Method and system for calculating heat conductivity coefficient of modern immature soil material

Abstract

The invention provides a method and system for calculating the heat conductivity coefficient of a modern immature soil material, and belongs to the technical field of building materials, and the method comprises the following steps: constructing a microscopic agglomeration mathematical model of an immature soil material to be tested, the microscopic agglomeration mathematical model being used for describing the mutual relation among the gradation, density and pore structure of the immature soil material to be tested; inputting the gradation and density of the to-be-tested immature soil material into the microscopic agglomeration mathematical model to obtain the solid heat conductivity coefficient of the to-be-tested immature soil material, the air heat conductivity coefficient in the pore space and the radiation coefficient in the pore space; adding the solid heat conductivity coefficient, the air heat conductivity coefficient and the radiation coefficient, and calculating the theoretical heat conductivity coefficient of the raw soil material to be measured; and correcting the theoretical heat conductivity coefficient to obtain the actual heat conductivity coefficient of the immature soil material to be measured. According to the method, the calculation accuracy degree of the heat conductivity coefficient of the modern immature soil material is effectively improved by constructing the microscopic agglomeration mathematical model, combining multi-mechanism heat transfer analysis and combining water and density correction.

Description

Technical Field

[0001] The present invention relates to the technical field of building materials, and particularly to a method and system for calculating the thermal conductivity of modern adobe materials. Background Art

[0002] As an environmentally friendly and energy-saving building material, modern adobe materials are increasingly widely used in the construction field. However, the thermal conductivity of adobe materials has an important impact on building energy consumption and thermal comfort, and how to accurately calculate its thermal conductivity has become a key technology. In the existing technology, although there has been some research on thermal conductivity performance, it mostly focuses on experimental tests, and usually assumes that the influence of the particle size distribution and density of the material on the thermal conductivity is fixed or negligible. Therefore, the existing technology often fails to fully consider the changes in the thermal conductivity performance of adobe materials under different particle size gradations and densities, resulting in large errors in the calculation results of the thermal conductivity.

[0003] Therefore, how to solve the problem of low accuracy in calculating the thermal conductivity of modern adobe materials in the existing technology has become a technical problem that needs to be solved urgently. Summary of the Invention

[0004] The present invention provides a method, system, electronic device and storage medium for calculating the thermal conductivity of modern adobe materials, so as to solve the defects in the existing technology and effectively improve the accuracy of calculating the thermal conductivity of modern adobe materials.

[0005] The present invention provides a method for calculating the thermal conductivity of modern adobe materials, including the following steps: Construct a microscopic aggregation mathematical model of the adobe material to be measured, and the microscopic aggregation mathematical model is used to describe the mutual relationship between the gradation, density and pore structure of the adobe material to be measured; Input the gradation and density of the adobe material to be measured into the microscopic aggregation mathematical model to obtain the solid thermal conductivity, the air thermal conductivity inside the pore space and the radiation coefficient inside the pore space of the adobe material to be measured; Add the solid thermal conductivity, the air thermal conductivity and the radiation coefficient to calculate the theoretical thermal conductivity of the adobe material to be measured; Correct the theoretical thermal conductivity to obtain the actual thermal conductivity of the adobe material to be measured.

[0006] According to the method for calculating the thermal conductivity of modern adobe materials provided by the present invention, the construction of the microscopic aggregation mathematical model of the adobe material to be measured specifically includes: Determine the mass, density and first porosity of the adobe material to be measured, and determine the aggregate area and pore area of the adobe material to be measured; Establish a first relational equation among the mass, the density, and the first porosity; Calculate the equivalent size length of the aggregate region according to the mass and the density; Establish a second relational equation among the aggregate area of the aggregate region, the mass, and the density according to the equivalent size length; Establish a third relational equation among the pore area of the pore region, the mass, and the density according to the aggregate area.

[0007] According to a method for calculating the thermal conductivity of a modern adobe material provided by the present invention, the first relational equation among the mass, the density, and the first porosity is expressed by the following formula: ; The second relational equation among the aggregate area, the mass, and the density is expressed by the following formula: ; The third relational equation among the pore area, the mass, and the density is expressed by the following formula: ; In the formula, is the mass, is the density, n is the first porosity, is the aggregate area, is the pore area.

[0008] According to a method for calculating the thermal conductivity of a modern adobe material provided by the present invention, inputting the gradation and density of the to-be-tested adobe material into the microscopic aggregation mathematical model to obtain the solid thermal conductivity, the air thermal conductivity inside the pore space, and the radiation coefficient inside the pore space of the to-be-tested adobe material specifically includes: Input the gradation and density of the to-be-tested adobe material into the microscopic aggregation mathematical model to obtain the aggregate area and pore area of the to-be-tested adobe material; Calculate the solid thermal conductivity according to the aggregate area and the aggregate thermal conductivity; Calculate the air thermal conductivity according to the pore area and the air thermal conductivity; Calculate the radiation coefficient according to the pore area, the temperature factor, the radiation coefficient of an absolute black body, and the average pore diameter of the pores.

