Bending-tensile strength prediction method based on fracture surface characteristics and porosity

Abstract

The invention discloses a flexural-tensile strength prediction method based on fracture surface characteristics and porosity, and belongs to the technical field of road engineering. The method comprises the following steps: preparing a geopolymer stabilized desert sand test piece; the geopolymer stabilized desert sand test piece is scanned through a laser confocal microscope, a fracture surface roughness parameter index set of the geopolymer stabilized desert sand test piece is obtained, and the fracture surface roughness parameter index set comprises the root mean square height, the fractal dimension, the steepness, the arithmetic mean height of the surface appearance and the core height; evaluating the significance of the fracture surface roughness parameter index set on the flexural-tensile strength based on a grey relational degree method to obtain a target fracture surface roughness parameter index; based on the roughness parameter index of the target fracture surface and the structural porosity, constructing an equation of flexural-tensile strength; and based on the flexural-tensile strength equation, predicting the flexural-tensile strength of the geopolymer-stabilized desert sand. According to the method, the accuracy and reliability of flexural-tensile strength prediction are improved.

Description

Technical Field

[0001] The present application belongs to the technical field of road engineering, and in particular to a method for predicting bending tensile strength based on fracture surface characteristics and porosity. Background Art

[0002] In response to the dual challenges of global climate change and ecological protection, the strategic value of geopolymer building materials as a substitute for cement is becoming increasingly prominent. At present, transportation infrastructure in desert areas faces complex working conditions such as environmental erosion, material degradation and insufficient bearing capacity. The engineering community is working hard to achieve structural performance breakthroughs through innovations in cementitious material systems. Geopolymers, with their strong interfacial bonding properties endowed by their three-dimensional network structure, provide a new path to break through the bottleneck of mechanical properties caused by the smoothness and poor gradation of desert sand particles.

[0003] The existing prediction technology of the flexural tensile strength of geopolymer-stabilized desert sand is mainly based on traditional cementitious material theory, but it still faces significant technical bottlenecks. First, the multi-scale coupling relationship between flexural tensile strength and fracture surface roughness parameters and porosity is difficult to quantitatively model, resulting in limited prediction accuracy of the single parameter regression method. Secondly, the two-dimensional morphology characterization technology cannot reconstruct the topological characteristics of the three-dimensional fracture surface, resulting in excessively high distortion rates in the extraction of key parameters such as steepness and core height. In addition, the empirical model based on standard specimens is difficult to adapt to the on-site heterogeneous sand bodies, and the destructive four-point flexural tensile test requires repeated preparation of specimens. The relevant technologies have problems such as low prediction accuracy of the flexural tensile strength of geopolymer-stabilized desert sand, complex calculations, and high calculation costs. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a method for predicting bending tensile strength based on fracture surface characteristics and porosity, which improves the accuracy and reliability of bending tensile strength prediction.

[0005] In a first aspect, the present application provides a method for predicting flexural tensile strength based on fracture surface characteristics and porosity, the method comprising: Preparation of geopolymer-stabilized desert sand specimens; Scanning the geopolymer-stabilized desert sand specimen by laser confocal microscopy to obtain a fracture surface roughness parameter index set of the geopolymer-stabilized desert sand specimen, wherein the fracture surface roughness parameter index set includes root mean square height, fractal dimension, steepness, arithmetic mean height of surface morphology and core height; The significance of the fracture surface roughness parameter index set on the bending tensile strength was evaluated based on the grey correlation method, and the target fracture surface roughness parameter index was obtained. Based on the target fracture surface roughness parameter index and structural porosity, the equation of flexural tensile strength is constructed; Based on the flexural-tensile strength equation, the flexural-tensile strength of geopolymer-stabilized desert sand is predicted.

[0006] According to an embodiment of the present application, the gray correlation method is used to evaluate the significance of the fracture surface roughness parameter index set on the bending tensile strength to obtain the target fracture surface roughness parameter index, including: The grey correlation degree between each index in the fracture surface roughness parameter index set and the bending tensile strength is calculated based on the grey correlation degree formula, and the grey correlation degree set is obtained; Sorting all the indicators in the fracture surface roughness parameter indicator set from large to small according to the grey correlation degree; The first index in the fracture surface roughness parameter index set is used as the target fracture surface roughness parameter index.

[0007] According to one embodiment of the present application, the calculation formula of the grey relational degree is as follows:

[0008] in, is the grey relational degree, is the grey correlation coefficient between the reference sequence and the comparison sequence, is the data volume of the reference sequence.

