Threshold judgment method for eliminating loess collapsibility through microwave irradiation

Abstract

The invention discloses a threshold judgment method for eliminating loess collapsibility through microwave irradiation, relates to the technical field of data prediction and updating, and is used for solving the problem of insufficient collapsibility control effect evaluation means when the structural change is not obvious, and the method comprises the following steps: acquiring and preprocessing a collapsible loess sample to obtain initial physical information data of the collapsible loess sample; microwave irradiation experiment conditions are set, and the collapsibility coefficient change trend of loess under the conditions is calculated. And judging the change of the internal structure according to trend evaluation whether a temperature distribution analysis method is adopted, if the change is weak, further obtaining the microstructure characteristics of the sample and the change of mineral components, and comprehensively evaluating the collapsibility reduction degree. If the reduction degree is high, void ratio parameters are introduced to carry out quantitative analysis on the collapsibility change, and a scanning electron microscope or X-ray diffraction analysis is selected to verify whether the collapsibility change reaches an expected control target or not, so that the stability and safety of loess are ensured.

Description

Technical Field

[0001] The present invention relates to the field of data prediction and update, and more specifically, to a method for determining the threshold of eliminating collapsibility of loess by microwave irradiation. Background Art

[0002] Loess is a type of soil with loose structure, high porosity, and weak cementation. It has certain strength under natural conditions, but it is prone to structural collapse when encountering water, forming the so-called "collapsibility", which poses a major threat to the safety of engineering construction. Traditional methods for treating collapsibility of loess mainly include chemical modification (such as lime and cement solidification) and physical modification (such as vibration compaction, heat treatment, etc.), but these methods often have problems such as long treatment cycle, unstable effect, and poor adaptability. In recent years, with the gradual in-depth research on microwave heating technology in the field of soil modification, its advantages such as non-contact, rapid heating, and energy controllability have made it a new direction for treating collapsibility of loess. Under the action of microwave irradiation, the internal moisture of loess migrates rapidly and the structure changes rapidly, which may cause the reorganization of pore structure and the enhancement of mineral cementation characteristics, and is expected to achieve the inhibition or elimination of collapsibility.

[0003] The existing technology has the following deficiencies: At present, the existing research lacks a quantitative correlation analysis between the evolution process of the temperature field and the change of collapsibility, and cannot scientifically determine the critical control parameters of microwave irradiation. At the same time, in the case where the structural change of loess is not significant, there is a lack of an auxiliary evaluation method for the degree of collapsibility reduction at the micro level (such as pore structure and mineral composition), which limits the scope of application and reliability of the technology. Therefore, a method for determining the threshold of eliminating collapsibility of loess by microwave irradiation is proposed.

[0004] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present disclosure, and thus it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0005] In order to overcome the above defects of the existing technology, the embodiments of the present invention provide a method for determining the threshold of eliminating collapsibility of loess by microwave irradiation, which uses a comprehensive determination technology combining dynamic monitoring of the microwave irradiation temperature field and analysis of the change trend of the collapsibility coefficient, and is supplemented by a multi-scale quantitative evaluation method for microstructural characteristics and mineral composition changes to solve the problems proposed in the above background art.

[0006] To achieve the above object, the present invention provides the following technical solution, a method for determining the threshold of eliminating collapsibility of loess by microwave irradiation, including the following steps: Step S1: Collect collapsible loess samples and perform pretreatment to obtain their initial physical information data; Step S2: Set the microwave irradiation experimental conditions based on the initial physical information data of the pre-treated loess samples, calculate the variation trend of the collapsibility coefficient of the loess samples under the microwave irradiation experimental conditions, and evaluate whether to use the temperature distribution analysis method to judge the change of the internal structure of the loess according to the variation trend of the collapsibility coefficient of the loess; Step S3: When it is judged that the change of the internal structure of the loess is weak, further obtain the microscopic structure characteristics and the change of mineral composition of the samples, comprehensively evaluate the degree of reduction of the collapsibility of the loess. If the degree of reduction of the collapsibility is high, introduce the void ratio parameter to quantitatively analyze the change of the collapsibility; Step S4: Select to use scanning electron microscopy test or X-ray diffraction analysis to verify whether the collapsibility of the loess reaches the expected control target according to the quantitative analysis results of the change of the collapsibility.

