Construction and application of prediction model for mechanical properties of hybrid carbon-steel fiber magnetite ultra-high performance concrete

Abstract

This application relates to the construction and application of a mechanical property prediction model for hybrid carbon-steel fiber magnetite ultra-high performance concrete, aiming to solve the problems of difficulty in quantifying the fiber synergistic effect, inaccurate mechanical property prediction, and inability to effectively link with structural health monitoring in existing hybrid fiber reinforced ultra-high performance concrete. This invention employs a key technical means of introducing fiber factors that comprehensively characterize the content and geometric features of carbon and steel fibers to modify typical compressive constitutive models, constructing a mechanical property prediction model that can accurately describe the behavior throughout the stress-strain process. Based on this, a systematic method for performance prediction, damage monitoring, and mix proportion optimization is developed. This model accurately characterizes the fiber hybrid effect, endowing the material with excellent crack resistance and self-sensing properties, and has strong universality, capable of accurately extrapolating unknown mix proportions, achieving integrated precise prediction of material mechanical behavior and intelligent structural monitoring.

Description

Technical Field

[0001] This invention relates to the field of concrete material performance prediction technology, specifically to the construction and application of a prediction model for the mechanical properties of hybrid carbon-steel fiber magnetite ultra-high performance concrete. Background Technology

[0002] As modern engineering construction develops towards ultra-high, ultra-large, and ultra-deep structures, the safety and durability monitoring of concrete structures faces higher requirements. Ultra-high performance concrete (UHPC) is widely used in critical infrastructure such as nuclear power plants, cross-sea bridges, and high-rise buildings due to its excellent mechanical properties and durability. However, UHPC structures are subjected to complex loads during service, and the evolution of internal damage is difficult to observe directly. Traditional embedded sensors (such as optical fibers, piezoelectric ceramics, and resistance strain gauges) have problems such as poor compatibility with the matrix, high cost, and insufficient durability, which limit their large-scale application in the health monitoring of UHPC structures.

[0003] Magnetite, with its excellent mechanical and electrical properties, is an ideal functional aggregate for self-sensing concrete. Introducing magnetite into unreinforced high-temperature concrete (UHPC) can endow the material with multifunctional characteristics. However, the high density and weak interfacial properties of magnetite aggregate exacerbate the complexity of the synergistic effect between fibers and the matrix. Establishing a theoretical model that accurately describes the mechanical properties of hybrid fiber-reinforced UHPC, while considering the influence of magnetite aggregate, has become a pressing technical challenge. Existing UHPC constitutive models are mostly based on empirical formulas or simple theoretical derivations, failing to fully consider the influence of fiber content, geometric characteristics, and their synergistic effects on the material's damage evolution mechanism, making it difficult to accurately predict the entire stress-strain process of hybrid fiber-reinforced magnetite UHPC.

[0004] Furthermore, combining the force-electric response characteristics of materials with mechanical constitutive models to achieve real-time monitoring and damage early warning of the service status of UHPC structures is an important development direction in the field of smart concrete. However, there is currently a lack of a systematic method that can correlate resistivity changes with mechanical constitutive models, thereby realizing a complete technical solution from "material performance prediction" to "structural damage monitoring".

[0005] Therefore, there is an urgent need to develop a model that can comprehensively consider the hybrid reinforcement effect of carbon fiber and steel fiber and accurately predict the mechanical properties of magnetite UHPC. Based on this model, corresponding performance prediction, damage monitoring and mix ratio optimization technologies should be developed to meet the urgent needs of intelligent health monitoring of modern major infrastructure.

[0006] The information disclosed in this background section is intended only to enhance the understanding of the background technology of this disclosure and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0007] This invention addresses the technical problems of difficulty in quantifying the fiber synergistic effect, inaccurate prediction of mechanical properties, and inability to effectively link with structural health monitoring in existing hybrid fiber-reinforced ultra-high performance concrete. It employs a key technical approach of introducing fiber factors that comprehensively characterize the content and geometric features of carbon and steel fibers to modify typical compressive constitutive models. This constructs a mechanical property prediction model capable of accurately describing the behavior throughout the stress-strain process. Based on this model, a systematic method for performance prediction, damage monitoring, and mix proportion optimization is developed, achieving the technical effect of integrating accurate prediction of material mechanical behavior with intelligent structural monitoring.