[0009] According to a method for calculating the thermal conductivity of a modern adobe material provided by the present invention, correcting the theoretical thermal conductivity to obtain the actual thermal conductivity of the to-be-tested adobe material specifically includes: According to the first porosity, density of the raw loess material to be measured, and the second porosity occupied by strongly bound water, the theoretical thermal conductivity is corrected to obtain the actual thermal conductivity of the raw loess material to be measured.

[0010] According to a method for calculating the thermal conductivity of a modern raw loess material provided by the present invention, the step of correcting the theoretical thermal conductivity according to the first porosity, density of the raw loess material to be measured, and the second porosity occupied by strongly bound water to obtain the actual thermal conductivity of the raw loess material to be measured specifically includes: The actual thermal conductivity is calculated by the following formula: ; In the formula, is the actual thermal conductivity, is the density, is the theoretical thermal conductivity, is the thermal conductivity of air, is the thermal conductivity of water, n is the first porosity, is the second porosity, is the first preset parameter, is the second preset parameter, is the third preset parameter.

[0011] The present invention also provides a system for calculating the thermal conductivity of a modern raw loess material, including the following modules: A first processing module, configured to construct a microscopic agglomeration mathematical model of the raw loess material to be measured, where the microscopic agglomeration mathematical model is used to describe the mutual relationship between the gradation, density, and pore structure of the raw loess material to be measured; A second processing module, configured to input the gradation and density of the raw loess material to be measured into the microscopic agglomeration mathematical model to obtain the solid thermal conductivity, the air thermal conductivity inside the pore space, and the radiation coefficient inside the pore space of the raw loess material to be measured; The second processing module is further configured to add the solid thermal conductivity, the air thermal conductivity, and the radiation coefficient to calculate the theoretical thermal conductivity of the raw loess material to be measured; A third processing module, configured to correct the theoretical thermal conductivity to obtain the actual thermal conductivity of the raw loess material to be measured.

[0012] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where when the processor executes the program, the method for calculating the thermal conductivity of a modern raw loess material as described in any one of the above is implemented.

[0013] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the method for calculating the thermal conductivity of the modern rammed earth material as described in any one of the above.

[0014] The present invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the method for calculating the thermal conductivity of the modern rammed earth material as described in any one of the above.

[0015] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: By constructing a microscopic aggregation mathematical model of the rammed earth material to be measured, the mutual relationship between gradation, density, and pore structure is systematically quantified, thereby providing an accurate microscopic geometric parameter basis for subsequent thermal conductivity calculation. By inputting the gradation and density of the rammed earth material to be measured into the microscopic aggregation mathematical model, the solid thermal conductivity, the air thermal conductivity inside the pore space, and the radiation coefficient are dynamically calculated, thereby solving the problem that the traditional method ignores the coupling effect of particle gradation and pore structure on the heat transfer mechanism, and significantly improving the accuracy of sub-item heat transfer calculation. By adding the solid thermal conductivity, the air thermal conductivity, and the radiation coefficient to construct a comprehensive mathematical model of the theoretical thermal conductivity, the systematic superposition of multi-mechanism heat transfer is realized for the first time, avoiding the systematic deviation caused by a single heat transfer model, and reducing the theoretical calculation error to within 5%. By correcting the theoretical thermal conductivity and introducing the combined water effect and the density quadratic correction function, the influence of strong bound water on the surface of clay particles and the non-linear change of density on the thermal conductivity are accurately quantified, further reducing the calculation error of the actual thermal conductivity, and effectively improving the accuracy of calculating the thermal conductivity of modern rammed earth materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 is one of the flow diagrams of the method for calculating the thermal conductivity of the modern rammed earth material provided by the present invention.

[0018] Figure 2 is another flow diagram of the method for calculating the thermal conductivity of the modern rammed earth material provided by the present invention.

[0019] Figure 3 is yet another flow diagram of the method for calculating the thermal conductivity of the modern rammed earth material provided by the present invention.

[0020] Figure 4 It is the fourth flow schematic diagram of the calculation method for the thermal conductivity of modern adobe materials provided by the present invention.

[0021] Figure 5 It is the structural schematic diagram of the calculation system for the thermal conductivity of modern adobe materials provided by the present invention.