[0007] In a preferred embodiment, in step S1, the ratio of the difference between the wet soil mass and the dry soil mass to the dry soil mass is defined as the natural moisture content; Divide the wet soil mass of the density measurement sample by the product of the volume of the density measurement sample and the sum of the natural moisture content and one to obtain the initial dry density; Based on the mass and temperature change of the constant temperature water, calculate the heat absorbed by the loess sample to obtain the natural specific heat capacity.

[0008] In a preferred embodiment, in step S2, the natural moisture content, the initial dry density and the natural specific heat capacity are constructed as the input vectors of the support vector regression method; Use the radial basis kernel function to map the input vectors to a high-dimensional feature space, and construct a microwave power prediction model by solving the minimization problem; Solve through the microwave power prediction model to obtain the microwave power; Calculate the total heat absorbed required for the complete evaporation of the moisture in the loess sample as the evaporation energy; Take the minimum deviation between the evaporation energy and the theoretical thermal energy provided by the microwave irradiation as the objective function of the Bayesian optimization method; Construct a posterior probability model through the Gaussian process and select sample points for the objective function based on the expected improvement function, and iteratively converge to the optimal solution, and the optimal solution is the irradiation time.

[0009] In a preferred embodiment, in step S2, measure the collapsibility coefficient of the loess sample in the initial state as the collapsibility coefficient before the experiment; Perform microwave irradiation experimental treatment on the loess sample according to the microwave power and irradiation time; After the microwave irradiation experiment is completed, measure the collapsibility coefficient of the loess sample again as the collapsibility coefficient after the experiment; Calculate the ratio of the collapsibility coefficient before the experiment to the collapsibility coefficient after the experiment; When the ratio of the collapsibility coefficient before the experiment to the collapsibility coefficient after the experiment is less than one, it indicates that the collapsibility is weakened; When the ratio of the collapsibility coefficient before the experiment to the collapsibility coefficient after the experiment is equal to one, it indicates no significant change; When the ratio of the collapsibility coefficient before the experiment to the collapsibility coefficient after the experiment is greater than one, it indicates that the collapsibility is enhanced.

[0010] In a preferred embodiment, in step S2, when the collapsibility is weakened, collect the temperature data of the loess sample during the irradiation process, establish a two-dimensional temperature spatial distribution matrix, and calculate the local temperature variance; Set a variance threshold and compare the local temperature variance with the variance threshold; If the local temperature variance is greater than the variance threshold, it is determined that the internal structure of the loess changes strongly; When the local temperature variance is less than the variance threshold, it is determined that the internal structure of the loess changes weakly.

[0011] In a preferred embodiment, in step S3, when it is determined that the internal structure of the loess changes weakly, obtain the microscopic structure characteristics of the loess, including the volume of the loess sample, the volume of pores, the outer perimeter of the loess particles, and the area of the loess particles; The porosity is the ratio of the pore volume to the volume of the loess sample; Calculate the particle shape index through the outer perimeter and the area of the loess particles; Analyze the mineral composition of the loess sample, including the mass of expansive minerals, the total mineral content in the loess sample, and the mass of quartz; The ratio of the mass of expansive minerals to the total mineral content in the loess sample is used as the expansive mineral content value; The ratio of the mass of quartz to the total mineral content in the loess sample is used as the quartz content value.

[0012] In a preferred embodiment, in step S3, comprehensively evaluate the degree of reduction in the collapsibility of the loess through the TOPSIS method by combining the microscopic structure characteristics and the changes in mineral composition; Normalize the porosity value, the particle shape index, the expansive mineral content value, and the quartz content value and combine them into a feature vector; The TOPSIS method calculates the relative closeness of the loess sample through the feature vector; Sort the relative closeness values in descending order and select the median of the sorted values as the closeness threshold; If the relative closeness is greater than the closeness threshold, it is determined that the degree of reduction in collapsibility is high; otherwise, it is determined that the degree of reduction in collapsibility is low.

