Bentonite heat conductivity coefficient estimation method, system, equipment and medium

Abstract

The invention discloses a method, a system, equipment and a medium for estimating the heat conductivity coefficient of bentonite, and belongs to the technical field of soil thermophysical property calculation, the bentonite is correspondingly characterized, the aggregate particle number and porosity expression of the bentonite is obtained, and the number expression of effective basic unit contact points in particles in a porous material is modified; calculating the ratio of the volume of the soil skeleton of the bentonite to the total volume according to the modified quantity expression; according to an aggregate particle quantity expression, a modified quantity expression and the ratio of the volume of the soil skeleton to the total volume, determining the relative density of montmorillonite interlayer contact in the bentonite, defining that the heat conductivity coefficient of the bentonite is in direct proportion to the relative density, obtaining the relationship between the heat conductivity coefficient of the bentonite and the porosity, and establishing a fractal heat conduction model; and estimating the heat conductivity coefficient of the bentonite. According to the method, the heat-conducting property of the dried bentonite can be quickly and accurately calculated through the fractal theory in combination with bentonite heat-conducting test and microstructure analysis.

Description

Technical Field

[0001] This invention relates to the field of soil thermal property calculation technology, and more specifically to a method and system for estimating the thermal conductivity of dry bentonite. Background Technology

[0002] Bentonite is composed of several to dozens of neatly arranged montmorillonite unit layers. These stacks aggregate to form larger bentonite particles, which in turn form a soil skeleton. In energy and environmental geotechnical engineering, where soil heat transfer is crucial, the thermal conductivity of soil is a vital soil property. Currently, it is primarily obtained through testing; however, thermal conductivity testing is time-consuming, expensive, and requires specialized technical personnel, involving sampling, sample preparation, and testing. Domestic and international scholars have conducted extensive research on the thermal conductivity characteristics of bentonite, mainly focusing on the influence of moisture content, dry density, quartz and graphite admixtures, and ambient temperature. The thermal conductivity of bentonite can be obtained through steady-state or transient tests conducted indoors.

[0003] Sakashita and Kumada first proposed a mathematical model for the thermal conductivity of dry bentonite. However, the model only included porosity and lacked consideration for factors such as mineral composition and pore structure. Due to the mineral composition and fractal characteristics of bentonite, it is difficult to simply apply the inherent fractal thermal conductivity model. Therefore, it is urgent to develop a new thermal conductivity prediction model for dry bentonite that takes into account mineral composition and pore structure.

[0004] Currently, most soil thermal conductivity prediction models require the thermal conductivity of dry and saturated soil as the minimum and maximum values, respectively. Through standardized model interpolation, the thermal conductivity of soil under any unsaturated state can be estimated. However, compared to the maximum value of saturated soil thermal conductivity, the minimum value of dry soil thermal conductivity is more difficult to predict accurately. This is mainly because the thermal conductivity of dry soil is also affected by the soil structure, while the pore structure has little impact on the thermal conductivity of saturated soil. Therefore, accurately estimating the thermal conductivity of bentonite under dry conditions is crucial for the reasonable prediction of bentonite thermal conductivity. Since bentonite is a typical porous medium with obvious fractal characteristics in its pore structure, considering the significant influence of pore structure on the thermal conductivity of porous media, many scholars have proposed porous media thermal conductivity models based on fractal characteristics. However, the mineral composition and fractal characteristics of bentonite make it difficult to simply apply inherent fractal thermal conductivity models. Currently, a fractal thermal conductivity model suitable for dry bentonite has not yet been established.

[0005] In summary, the existing technology has not yet established a fractal thermal conductivity model for dry bentonite. Since the study of the thermal conductivity of dry soil needs to consider the influence of soil structure, the inherent fractal thermal conductivity model cannot be simply applied, which makes it impossible to accurately estimate the thermal conductivity of bentonite under dry conditions. Summary of the Invention

[0006] To address the problems existing in the above-mentioned fields, this invention proposes a method, system, equipment, and medium for estimating the thermal conductivity of bentonite. This invention can solve the technical problem that the fractal thermal conductivity model for dry bentonite has not yet been established in the prior art. Since the study of the thermal conductivity of dry soil needs to consider the influence of soil structure, the inherent fractal thermal conductivity model cannot be simply applied, which leads to the inability to accurately estimate the thermal conductivity of bentonite in the dry state.

