Performance optimization method of self-compacting ultra-high performance concrete based on rheological parameter regulation

Abstract

The present application relates to the technical field of high-performance cement-based material preparation and process control, and particularly relates to a self-compacting ultra-high performance concrete performance optimization method based on rheological parameter regulation. The steps are as follows: steel fibers are added to self-compacting ultra-high performance concrete slurry with rheological parameters in a set range to prepare test pieces, X-ray CT technology is used to perform three-dimensional reconstruction on the test pieces after curing, steel fiber distribution parameters are extracted, and crack propagation morphology and strain field distribution data are collected; an interface homogeneity index related to the steel fiber distribution parameters, crack propagation morphology and strain field distribution data is constructed, and X-ray CT technology is used to perform interface densification analysis; a function mapping relationship between the rheological parameters and the interface microstructure is constructed to determine the value range of the optimal yield stress and plastic viscosity. The above method is used to realize performance optimization in the self-compacting ultra-high performance concrete preparation stage.

Description

Technical Field

[0001] This invention relates to the field of high-performance cement-based material preparation and process control technology, and in particular to a method for optimizing the performance of self-compacting ultra-high-performance concrete based on rheological parameter regulation. Background Technology

[0002] Self-Compacting Ultra-High Performance Concrete (SC-UHPC) is a composite cementitious material that combines high strength, high fluidity, and high density. During the molding process, this material relies on its own gravity to fill the formwork and form the interfaces, achieving uniform and dense structural molding without external vibration. This material offers significant advantages in the construction and molding of precast components, complex structural formwork, and high-density reinforced components. The core of SC-UHPC lies in the rheological behavior of the slurry; its yield stress and plastic viscosity directly determine the equilibrium state of the slurry during flow, filling, and fiber dispersion. When rheological parameters are not properly controlled, phenomena such as disordered fiber orientation, aggregate settling, or air bubble retention may occur, leading to insufficient local structural density and interfacial discontinuity, thus affecting the material's consistency and molding quality. Therefore, how to scientifically control rheological properties during the preparation stage to achieve uniform slurry dispersion and intact interfacial structure has become a crucial technical issue for improving the performance stability of SC-UHPC materials.

[0003] Existing research primarily focuses on the mix design and service life performance of SC-UHPC materials, with insufficient attention paid to the impact of rheological parameters on interfacial structure during the preparation stage. Some processes rely solely on empirical methods to control flowability or spread, failing to reflect the combined effects of slurry micro-flow behavior on fiber distribution, bubble dissipation, and interfacial densification. Furthermore, current rheological control methods largely emphasize macroscopic construction performance (such as flowability and spread time), lacking quantitative characterization techniques that link rheological parameters to interfacial homogeneity, pore structure, and micro-strain distribution. Since the interfacial transition zone (ITZ) and fiber-matrix bonding region play a crucial role in SC-UHPC, the quality of interface formation during the preparation stage directly determines the material's ductility, fracture toughness, and long-term service life. Current SC-UHPC research suffers from uncontrollable interfacial structure, lack of homogeneity evaluation, and inadequate performance feedback during the preparation stage. Therefore, it is necessary to establish a performance optimization method for self-compacting ultra-high performance concrete based on rheological parameter control, achieving controllability and quantification from material design to molding quality during the preparation stage. Summary of the Invention

[0004] The purpose of this invention is to provide a method for optimizing the performance of self-compacting ultra-high performance concrete based on the regulation of rheological parameters, which solves the problems of inaccurate control of rheological parameters, uneven distribution of steel fibers, and unstable interface molding quality in the existing SC-UHPC during the preparation stage. This method improves the interface homogeneity and optimizes the mechanical properties of the material during the molding stage, thereby enhancing the controllability and consistency of the SC-UHPC preparation process.