[0013] In a preferred embodiment, in step S3, when the degree of collapsibility reduction is high, the void ratio is further calculated through porosity to quantitatively analyze the change in collapsibility; A preset sampling period is set, and the difference between the void ratio at the start sampling moment and the void ratio at the end sampling moment is calculated to obtain the change in void ratio; The ratio of the change in void ratio to the void ratio at the start sampling moment is used as the degree of collapsibility change.

[0014] In a preferred embodiment, in step S4, a preset collapsibility threshold is compared with the degree of collapsibility change. If the degree of collapsibility change is greater than the preset collapsibility threshold, it is determined that the degree of collapsibility change is high; otherwise, it is determined that the degree of collapsibility change is low; When the degree of collapsibility change is high, a scanning electron microscope test analysis is used to verify whether the collapsibility of the loess reaches the expected control target; When the degree of collapsibility change is low, an X-ray diffraction analysis is used to verify whether the collapsibility of the loess reaches the expected control target.

[0015] The technical effects and advantages of the present invention: The present invention collects collapsible loess samples and performs pretreatment to obtain their initial physical information data, sets microwave irradiation experimental conditions, calculates the change trend of the collapsibility coefficient of the loess under the microwave irradiation experimental conditions, and evaluates whether to use the temperature distribution analysis method to judge the change in the internal structure of the loess according to the change trend of the collapsibility coefficient of the loess. When it is judged that the change in the internal structure of the loess is weak, the microscopic structure characteristics and mineral composition changes of the sample are further obtained, and the degree of collapsibility reduction of the loess is comprehensively evaluated. If the degree of collapsibility reduction is relatively high, the void ratio parameter is introduced to quantitatively analyze the change in collapsibility, and a scanning electron microscope test or X-ray diffraction analysis is selected to verify whether the collapsibility of the loess reaches the expected control target, ensuring the stability and safety of the loess. Description of the Drawings

[0016] Figure 1 It is a flowchart for implementing the method for determining the threshold of eliminating the collapsibility of loess by microwave irradiation of the present invention.

[0017] Figure 2 It is a schematic diagram of the steps of the method for determining the threshold of eliminating the collapsibility of loess by microwave irradiation of the present invention. Detailed Embodiments

[0018] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention. Embodiment

[0019] Please refer to Figures 1 to 2 , the threshold determination method for eliminating the collapsibility of loess by microwave irradiation, and the specific operation process is as follows: Step S1: Collect collapsible loess samples and perform pre-treatment to obtain their initial physical information data; Step S2: Set the microwave irradiation experimental conditions based on the initial physical information data of the pre-treated loess samples, calculate the change trend of the collapsibility coefficient of the loess samples under the microwave irradiation experimental conditions, and evaluate whether to use the temperature distribution analysis method to judge the change of the internal structure of the loess according to the change trend of the collapsibility coefficient of the loess; Step S3: When it is judged that the change of the internal structure of the loess is weak, further obtain the microscopic structure characteristics and mineral component changes of the samples, comprehensively evaluate the degree of reduction of the collapsibility of the loess. If the degree of reduction of the collapsibility is high, introduce the void ratio parameter to quantitatively analyze the change of the collapsibility; Step S4: Select to use scanning electron microscopy test or X-ray diffraction analysis to verify whether the collapsibility of the loess reaches the expected control target according to the quantitative analysis results of the change of the collapsibility.