[0007] To address the aforementioned technical problems, this invention discloses a method for estimating the thermal conductivity of bentonite, comprising the following steps:

[0008] Based on the cohesive property of bentonite having a multi-layered aggregated structure, bentonite was characterized accordingly, and expressions for the number of aggregated particles and porosity of bentonite were obtained.

[0009] Based on the expressions for the number of aggregated particles and porosity of bentonite, the expression for the number of effective basic unit contact points within particles in porous materials is modified; based on the modified expression, the volume ratio of the soil skeleton to the total volume of bentonite is calculated; based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume, the relative density of montmorillonite interlayer contact in bentonite is determined.

[0010] Based on the relative density of the montmorillonite interlayer contact in bentonite, the thermal conductivity of bentonite is defined to be proportional to the relative density, thus obtaining the relationship between the thermal conductivity and porosity of bentonite. Based on the relationship between thermal conductivity and porosity, a fractal thermal conductivity model is established to estimate the thermal conductivity of bentonite, thus obtaining the estimated result of the thermal conductivity of bentonite.

[0011] Preferably, obtaining the expression for the number of aggregated particles and porosity of bentonite includes the following steps:

[0012] The number of aggregated particles, Q, is:

[0013]

[0014] The pore volume fraction n is:

[0015]

[0016] In the formula, P s and f c These represent the scaling factors for aggregated particles and the basic unit morphology within aggregated particles, respectively; D is the fractal dimension; d a and d n These are the average diameters of the aggregated particles and the basic units within the aggregated particles, respectively.

[0017] Bentonite is characterized using expressions for Q and n, where Q is the number of montmorillonite particles, n is the porosity, and d... a and d n These represent the average diameters of the bentonite particles and the montmorillonite layer, respectively.

[0018] Preferably, modifying the expression for the number of effective basic unit contact points within particles of porous materials includes the following steps:

[0019] The expression for the number of effective basic unit contact points within the particles of the porous material is:

[0020]

[0021] The interlayer contact forms of montmorillonite are mostly surface-cation-surface contact or edge-surface contact. Considering that the interlayer contact of montmorillonite includes the contact between cations and montmorillonite layers, the expression for the number of effective basic unit contact points within the particles of porous materials is modified, resulting in the modified expression:

[0022]

[0023] In the formula, α is a proportionality factor related to the cation radius.

[0024] Preferably, the calculation of the volume ratio of the bentonite's soil skeleton to the total volume includes the following steps:

[0025] Due to the presence of pores within the particles, the volume of the bentonite skeleton formed by the connections between particles is not only the volume of the solid material, thus yielding the volume V of the skeleton. s The proportion of the total volume V is:

[0026]

[0027] In the formula, C α These are parameters related to the contact properties of clay particles within the soil skeleton.

[0028] Preferably, the relative density of the montmorillonite interlayer contact in the bentonite is:

[0029]

[0030] In the formula, β is only related to α and C α Relevant parameters;

[0031] The larger the relative density ρ value, the more contact points are used for heat transfer, and the smoother the heat transfer. In other words, the higher the ρ value, the greater the thermal conductivity.

[0032] Preferably, the relationship between the thermal conductivity and porosity of the bentonite is expressed as follows:

[0033]

[0034] In the formula, λ0 is the thermal conductivity of bentonite when n=0, which is called the solid phase thermal conductivity.

[0035] Preferably, estimating the thermal conductivity of bentonite includes the following steps:

[0036] When the mineral composition of bentonite is known, the value of λ0 is obtained by weighted average of the thermal conductivity of different minerals;

[0037] Substituting λ0 into the relationship between the thermal conductivity and porosity of bentonite, we obtain the thermal conductivity λ of bentonite.