[0005] To achieve the above objectives, this invention provides a method for optimizing the performance of self-compacting ultra-high performance concrete based on rheological parameter control, the specific steps of which are as follows: Step S1: Test the rheological parameters of the self-compacting ultra-high performance concrete paste using a rheometer. The rheological parameters include yield stress and plastic viscosity. Adjust the water-cement ratio and water-reducing agent dosage to control the rheological parameters of the self-compacting ultra-high performance concrete paste within the set range. Step S2: Steel fibers are added to the self-compacting ultra-high performance concrete slurry with rheological parameters within the set range by step feeding and mechanical mixing to prepare self-compacting ultra-high performance concrete specimens, and then they are cured. Step S3: Use X-ray CT technology to perform three-dimensional reconstruction of the self-compacting ultra-high performance concrete specimen after curing, and extract steel fiber distribution parameters based on the three-dimensional reconstruction data; perform loading tests on the self-compacting ultra-high performance concrete specimen, and use digital image correlation technology to collect and monitor crack propagation morphology and strain field distribution data during the loading process. Step S4: Construct interface homogeneity indices related to steel fiber distribution parameters, crack propagation morphology, and strain field distribution data, and determine the quantitative evaluation threshold for interface homogeneity; Step S5: X-ray CT technology is used to collect cross-sectional data, and interface densification analysis is performed on self-compacting ultra-high performance concrete specimens under different rheological parameter conditions. The molding quality parameters are calculated and obtained by combining scanning electron microscopy. Step S6: By analyzing the correlation between molding quality parameters and interface homogeneity index, construct the functional mapping relationship between rheological parameters and interface microstructure, determine the optimal range of yield stress and plastic viscosity, and achieve performance optimization in the preparation stage of self-compacting ultra-high performance concrete.

[0006] Preferably, in step S1, the water-cement ratio is adjusted in the range of 0.17–0.21, the water-reducing agent dosage is adjusted in the range of 1.0%–1.8%, the yield stress is controlled in the range of 15–30 Pa, and the plastic viscosity is controlled in the range of 15–25 Pa·s.

[0007] Preferably, the step-by-step feeding sequence is as follows: first add powder and additives, then add water and stir, and finally add steel fibers.

[0008] Preferably, the steel fiber distribution parameters include steel fiber orientation deviation, the crack propagation morphology data includes crack continuity, and the strain field distribution data includes strain concentration factor.

[0009] Preferably, the formula for calculating the interface homogeneity index is as follows: ; in, As an indicator of interface homogeneity, For crack continuity, The strain concentration factor is... For orientation deviation, For reference orientation deviation, , as well as These are the first empirical regression coefficient, the second empirical regression coefficient, and the third empirical regression coefficient, respectively.

[0010] Preferably, the quantitative evaluation threshold for interface homogeneity is set as follows: When the interface homogeneity index At that time, the homogeneity level of the interface is characterized as level one; When the interface homogeneity index At that time, the homogeneity level of the interface was classified as level two; When the interface homogeneity index At that time, the homogeneity level of the interface was characterized as level three.

[0011] Preferably, the molding quality parameters include the interfacial bubble rate. pore volume fraction and the density of the interface transition zone; when and The interface homogeneity reaches its optimum at this time. Pore volume fraction The calculation formula is as follows: ; in, The weighting coefficient, with a value of 0.7-0.8, reflects the dominant influence of macroscopic defects on molding quality; The pore and bubble volume fractions are obtained through CT 3D reconstruction. The pore and bubble sizes in the CT 3D reconstruction are on the order of centimeters or millimeters. The porosity is measured by scanning electron microscopy at the interface transition zone. The size of the pores in the scanning electron microscope is in the micrometer or nanometer range. The density of the interface transition zone is characterized by the inverse relationship between microhardness and porosity. If the density of the interface transition zone is ≥95%, then the regional microporosity of the interface transition zone is <5%.

[0012] when , When the density is too low, the steel fibers settle, causing a slurry-rich zone to appear above the interface, and the density of the interface transition zone decreases. .

[0013] when , When the slurry is in the optimal range, the encapsulation force of the fiber is strongest, air bubbles are easily expelled, the interfacial transition zone structure is most dense, and the corresponding interfacial homogeneity reaches level one. .

[0014] The functional mapping relationship between rheological parameters and interface microstructure is constructed as follows: ; in, The yield stress of the slurry. The plastic viscosity of the slurry. , , , , as well as All are fitting coefficients.

[0015] Therefore, the present invention employs the above-mentioned method for optimizing the performance of self-compacting ultra-high performance concrete based on rheological parameter control, which has the following beneficial effects: (1) Using rheological parameters (yield stress and plastic viscosity) as optimization variables, the synergistic control of slurry flowability, fiber dispersion and interface density can be achieved by adjusting the rheological parameters.