[0020] The specific implementation is as follows: In step S1, collect collapsible loess samples in the target area on-site, and use the undisturbed sampling method to ensure the integrity of the sample structure. After sampling, seal the loess samples to avoid the influence of water evaporation or structural disturbance on the test results; Bring the collected loess samples into the laboratory environment for pre-treatment, remove large particle impurities from the loess samples, place them under the standard curing temperature conditions for static settlement to achieve water balance, and calibrate the quality of the loess samples to ensure the stability of the state of the loess samples. After completing the pre-treatment of the loess samples, start to obtain the initial physical information data of the loess, specifically including the natural moisture content, initial dry density and natural specific heat capacity; First, use the drying method to measure the natural moisture content. The specific operation of the drying method is to take the loess sample and weigh the wet soil mass with a precision balance, then place it in an oven for constant temperature drying and take it out, cool it to room temperature, and weigh the dry soil mass again. Define the natural moisture content as the ratio of the difference between the wet soil mass and the dry soil mass to the dry soil mass. The natural moisture content is used to reflect the degree of water saturation in the natural state of the soil sample. The higher the natural moisture content, the higher the degree of water saturation of the loess sample; Secondly, measure the initial dry density, and measure the dry soil mass of the soil body per unit volume by the cutting ring method. The specific operation of the cutting ring method is to use the cutting ring to press vertically into the loess sample, scrape off the excess soil at the upper and lower edges, take the density measurement sample, weigh the wet soil mass of the density measurement sample in the water-containing state, and combine the natural moisture content to calculate the dry soil mass of the density measurement sample. The specific calculation formula for calculating the initial dry density is , where, is the initial dry density, reflecting the compaction state of the soil mass, is the mass of loess in the density measurement sample under the water-containing state, is the natural water content, is the volume of the density measurement sample taken by the cutting ring; Finally, calculate the natural specific heat capacity, which is measured by a mixing calorimeter. The natural specific heat capacity is calculated through the principle of conservation of heat. The specific operation is to place the loess sample in an oven to dry at a constant temperature and then cool it to room temperature. Prepare constant-temperature water as the heat exchange medium. Place the dried loess sample and the constant-temperature water together in a calorimeter container with good heat insulation performance, fully contact and reach the thermal equilibrium state. Based on the principle of conservation of heat, the specific calculation formula for the natural specific heat capacity is , where is the natural specific heat capacity, is the specific heat capacity of water, is the mass of the constant-temperature water, is the mass of the dried loess sample, is the initial temperature of the constant-temperature water, is the final mixed temperature after stabilization of the dried loess sample and the constant-temperature water, is the initial temperature of the loess sample; It should be noted that the undisturbed sampling method refers to the method of directly obtaining an undisturbed or undamaged soil sample volume from the target soil layer using a sampling tool with a protective structure during geotechnical sampling, which is used to maximize the preservation of the natural structure, moisture state, density and other physical properties of the soil mass; the cutting ring is a special tool for cylindrical soil sampling and density determination, with a fixed inner diameter, height and volume; the mixing calorimeter is an experimental device for measuring the specific heat capacity of solid samples, constructed based on the principle of conservation of heat and operating in an adiabatic or quasi-adiabatic environment.