[0008] To achieve the above objectives, this invention designs mix proportions based on the modified Andreasen and Andersen (A&A) continuous packing model, and prepares single-admixture and mixed-admixture specimens with carbon fiber content of 0.15%~0.6% of the total concrete volume and steel fiber content of 0.5%~2.0% of the total concrete volume, for a total of 24 mix proportions.

[0009] By conducting uniaxial compression tests combined with digital image correlation (DIC) technology to monitor the failure process of test specimens in real time and simultaneously acquiring load-displacement data, stress-strain curves of magnetite ultra-high performance concrete (MUHPC) with different fiber contents were obtained. The results show that MUHPC with carbon fiber as the sole admixture exhibits brittle burst failure, with a steeply decreasing stress-strain curve. MUHPC with steel fiber as the sole admixture and MUHPC with a carbon-steel fiber blend exhibits ductile failure. The higher the steel fiber content, the denser the microcracks and the smaller the crack width. Furthermore, the peak stress increases linearly with increasing steel fiber content. The elastic modulus of MUHPC increases with increasing carbon fiber and steel fiber content. The blended fibers exhibit a synergistic reinforcement effect. The two types of fibers hinder crack propagation at multiple levels, enabling MUHPC to transition from brittle fracture to ductile failure, significantly improving compressive toughness.

[0010] Based on the above experimental phenomena and stress-strain curve characteristics, the curve parameters of the uniaxial compression constitutive model were further fitted, and a stress-strain relationship considering the fiber hybrid synergistic reinforcement effect was constructed, providing a basis for predicting the mechanical properties of MUHPC.

[0011] The first aspect disclosed in this application provides a method for constructing a prediction model for the mechanical properties of hybrid carbon-steel fiber magnetite ultra-high performance concrete, comprising the following steps: S1: Prepare multiple groups of hybrid carbon-steel fiber magnetite ultra-high performance concrete specimens with different fiber contents; wherein, the matrix of the ultra-high performance concrete includes cement, silica fume, fly ash, river sand, magnetite aggregate, mixing water, water-reducing agent and dispersant; the fibers include carbon fiber and steel fiber, and the volume content of carbon fiber and steel fiber in each group of specimens is different. S2: Perform uniaxial compression tests on each group of specimens, collect stress and strain data of each group of specimens throughout the entire loading process to failure, and plot the stress-strain curves of each group of specimens based on the stress and strain data. S3: Determine the peak stress of each group of specimens based on the complete stress-strain curves. s cr and the corresponding peak strain e cr ; S4: Introducing fiber factors to characterize the combined effects of carbon fiber and steel fiber content and geometric characteristics on the mechanical properties of concrete. F ; S5: Based on the typical constitutive model under pressure, utilizing the aforementioned fiber factor F For the rising segment parameters of the constitutive model α and descent parameters β Make corrections and establish a dimensionless stress. y = s / s cr and dimensionless strain x = e / e cr The constitutive equation for variables is as follows: ; in, α and β All of them are the fiber factors F The function; S6: Based on the stress-strain curve data of each group of specimens, determine the parameters by fitting. α and β With fiber factors F The functional relationship between them is used to construct a predictive model for the mechanical properties of the hybrid carbon-steel fiber magnetite ultra-high performance concrete.

[0012] In some embodiments of this disclosure, the fiber factor described in step S4 F Determined by the following formula: F=F sf +F cf ; in,F sf The fiber component of steel fiber, F cf The fiber factor of carbon fiber; the fiber factor of a single fiber is calculated according to the formula. F i = kV i l i / d i The calculation determines that, among which V i This refers to the volumetric content of the fiber. l i For the length of the fiber, d i The diameter of the fiber. k This is a correction factor related to fiber type.

[0013] In some embodiments of this disclosure, the constitutive equation in step S5 has an ascending segment function form as follows: f 1( x , α ) = αx + (3-2 α ) x 2 + ( α -2) x 3 The descent segment function is in the form of f 2( x , β ) = x / [ β ( x -1) 2 + x ].