[0038] Preferably, it also includes a system for estimating the thermal conductivity of bentonite, comprising:

[0039] The bentonite parameter characterization module is used to characterize bentonite based on its cohesive properties of having a multi-layered aggregated structure, and to obtain expressions for the number of aggregated particles and porosity of bentonite.

[0040] The bentonite parameter correction module is used to modify the expression for the number of effective basic unit contact points within particles in porous materials based on the expression for the number of aggregated particles and porosity of bentonite; calculate the volume ratio of the soil skeleton to the total volume of bentonite based on the modified expression; and determine the relative density of montmorillonite interlayer contact in bentonite based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume.

[0041] The bentonite thermal conductivity determination module is used to define the thermal conductivity of bentonite as being proportional to its relative density based on the relative density of the montmorillonite interlayer contact, and to derive the relationship between the thermal conductivity and porosity of bentonite. Based on the relationship between thermal conductivity and porosity, a fractal thermal conductivity model is established to estimate the thermal conductivity of bentonite, and the estimated result of the thermal conductivity of bentonite is obtained.

[0042] Preferably, the device further includes a computer apparatus, the computer apparatus comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the following steps:

[0043] Based on the cohesive property of bentonite having a multi-layered aggregated structure, bentonite was characterized accordingly, and expressions for the number of aggregated particles and porosity of bentonite were obtained.

[0044] Based on the expressions for the number of aggregated particles and porosity of bentonite, the expression for the number of effective basic unit contact points within particles in porous materials is modified; based on the modified expression, the volume ratio of the soil skeleton to the total volume of bentonite is calculated; based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume, the relative density of montmorillonite interlayer contact in bentonite is determined.

[0045] Based on the relative density of the montmorillonite interlayer contact in bentonite, the thermal conductivity of bentonite is defined to be proportional to the relative density, thus obtaining the relationship between the thermal conductivity and porosity of bentonite. Based on the relationship between thermal conductivity and porosity, a fractal thermal conductivity model is established to estimate the thermal conductivity of bentonite, thus obtaining the estimated result of the thermal conductivity of bentonite.

[0046] Preferably, the system further includes a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the following steps:

[0047] Based on the cohesive property of bentonite having a multi-layered aggregated structure, bentonite was characterized accordingly, and expressions for the number of aggregated particles and porosity of bentonite were obtained.

[0048] Based on the expressions for the number of aggregated particles and porosity of bentonite, the expression for the number of effective basic unit contact points within particles in porous materials is modified; based on the modified expression, the volume ratio of the soil skeleton to the total volume of bentonite is calculated; based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume, the relative density of montmorillonite interlayer contact in bentonite is determined.

[0049] Based on the relative density of the montmorillonite interlayer contact in bentonite, the thermal conductivity of bentonite is defined to be proportional to the relative density, thus obtaining the relationship between the thermal conductivity and porosity of bentonite. Based on the relationship between thermal conductivity and porosity, a fractal thermal conductivity model is established to estimate the thermal conductivity of bentonite, thus obtaining the estimated result of the thermal conductivity of bentonite.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] The proposed method for estimating the thermal conductivity of bentonite overcomes the shortcomings of existing technologies where a fractal thermal conductivity model for dry bentonite has not yet been established, making it impossible to accurately estimate the thermal conductivity of bentonite in a dry state. This method modifies the expression for the number of effective basic unit contact points within porous materials, based on the characteristics that heat transfer in bentonite primarily occurs through contact between solid phases and that montmorillonite interlayer contact primarily takes the form of surface-cation-surface or edge-surface contact. Furthermore, considering that bentonite particles contain pores and that the volume of the bentonite skeleton formed by particle-particle connections is not solely the volume of solid matter, the method calculates the ratio of the bentonite skeleton volume to the total volume, and then calculates the relative density of montmorillonite interlayer contact within the bentonite, concluding that a higher relative density corresponds to a higher thermal conductivity. Finally, based on the relationship between thermal conductivity and porosity, a fractal thermal conductivity mathematical model is established to accurately calculate the thermal conductivity of bentonite. This method fully considers the main factors of mineral composition and pore structure. Through fractal theory, combined with bentonite thermal conductivity testing and micromorphological analysis, a fractal thermal conductivity model suitable for dry bentonite is constructed and verified. This provides a new approach to constructing a thermal conductivity prediction model for dry bentonite, establishing the relationship between the thermal conductivity and porosity of dry bentonite. Attached Figure Description