[0021] In step S2, based on the initial physical information of the preprocessed loess sample, set the parameter indexes of the microwave irradiation experimental conditions, including the microwave power and irradiation time; First, use the support vector regression method to establish a microwave power prediction model. Construct the natural water content, initial dry density and natural specific heat capacity as the input vector. Based on the historical data of microwave irradiation experiments of loess samples under different combinations of natural water content, initial dry density and natural specific heat capacity, construct a training sample set. Use the radial basis kernel function to map the input vector to a high-dimensional feature space. Construct a microwave power prediction model by solving the minimization problem. The output of the model is , where is the microwave power, is the kernel function, and are Lagrange multipliers, b is the bias term, is the training sample set, is the input vector, i is the index value of the training sample set, and n is the number of training samples. Through model solution, the microwave power matching the initial physical information of the loess sample is obtained. Subsequently, based on the natural water content, the evaporation energy required for evaporation is calculated. The evaporation energy reflects the total heat absorbed for complete evaporation of water in a unit mass of the loess sample. Taking the evaporation energy as the target heat input, the Bayesian optimization method is used to calculate the irradiation time that meets the evaporation heat energy requirement. The Bayesian optimization method takes the minimum deviation between the evaporation energy and the theoretical heat energy provided by microwave irradiation as the objective function, constructs a posterior probability model through a Gaussian process, and selects sample points based on the expected improvement function, iteratively converging to the optimal solution, which is the irradiation time. After calculating the microwave power and irradiation time, enter the microwave irradiation experiment stage. By setting the microwave power and irradiation time, verify the influence degree of microwave irradiation on the collapsibility of loess, and evaluate the strength of its structural change based on the change of the collapsibility coefficient and the temperature field distribution. First, measure the collapsibility coefficient of the loess sample in the initial state as the pre-experiment collapsibility coefficient. The collapsibility coefficient is a measure of the volume compression degree of loess caused by water infiltration under loading conditions, defined as the ratio of the vertical compression deformation amount of the loess sample under saturated loading conditions to the original height of the loess sample. Subsequently, according to the microwave power and irradiation time determined by the above calculation, perform microwave irradiation experiment treatment on the loess sample. After the microwave irradiation experiment is completed, cool it to room temperature, and measure the collapsibility coefficient of the loess sample again under the same loading conditions and measurement methods as the post-experiment collapsibility coefficient. Calculate the ratio of the pre-experiment collapsibility coefficient to the post-experiment collapsibility coefficient, denoted as to quantify the change trend of the collapsibility coefficient of the loess sample before and after the microwave irradiation experiment. When it indicates that the collapsibility is weakened; When it indicates no significant change; When it indicates that the collapsibility is enhanced; When the collapsibility is weakened, to further identify the microscopic influence degree of the microwave irradiation effect on the internal structure of loess, the temperature distribution analysis method is used to evaluate the change of the internal structure of loess during irradiation. The temperature distribution analysis method collects the temperature data of the loess sample during irradiation through an embedded thermocouple matrix, establishes a two-dimensional temperature spatial distribution matrix, calculates the local temperature variance, and evaluates the distribution consistency of heat energy inside the loess. Set the variance threshold, and compare the local temperature variance with the variance threshold. The above variance threshold is obtained by professionals through experiments and will not be elaborated here; If the local temperature variance is greater than the variance threshold, it is determined that the internal structure of the loess changes strongly, and the heat energy transmission in the loess sample shows significant non-uniformity, usually corresponding to obvious pore structure changes or crack generation; When the local temperature variance is less than the variance threshold, it is determined that the internal structure of the loess changes weakly, indicating that the macroscopic heat conduction is relatively uniform, the degree of structural damage is relatively light, and there may still be microscopic-scale mineral composition changes and fine pore structure adjustments inside the loess sample. The above changes do not show significant gradient non-uniformity in the temperature field, but have an important impact on collapsibility. Therefore, under the condition that the structural change is judged to be weak through temperature distribution analysis, the microscopic structure characteristics and mineral composition changes of the loess sample are further collected to comprehensively evaluate the reduction degree of the collapsibility of the loess; It should be noted that the support vector regression method is a regression analysis technique based on the support vector machine theory. By constructing a regression model, it realizes the fitting of the non-linear mapping relationship between the input data and the target variable; the radial basis kernel function is a commonly used kernel function form, which is used to map the input data to a high-dimensional feature space to achieve the linear separability of non-linear data; the Bayesian optimization method is a global optimization strategy based on Bayesian statistical theory. By constructing a probability model of the objective function and combining the acquisition function, the optimal sampling points are selected within a limited number of evaluations; the Gaussian process is a non-parametric Bayesian statistical model, which defines the correlation between any points in the input space through the mean function and the covariance function; the expected improvement function is a commonly used acquisition function, which is used to guide the selection of sampling points in Bayesian optimization; the embedded thermocouple matrix refers to an array structure composed of multiple thermocouple sensors embedded inside the material or sample to be measured according to a certain spatial layout rule.