[0009] According to one embodiment of the present application, the geopolymer-stabilized desert sand specimen is scanned by a laser confocal microscope to obtain a fracture surface roughness parameter index set of the geopolymer-stabilized desert sand specimen, including: The geopolymer-stabilized desert sand specimen was scanned by laser confocal microscopy to obtain the three-dimensional data points of the geopolymer-stabilized desert sand specimen. ; For the three-dimensional data points Perform three-dimensional reconstruction to obtain laser confocal images of geopolymer-stabilized desert sand; Based on the laser confocal image, a set of indexes of fracture surface roughness parameters of the geopolymer-stabilized desert sand specimen is calculated.

[0010] According to one embodiment of the present application, the calculation formula of the bending tensile strength equation is as follows:

[0011] Among them, F is the flexural strength, S is the target fracture surface roughness parameter index, and P is the structural porosity.

[0012] According to an embodiment of the present application, the fractal dimension is calculated using the box dimension method, and the calculation formula is as follows:

[0013] Where D is the fractal dimension, is the minimum number of boxes required to cover the set each time, is the side length of the box.

[0014] According to one embodiment of the present application, the geopolymer-stabilized desert sand specimen includes geopolymer and desert sand, and the geopolymer includes fly ash, slag and an activator.

[0015] In a second aspect, the present application provides a device for predicting bending tensile strength based on fracture surface characteristics and porosity, the device comprising: Fabrication module for making geopolymer-stabilized desert sand specimens; The first processing module is used to scan the geopolymer-stabilized desert sand specimen through a laser confocal microscope to obtain a fracture surface roughness parameter index set of the geopolymer-stabilized desert sand specimen, wherein the fracture surface roughness parameter index set includes root mean square height, fractal dimension, steepness, arithmetic mean height of surface morphology and core height; The second processing module is used to evaluate the significance of the fracture surface roughness parameter index set on the bending tensile strength based on the grey correlation method to obtain the target fracture surface roughness parameter index; A construction module for constructing an equation for flexural strength based on target fracture surface roughness parameter index and structural porosity; A prediction module is used to predict the flexural tensile strength of geopolymer-stabilized desert sand based on the flexural tensile strength equation.

[0016] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for predicting bending tensile strength based on fracture surface characteristics and porosity as described in the first aspect above is implemented.

[0017] In a fourth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for predicting flexural strength based on fracture surface characteristics and porosity as described in the first aspect above.

[0018] In a fifth aspect, the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the bending tensile strength prediction method based on fracture surface characteristics and porosity as described in the first aspect.

[0019] In a sixth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the method for predicting flexural strength based on fracture surface characteristics and porosity as described in the first aspect above.

[0020] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application.

[0021] The present invention provides a method for predicting flexural tensile strength based on fracture surface characteristics and porosity, which has the following beneficial effects compared with the prior art: (1) The present invention obtains a set of fracture surface roughness parameter indices by scanning geopolymer-stabilized desert sand specimens based on a laser confocal microscope, and evaluates the significance of fracture surface roughness parameters on flexural strength using a grey correlation method. This method can more accurately predict the flexural strength of geopolymer-stabilized desert sand, reduce repeated testing and experimental costs, and improve the accuracy and efficiency of flexural strength prediction by evaluating and modeling key parameters, while reducing the calculation cost and complexity of flexural strength.

[0022] (2) The present invention calculates the grey correlation between each index in the fracture surface roughness parameter index set and the bending tensile strength based on the grey correlation formula, sorts the indexes from large to small according to the grey correlation, and selects the index with the highest ranking as the target fracture surface roughness parameter index. The relationship between each fracture surface roughness parameter and the bending tensile strength can be effectively evaluated, the accuracy and efficiency of the bending tensile strength prediction are improved, and the calculation cost and complexity of the bending tensile strength are reduced.

[0023] (3) The present invention constructs an equation through the target fracture surface roughness parameter index and the structural porosity to obtain the predicted value of the flexural strength, which reveals the intrinsic mechanism of geopolymer-stabilized desert sand from a microscopic perspective, realizes the prediction of flexural strength, and improves the reliability of the mechanical property evaluation of geopolymer-stabilized desert sand. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which: Figure 1 It is a schematic flow chart of a method for predicting bending tensile strength based on fracture surface characteristics and porosity provided in an embodiment of the present application; Figure 2 It is a laser confocal scanning image of oligomer-stabilized desert sand at different ratios provided in the examples of the present application; Figure 3 is a schematic diagram of the arithmetic mean height of the fracture surface provided in the embodiment of the present application; Figure 4 It is a schematic diagram of fractal dimensions under different mix ratios provided in the embodiments of the present application; Figure 5 It is a schematic structural diagram of a bending tensile strength prediction device based on fracture surface characteristics and porosity provided in an embodiment of the present application; Figure 6It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0026] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0027] In combination with the accompanying drawings, the flexural tensile strength prediction method based on fracture surface characteristics and porosity, the flexural tensile strength prediction device based on fracture surface characteristics and porosity, the electronic device and the readable storage medium provided in the embodiments of the present application are described in detail through specific embodiments and their application scenarios.