[0022] Figure 6 It is the structural schematic diagram of the electronic device provided by the present invention. Specific Embodiments

[0023] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0024] It should be noted that in the description of the present invention, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including the element. The orientation or positional relationship indicated by terms such as "upper", "lower", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the system or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and thus cannot be construed as a limitation on the present invention. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0025] The terms "first", "second", etc. in the present invention are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same type and do not limit the number of objects. For example, the first object can be one or multiple. In addition, "and / or" means at least one of the connected objects, and the character " / " generally indicates an "or" relationship between the associated objects before and after.

[0026] The following combinationFigures 1 - 6 Describe the calculation method, system, electronic device and storage medium of the thermal conductivity of the modern adobe materials provided by the present invention.

[0027] Figure 1 It is one of the flow schematic diagrams of the calculation method of the thermal conductivity of the modern adobe materials provided by the present invention, as Figure 1 shown, including but not limited to the following steps: Step 101: Construct a microscopic agglomeration mathematical model of the adobe material to be measured, and the microscopic agglomeration mathematical model is used to describe the mutual relationship between the gradation, density and pore structure of the adobe material to be measured.

[0028] When calculating the thermal conductivity of modern adobe materials, it is first necessary to construct its microscopic agglomeration model. The core purpose of this step is to establish a mathematical description basis for the heat conduction behavior of the material by quantifying the internal structural characteristics of the material (such as particle gradation, density and porosity). Since the thermal conductivity of modern adobe materials is significantly affected by their microscopic structure (such as the distribution of aggregates and pores), it is difficult to comprehensively reflect their thermal characteristics only by experimental measurement. Therefore, it is necessary to establish a connection between the microscopic structure and the macroscopic thermal conductivity through a theoretical model.

[0029] The constructed microscopic agglomeration model can accurately describe the quantitative relationship between the gradation, density and pore structure of the adobe material to be measured. The advantage of this model is that it can not only reflect the basic physical properties of the material, but also provide a reliable theoretical basis for calculating the solid thermal conductivity, air thermal conductivity and radiation coefficient through the quantification of the aggregate area and pore area.

[0030] In a possible implementation manner, Figure 2 It is the second flow schematic diagram of the calculation method of the thermal conductivity of the modern adobe materials provided by the present invention, as Figure 2 shown, the microscopic agglomeration mathematical model of the adobe material to be measured is constructed through the following steps: Step 201: Determine the mass, density and the first porosity of the adobe material to be measured, and determine the aggregate area and pore area of the adobe material to be measured.

[0031] Step 202: Establish a first relationship equation between the mass, density and the first porosity.

[0032] Step 203: Calculate the equivalent size length of the aggregate area according to the mass and density.

[0033] Step 204: Establish a second relationship equation between the aggregate area, mass and density of the aggregate area according to the equivalent size length.

[0034] Step 205: Establish a third relationship equation between the pore area, mass and density of the pore area according to the aggregate area.

[0035] In a possible implementation, the first relational equation among mass, density, and the first porosity is expressed by the following formula: ; The second relational equation among aggregate area, mass, and density is expressed by the following formula: ; The third relational equation among pore area, mass, and density is expressed by the following formula: ; In the formula, is the mass, is the density, n is the first porosity, is the aggregate area, is the pore area.

[0036] When calculating the thermal conductivity of modern adobe materials, constructing a microscopic aggregation model is a crucial initial step. The purpose of this step is to establish a mathematical description basis for the heat conduction behavior of the material by quantifying the internal structural characteristics of the material (such as particle size distribution, density, and porosity). Since the thermal conductivity of modern adobe materials is significantly affected by their microscopic structure (such as the distribution of aggregates and pores), it is difficult to comprehensively reflect their thermal characteristics only by experimental measurement. Therefore, it is necessary to relate the microscopic structure to the macroscopic thermal conductivity through a theoretical model.

[0037] During specific implementation, first determine the mass and density of the adobe material to be measured, as well as the first porosity n. These parameters are the basis for describing the microscopic structure of the material. Among them, the first porosity n represents the ratio of the pore volume to the total volume of the material. For homogeneous materials, it can be approximated as the ratio of the total area occupied by pores to the total area occupied by the material. The first porosity directly affects the length and complexity of the heat conduction path. Through the formula establish the relationship among mass, density, and the first porosity to ensure that the model can accurately reflect the basic physical properties of the material. The core of this step lies in relating the macroscopic physical quantities of the material (such as density and mass) to the microscopic structural characteristics (such as porosity) to provide a data basis for subsequent calculations.

[0038] Next, calculate the equivalent size length Δ of the aggregate region according to the mass and density. The equivalent size length is a key parameter for describing the geometric characteristics of the aggregate region and is calculated through the formula This parameter provides a basis for subsequent calculations of the aggregate area and pore area. The calculation of the equivalent size length not only reflects the geometric characteristics of the aggregate region but also provides a basis for the subsequent quantification of the heat conduction path.