[0022] In step S3, when it is judged that the internal structure of the loess changes weakly, the microscopic structure image of the loess sample is obtained through scanning electron microscope testing, and the microscopic structure characteristics of the loess in the microscopic structure image are obtained, including the volume of the loess sample, the pore volume of the loess, the outer perimeter of the loess particles, and the area of the loess particles; The porosity is the ratio of the pore volume in the loess to the volume of the loess sample, and the ratio of the pore volume of the loess to the volume of the loess sample is used as the porosity value; the higher the porosity value, the stronger the collapsibility; Among the loess particle morphologies, the irregular loess is prone to collapsibility, and the regularity is measured by calculating the roundness of the loess particles: , where P is the outer perimeter of the loess particle, A is the area of the particle, and R is the particle morphology index; The mineral composition of the loess sample is analyzed by X-ray diffraction, including the mass of the swelling mineral, the total mineral content in the loess sample, and the quartz mass; The swelling mineral content is the content of swelling minerals in loess particles, and the ratio of the mass of swelling minerals to the total mineral content in the loess sample is taken as the swelling mineral content value; The quartz content is the non-swelling mineral in the loess sample. The higher the quartz content, the lower the collapsibility. The ratio of the quartz mass to the total mineral content in the loess sample is taken as the quartz content value; Comprehensively evaluate the degree of collapsibility reduction of loess through the TOPSIS method by combining microscopic structural characteristics and mineral composition changes: Analyze the microscopic structural characteristics and mineral composition changes of multiple loess samples, normalize the porosity value, particle morphology index, swelling mineral content value, and quartz content value, and combine them into a feature vector; In each feature vector, the maximum and minimum values of the porosity value, particle morphology index, and swelling mineral content value are taken as the ideal value and the negative ideal value respectively, and the minimum and maximum values of the quartz content value are taken as the ideal value and the negative ideal value respectively; Calculate the degree of closeness of each feature vector to the ideal value and the negative ideal value by calculating the distance; the distance between the feature vector and the ideal value is: , where is the jth evaluation index of the ith sample, is the ideal value of the jth index, and n is the number of evaluation indexes, is the distance between the ith sample and the ideal value; the distance between the feature vector and the negative ideal value is: , where is the negative ideal value of the jth index, is the distance between the ith sample and the negative ideal value; Calculate the relative closeness through the ideal value and the negative ideal value: , where is the relative closeness of the ith loess sample; the greater the relative closeness, the greater the degree of collapsibility reduction of the loess sample; Sort the relative closeness values in descending order, and select the median of the sorted values as the closeness threshold. If the relative closeness is greater than the closeness threshold, it is judged that the degree of collapsibility reduction is high; otherwise, it is judged that the degree of collapsibility reduction is low; When the degree of collapsibility reduction is high, quantitatively analyze the change in collapsibility by calculating the void ratio, and calculate the void ratio through the porosity: , where is the porosity, is the void ratio; Preset the sampling period, subtract the void ratio at the start sampling time from the void ratio at the end sampling time to obtain the change in void ratio; It should be noted that the start time of the preset sampling period is set when the loess sample is not affected by collapsibility, and the end time of the sampling period is set when the void ratio of the loess sample remains unchanged; If the change amount of the void ratio of the loess sample is larger, it indicates that the collapsibility of the loess sample is larger; if the change amount of the void ratio is smaller, it indicates that the collapsibility of the loess sample is smaller; The ratio of the change amount of the void ratio to the void ratio at the start sampling time is used as the degree of collapsibility change.

[0023] Through the TOPSIS method, the evaluation indicators are comprehensively ranked, the proximity threshold is determined by the median, the degree of collapsibility reduction is quantified, and further by calculating the degree of void ratio change, the dynamic quantitative analysis of collapsibility change is realized, which can provide more accurate collapsibility prediction and evaluation, and provide data support for subsequent control measures.

[0024] It should be noted that scanning electron microscopy test is a high-resolution microscope that uses an electron beam to scan the surface of a sample and obtains images and material compositions by analyzing the interaction between the sample and the electron beam; X-ray diffraction is a method that uses the principle of the interaction between X-rays and matter to analyze the crystal structure, mineral composition and phase composition of materials, and infers the properties such as crystal structure, mineral species, and crystal size of the loess sample based on information such as diffraction angle and intensity; the TOPSIS method is a multi-criteria decision analysis method that evaluates the advantages and disadvantages of each sample by the distance from the ideal solution and the negative ideal solution, and finally determines the ranking of the degree of collapsibility reduction.

[0025] In step S4, the preset collapsibility threshold is compared with the degree of collapsibility change. If the degree of collapsibility change is greater than the preset collapsibility threshold, it is judged that the degree of collapsibility change is high; otherwise, it is judged that the degree of collapsibility change is low; When the degree of collapsibility change is high, scanning electron microscopy test analysis is used to verify whether the collapsibility of the loess reaches the expected control target; When the degree of collapsibility change is low, X-ray diffraction analysis is used to verify whether the collapsibility of the loess reaches the expected control target.