[0052] Figure 1 A flowchart illustrating the overall method for estimating the thermal conductivity of bentonite provided by this invention;

[0053] Figure 2 A flowchart of a fractal thermal conductivity model applicable to dry bentonite provided in an embodiment of the present invention;

[0054] Figure 3 The structure of bentonite;

[0055] Figure 4 This is a comparison chart of the measured thermal conductivity of three types of bentonite and the model simulation curve in the embodiments of the present invention;

[0056] Figure 5 This is a comparison chart of the measured thermal conductivity and the simulated calculated values ​​of three types of bentonite in the embodiments of the present invention. Detailed Implementation

[0057] The following will refer to the appendices in the embodiments of the present invention. Figure 1-5 The technical solutions in the embodiments of the present invention will be clearly and completely described. It should be understood that the terminology used in the present invention is only for describing particular implementation methods and is not intended to limit the present invention.

[0058] like Figure 1 As shown, this invention provides a method for estimating the thermal conductivity of bentonite, comprising the following steps:

[0059] Step 1: Based on the cohesive property of bentonite having a multi-layered aggregated structure, the bentonite is characterized accordingly to obtain the expression for the number of aggregated particles and porosity of bentonite.

[0060] Step 2: Based on the expressions for the number of aggregated particles and porosity of bentonite, modify the expression for the number of effective basic unit contact points within the particles of porous materials; based on the modified expression, calculate the volume ratio of the soil skeleton to the total volume of bentonite; based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume, determine the relative density of montmorillonite interlayer contact in bentonite.

[0061] Step 3: Based on the relative density of the montmorillonite interlayer contact in bentonite, the thermal conductivity of bentonite is defined as being proportional to the relative density. The relationship between the thermal conductivity and porosity of bentonite is then derived. By establishing a mathematical model of fractal thermal conductivity, the thermal conductivity of bentonite is estimated, and the estimated result of the thermal conductivity of bentonite is obtained.

[0062] This application can effectively reflect the influence of multiple factors on the thermal conductivity of soft soil, and realize the rapid and accurate calculation of the thermal conductivity of soft soil with high water content.

[0063] Example

[0064] like Figure 2 As shown in the figure, this invention proposes a method for calculating the thermal conductivity of soft soil with high water content, including the following steps:

[0065] S1: Based on the cohesive property of bentonite having a multi-layered aggregated structure, the expression of the number of aggregated particles and pore volume fraction as proposed by Xu et al (2014) is adopted;

[0066] S2: Based on the principle that the heat transfer of bentonite mainly occurs through the contact between solid phases, the number of effective basic unit contact points within the particles of Son and Hsu porous materials, Q, is used. C The form of expression;

[0067] S3: Based on the characteristics that the heat transfer of bentonite is mainly through the contact between solid phases and that the interlayer contact of montmorillonite is mostly surface-cation-surface contact or edge-surface contact, the number of effective basic unit contact points within the particles of Son and Hsu porous materials, Q, is calculated. C The expression form was modified;

[0068] S4: Based on the fact that there are pores within bentonite particles and that the volume of the bentonite skeleton formed by the connection between particles is not only the volume of solid material, we obtain the proportion of the volume of the skeleton Vs to the total volume V.

[0069] S5: Based on the average density of the interlayer contact of montmorillonite in the particles, Q C / V S Given the density of bentonite particles as Q / V, we obtain the expression for the relative density of the montmorillonite interlayer contact in bentonite. Based on the fact that the higher the ρ, the greater the thermal conductivity, we further assume that the thermal conductivity of bentonite is proportional to ρ. Combining the above expression, we obtain the relationship between the thermal conductivity of bentonite and the porosity n, and establish a mathematical model for fractal thermal conduction.