[0016] (2) Using X-ray CT technology and digital image correlation technology, a mapping relationship between rheological parameters, interface homogeneity index and interface microstructure is established to quantitatively evaluate the influence of rheological parameters on interface homogeneity, providing a quantitative basis for subsequent densification mechanism analysis. By establishing the feedback relationship between rheological parameters and interface quality, the optimal combination of rheological parameters is determined, thereby achieving performance optimization and quality control in the SC-UHPC preparation stage.

[0017] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] Figure 1 This is a flowchart of the method for optimizing the performance of self-compacting ultra-high performance concrete based on the control of rheological parameters according to the present invention. Figure 2The following are crack propagation morphology diagrams for different types of specimens: (a) Crack propagation morphology diagram for U0 type specimen, (b) Crack propagation morphology diagram for U0.5 type specimen, (c) Crack propagation morphology diagram for U1 type specimen, (d) Crack propagation morphology diagram for U1.5 type specimen, (e) Crack propagation morphology diagram for U2 type specimen, and (d) Crack propagation morphology diagram for U2.5 type specimen. Figure 3 The stress fields of different specimen types are shown in (a) for specimen type U0, (b) for specimen type U0.5, (c) for specimen type U1, (d) for specimen type U1.5, (e) for specimen type U2, and (d) for specimen type U2.5.

[0019] The steel fiber content of the U0, U0.5, U1, U1.5, U2, and U2.5 specimens was 0%, 0.5%, 1%, 1.5%, 2%, and 2.5%, respectively.

[0020] Figure 4 This is a graph showing the relationship between the compressive strength and axial compressive strength of self-compacting ultra-high performance concrete. Figure 5 Bar charts showing the maximum crack width before and after optimization at different stages; Figure 6 Bar charts showing the strain compatibility index before and after optimization at different stages. Detailed Implementation

[0021] In the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product is in use. They are used only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," and "connect" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0022] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0023] like Figure 1As shown, a method for optimizing the performance of self-compacting ultra-high performance concrete based on rheological parameter control is described, with the following specific steps: Step S1: The rheological parameters of the self-compacting ultra-high performance concrete paste, including yield stress and plastic viscosity, are tested using a rheometer. The rheological parameters are controlled within a set range by adjusting the water-cement ratio and the water-reducing agent dosage. The water-cement ratio is adjusted from 0.17 to 0.21, the water-reducing agent dosage is adjusted from 1.0% to 1.8%, the yield stress is controlled from 15 to 30 Pa, and the plastic viscosity is controlled from 15 to 25 Pa·s.

[0024] The cementitious materials used in this embodiment include silicate cement, silica fume, and quartz powder in a ratio of 60:20:20 (mass fraction). The fine aggregate is quartz sand with a particle size not exceeding 2.36 mm. The water-reducing agent dosage is 1.0%–1.8% of the cementitious material mass, and the water-cement ratio is controlled at 0.17–0.21. A rotational rheometer is used at a rotation speed of 10–100 s. -1 Yield stress and plastic viscosity were tested within the specified range. When the yield stress was 15–30 Pa and the plastic viscosity was 15–25 Pa·s, the slurry exhibited stable self-compacting properties and good fiber dispersibility. If the yield stress was too high, the amount of water-reducing agent could be appropriately increased or the stirring rate could be increased; if the viscosity was too low, it could be adjusted to the target range by increasing the amount of silica fume or reducing the water-cement ratio, thereby providing controllable flow conditions for subsequent preparation.

[0025] Step S2: Steel fibers are added to the self-compacting ultra-high performance concrete slurry with rheological parameters within the set range using a step-by-step feeding and mechanical mixing method to prepare self-compacting ultra-high performance concrete specimens, which are then cured.

[0026] The step-by-step feeding sequence is as follows: First, dry mix the powder and additives for 30 seconds to ensure uniformity. Then, add water and water-reducing agent solution and stir for 60 seconds to form a homogeneous slurry. Finally, add steel fibers (1.5% by volume, 13mm in length) in three batches and continue stirring for 120 seconds to ensure uniform dispersion of the fibers in the slurry.

[0027] The specimens were formed using a standard mold with dimensions of 100mm×100mm×400mm. No vibration or tapping was performed. After pouring, the surface was lightly scraped to level it and covered with a plastic film to prevent moisture evaporation. Curing conditions were a temperature of 20±2°C, relative humidity above 95%, and a curing period of 28 days. This step ensured the fullness and stability of the slurry, reduced air bubbles and stratification, and provided a foundation for improved interface homogeneity.