[0028] Among them, the bending tensile strength prediction method based on fracture surface characteristics and porosity can be applied to the terminal, and can be specifically executed by hardware or software in the terminal.

[0029] The terminal includes, but is not limited to, a portable communication device such as a mobile phone or a tablet computer having a touch-sensitive surface (e.g., a touch screen display and / or a touch pad). It should also be understood that in some embodiments, the terminal may not be a portable communication device, but a desktop computer having a touch-sensitive surface (e.g., a touch screen display and / or a touch pad).

[0030] In the following various embodiments, a terminal including a display and a touch-sensitive surface is described. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, a mouse and a joystick.

[0031] The embodiment of the present application provides a method for predicting bending-tensile strength based on fracture surface characteristics and porosity. The execution subject of the method can be an electronic device or a functional module or functional entity in the electronic device that can implement the method for predicting bending-tensile strength based on fracture surface characteristics and porosity. The electronic devices mentioned in the embodiment of the present application include but are not limited to mobile phones, tablet computers, computers, cameras, and wearable devices. The method for predicting bending-tensile strength based on fracture surface characteristics and porosity provided in the embodiment of the present application is described below using an electronic device as an example of the execution subject.

[0032] In traditional water-stable base, river sand and cement are the main raw materials. Among them, the high energy consumption and high emissions in the production process of cement not only consume fossil fuels, but also release a large amount of carbon dioxide, which is one of the main sources of greenhouse gas emissions. Geopolymer is a green cementitious material with excellent properties such as high strength, fire resistance and frost resistance formed by alkali-activated industrial waste tailings such as metakaolin, fly ash and slag. It has the potential to replace cement on a large scale. Its wide application in the field of civil engineering can not only consume a large amount of silicate solid waste, but also help to cope with global climate change and complete the task of greenhouse gas emission reduction. On the other hand, the large-scale mining of river sand has brought serious negative impacts on the environment, including the destruction of ecosystems, water pollution and unstable river channel structure. Therefore, seeking environmentally friendly substitutes for river sand and applying them in civil engineering has become a current research hotspot. At the same time, due to the characteristics of desert sand such as smooth particles and poor grading, its adhesion with cement is poor, resulting in a low replacement rate of desert sand in ordinary silicate concrete. Geopolymers can provide stronger bonding force due to their special three-dimensional network structure. Therefore, using geopolymers as bonding materials to stabilize desert sand and apply them to pavement structures can not only significantly reduce the use of cement and reduce carbon emissions, but also effectively solve the problems of low utilization rate of desert sand resources and high dependence on river sand resources, thereby achieving comprehensive and high-value utilization of solid waste resources.

[0033] In order to better understand the changes in the mechanical properties of geopolymer-stabilized desert sand pavement base, it is first necessary to clarify the response of the pavement base under external loads, temperature changes and environmental influences. With the continuous increase in traffic volume in desert areas, traditional pavement materials are gradually unable to meet the requirements of bearing capacity, durability and stability. Geopolymer materials have become a potential choice for improving the performance of pavement bases in desert areas due to their excellent strength, durability and environmental adaptability. In the study of geopolymer-stabilized sand, the mechanical properties are usually affected by factors such as the morphology and contact characteristics of sand particles and the microstructure formed after the geopolymer condenses. In particular, the fracture surface characteristics and roughness of the material play an important role in the performance of mechanical properties. Therefore, how to accurately evaluate the changes in the mechanical properties of geopolymer-stabilized desert sand through the quantitative analysis of the fracture surface characteristic roughness parameters has become one of the focuses of current research.

[0034] Existing research mainly focuses on the macroscopic mechanical properties of materials, such as compressive strength and tensile strength, but at the microscopic level, especially the influence of fracture surface characteristic roughness parameter indicators on mechanical properties has not been fully explored, and there is a problem of low accuracy in predicting the flexural and tensile strength of geopolymer-stabilized desert sand.

[0035] Figure 1 is a flow chart of a method for predicting bending tensile strength based on fracture surface characteristics and porosity provided in an embodiment of the present application, such as Figure 1 As shown, the method for predicting bending tensile strength based on fracture surface characteristics and porosity includes: step 110, step 120, step 130, step 140 and step 150.

