity based on the current temperature value of the porous medium is specifically as follows: The initial heat capacity of the porous medium in a dry state is obtained, and a preset first temperature range and a second temperature range are obtained. The first temperature range is used to determine whether there is a water phase change in the porous medium, and the second temperature range is used to determine whether there is skeleton decomposition in the porous medium. If the temperature value is within the first temperature range, the first equivalent heat capacity is adjusted according to the liquid saturation to obtain the apparent specific heat capacity, wherein the first equivalent heat capacity is used to characterize the latent heat of vaporization of water. If the temperature value is within the second temperature range, then a second equivalent heat capacity for characterizing the endothermic decomposition of the skeleton is determined based on the temperature value, and the apparent specific heat capacity is obtained by combining the second equivalent heat capacity and the initial heat capacity.

4. The method for inverting and measuring the thermal properties of porous media as described in claim 1, characterized in that, The apparent specific heat capacity is obtained by adjusting the first equivalent heat capacity according to the liquid saturation, specifically as follows: The first equivalent heat capacity is determined based on the temperature value; The first equivalent heat capacity is adjusted according to the liquid saturation, and the apparent specific heat capacity is obtained by combining the adjusted equivalent heat capacity term with the initial heat capacity.

5. The method for inverting and measuring the thermal properties of porous media as described in claim 3 or 4, characterized in that, The liquid saturation is determined based on a steady-state seepage model, specifically: The obtained water level, steady-state flux, saturated permeability coefficient, and saturated water content are input into the steady-state seepage model to obtain the volumetric water content distribution value of the porous medium in the initial state and the liquid saturation.

6. The method for inverting and measuring the thermal properties of porous media as described in claim 1, characterized in that, The step of inverting the first model parameters and the second model parameters in the heat transfer model based on the temperature measurement data to obtain the first target parameters and the second target parameters specifically involves: Obtain an objective function with the first model parameters and the second model parameters as optimization variables, and calculate the loss value between the temperature measurement data and the simulated temperature data output by the heat transfer model based on the objective function; The heat transfer model is iteratively optimized based on the loss value until a preset stopping condition is met, at which point the iteration stops and the first target parameter and the second target parameter are obtained.

7. The method for inverting and measuring the thermal properties of porous media as described in claim 2, characterized in that, The first function is: ; in, It is the first thermal conductivity. It is a coupled linear term of solid-state heat conduction and gas-state heat conduction. It is the thermal radiation term. The first model parameters include A and B, and C is the second model parameter. The second function is: ; ; ; in, It is solid-state conduction, approximately , It's porosity. It is the thermal conductivity of water. It is a weighting factor.

8. The method for inverting and measuring the thermal properties of porous media as described in claim 1, characterized in that, The energy conservation equation is as follows: ; in, These are spatial coordinates representing depth. It is time. It's temperature. It is the effective density, and , It is the apparent specific heat capacity.

9. A system for inverting and measuring the thermal properties of porous media, characterized in that, include: Measurement module, fitting module, and inversion module; The measurement module is used to acquire temperature measurement data of the porous medium at different depths in the target heat transfer direction during the heating process. The fitting module is used to obtain a heat transfer model, wherein the heat transfer model is used to dynamically correct the apparent specific heat capacity and target thermal conductivity based on the temperature value of the porous medium at the current moment, so as to calculate the temperature value at the next moment. The target thermal conductivity is determined according to a first model parameter and a second model parameter. The first model parameter is used to characterize solid heat conduction, and the second model parameter is used to characterize pore heat radiation. The heat transfer model is a one-dimensional heat transfer model determined according to the energy conservation equation in the target heat transfer direction. The inversion module is used to invert the first model parameters and the second model parameters in the heat transfer model based on the temperature measurement data to obtain the first target parameters and the second target parameters.

10. A computer-readable storage medium, characterized in that, include: A stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the inversion measurement method for thermal property parameters of porous media as described in any one of claims 1-8.

Images