[0070] like Figure 3 The diagram illustrates the structure of bentonite. In this embodiment, the most abundant mineral in bentonite is montmorillonite. The structure of montmorillonite is generally considered to consist of an alumina octahedral sheet sandwiched between two silicon tetrahedral sheets. The unit layer thickness of montmorillonite is approximately 0.96 nm, and its lateral dimensions are approximately 200-1000 nm. The surface of the montmorillonite layer typically carries a large amount of negative charge, while the edges carry a small amount of negative charge; therefore, bentonite as a whole carries a negative charge.

[0071] To maintain charge balance, it adsorbs a certain amount of cations (exchangeable) from the outside. These cations then generate electrostatic attraction on another montmorillonite surface, causing the montmorillonite layers to bond together and aggregate into stacks. These stacks may consist of several to dozens of neatly arranged montmorillonite unit layers. Similarly, these stacks also aggregate to form larger bentonite particles, which in turn aggregate to form a soil skeleton.

[0072] In step S1, for cohesive rock and soil masses with multi-layered aggregated structures, Xu et al. (2014) suggested that the number of aggregated particles and the pore volume fraction can be expressed in the following forms:

[0073]

[0074]

[0075] In the formula, Q represents the number of aggregated particles, and n represents the pore volume fraction. S and f c It is a scaling factor concerning aggregated particles and the morphology of basic units within aggregated particles; D is the fractal dimension; d a and d n These are the average diameters of the aggregated particles and the basic units within the aggregated particles, respectively.

[0076] Similarly, the above formula can be used to characterize bentonite, where Q is the number of montmorillonite particles, n is the porosity, and d... a and d n These represent the average diameters of the bentonite particles and the montmorillonite layer, respectively.

[0077] In step S2, bentonite contains a large number of pores, generally divided into inter-particle pores and intra-particle pores. Compared with the thermal conductivity of solid materials, the thermal conductivity of pore gases is very low; therefore, heat is mainly transferred through the contact between solid phases. The number of effective basic unit contact points within particles in Son and Hsu porous materials can be represented by QC:

[0078]

[0079] In step S3, montmorillonite differs from other substances in that the interlayer contact of montmorillonite is mostly surface-cation-surface contact or edge-surface contact. Therefore, the interlayer contact of montmorillonite should also take into account the contact between cations and montmorillonite layers, and formula (3) needs to be modified:

[0080]

[0081] In the formula, α is a proportionality factor related to the cation radius.

[0082] In step S4, due to the presence of pores within the particles, the volume of the bentonite skeleton formed by the connection of particles is not only the volume of the solid material; at this point, the volume V of the skeleton is... S The proportion of the total volume V can be expressed by the following formula:

[0083]

[0084] In the formula, C α These are parameters related to the contact properties of clay particles within the soil skeleton.

[0085] In step S4, the average density of the interlayer contact of montmorillonite in the particles is Q. C / V S If the density of bentonite particles is Q / V, then the relative density ρ of the montmorillonite interlayer contact in bentonite can be expressed as:

[0086]

[0087] In the formula, β is only related to α and C α The relevant parameters; a higher relative density ρ value indicates more contact points available for heat transfer, resulting in smoother heat transfer. Therefore, the higher the ρ value, the greater the thermal conductivity.

[0088] Assuming the thermal conductivity of bentonite is proportional to ρ, and combining the above equations, we can derive the relationship between the thermal conductivity of bentonite and its porosity n:

[0089]

[0090] In the formula, λ0 is the thermal conductivity of bentonite when n=0, which is also known as the solid phase thermal conductivity.

[0091] When the mineral composition of bentonite is known, λ0 can be the weighted average of the thermal conductivity of different minerals.