[0036] Step 110, preparing a geopolymer-stabilized desert sand specimen; In some embodiments, the geopolymer-stabilized desert sand specimen is a geopolymer-desert sand mixture, which is prepared by mixing desert sand as aggregate and geopolymer as binder.

[0037] Step 120, scanning the geopolymer-stabilized desert sand specimen by laser confocal microscopy to obtain a fracture surface roughness parameter index set of the geopolymer-stabilized desert sand specimen, wherein the fracture surface roughness parameter index set includes root mean square height, fractal dimension, steepness, arithmetic mean height of surface morphology, and core height; It is easy to understand that in order to quantify the surface roughness of geopolymer-stabilized desert sand specimens, the roughness parameters calculated through the fracture surface morphology information can reflect the morphology of the geopolymer-stabilized desert sand surface, and these roughness parameters will affect the global characteristics of the geopolymer-stabilized desert sand surface morphology.

[0038] In some embodiments, the scanning of the geopolymer-stabilized desert sand specimen by a laser confocal microscope to obtain a fracture surface roughness parameter index set of the geopolymer-stabilized desert sand specimen includes: The geopolymer-stabilized desert sand specimen was scanned by laser confocal microscopy to obtain the three-dimensional data points of the geopolymer-stabilized desert sand specimen. ; For the three-dimensional data points Perform three-dimensional reconstruction to obtain laser confocal images of geopolymer-stabilized desert sand; Based on the laser confocal image, a set of indexes of fracture surface roughness parameters of the geopolymer-stabilized desert sand specimen is calculated.

[0039] For example, the fracture surface of the geopolymer-stabilized desert sand specimen is scanned by laser confocal microscopy to obtain three-dimensional data points of the fracture surface. , the three-dimensional data points of the fracture surface were reconstructed to obtain the laser confocal image of the geopolymer-stabilized desert sand, Figure 2 : are laser confocal scanning images of oligomer-stabilized desert sand at different ratios provided in the examples of the present application, such as Figure 2 As shown, the fracture surface roughness parameter index set is obtained by calculating the three-dimensional data points of the fracture surface.

[0040] The steepness parameter is used to evaluate the sharpness of the height distribution and is related to the geometry of the peaks and valleys. The calculation formula for steepness is as follows:

[0041] Among them, Sku is the steepness, A is the surface area of ​​the fracture surface, Z(x,y) is the target area, and Sq is the root mean square height.

[0042] The core height parameter is the distance between the upper and lower levels of the core surface of the fracture surface.

[0043] The root mean square height parameter is the root mean square value of Z(x,y) in the target area. The calculation formula of the root mean square height is as follows:

[0044] Figure 3 is a schematic diagram of the arithmetic mean height of the fracture surface provided in the embodiment of the present application, such as Figure 3 As shown, the arithmetic mean height parameter of the surface topography is the arithmetic mean of the absolute coordinates in the target area, and the calculation formula of the arithmetic mean height of the surface topography is as follows;

[0045] Where Sa is the arithmetic mean height of the surface topography.

[0046] In this embodiment, a laser confocal microscope is used to scan a geopolymer-stabilized desert sand specimen, obtain three-dimensional data points, and perform three-dimensional reconstruction to obtain a laser confocal image of the geopolymer-stabilized desert sand. A fracture surface roughness parameter index set is calculated based on the image, which can characterize the microscopic fracture characteristics of the geopolymer-stabilized desert sand. The accuracy of the fracture surface roughness analysis of the geopolymer-stabilized desert sand specimen is improved.

[0047] Step 130: Evaluate the significance of the fracture surface roughness parameter index set on the bending tensile strength based on the grey correlation method to obtain the target fracture surface roughness parameter index; It is worth noting that different roughness parameters may have different results in quantifying the surface roughness of geopolymer-stabilized desert sand. The significance of the fracture surface roughness parameter index set on the flexural strength was evaluated by the grey correlation method, and the index with the strongest significance on the flexural strength was taken as the target fracture surface roughness parameter index.

[0048] In some embodiments, a three-point bending beam test is used to fracture the test surface to obtain a bending tensile strength index. The calculation formula of the bending tensile strength is as follows:

[0049] Among them, F is the bending tensile strength, q is the ultimate load, L is the span, b is the specimen width, and h is the specimen height.

[0050] Step 140: constructing an equation for flexural strength based on the target fracture surface roughness parameter index and the structural porosity; In some embodiments, the target fracture surface roughness parameter index is the root mean square height, and the equation of flexural strength is constructed by the root mean square height and the structural porosity. The relationship between the root mean square height, porosity and flexural strength is obtained through experiments and obeys the equation .