[0026] By comparing the preset collapsibility threshold with the quantitative analysis results, a differential analysis and verification mechanism is selected to further confirm whether the loess has reached the expected collapsibility control target and verify the accuracy of the collapsibility evaluation.

[0027] It should be noted that when X-ray diffraction is used for small collapsibility changes, the collapsibility is verified to meet the expected goals and it is confirmed whether the collapsibility change is related to the change in mineral composition by analyzing the change in mineral composition of loess samples, especially the content and type of expansive minerals; scanning electron microscopy testing is used for large collapsibility changes, which can provide high-resolution microscopic structure images, analyze the microscopic morphology of loess, the arrangement of soil particles, pore structure, particle morphology, etc., and evaluate whether the collapsibility reaches the expected control goal by observing the influence of collapsibility changes on microscopic structure characteristics; the preset collapsibility threshold is used to judge the level of collapsibility change, which is specifically set by professionals. For example, the normal range of collapsibility changes in loess samples is statistically analyzed, and a maximum and a minimum change value are set as the standard for collapsibility changes. The method is not unique and will not be elaborated here.

[0028] The above formulas are all dimensionless and take their numerical values for calculation. The formula is obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation.

[0029] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, server or data center to another website, computer, server or data center in a wired or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0030] It should be understood that in various embodiments of the present application, the sequence numbers of the above processes do not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0031] Those of ordinary skill in the art will realize that the units and algorithm steps of each example described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0032] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0033] In several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0034] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0035] In addition, the functional units in each embodiment of this application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0036] When the above-mentioned functions 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 this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This 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 described in various embodiments of this application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0037] As described above, the foregoing are only specific implementation manners of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A method for determining the threshold of eliminating collapsibility of loess by microwave irradiation, characterized in that: It includes the following steps: Step S1: Collect collapsible loess samples and conduct preprocessing to obtain their initial physical information data; Step S2: Set the microwave irradiation experimental conditions based on the initial physical information data of the preprocessed loess samples, calculate the change trend of the collapsibility coefficient of the loess samples under the microwave irradiation experimental conditions, and evaluate whether to use the temperature distribution analysis method to judge the change of the internal structure of the loess according to the change trend of the collapsibility coefficient of the loess; Step S3: When it is judged that the change of the internal structure of the loess is weak, further obtain the microscopic structure characteristics and mineral composition changes of the samples, comprehensively evaluate the degree of reduction of the collapsibility of the loess. If the degree of reduction of the collapsibility is high, introduce the void ratio parameter to quantitatively analyze the change of the collapsibility; Step S4: Select to use scanning electron microscopy test or X-ray diffraction analysis to verify whether the collapsibility of the loess reaches the expected control target according to the quantitative analysis results of the change of the collapsibility.

2. The method for determining the threshold of eliminating the collapsibility of loess by microwave irradiation according to claim 1, wherein: In step S1, the ratio of the difference between the wet soil mass and the dry soil mass to the dry soil mass is defined as the natural water content; Divide the wet soil mass of the density measurement sample by the product of the volume of the density measurement sample and the sum of the natural water content and one to obtain the initial dry density; Based on the mass and temperature changes of the constant temperature water, calculate the heat absorbed by the loess sample to obtain the natural specific heat capacity.

3. The method for determining the threshold of eliminating the collapsibility of loess by microwave irradiation according to claim 2, wherein: In step S2, construct the natural water content, the initial dry density and the natural specific heat capacity as the input vector of the support vector regression method; Use the radial basis kernel function to map the input vector to a high-dimensional feature space, and construct a microwave power prediction model by solving the minimization problem; Solve through the microwave power prediction model to obtain the microwave power; Calculate the total heat absorbed required for the complete evaporation of water in the loess sample as the evaporation energy; Take the minimum deviation between the evaporation energy and the theoretical thermal energy provided by the microwave irradiation as the objective function of the Bayesian optimization method; Construct a posterior probability model through the Gaussian process and select sample points for the objective function based on the expected improvement function, and iterate to converge to the optimal solution, and the optimal solution is the irradiation time.