[0014] In some embodiments of this disclosure, the carbon fiber is a short-cut carbon fiber with a length of 3 mm and a diameter of 7 μm, and its volumetric doping is 0.15%~0.6%; the steel fiber is a copper-plated micro-steel fiber with a length of 13 mm and a diameter of 0.2 mm, and its volumetric doping is 0.5%~2.0%; then the parameters are obtained by fitting. α and β With fiber factors F The functional relationship between them is as follows: .

[0015] In some embodiments of this disclosure, fiber factors are introduced. F Then, the constitutive model can be expressed as: ; in, y= s / s cr , x = y / y cr For dimensionless stress and strain, s , e and e cr These represent the stress, strain, and peak strain of the concrete, respectively.

[0016] The second aspect of this application discloses a method for predicting the mechanical properties of hybrid carbon-steel fiber magnetite ultra-high performance concrete, comprising the following steps: P1: Obtain the material mix proportion parameters of the carbon-steel fiber magnetite ultra-high performance concrete to be predicted, including at least the volume content of carbon fiber, the geometric parameters of carbon fiber, the volume content of steel fiber, and the geometric parameters of steel fiber. P2: Calculate the fiber factor based on the parameters obtained in step P1. F ; P3: Calculate the fiber factor obtained in step P2. F Substitute the parameters determined by any of the construction methods described above. α and β With fiber factors F In the functional relationship, the corresponding... α and β value; P4: The result obtained in step P3 α and β Substituting the values ​​into the constitutive equation according to any one of the terms, we obtain the dimensionless stress-strain relationship of the concrete to be predicted. P5: Obtain the peak stress of the concrete to be predicted s cr and peak strain e cr By combining the dimensionless stress-strain relationship obtained in step P4, the full stress-strain curve of the concrete to be predicted is obtained, thereby realizing the prediction of the mechanical properties of the concrete.

[0017] In some embodiments of this disclosure, the peak stress described in step P5 s cr and peak strain e cr The method is determined through material testing or estimated using empirical formulas based on the mix proportion parameters of the concrete to be predicted.

[0018] The third aspect disclosed in this application provides a method for monitoring damage in hybrid carbon-steel fiber magnetite ultra-high performance concrete structures, comprising the following steps: M1: Construct a mechanical property prediction model for hybrid carbon-steel fiber magnetite ultra-high performance concrete of the target structure, wherein the prediction model is obtained according to any of the construction methods described herein; M2: During the service life of the target structure, the resistivity data of the concrete is collected in real time or periodically; M3: Based on the resistivity data collected in step M2, and combined with the pre-generated correspondence between resistivity change rate and stress / strain (see the table below for the existing tensile / compressive resistance model of self-sensing concrete), determine the actual stress / strain state of the target structure at the current moment.

[0019] M4: Substitute the actual stress / strain state determined in step M3 into the mechanical performance prediction model constructed in step M1 to predict the damage evolution trend and remaining bearing capacity of the target structure under the current stress / strain state. M5: Based on the prediction results of step M4, assess the safety status of the target structure and issue an early warning signal when the predicted damage level exceeds a preset threshold.

[0020] In some embodiments of this disclosure, the resistivity data in step M2 is collected by an electrode embedded in the concrete or by a surface contact electrode; the relationship between the resistivity change rate and stress / strain in step M3 is determined in advance by calibration tests or estimated by empirical formulas based on the amount of carbon fiber and steel fiber in the concrete.

[0021] The fourth aspect of this application discloses a method for determining the mix proportion of hybrid carbon-steel fiber magnetite ultra-high performance concrete, comprising the following steps: D1: Set the target mechanical performance indicators of the concrete, including at least the target peak stress and the target peak strain; D2: Constructing with fiber factors F A mechanical performance prediction model with independent variables, wherein the prediction model is obtained according to any of the construction methods described herein; D3: Based on the target mechanical performance index set in step D1, calculate the required fiber factor. F The range of values ​​for ; D4: Fiber factor determined in step D3 F Within the range of values, various combinations of carbon fiber and steel fiber dosages are determined, wherein the dosage combinations satisfy the constraints of carbon fiber volume dosage of 0.1% to 0.8% and steel fiber volume dosage of 0.3% to 2.5%. D5: From the various admixture combinations determined in step D4, select the optimal admixture combination that meets the preset workability and / or economic requirements as the mix proportion of the target concrete.