[0051] Step 150: Based on the flexural-tensile strength equation, predict the flexural-tensile strength of the geopolymer-stabilized desert sand.

[0052] According to the flexural tensile strength prediction method based on fracture surface characteristics and porosity provided in the embodiments of the present application, a set of fracture surface roughness parameter indicators is obtained by scanning the geopolymer-stabilized desert sand specimen based on a laser confocal microscope, and the significance of the fracture surface roughness parameters on the flexural tensile strength is evaluated in combination with the grey correlation method. The flexural tensile strength of the geopolymer-stabilized desert sand can be predicted more accurately, reducing repeated testing and experimental costs. By evaluating and modeling key parameters, the accuracy and efficiency of the flexural tensile strength prediction are improved, and the calculation cost and complexity of the flexural tensile strength are reduced.

[0053] In some embodiments, the gray correlation method is used to evaluate the significance of the fracture surface roughness parameter index set on the bending tensile strength to obtain the target fracture surface roughness parameter index, including: The grey correlation degree between each index in the fracture surface roughness parameter index set and the bending tensile strength is calculated based on the grey correlation degree formula, and the grey correlation degree set is obtained; Sorting all the indicators in the fracture surface roughness parameter indicator set from large to small according to the grey correlation degree; The first index in the fracture surface roughness parameter index set is used as the target fracture surface roughness parameter index.

[0054] It is easy to understand that the grey correlation method screens out the key factors that have the greatest impact on the reference sequence by comparing the correlation between the reference sequence and the comparison sequence and sorting them.

[0055] In some embodiments, the flexural tensile strength of geopolymer-stabilized desert sand is used as a reference sequence, and the root mean square height, fractal dimension, steepness, arithmetic mean height of surface morphology and core height are used as comparison sequences, and the grey correlation degree of each comparison sequence and the reference sequence is calculated. The calculation process is as follows: (1) Define sequence , determine the parameter sequence and compare sequences .

[0056] (2) Normalization. Since the dimensions (units, properties) of the original data of each series are different, the original data are dimensionlessly processed by averaging. The calculation formula for averaging is as follows:

[0057] (3) Calculate the absolute value difference. Calculate the absolute value difference between the reference sequence and the comparison sequence in the same period. The calculation formula is as follows:

[0058] (4) Determine the maximum and minimum values, compare the values ​​of all absolute value differences, and determine the maximum and minimum absolute value differences. The calculation formula is as follows:

[0059]

[0060] (5) Calculate the grey correlation coefficient between the reference sequence and the comparison sequence. The calculation formula is as follows:

[0061] (6) In some embodiments, the calculation formula of the grey relational degree is as follows:

[0062] in, is the grey relational degree, is the grey correlation coefficient between the reference sequence and the comparison sequence, is the data volume of the reference sequence.

[0063] Exemplarily, the calculation results obtained by the grey correlation method are shown in Table 1, and the significance ranking is root mean square height > arithmetic mean height > core height > steepness > fractal dimension. It can be seen from Table 1 that the root mean square height is the most significant indicator affecting the flexural strength.

[0064] Table 1

[0065] In this embodiment, the grey correlation degree is obtained by using the grey correlation calculation formula to screen out the key factors that have the greatest impact on the reference sequence, which can more effectively evaluate the impact of different factors on the flexural tensile strength of geopolymer-stabilized desert sand, improve the accuracy of flexural tensile strength prediction, and reduce the number and cost of experiments.

[0066] For example, a MesoMR23-060V-1 nuclear magnetic resonance analysis device may be used to test the porosity of a specimen.

[0067] In this embodiment, the grey correlation between each index in the fracture surface roughness parameter index set and the bending tensile strength is calculated based on the grey correlation formula, and the indexes are sorted from large to small according to the grey correlation, and the index with the highest ranking is selected as the target fracture surface roughness parameter index. The relationship between each fracture surface roughness parameter and the bending tensile strength can be effectively evaluated, the accuracy and efficiency of the bending tensile strength prediction are improved, and the calculation cost and complexity of the bending tensile strength are reduced.

[0068] In some embodiments, the calculation formula of the bending tensile strength equation is as follows:

[0069] Among them, F is the flexural strength, S is the target fracture surface roughness parameter index, and P is the structural porosity.