[0092] Using a fractal thermal conductivity model, the thermal conductivity of three types of bentonite—USA Mx-80, Japan Kunigel-1, and China Gmz-07—was calculated according to the above formula. Figure 4 The figure shown is a comparison between the measured thermal conductivity of three types of bentonite and the model simulation curves in an embodiment of the present invention; as shown... Figure 5 The figure shown is a comparison chart of the measured thermal conductivity and the simulated calculated values ​​of three types of bentonite in this embodiment of the invention. A comparison of the simulated calculated values ​​and the measured thermal conductivity values ​​of the three types of bentonite reveals the following:

[0093] The thermal conductivity of three types of dry bentonite at different dry densities shows that the higher the dry density, the greater the thermal conductivity of the bentonite. When the dry density is the same, the thermal conductivity of the three types of bentonite is roughly the same, but there are also some differences. This is mainly related to the mineral composition and pore structure (fractal dimension) of the bentonite.

[0094] The isothermal adsorption curves of all bentonite samples belong to Type IV in Brunauer's classification, representing the case of capillary condensation during multilayer adsorption in porous media. The hysteresis loops of the isothermal adsorption-desorption curves of all bentonite samples are generally located between relative pressures p / p0 = 0.45 and 0.99, indicating that these bentonite samples are predominantly mesoporous (pore size 2–50 nm), and N2 undergoes significant capillary condensation within them. Since the N2 isothermal adsorption curves of the bentonite powder samples indicate that capillary condensation is the main adsorption process, the FHH equation method can be used to calculate the fractal dimension of bentonite. This demonstrates that the present invention has good practicality and reliability in calculating the thermal conductivity of bentonite.

[0095] Overall, the method for estimating the thermal conductivity of bentonite proposed in this invention provides a new approach and method for obtaining the thermal conductivity of bentonite.

[0096] This application also proposes a system for estimating the thermal conductivity of bentonite, including:

[0097] The bentonite parameter characterization module is used to characterize bentonite based on its cohesive properties of having a multi-layered aggregated structure, and to obtain expressions for the number of aggregated particles and porosity of bentonite.

[0098] The bentonite parameter correction module is used to modify the expression for the number of effective basic unit contact points within particles in porous materials based on the expression for the number of aggregated particles and porosity of bentonite; calculate the volume ratio of the soil skeleton to the total volume of bentonite based on the modified expression; and determine the relative density of montmorillonite interlayer contact in bentonite based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume.

[0099] The bentonite thermal conductivity determination module is used to define the thermal conductivity of bentonite as being proportional to its relative density based on the relative density of the montmorillonite interlayer contact, and to derive the relationship between the thermal conductivity and porosity of bentonite. Based on the relationship between thermal conductivity and porosity, the module estimates the thermal conductivity of bentonite and obtains the estimated thermal conductivity result.

[0100] This application also proposes a computer device, which includes a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, the processor performs the following steps:

[0101] Based on the cohesive property of bentonite having a multi-layered aggregated structure, bentonite was characterized accordingly, and expressions for the number of aggregated particles and porosity of bentonite were obtained.

[0102] Based on the expressions for the number of aggregated particles and porosity of bentonite, the expression for the number of effective basic unit contact points within particles in porous materials is modified; based on the modified expression, the volume ratio of the soil skeleton to the total volume of bentonite is calculated; based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume, the relative density of montmorillonite interlayer contact in bentonite is determined.

[0103] Based on the relative density of the montmorillonite interlayer contact in bentonite, the thermal conductivity of bentonite is defined to be proportional to the relative density, thus obtaining the relationship between the thermal conductivity and porosity of bentonite. Based on the relationship between thermal conductivity and porosity, the thermal conductivity of bentonite is estimated, and the estimated result of the thermal conductivity of bentonite is obtained.

[0104] This application also proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the following steps:

[0105] Based on the cohesive property of bentonite having a multi-layered aggregated structure, bentonite was characterized accordingly, and expressions for the number of aggregated particles and porosity of bentonite were obtained.

[0106] Based on the expressions for the number of aggregated particles and porosity of bentonite, the expression for the number of effective basic unit contact points within particles in porous materials is modified; based on the modified expression, the volume ratio of the soil skeleton to the total volume of bentonite is calculated; based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume, the relative density of montmorillonite interlayer contact in bentonite is determined.