4. The method for determining the threshold of eliminating the collapsibility of loess by microwave irradiation according to claim 3, wherein: In step S2, measure the collapsibility coefficient of the loess sample in the initial state as the collapsibility coefficient before the experiment; Perform microwave irradiation experimental treatment on the loess sample according to the microwave power and irradiation time; After the microwave irradiation experiment is completed, measure the collapsibility coefficient of the loess sample again as the collapsibility coefficient after the experiment; Calculate the ratio of the collapsibility coefficient before the experiment to the collapsibility coefficient after the experiment; When the ratio of the collapsibility coefficient before the experiment to the collapsibility coefficient after the experiment is less than one, it indicates that the collapsibility is weakened; When the ratio of the collapsibility coefficient before the experiment to the collapsibility coefficient after the experiment is equal to one, it indicates that there is no significant change; When the ratio of the collapsibility coefficient before the experiment to the collapsibility coefficient after the experiment is greater than one, it indicates that the collapsibility is enhanced.

5. The method for determining the threshold of eliminating the collapsibility of loess by microwave irradiation according to claim 4, wherein: In step S2, when the collapsibility is weakened, temperature data of the loess sample during the irradiation process is collected, a two-dimensional temperature spatial distribution matrix is established, and the local temperature variance is calculated. A variance threshold is set, and the local temperature variance is compared with the variance threshold. If the local temperature variance is greater than the variance threshold, it is determined that the internal structure change of the loess is strong. When the local temperature variance is less than the variance threshold, it is determined that the internal structure change of the loess is weak.

6. The method for determining the threshold of eliminating the collapsibility of loess by microwave irradiation according to claim 5, characterized in that: In step S3, when it is determined that the internal structure change of the loess is weak, the microscopic structure characteristics of the loess are obtained, including the volume of the loess sample, the pore volume, the outer perimeter of the loess particles, and the area of the loess particles. The porosity is the ratio of the pore volume to the volume of the loess sample. The particle shape index is calculated through the outer perimeter and the area of the loess particles. The mineral composition of the loess sample is analyzed, including the mass of the swelling minerals, the total mineral content in the loess sample, and the mass of quartz. The ratio of the mass of the swelling minerals to the total mineral content in the loess sample is used as the swelling mineral content value. The ratio of the mass of quartz to the total mineral content in the loess sample is used as the quartz content value.

7. The method for determining the threshold of eliminating the collapsibility of loess by microwave irradiation according to claim 6, characterized in that: In step S3, the degree of reduction of the collapsibility of the loess is comprehensively evaluated by the TOPSIS method based on the microscopic structure characteristics and the change of mineral composition. The porosity value, the particle shape index, the swelling mineral content value, and the quartz content value are normalized and combined into a feature vector. The TOPSIS method calculates the relative closeness of the loess sample through the feature vector. The relative closeness values are sorted in descending order, and the median after sorting is selected as the closeness threshold. If the relative closeness is greater than the closeness threshold, it is judged that the degree of reduction of the collapsibility is high; otherwise, it is judged that the degree of reduction of the collapsibility is low.

8. The method for determining the threshold of eliminating the collapsibility of loess by microwave irradiation according to claim 7, characterized in that: In step S3, when the degree of reduction of the collapsibility is high, the void ratio is further calculated through the porosity to quantitatively analyze the change of the collapsibility. A preset sampling period is set, and the difference between the void ratio at the start sampling time and the void ratio at the end sampling time is obtained to get the change amount of the void ratio. The ratio of the change amount of the void ratio to the void ratio at the start sampling time is used as the degree of change of the collapsibility.

9. The method for determining the threshold of eliminating the collapsibility of loess by microwave irradiation according to claim 8, characterized in that: In step S4, a preset collapsibility threshold is compared with the degree of change of the collapsibility. If the degree of change of the collapsibility is greater than the preset collapsibility threshold, it is judged that the degree of change of the collapsibility is high; otherwise, it is judged that the degree of change of the collapsibility is low. When the degree of change of the collapsibility is high, a scanning electron microscope test analysis is used to verify whether the collapsibility of the loess reaches the expected control target. When the degree of change of the collapsibility is low, an X-ray diffraction analysis is used to verify whether the collapsibility of the loess reaches the expected control target.

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