[0070] In some embodiments, Table 2 shows the changes in the roughness parameter index and porosity of the fracture surface of geopolymer-stabilized desert sand under different ratios provided in the embodiments of the present application. As shown in Table 2, as the ratio changes from GDS (Geopolymerstabilized Desert Sand, geopolymer-stabilized desert sand) 3.0 to GDS9.0, the root mean square height, arithmetic mean height, core height, steepness, fractal dimension and bending tensile strength show a positive correlation trend, while the porosity and bending tensile strength show a negative correlation. Therefore, it can be obtained that the larger the roughness parameter index value and the smaller the porosity, the stronger the mechanical properties. This rough surface can increase the locking effect between the particles inside the specimen and improve the overall strength of the material. At the same time, the rough fracture surface has more microscopic toughness characteristics, such as crack bifurcation, competitive expansion of multiple crack paths, etc. This complex fracture path may disperse stress concentration, thereby delaying the penetration of cracks. In addition, more energy is required to maintain the expansion of cracks. This high energy dissipation process means that the material can withstand a larger load and ultimately show a higher strength. However, higher porosity reduces the density of the structure, causing the number of clusters to gradually decrease, the structure to become gradually loose, and the flexural strength to decrease.

[0071] Table 2

[0072] For example, based on the selection of the roughness parameter index that most significantly affects the mechanical properties of the bending tensile strength, the porosity P of the mixture is further combined with the linear regression equation to jointly construct a relationship between the porosity and the surface morphology characteristics to reflect the bending tensile strength. The target fracture surface roughness parameter index, porosity and bending tensile strength are calculated to satisfy the following equation: .

[0073] In this embodiment, an equation is constructed by using the target fracture surface roughness parameter index and the structural porosity to obtain a predicted value of the flexural tensile strength, which reveals the intrinsic mechanism of geopolymer-stabilized desert sand from a microscopic perspective, achieves the prediction of flexural tensile strength, and improves the reliability of the mechanical property evaluation of geopolymer-stabilized desert sand.

[0074] In some embodiments, the fractal dimension is calculated using the box dimension method, and the calculation formula is as follows:

[0075] Where D is the fractal dimension, is the minimum number of boxes required to cover the set each time, is the side length of the box. It should be noted that the fractal behavior exhibited by the fracture surface can be quantified by the box counting method, and the box dimension is calculated based on the three-dimensional box covering method: Assuming a cube with a side length of δ, its side length can be defined as: , , , Then, the fracture surface is measured with a cubic box with a side length of δ. There are N (δ) cubic boxes on the fracture surface. The total number of cubic boxes N ( The relationship between ) and the side length δ can be expressed by the following formula:

[0076] in, is the number of covered cubes, is the side length of the box, D is the fractal dimension, is the minimum number of boxes required to cover the set each time.

[0077] The number of covered cubes is calculated as follows:

[0078] in, is the integral function, is the relative height of the difference point.

[0079] Figure 4 Schematic diagram of fractal dimensions under different mix ratios provided in the embodiments of the present application, such as Figure 4As shown in the figure, the fractal dimensions of 5 groups of mix ratios are obtained by fitting calculation. The calculation formula of the fractal dimension is as follows:

[0080] In this embodiment, the fractal dimension is calculated by the box dimension method. By analyzing the fractal characteristics of geopolymer-stabilized desert sand, the influence of its microstructure on the flexural strength can be more accurately revealed, thereby improving the accuracy of flexural strength prediction.

[0081] In some embodiments, the geopolymer-stabilized desert sand specimen includes geopolymer and desert sand, wherein the geopolymer includes fly ash, slag, and an activator.

[0082] In some embodiments, low-calcium fly ash and blast furnace slag are used to prepare geopolymers through alkali activation, industrial sodium hydroxide, water glass and deionized water are used to prepare alkaline activators, Kubuqi Desert is used as fine aggregate, and the fly ash-slag (1:1) and desert sand mass ratios of 1:3.0, 1:4.5, 1:6.0, 1:7.5 and 1:9.0 are selected for the design of the test scheme. The mix design is shown in Table 3. The compaction test is used to determine the optimal moisture content of the desert sand-fly ash-slag raw materials, and the GDS base specimens are prepared on this basis. Sodium hydroxide is added to water glass, the modulus is adjusted to 1.4, and deionized water is added to adjust the concentration to 70%. After the activator and desert sand were mixed and simmered for 2 hours, the desert sand was mixed with fly ash and slag according to the mix ratio design in Table 3. After being mixed evenly with a mortar mixer, it was injected into a 40mm×40mm×160mm mold for compaction and molding. After standing for 4 hours and demoulding, it was cured for 7 days. After the curing, the sample was saturated with water for 24 hours using a vacuum water saturation instrument. The sample porosity was tested using a MesoMR23-060V-1 nuclear magnetic resonance analysis system. After the test, the sample was fractured in a three-point bending form so that two samples of about 1 cm in length were obtained from the fractured sample for microscopic analysis. Using an OLS5100 laser confocal microscope, the research area L×M=2560μm×2571μm was selected from the bottom of the surface depression to the top of the surface protrusion to obtain image slices, and then the commercial software of the confocal microscope OLS5100 laser confocal microscope was used to perform contour and roughness surface analysis on the fracture surface and obtain a roughness parameter index set.