[0107] Based on the relative density of the montmorillonite interlayer contact in bentonite, the thermal conductivity of bentonite is defined to be proportional to the relative density, thus obtaining the relationship between the thermal conductivity and porosity of bentonite. Based on the relationship between thermal conductivity and porosity, the thermal conductivity of bentonite is estimated, and the estimated result of the thermal conductivity of bentonite is obtained.

[0108] In summary, this invention addresses the limitations of traditional indoor thermal conductivity testing (steady-state or transient) for obtaining the thermal conductivity of bentonite, which requires significant manpower, is expensive, and time-consuming. It proposes a numerical alternative method for estimating the thermal conductivity of bentonite using various theoretical and empirical models. This invention fully considers the main factors of mineral composition and pore structure, and through fractal theory, combines bentonite thermal conductivity testing with microscopic morphology analysis to construct and verify a fractal thermal conductivity model suitable for dry bentonite. This method has a clear approach and well-defined steps, providing a novel predictive model for the thermal conductivity of dry bentonite and its porosity.

[0109] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

[0110] Furthermore, unless otherwise stated, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. All references to this specification are incorporated by way of citation to disclose and describe methods relating to those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.

Claims

1. A method for estimating the thermal conductivity of bentonite, characterized in that, Includes the following steps: Based on the cohesive property of bentonite having a multi-layered aggregated structure, bentonite was characterized accordingly, and expressions for the number of aggregated particles and porosity of bentonite were obtained. Based on the expressions for the number of aggregated particles and porosity of bentonite, the expression for the number of effective basic unit contact points within particles in porous materials is modified; based on the modified expression, the volume ratio of the soil skeleton to the total volume of bentonite is calculated; based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume, the relative density of montmorillonite interlayer contact in bentonite is determined. Based on the relative density of the montmorillonite interlayer contact in bentonite, the thermal conductivity of bentonite is defined to be proportional to its relative density, thus deriving the relationship between the thermal conductivity and porosity of bentonite. A fractal thermal conductivity model is established based on the relationship between thermal conductivity and porosity to estimate the thermal conductivity of bentonite, thus obtaining the estimated results of the thermal conductivity of bentonite.

2. The method for estimating the thermal conductivity of bentonite according to claim 1, characterized in that, The method for obtaining the expression for the number of aggregated particles and porosity of bentonite includes the following steps: The number of aggregated particles, Q, is: The pore volume fraction n is: In the formula, P s and f c These represent the scaling factors for aggregated particles and the basic unit morphology within aggregated particles, respectively; D is the fractal dimension; d a and d n These are the average diameters of the aggregated particles and the basic units within the aggregated particles, respectively. Bentonite is characterized using expressions for Q and n, where Q is the number of montmorillonite particles, n is the porosity, and d... a and d n These represent the average diameters of the bentonite particles and the montmorillonite layer, respectively.

3. The method for estimating the thermal conductivity of bentonite according to claim 2, characterized in that, The modification of the expression for the number of effective basic unit contact points within particles of porous materials includes the following steps: The expression for the number of effective basic unit contact points within the particles of the porous material is: The interlayer contact forms of montmorillonite are mostly surface-cation-surface contact or edge-surface contact. Considering that the interlayer contact of montmorillonite includes the contact between cations and montmorillonite layers, the expression for the number of effective basic unit contact points within the particles of porous materials is modified, resulting in the modified expression: In the formula, α is a proportionality factor related to the cation radius.

4. The method for estimating the thermal conductivity of bentonite according to claim 3, characterized in that, The calculation of the volume ratio of the soil skeleton to the total volume of bentonite is described. Includes the following steps: Due to the presence of pores within the particles, the volume of the bentonite skeleton formed by the connections between particles is not solely the volume of the solid material. Therefore, the proportion of the skeleton volume Vs to the total volume V is: In the formula, C α These are parameters related to the contact properties of clay particles within the soil skeleton.