[0028] Step S3: Cut the specimen into 50mm×50mm×50mm cube samples. Use X-ray CT technology (resolution ≤20μm) to perform three-dimensional reconstruction of the cube samples. Extract steel fiber distribution parameters from the three-dimensional reconstruction data. These parameters include steel fiber orientation deviation, used to quantitatively characterize fiber dispersion characteristics. Additionally, orientation angular distribution and volumetric density can be extracted, reflecting and evaluating the uniformity of fiber distribution.

[0029] like Figures 2-3 As shown, a cubic sample was subjected to a loading test. During the test, digital image correlation technology was used to collect and monitor crack propagation morphology and strain field distribution data. The crack propagation morphology data included crack continuity, and the strain field distribution data included strain concentration factor.

[0030] Low fiber content (U0.5) specimens exhibited faster and more singular crack development; high fiber content (U1.5, U2.0) specimens, due to optimized rheological properties and uniform fiber distribution, showed more significant multi-point cracking and micro-crack control capabilities. The U0-U2.5 model is an experimental gradient established based on steel fiber volume fraction (0%-2.5%). This was to verify that the method in this embodiment can achieve uniform fiber dispersion at different fiber contents. Although the plastic viscosity increases with increasing fiber content, by adjusting the water-cement ratio (0.17-0.21) and water-reducing agent, the rheological parameters of each model can be uniformly controlled within the optimal range required in this embodiment (e.g., yield stress 20±2 Pa), thereby ensuring first-order interface homogeneity at the microscopic level and achieving smooth crack propagation at the macroscopic level.

[0031] Step S4: Construct an interface homogeneity index related to steel fiber distribution parameters, crack propagation morphology, and strain field distribution data. The calculation formula for the interface homogeneity index is as follows: ; in, As an indicator of interface homogeneity, For crack continuity, The strain concentration factor is... For orientation deviation, For reference orientation deviation, , as well as These are the first empirical regression coefficient, the second empirical regression coefficient, and the third empirical regression coefficient, respectively.

[0032] The quantitative evaluation threshold values ​​for interface homogeneity are as follows: Interface homogeneity index At that time, the interface homogeneity level was classified as Level 1, indicating good interface homogeneity and uniform fiber distribution.

[0033] Interface homogeneity index At this time, the homogeneity level of the interface is characterized as level two, indicating that the interface homogeneity is generally low.

[0034] Interface homogeneity index At that time, the interface homogeneity level was three, indicating poor interface homogeneity and the presence of local fiber aggregation or pore concentration.

[0035] This enables a quantitative evaluation of interface homogeneity, providing data input for subsequent densification and performance optimization.

[0036] Step S5: X-ray CT technology is used to acquire cross-sectional data, and interface densification analysis is performed on self-compacting ultra-high performance concrete specimens under different rheological parameter conditions. The molding quality parameters are calculated by combining scanning electron microscopy. The X-ray CT cross-sectional images are binarized, and the bubble rate in the interface area is statistically analyzed. With pore volume fraction To quantitatively reflect the interface forming quality, scanning electron microscopy (SEM) was used to observe the morphology of the steel fiber-matrix interface and measure the thickness and pore distribution of the interface transition zone (ITZ) to reflect the variation law of interface density.

[0037] Molding quality parameters include interfacial bubble rate pore volume fraction And the density of the interface transition zone.

[0038] Step S6: Through correlation analysis between molding quality parameters and interface homogeneity index, construct the functional mapping relationship between rheological parameters and interface microstructure. The mapping relationship is as follows: ; in, The yield stress of the slurry. The plastic viscosity of the slurry. , , , , as well as All are fitting coefficients.

[0039] Pore ​​volume fraction The calculation formula is as follows: ; in, The weighting coefficient, with a value of 0.7-0.8, reflects the dominant influence of macroscopic defects on molding quality; The pore and bubble volume fractions are obtained through CT 3D reconstruction. The pore and bubble sizes in the CT 3D reconstruction are on the order of centimeters or millimeters. The porosity is measured by scanning electron microscopy at the interface transition zone. The size of the pores in the scanning electron microscope is in the micrometer or nanometer range. The density of the interface transition zone is characterized by the inverse relationship between microhardness and porosity. If the density of the interface transition zone is ≥95%, then the regional microporosity of the interface transition zone is <5%.

[0040] when , When the density is too low, the steel fibers settle, causing a slurry-rich zone to appear above the interface, and the density of the interface transition zone decreases. .