[0083] The calculation formula for the adjusted modulus of the alkaline activator solution is as follows:

[0084] in, is the original modulus of the water glass solution when it leaves the factory, M is the target modulus of the water glass solution, is the mass percentage of sodium oxide contained in the initial water glass solution, It is the mass of sodium hydroxide required to adjust the initial water glass solution to the target modulus per 100 grams.

[0085] Table 3

[0086] In this embodiment, the geopolymer material is prepared by combining fly ash, slag and an activator, which has good mechanical properties and durability, can effectively improve the compressive strength and corrosion resistance of concrete, promote the application of environmentally friendly building materials, help reduce dependence on traditional cement, and reduce carbon emissions.

[0087] The bending tensile strength prediction method based on fracture surface characteristics and porosity provided in the embodiment of the present application can be executed by a bending tensile strength prediction device based on fracture surface characteristics and porosity. In the embodiment of the present application, the bending tensile strength prediction method based on fracture surface characteristics and porosity is executed by a bending tensile strength prediction device based on fracture surface characteristics and porosity as an example to illustrate the bending tensile strength prediction device based on fracture surface characteristics and porosity provided in the embodiment of the present application.

[0088] The present application also provides a device for predicting bending tensile strength based on fracture surface characteristics and porosity. Figure 5 As shown, the bending tensile strength prediction device based on fracture surface characteristics and porosity includes: a manufacturing module 510, a first processing module 520, a second processing module 530, a construction module 540 and a prediction module 550.

[0089] A manufacturing module 510 is used to manufacture a geopolymer-stabilized desert sand specimen; The first processing module 520 is used to scan the geopolymer-stabilized desert sand specimen through a laser confocal microscope to obtain a fracture surface roughness parameter index set of the geopolymer-stabilized desert sand specimen, wherein the fracture surface roughness parameter index set includes root mean square height, fractal dimension, steepness, arithmetic mean height of surface morphology and core height; The second processing module 530 is used to evaluate the significance of the fracture surface roughness parameter index set on the bending tensile strength based on the grey correlation method to obtain the target fracture surface roughness parameter index; A construction module 540 is used to construct an equation for bending tensile strength based on a target fracture surface roughness parameter index and a structural porosity; The prediction module 550 is used to predict the flexural tensile strength of the geopolymer-stabilized desert sand based on the flexural tensile strength equation.

[0090] According to the flexural tensile strength prediction method based on fracture surface characteristics and porosity provided in the embodiments of the present application, a set of fracture surface roughness parameter indicators is obtained by scanning the geopolymer-stabilized desert sand specimen based on a laser confocal microscope, and the significance of the fracture surface roughness parameters on the flexural tensile strength is evaluated in combination with the grey correlation method. The flexural tensile strength of the geopolymer-stabilized desert sand can be predicted more accurately, reducing repeated testing and experimental costs. By evaluating and modeling key parameters, the accuracy and efficiency of the flexural tensile strength prediction are improved, and the calculation cost and complexity of the flexural tensile strength are reduced.

[0091] The bending tensile strength prediction device based on fracture surface characteristics and porosity provided in the embodiment of the present application can achieve Figures 1 to 4 To avoid repetition, the various processes implemented in the embodiment of the method for predicting flexural tensile strength based on fracture surface characteristics and porosity are not described here.

[0092] In some embodiments, Figure 6 As shown, an embodiment of the present application also provides an electronic device 600, including a processor 601, a memory 602, and a computer program stored in the memory 602 and executable on the processor 601. When the program is executed by the processor 601, each process of the embodiment of the bending tensile strength prediction method based on fracture surface characteristics and porosity is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0093] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0094] An embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned embodiment of the method for predicting bending tensile strength based on fracture surface characteristics and porosity are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0095] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0096] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the above-mentioned method for predicting bending tensile strength based on fracture surface characteristics and porosity.

[0097] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0098] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, which are coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-mentioned embodiment of the bending tensile strength prediction method based on fracture surface characteristics and porosity, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0099] It should be understood that the chip mentioned in the embodiments of the present application may also be referred to as a device-level chip, a device chip, a chip device, or an on-chip device chip, etc.

[0100] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0101] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, disk, CD), including a number of instructions for a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the bending tensile strength prediction method based on fracture surface characteristics and porosity of each embodiment of the present application.

[0102] In the description of this application, "first feature" or "second feature" may include one or more of the features.