5. The method for estimating the thermal conductivity of bentonite according to claim 4, characterized in that, The relative density of the montmorillonite interlayer contact in the bentonite is: In the formula, β is only related to α and C α Relevant parameters; The larger the relative density ρ value, the more contact points are used for heat transfer, and the smoother the heat transfer. In other words, the higher the ρ value, the greater the thermal conductivity.

6. The method for estimating the thermal conductivity of bentonite according to claim 5, characterized in that, The relationship between the thermal conductivity and porosity of the bentonite is as follows: In the formula, λ0 is the thermal conductivity of bentonite when n=0, which is called the solid phase thermal conductivity.

7. The method for estimating the thermal conductivity of bentonite according to claim 6, characterized in that, The estimation of the thermal conductivity of bentonite includes the following steps: When the mineral composition of bentonite is known, the value of λ0 is obtained by weighted average of the thermal conductivity of different minerals; Substituting λ0 into the relationship between the thermal conductivity and porosity of bentonite, we obtain the thermal conductivity λ of bentonite.

8. A system for estimating the thermal conductivity of bentonite, characterized in that, include: The bentonite parameter characterization module is used to characterize bentonite based on its cohesive properties of having a multi-layered aggregated structure, and to obtain expressions for the number of aggregated particles and porosity of bentonite. The bentonite parameter correction module is used to modify the expression for the number of effective basic unit contact points within particles in porous materials based on the expression for the number of aggregated particles and porosity of bentonite; calculate the volume ratio of the soil skeleton to the total volume of bentonite based on the modified expression; and determine the relative density of montmorillonite interlayer contact in bentonite based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume. The bentonite thermal conductivity determination module is used to define the thermal conductivity of bentonite as being proportional to its relative density based on the relative density of the montmorillonite interlayer contact in bentonite, and to derive the relationship between the thermal conductivity and porosity of bentonite. A fractal thermal conductivity model is established based on the relationship between thermal conductivity and porosity to estimate the thermal conductivity of bentonite, thus obtaining the estimated results of the thermal conductivity of bentonite.

9. A computer device, characterized in that, The computer device includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the following steps: Based on the cohesive property of bentonite having a multi-layered aggregated structure, bentonite was characterized accordingly, and expressions for the number of aggregated particles and porosity of bentonite were obtained. Based on the expressions for the number of aggregated particles and porosity of bentonite, the expression for the number of effective basic unit contact points within particles in porous materials is modified; based on the modified expression, the volume ratio of the soil skeleton to the total volume of bentonite is calculated; based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume, the relative density of montmorillonite interlayer contact in bentonite is determined. Based on the relative density of the montmorillonite interlayer contact in bentonite, the thermal conductivity of bentonite is defined to be proportional to its relative density, thus deriving the relationship between the thermal conductivity and porosity of bentonite. A fractal thermal conductivity model is established based on the relationship between thermal conductivity and porosity to estimate the thermal conductivity of bentonite, thus obtaining the estimated results of the thermal conductivity of bentonite.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to perform the following steps: Based on the cohesive property of bentonite having a multi-layered aggregated structure, bentonite was characterized accordingly, and expressions for the number of aggregated particles and porosity of bentonite were obtained. Based on the expressions for the number of aggregated particles and porosity of bentonite, the expression for the number of effective basic unit contact points within particles in porous materials is modified; based on the modified expression, the volume ratio of the soil skeleton to the total volume of bentonite is calculated; based on the expression for the number of aggregated particles, the modified expression, and the volume ratio of the soil skeleton to the total volume, the relative density of montmorillonite interlayer contact in bentonite is determined. Based on the relative density of the montmorillonite interlayer contact in bentonite, the thermal conductivity of bentonite is defined to be proportional to its relative density, thus deriving the relationship between the thermal conductivity and porosity of bentonite. A fractal thermal conductivity model is established based on the relationship between thermal conductivity and porosity to estimate the thermal conductivity of bentonite, thus obtaining the estimated results of the thermal conductivity of bentonite.

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