[0039] Based on the equivalent size length, through the formula Calculating the aggregate area , which is the proportion of the area of solid aggregates in the unit cross-section. The calculation result of the aggregate area directly reflects the heat conduction ability of the solid part in the material. The thermal conductivity of the solid aggregates ( ) is an important part of the thermal conductivity of the material, and its calculation depends on the accurate quantification of the aggregate area.

[0040] Subsequently, the pore area is calculated through the formula Calculating the pore area , which is the proportion of the area occupied by pores in the unit cross-section. The pore area is an important parameter describing the air and radiation heat transfer paths in the material, and its calculation result provides a basis for the subsequent calculation of the air thermal conductivity and radiation coefficient. The calculation of the pore area not only quantifies the distribution characteristics of pores in the material but also provides a key input for the construction of subsequent heat conduction models.

[0041] Through the above steps, the constructed microscopic aggregate model can accurately describe the quantitative relationship among the gradation, density, and pore structure of the raw loess material to be measured. The advantage of this model is that it can not only reflect the basic physical properties of the material but also provide a reliable theoretical basis for the subsequent calculation of the solid thermal conductivity, air thermal conductivity, and radiation coefficient through the quantification of the aggregate area and pore area. Experiments show that the error between the thermal conductivity calculated based on this model and the actual measured value is controlled within 2%, significantly improving the accuracy and reliability of the calculation of the thermal conductivity of modern raw loess materials and providing a scientific basis for its application in construction engineering.

[0042] Step 102: Input the gradation and density of the raw loess material to be measured into the microscopic aggregate mathematical model to obtain the solid thermal conductivity of the raw loess material to be measured, the air thermal conductivity inside the pore space, and the radiation coefficient inside the pore space.

[0043] When calculating the thermal conductivity of the modern raw loess material to be measured, the traditional method fails to fully consider the coupling effect of particle gradation and pore structure, resulting in large discreteness and low reliability of the calculation results. Therefore, in this embodiment, by inputting the gradation and density of the material to be measured into the pre-constructed microscopic aggregate mathematical model, the three heat transfer mechanisms of solid heat conduction, pore air heat conduction, and radiation heat transfer are systematically decomposed, and finally, the accurate calculation of the thermal conductivity is achieved.

[0044] In a possible implementation manner, Figure 3 is the third schematic flow chart of the method for calculating the thermal conductivity of the modern raw loess material provided by the present invention. As shown in Figure 3 , step 102 specifically includes steps 301 - 304: Step 301: Input the gradation and density of the raw loess material to be measured into the microscopic aggregate mathematical model to obtain the aggregate area and pore area of the raw loess material to be measured.

[0045] Step 302: Calculate the solid thermal conductivity based on the aggregate area and the aggregate thermal conductivity.

[0046] Step 303: Calculate the air thermal conductivity based on the pore area and the air thermal conductivity.

[0047] Step 304: Calculate the radiation coefficient based on the pore area, the temperature factor, the radiation coefficient of an absolute black body, and the average pore diameter of the pores.

[0048] In this embodiment, there is no restriction on the acquisition channels of the density and gradation of the raw earth material to be measured. The soil block samples can be obtained in advance according to the density and gradation, or the soil block samples with unknown density and gradation can be obtained through experimental analysis.

[0049] Secondly, substitute the gradation and density into the thermal conductivity mathematical model constructed by the modern raw earth material microscopic aggregation model to calculate the solid thermal conductivity, the air thermal conductivity, and the radiation coefficient.

[0050] Specifically, substitute the gradation parameters (including the percentages of gravel, sand, silt, and clay) and the density of the raw earth material to be measured into the pre-constructed microscopic aggregation mathematical model. According to the optimized gradation range proposed by the International Raw Earth Building Center (gravel 5 - 42%, sand 30 - 50%, silt 18 - 30%, clay 10 - 15%), the model calculates the aggregate area through the formula and further obtains the pore area through the formula This process maps the macroscopic parameters (density, gradation) to microscopic geometric features, quantifies the distribution ratio of aggregates and pores, and provides a basis for subsequent sub-item heat transfer calculations. For example, when the density is 2000 kg / m³ and the mass is 2150 kg, the calculated results are , , indicating that the aggregates occupy 85% of the material cross-section and the porosity is 15%.

[0051] Secondly, calculate the solid thermal conductivity based on the aggregate area and the gradation composition. Due to ignoring the gradation differences, the traditional method often assumes that the material is a homogeneous body, resulting in the confusion of calculation results for materials with high gravel content (high thermal conductivity component) and high clay content (low thermal conductivity component). In this embodiment, through the weighted summation method, the thermal conductivities of each component (clay thermal conductivity , sand thermal conductivity , stone thermal conductivity ) are superimposed according to the gradation ratio. For example, if the measured gradation is 40% clay, 35% sand, and 25% stone, then . Through the formula , where is the temperature gradient, and are temperature and length respectively, accurately reflecting the contribution differences of particles with different particle sizes to solid heat transfer, and solving the systematic deviation introduced by the traditional model due to the simplified grading.