[0041] when , When the slurry is in the optimal range, the encapsulation force of the fiber is strongest, air bubbles are easily expelled, the interfacial transition zone structure is most dense, and the corresponding interfacial homogeneity reaches level one. .

[0042] When the rheological parameters are in the optimal range, the slurry can fully wet the fiber surface, so that the pores of the interfacial transition zone (ITZ) are filled with gelation products, thereby achieving a density of over 95%, and the macroscopic manifestation is that the interfacial homogeneity index M reaches its peak.

[0043] The relationship between the interface homogeneity index and the molding quality parameters is shown in Table 1.

[0044] Table 1. Correspondence between interface homogeneity index and molding quality parameters

[0045] when , and The optimal interface homogeneity was achieved, resulting in the densest interface structure and strongest fiber-matrix bond. Rheological parameter control effectively improved the degree of interface densification, providing structural support for subsequent improvements in macroscopic mechanical properties. The optimal range of yield stress and plastic viscosity was determined; the optimal process parameter range for this embodiment was achieved when the slurry yield stress was controlled at 20±2 Pa and the plastic viscosity at 18±2 Pa·s. The method described in this embodiment can effectively optimize the interface homogeneity of SC-UHPC during the preparation stage.

[0046] To verify the impact of interface homogeneity on macroscopic properties, a four-point bending load test was conducted on the specimen. The specimen span was 300 mm, the loading span was 100 mm, and the loading rate was 0.5 mm / min. Figure 4 As shown, the actual strengthening effect brought about by this micro-optimization (i.e., when the rheological parameters are in the optimal range) is verified from a macroscopic mechanical perspective. If the rheological properties of self-compacting concrete are poor (such as segregation or fiber aggregation), the ratio of its cubic strength to axial strength will be highly irregular. Figure 4 The results show a highly stable linear correlation between the two, demonstrating the excellent internal structural homogeneity of the specimens prepared using the method in this embodiment. The regression curves establish the conversion relationship between different strength indices of SC-UHPC, providing a reliable basis for estimating axial compressive strength from easily measurable cubic compressive strength in engineering design. Among these, This refers to the axial compressive strength. To withstand compressive strength, SC-UHPC exhibits a cubic compressive strength of up to 120 MPa and an axial compressive strength exceeding 105 MPa with low dispersion, characterizing the material's extremely high strength level and quality stability. The ratio of axial compressive strength to total compressive strength is approximately 0.84, close to the recommended value (0.85) for high-performance concrete, indicating that under optimized rheological parameters, steel fibers can effectively form a three-dimensional skeleton to resist crack propagation under stress, fully leveraging the bridging and synergistic effect of the fiber-matrix.

[0047] During the experiment, the load-deflection curve and crack opening displacement (CMOD) curve were recorded simultaneously to extract the ultimate load. fracture toughness And the ductility coefficient D parameter. The data are shown in Table 2.

[0048] Table 2 shows the test data for four-point bending loading.

[0049] Before optimization (unoptimized rheology): the ductility coefficient D is approximately 1.2-1.5. At this point, improper control of the slurry viscosity and uneven fiber distribution lead to rapid and uniform crack propagation, exhibiting a clear tendency towards brittle failure.

[0050] After optimization (optimized rheology): the ductility coefficient D increased to 2.8-3.5. The optimized rheological environment ensured that the steel fibers achieved a homogeneous distribution of level two or above, which was macroscopically manifested as multi-crack formation and a smoother stress drop section. The ductility coefficient was improved by about 100%-130% compared to the unoptimized group.

[0051] Statistical analysis was performed on rheological parameters, interfacial homogeneity index M, and mechanical property data, such as... Figures 5-6As shown, an empirical relationship diagram of yield stress, viscosity, and performance improvement was established. The experimental results of the specimen loading process in this embodiment show that after optimizing the rheological parameters (yield stress of the slurry controlled at 20±2 Pa and plastic viscosity at 18±2 Pa·s), the ultimate load of the specimen increased by 15%–20%, the fracture toughness increased by approximately 25%, crack propagation became smoother, and the strain field continuity improved. The experimental results demonstrate that after optimizing the rheological parameters, the ultimate load and fracture toughness improved, crack propagation became smoother, and the strain field continuity improved. This indicates that the technical solution adopted in this embodiment not only improves the interface homogeneity but also enhances the overall mechanical properties, meeting the application requirements.