[0103] In the description of the present application, “plurality” means two or more.

[0104] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0105] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0106] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A method for predicting flexural tensile strength based on fracture surface characteristics and porosity, characterized in that: The method comprises: Preparation of geopolymer-stabilized desert sand specimens; Scanning the geopolymer-stabilized desert sand specimen by laser confocal microscopy to obtain a fracture surface roughness parameter index set of the geopolymer-stabilized desert sand specimen, wherein the fracture surface roughness parameter index set includes root mean square height, fractal dimension, steepness, arithmetic mean height of surface morphology and core height; The significance of the fracture surface roughness parameter index set on the bending tensile strength was evaluated based on the grey correlation method, and the target fracture surface roughness parameter index was obtained. Based on the target fracture surface roughness parameter index and structural porosity, the equation of flexural tensile strength is constructed; Based on the flexural-tensile strength equation, the flexural-tensile strength of geopolymer-stabilized desert sand is predicted.

2. The method for predicting flexural tensile strength based on fracture surface characteristics and porosity according to claim 1, characterized in that: The gray correlation method is used to evaluate the significance of the fracture surface roughness parameter index set on the bending tensile strength, and obtain the target fracture surface roughness parameter index, including: The grey correlation degree between each index in the fracture surface roughness parameter index set and the bending tensile strength is calculated based on the grey correlation degree formula, and the grey correlation degree set is obtained; Sorting all the indicators in the fracture surface roughness parameter indicator set from large to small according to the grey correlation degree; The first index in the fracture surface roughness parameter index set is used as the target fracture surface roughness parameter index.

3. The method for predicting flexural tensile strength based on fracture surface characteristics and porosity according to claim 2, characterized in that: The calculation formula of the grey relational degree is as follows: ； in, is the grey relational degree, is the grey correlation coefficient between the reference sequence and the comparison sequence, is the data volume of the reference sequence.

4. The method for predicting flexural tensile strength based on fracture surface characteristics and porosity according to claim 1, characterized in that: The geopolymer-stabilized desert sand specimen is scanned by a laser confocal microscope to obtain a fracture surface roughness parameter index set of the geopolymer-stabilized desert sand specimen, including: The geopolymer-stabilized desert sand specimen was scanned by laser confocal microscopy to obtain the three-dimensional data points of the geopolymer-stabilized desert sand specimen. ; For the three-dimensional data points Perform three-dimensional reconstruction to obtain laser confocal images of geopolymer-stabilized desert sand; Based on the laser confocal image, a set of indexes of fracture surface roughness parameters of the geopolymer-stabilized desert sand specimen is calculated.

5. The method for predicting flexural tensile strength based on fracture surface characteristics and porosity according to claim 1, characterized in that: The calculation formula of the flexural strength equation is as follows: ； Among them, F is the flexural strength, S is the target fracture surface roughness parameter index, and P is the structural porosity.

6. The method for predicting flexural tensile strength based on fracture surface characteristics and porosity according to claim 1, characterized in that: The fractal dimension is calculated using the box dimension method, and the calculation formula is as follows: ； Where D is the fractal dimension, is the minimum number of boxes required to cover the set each time, is the side length of the box.

7. The method for predicting flexural tensile strength based on fracture surface characteristics and porosity according to claim 1, characterized in that: The geopolymer-stabilized desert sand specimen comprises geopolymer and desert sand, wherein the geopolymer comprises fly ash, slag and an activator.

8. A device for predicting flexural tensile strength based on fracture surface characteristics and porosity, implemented by the method for predicting flexural tensile strength based on fracture surface characteristics and porosity according to any one of claims 1 to 7, characterized in that: The device comprises: Fabrication module for making geopolymer-stabilized desert sand specimens; The first processing module is used to scan the geopolymer-stabilized desert sand specimen through a laser confocal microscope to obtain a fracture surface roughness parameter index set of the geopolymer-stabilized desert sand specimen, wherein the fracture surface roughness parameter index set includes root mean square height, fractal dimension, steepness, arithmetic mean height of surface morphology and core height; The second processing module is used to evaluate the significance of the fracture surface roughness parameter index set on the bending tensile strength based on the grey correlation method to obtain the target fracture surface roughness parameter index; A construction module for constructing an equation for flexural strength based on target fracture surface roughness parameter index and structural porosity; A prediction module is used to predict the flexural tensile strength of geopolymer-stabilized desert sand based on the flexural tensile strength equation.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the bending tensile strength prediction method based on fracture surface characteristics and porosity as described in any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for predicting flexural tensile strength based on fracture surface characteristics and porosity as described in any one of claims 1 to 7 is implemented.

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