[0052] For the thermal conductivity of air inside the pore space, the traditional method often directly uses the thermal conductivity of air , but does not consider the influence of the change in porosity on the effective heat transfer path. In this embodiment, through the formula , the pore area is used as a correction factor to dynamically adjust the contribution of air heat transfer. For example, when , the air heat transfer contribution is 0.0267×0.15 = 0.004 W / (m·K), while if the traditional method ignores correction (assuming ), it will overestimate the air heat transfer by more than 6 times, resulting in a serious deviation of the calculation result from the measured value.

[0053] For the radiative heat transfer inside the pores, the traditional model often directly ignores this part of the influence because it assumes that the pore shape is irregular and difficult to integrate. In this embodiment, based on the spherical bubble assumption, through the formula , the radiative heat transfer is simplified as a function of the pore area , the average pore diameter and the temperature factor . Among them, the average pore diameter can be determined by scanning electron microscope (SEM) image analysis or mercury intrusion porosimetry, and the temperature factor is determined by the temperature difference gradient on the material surface. The absolute blackbody radiation coefficient takes 5.67×10⁻ 8 W / (m²·K 4 ). Experiments show that when the porosity n > 20%, the contribution of radiative heat transfer can reach 10% - 15% of the total thermal conductivity. Ignoring this part will result in the theoretical value being 1.2 - 1.8 W / (m·K) lower than the measured value. Through the above method, this embodiment reduces the calculation complexity while fully retaining the influence of radiative heat transfer, especially significantly improving the calculation accuracy in highly porous rammed earth materials.

[0054] Step 103: Add the solid thermal conductivity, the air thermal conductivity, and the radiation coefficient to calculate the theoretical thermal conductivity of the to-be-tested rammed earth material.

[0055] In the calculation of the thermal conductivity of traditional adobe materials, due to the lack of systematic quantification of the coupling effects of solid conduction, air conduction, and radiative heat transfer, a single heat transfer mechanism (such as only considering solid conduction) or empirical formulas are often used for estimation, resulting in a significant deviation between the calculated results and the measured values (the error is generally > 10%). Therefore, in this embodiment, by , the air thermal conductivity , and the radiation coefficient are superimposed through multiple mechanisms to construct a comprehensive mathematical model of the theoretical thermal conductivity λ, significantly improving the calculation accuracy.

[0056] Specifically, after completing the sub-item calculations of each component in step 102, the three need to be weighted and superimposed based on the formula derived from the microscopic aggregation model. The formula is expressed as: ; Among them, the first term is the contribution of solid conduction, and its coefficient 0.4244 is obtained through experimental calibration to correct the difference between the cubic aggregate model and the actual irregular shape; the second term represents the thermal conduction of air in the pores, which is directly related to the pore area (i.e., ); the third term is the contribution of radiative heat transfer, and the radiative heat flux intensity is quantified through the product of the average pore diameter and the pore area .

[0057] Traditional methods deviate from the measured results because they ignore the radiation term or do not correct the solid shape factor (such as directly using instead of ). In this embodiment, by introducing the shape correction coefficient 0.4244 (inverse fitting based on the thermal conductivity experiments of different gradation samples) and the radiative heat transfer term, the physical essence of multi-mechanism heat transfer is systematically restored.

[0058] Furthermore, the coefficients and parameters of each term in the formula are based on measurable or fixed constants (such as taking 5.67×10⁻ 8 W / (m²·K 4 )) to avoid the uncertainty introduced by empirical assumptions. For example, the temperature factor is determined by the temperature difference gradient on the material surface, the average pore diameter is obtained by statistical analysis of scanning electron microscope images, and It can be directly calculated through conventional density tests and mass measurements. Through strict formula correlation and parameter transparency, this method ensures the repeatability and engineering applicability of the calculation process. In practical applications, only by inputting the grading ratio, density, and average pore size, the theoretical thermal conductivity can be quickly output through the formula, providing immediate theoretical support for the thermal design of adobe walls (such as optimizing the thickness of the insulation layer).

[0059] It has been verified that this method reduces the calculation error of thermal conductivity from more than 10% in the traditional model to within 5%, and through subsequent combined water correction (step 104), the error can be further controlled below 2%, providing a highly reliable basis for the proportion optimization of modern adobe materials and engineering thermal design.

[0060] Step 104: Correct the theoretical thermal conductivity to obtain the actual thermal conductivity of the adobe material to be tested.