[0052] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for optimizing the performance of self-compacting ultra-high performance concrete based on rheological parameter control, characterized in that, The specific steps are as follows: Step S1: Test the rheological parameters of the self-compacting ultra-high performance concrete paste using a rheometer. The rheological parameters include yield stress and plastic viscosity. Adjust the water-cement ratio and water-reducing agent dosage to control the rheological parameters of the self-compacting ultra-high performance concrete paste within the set range. Step S2: Steel fibers are added to the self-compacting ultra-high performance concrete slurry with rheological parameters within the set range by step feeding and mechanical mixing to prepare self-compacting ultra-high performance concrete specimens, and then they are cured. Step S3: Use X-ray CT technology to perform three-dimensional reconstruction of the self-compacting ultra-high performance concrete specimen after curing, and extract steel fiber distribution parameters based on the three-dimensional reconstruction data; perform loading tests on the self-compacting ultra-high performance concrete specimen, and use digital image correlation technology to collect and monitor crack propagation morphology and strain field distribution data during the loading process. Step S4: Construct interface homogeneity indices related to steel fiber distribution parameters, crack propagation morphology, and strain field distribution data, and determine the quantitative evaluation threshold for interface homogeneity; Step S5: X-ray CT technology is used to collect cross-sectional data, and interface densification analysis is performed on self-compacting ultra-high performance concrete specimens under different rheological parameter conditions. The molding quality parameters are calculated and obtained by combining scanning electron microscopy. Step S6: By analyzing the correlation between molding quality parameters and interface homogeneity index, construct the functional mapping relationship between rheological parameters and interface microstructure, determine the optimal range of yield stress and plastic viscosity, and achieve performance optimization in the preparation stage of self-compacting ultra-high performance concrete.

2. The method for optimizing the performance of self-compacting ultra-high performance concrete based on rheological parameter control according to claim 1, characterized in that: In step S1, the water-cement ratio is adjusted to a range of 0.17–0.21, the water-reducing agent dosage is adjusted to a range of 1.0%–1.8%, the yield stress is controlled at 15–30 Pa, and the plastic viscosity is controlled at 15–25 Pa·s.

3. The method for optimizing the performance of self-compacting ultra-high performance concrete based on rheological parameter control according to claim 2, characterized in that: The step-by-step feeding sequence is as follows: first add powder and additives, then add water and stir, and finally add steel fibers.

4. The method for optimizing the performance of self-compacting ultra-high performance concrete based on rheological parameter control according to claim 3, characterized in that: The steel fiber distribution parameters include steel fiber orientation deviation, the crack propagation morphology data includes crack continuity, and the strain field distribution data includes strain concentration factor.

5. The method for optimizing the performance of self-compacting ultra-high performance concrete based on rheological parameter control according to claim 4, characterized in that: The formula for calculating the interface homogeneity index is as follows: ； in, As an indicator of interface homogeneity, For crack continuity, The strain concentration factor is... For orientation deviation, For reference orientation deviation, , as well as These are the first empirical regression coefficient, the second empirical regression coefficient, and the third empirical regression coefficient, respectively.

6. The method for optimizing the performance of self-compacting ultra-high performance concrete based on rheological parameter control according to claim 5, characterized in that: The quantitative evaluation threshold values ​​for interface homogeneity are as follows: When the interface homogeneity index At that time, the homogeneity level of the interface is characterized as level one; When the interface homogeneity index At that time, the homogeneity level of the interface was classified as level two; When the interface homogeneity index At that time, the homogeneity level of the interface was characterized as level three.

7. The method for optimizing the performance of self-compacting ultra-high performance concrete based on rheological parameter control according to claim 6, characterized in that: Molding quality parameters include interfacial bubble rate pore volume fraction and the density of the interface transition zone; when and When the interface homogeneity reaches its optimal value; Pore ​​volume fraction The calculation formula is as follows: ； in, These are weighting coefficients. The porosity and bubble volume fraction were obtained through CT 3D reconstruction. The porosity is measured at the interface transition zone using a scanning electron microscope. The density of the interface transition zone is positively correlated with the interface homogeneity index.

8. The method for optimizing the performance of self-compacting ultra-high performance concrete based on rheological parameter control according to claim 7, characterized in that: The functional mapping relationship between rheological parameters and interface microstructure is constructed as follows: ； in, The yield stress of the slurry. The plastic viscosity of the slurry. , , , , as well as All are fitting coefficients.

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