[0061] In the calculation of the thermal conductivity of traditional adobe materials, due to the failure to consider the interference of strongly bound water on the pore heat transfer on the surface of clay particles and the non-linear effect of density change on the microscopic structure of the material, there is still a significant deviation (error about 5%) between the theoretical model and the measured value. Therefore, in this embodiment, through the introduction of a combined water correction term and a density quadratic correction function, multi-factor coupling correction is performed on the theoretical thermal conductivity λ obtained in step 103, and finally the actual thermal conductivity is obtained, and the calculation error is reduced to within 2%.

[0062] In a possible implementation manner, Figure 4 is the fourth flow chart of the thermal conductivity calculation method of the modern adobe material provided by the present invention. As Figure 4 shown, step 104 specifically includes the following steps: Step 401: Correct the theoretical thermal conductivity according to the first porosity, density, and the second porosity occupied by strongly bound water of the adobe material to be tested to obtain the actual thermal conductivity of the adobe material to be tested.

[0063] Specifically, first, the influence of strongly bound water on the surface of clay particles needs to be quantified. Research shows that due to the negatively charged surface characteristics of clay particles, about 3.9% of strongly bound water (the second porosity can be adsorbed, and this part of water molecules cannot be removed under normal temperature and pressure, and its separation temperature needs to exceed 150°C. Due to ignoring the existence of this part of water, the traditional model wrongly regards all pores as air-filled, resulting in an overestimation of the air thermal conductivity contribution. In this embodiment, by splitting the porosity n into air pores ( and combined water pores ( ), and respectively assigning the air thermal conductivity (0.0267 W / (m·K)) and the water thermal conductivity (0.6 W / (m·K)). For example, when the total porosity n = 18%, the air porosity is 14.1% ( ), the bound water porosity is 3.9%, then the air heat conduction term is corrected to , and the water heat conduction term is , thus accurately distinguishing the heat transfer contributions of different porous media.

[0064] In a possible implementation, the actual thermal conductivity is calculated by the following formula: ; where, is the actual thermal conductivity, is the density, is the theoretical thermal conductivity, is the air thermal conductivity, is the water thermal conductivity, n is the first porosity, is the second porosity, is the first preset parameter, is the second preset parameter, is the third preset parameter.

[0065] Secondly, it is necessary to solve the non-linear effect of density ρ on the thermal conductivity. Experiments show that when the density increases from 1800 kg / m³ to 2200 kg / m³, the thermal conductivity does not increase linearly, but shows a quadratic curve characteristic of rising rapidly first and then slowing down. The error of the traditional linear model (such as λ = αρ + b) can reach 8% in this range. In this embodiment, through fitting experimental data, a density quadratic correction term is introduced into the correction formula to dynamically adjust the weight of the theoretical value λ. For example, when ρ = 2000 kg / m³, the correction factor is , indicating that the theoretical value needs to be reduced by 4.8% to match the measured data. This correction term is determined by regression analysis of 120 groups of samples with different densities, and its coefficients , , are statistically significant (R² = 0.983).

[0066] Through the above correction, this embodiment solves the systematic deviation in the traditional method due to ignoring the non-linear effects of bound water and density. Verification of 360 groups of raw soil samples covering different climate zones (dry, wet) shows that the calculation error is stable within 2%, and the model remains robust under a wide density range (1600 - 2300 kg / m³) and complex grading conditions. In addition, the corrected model provides a quantitative tool for actively regulating the material ratio in engineering (such as increasing the gravel ratio to reduce ) by explicitly correlating density, grading and bound water parameters, helping to achieve precision and standardization in the energy-efficient design of raw soil buildings.

[0067] Refer to Figure 5 , Figure 5 which is a schematic structural diagram of a thermal conductivity calculation system for modern adobe materials provided by the present invention. The system includes: A first processing module, configured to construct a microscopic agglomeration mathematical model of the adobe material to be measured, where the microscopic agglomeration mathematical model is used to describe the mutual relationship among the gradation, density, and pore structure of the adobe material to be measured; A second processing module, configured to input the gradation and density of the adobe material to be measured into the microscopic agglomeration mathematical model to obtain the solid thermal conductivity, the air thermal conductivity inside the pore space, and the radiation coefficient inside the pore space of the adobe material to be measured; The second processing module is further configured to add the solid thermal conductivity, the air thermal conductivity, and the radiation coefficient to calculate the theoretical thermal conductivity of the adobe material to be measured; A third processing module, configured to correct the theoretical thermal conductivity to obtain the actual thermal conductivity of the adobe material to be measured.

[0068] In a possible implementation manner, the first processing module is further configured to: Determine the mass, density, and first porosity of the adobe material to be measured, and determine the aggregate area and pore area of the adobe material to be measured; Establish a first relationship equation among the mass, density, and first porosity; Calculate the equivalent size length of the aggregate area according to the mass and density; Establish a second relationship equation among the aggregate area, mass, and density of the aggregate area according to the equivalent size length; Establish a third relationship equation among the pore area, mass, and density of the pore area according to the aggregate area.

[0069] In a possible implementation manner, the second processing module is further configured to: Input the gradation and density of the adobe material to be measured into the microscopic agglomeration mathematical model to obtain the aggregate area and pore area of the adobe material to be measured; Calculate the solid thermal conductivity according to the aggregate area and the aggregate thermal conductivity; Calculate the air thermal conductivity according to the pore area and the air thermal conductivity; Calculate the radiation coefficient according to the pore area, the temperature factor, the radiation coefficient of an absolute black body, and the average pore diameter of the pores.

[0070] In a possible implementation manner, the third processing module is further configured to correct the theoretical thermal conductivity according to the first porosity, density, and second porosity occupied by strongly bound water of the adobe material to be measured to obtain the actual thermal conductivity of the adobe material to be measured.

[0071] In a possible implementation, the third processing module is further configured to calculate the actual thermal conductivity through the following formula: ; In the formula, is the actual thermal conductivity, is the density, is the theoretical thermal conductivity, is the air thermal conductivity, is the water thermal conductivity, n is the first porosity, is the second porosity, is the first preset parameter, is the second preset parameter, is the third preset parameter.

[0072] It should be noted that the thermal conductivity calculation system of modern adobe materials provided by the present invention can execute the thermal conductivity calculation method of modern adobe materials in any of the above embodiments during specific operation, and this embodiment will not be elaborated here.

[0073] Figure 6 is a schematic structural diagram of an electronic device provided by the present invention. As Figure 6 shown, the electronic device may include: a processor 610 (processor), a communication interface 620 (Communications Interface), a memory 630 (memory), and a communication bus 640. Among them, the processor 610, the communication interface 620, and the memory 630 complete mutual communication through the communication bus 640. The processor 610 can call the logical instructions in the memory 630 to execute the thermal conductivity calculation method of modern adobe materials, and the method includes: constructing a microscopic aggregation mathematical model of the adobe material to be measured, where the microscopic aggregation mathematical model is used to describe the mutual relationship between the gradation, density, and pore structure of the adobe material to be measured; inputting the gradation and density of the adobe material to be measured into the microscopic aggregation mathematical model to obtain the solid thermal conductivity, the air thermal conductivity inside the pore space, and the radiation coefficient inside the pore space of the adobe material to be measured; adding the solid thermal conductivity, the air thermal conductivity, and the radiation coefficient to calculate the theoretical thermal conductivity of the adobe material to be measured; and correcting the theoretical thermal conductivity to obtain the actual thermal conductivity of the adobe material to be measured.

[0074] In addition, when the logical instructions in the above-mentioned memory 630 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0075] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the method for calculating the thermal conductivity of modern rammed earth materials provided in the above-mentioned various embodiments. The method includes: constructing a microscopic agglomeration mathematical model of the rammed earth material to be measured, where the microscopic agglomeration mathematical model is used to describe the mutual relationship between the gradation, density, and pore structure of the rammed earth material to be measured; inputting the gradation and density of the rammed earth material to be measured into the microscopic agglomeration mathematical model to obtain the solid thermal conductivity, the air thermal conductivity inside the pore space, and the radiation coefficient inside the pore space of the rammed earth material to be measured; adding the solid thermal conductivity, the air thermal conductivity, and the radiation coefficient to calculate the theoretical thermal conductivity of the rammed earth material to be measured; and correcting the theoretical thermal conductivity to obtain the actual thermal conductivity of the rammed earth material to be measured.

[0076] On another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to execute the method for calculating the thermal conductivity of modern rammed earth materials provided in the above-mentioned various embodiments. The method includes: constructing a microscopic agglomeration mathematical model of the rammed earth material to be measured, where the microscopic agglomeration mathematical model is used to describe the mutual relationship between the gradation, density, and pore structure of the rammed earth material to be measured; inputting the gradation and density of the rammed earth material to be measured into the microscopic agglomeration mathematical model to obtain the solid thermal conductivity, the air thermal conductivity inside the pore space, and the radiation coefficient inside the pore space of the rammed earth material to be measured; adding the solid thermal conductivity, the air thermal conductivity, and the radiation coefficient to calculate the theoretical thermal conductivity of the rammed earth material to be measured; and correcting the theoretical thermal conductivity to obtain the actual thermal conductivity of the rammed earth material to be measured.

[0077] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative work.

[0078] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiments.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features. And these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating the thermal conductivity of modern adobe materials, characterized in that Including: Construct a microscopic aggregation mathematical model for the raw soil material to be tested, where the microscopic aggregation mathematical model is used to describe the mutual relationship between the gradation, density, and pore structure of the raw soil material to be tested; Input the gradation and density of the raw soil material to be tested into the microscopic aggregation mathematical model to obtain the solid thermal conductivity, the air thermal conductivity inside the pore space, and the radiation coefficient inside the pore space of the raw soil material to be tested; Add the solid thermal conductivity, the air thermal conductivity, and the radiation coefficient to calculate the theoretical thermal conductivity of the raw soil material to be tested; Correct the theoretical thermal conductivity to obtain the actual thermal conductivity of the raw soil material to be tested.

2. The calculation method of the thermal conductivity of modern adobe materials according to claim 1, characterized in that The construction of the microscopic aggregation mathematical model for the raw soil material to be tested specifically includes: Determine the mass, density, and first porosity of the raw soil material to be tested, and determine the aggregate area and pore area of the raw soil material to be tested; Establish a first relationship equation among the mass, the density, and the first porosity; Calculate the equivalent size length of the aggregate area according to the mass and the density; Establish a second relationship equation among the aggregate area, the mass, and the density of the aggregate area according to the equivalent size length; Establish a third relationship equation among the pore area, the mass, and the density of the pore area according to the aggregate area.

3. The calculation method of the thermal conductivity of modern adobe materials according to claim 2, characterized in that, The first relationship equation among the mass, the density, and the first porosity is expressed by the following formula: ； The second relationship equation among the aggregate area, the mass, and the density is expressed by the following formula: ； The third relationship equation among the pore area, the mass, and the density is expressed by the following formula: ； In the formula, is the said mass, is the said density, n is the said first porosity, is the said aggregate area, is the said pore area.

4. The method for calculating the thermal conductivity of modern adobe materials according to claim 1, wherein The step of inputting the gradation and density of the raw soil material to be tested into the microscopic aggregation mathematical model to obtain the solid thermal conductivity, the air thermal conductivity inside the pore space, and the radiation coefficient inside the pore space of the raw soil material to be tested specifically includes: Input the gradation and density of the raw soil material to be tested into the microscopic aggregation mathematical model to obtain the aggregate area and pore area of the raw soil material to be tested; Calculate the solid thermal conductivity according to the aggregate area and the aggregate thermal conductivity; Calculate the air thermal conductivity according to the pore area and the air thermal conductivity; Calculate the radiation coefficient according to the pore area, the temperature factor, the radiation coefficient of an absolute black body, and the average pore diameter of the pores.

5. The calculation method of the thermal conductivity of modern adobe materials according to claim 1, characterized in that, The step of correcting the theoretical thermal conductivity to obtain the actual thermal conductivity of the raw soil material to be tested specifically includes: Correct the theoretical thermal conductivity according to the first porosity, density, and second porosity occupied by strongly bound water of the raw soil material to be tested to obtain the actual thermal conductivity of the raw soil material to be tested.

6. The method for calculating the thermal conductivity of modern adobe materials according to claim 5, characterized in that The step of correcting the theoretical thermal conductivity according to the first porosity, density, and second porosity occupied by strongly bound water of the raw soil material to be tested to obtain the actual thermal conductivity of the raw soil material to be tested specifically includes: The actual thermal conductivity is calculated by the following formula: ； In the formula, is the actual thermal conductivity, is the density, is the theoretical thermal conductivity, is the thermal conductivity of air, is the thermal conductivity of water, and n is the first porosity, is the second porosity, is the first preset parameter, is the second preset parameter, is the third preset parameter.

7. A calculation system for the thermal conductivity of modern adobe materials, characterized in that, Including: The first processing module is used to construct a microscopic aggregation mathematical model of the raw soil material to be tested, and the microscopic aggregation mathematical model is used to describe the mutual relationship among the gradation, density, and pore structure of the raw soil material to be tested; The second processing module is used to input the gradation and density of the raw soil material to be tested into the microscopic aggregation mathematical model to obtain the solid thermal conductivity, the air thermal conductivity inside the pore space, and the radiation coefficient inside the pore space of the raw soil material to be tested; The second processing module is further used to add the solid thermal conductivity, the air thermal conductivity, and the radiation coefficient to calculate the theoretical thermal conductivity of the raw soil material to be tested; The third processing module is used to correct the theoretical thermal conductivity to obtain the actual thermal conductivity of the raw soil material to be tested.

8. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the method for calculating the thermal conductivity of the modern raw soil material according to any one of claims 1-6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for calculating the thermal conductivity of the modern raw soil material according to any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for calculating the thermal conductivity of the modern raw soil material according to any one of claims 1-6.

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