[0022] One or more technical solutions provided in the embodiments of this application have at least one of the following technical effects or advantages: 1. A mechanical property prediction model considering fiber hybridization effects was constructed, filling a theoretical gap: This invention introduces a fiber factor that comprehensively characterizes the content and geometric features of carbon fiber and steel fiber. F A piecewise constitutive equation with dimensionless stress and dimensionless strain as variables was established. This model overcomes the shortcomings of existing constitutive models in quantifying the synergistic effect of fiber hybridization, and can accurately describe the stress-strain relationship of the material throughout the entire process from elastic deformation and crack propagation to failure, providing a systematic theoretical tool for studying the mechanical behavior of hybrid fiber reinforced UHPC.

[0023] 2. Accurate prediction of the mechanical properties of materials with unknown mix proportions is achieved, demonstrating universality: Based on the constructed model, this invention further provides a method for predicting mechanical properties. This method only requires obtaining the fiber content and geometric parameters of the material to be predicted, and can then be used to predict mechanical properties through fiber factors. F This method rapidly calculates the full stress-strain curve. Compared to traditional methods that rely on numerous physical tests, this approach significantly reduces the trial-and-error costs and time required in materials development, providing engineers with an efficient and reliable means of performance evaluation.

[0024] 3. Innovative coupling of force-electric response with constitutive models enables intelligent monitoring of structural damage: This invention organically combines the piezoresistive properties of materials with mechanical constitutive models, proposing a method for monitoring structural damage. By acquiring resistivity data in real time to invert the actual stress / strain state of the structure, and then substituting it into a mechanical prediction model to assess the damage evolution trend, a closed-loop monitoring system from "physical parameter perception" to "mechanical state deduction" is achieved. This breaks through the limitation of traditional monitoring methods that can only acquire local data, providing a completely new technical path for the full life-cycle health management of UHPC structures.

[0025] 4. A reverse optimization design method from "performance targets" to "mixing ratio parameters" was constructed: Based on the established relationship between fiber factors and constitutive models, this invention proposes a mixing ratio optimization design method. This method can back-calculate the required range of fiber factor values ​​based on the target mechanical properties (such as peak stress and peak strain) set in the engineering project, and screen out the optimal fiber content combination that meets the requirements of working performance and economy. This provides a scientific basis for the forward design and engineering application of multifunctional, high-performance UHPC materials.

[0026] 5. Fundamentally improved crack resistance and self-sensing properties: The material involved in this invention, through a hybrid design of carbon fiber and steel fiber, forms a multi-level conductive path and a synergistic reinforcement mechanism. Carbon fiber inhibits the initiation of microcracks, while steel fiber delays the propagation of macroscopic cracks. Together, they transform the failure mode of concrete from brittle fracture to ductile failure, significantly improving compressive toughness and energy absorption capacity. Simultaneously, the construction of the multi-level conductive network is coupled with the semiconductor properties of magnetite aggregate, greatly enhancing the material's piezoresistive sensitivity and stability, providing a reliable physical basis for the aforementioned model prediction and damage monitoring. Attached Figure Description

[0027] Figure 1 The following are the raw materials for ultra-high performance concrete made of steel-carbon fiber mixed with magnetite in one embodiment of this application: A-cement; B-fly ash; C-silica fume; D, E-magnetite (D: particle size 0-0.6mm, E: particle size 0.6-1.18mm); F, G-river sand (F: particle size 0-0.6mm, G: particle size 0.6-1.18mm); H, I-fiber (H: steel fiber, I: carbon fiber); J, K-water reducing agent; L, M-dispersant.

[0028] Figure 2 The test loading device in one embodiment of this application is a 600kN microcomputer-controlled universal testing machine.

[0029] Figure 3 This is for the preparation of speckle patterns on a specimen in one embodiment of this application.

[0030] Figure 4 The vertical strain field variation of carbon fiber MUHPC in one embodiment of this application ( s (Strain); where the volumetric carbon fiber content of (a)-(d) is 0.15%, 0.30%, 0.45%, and 0.60%, respectively.

[0031] Figure 5 The vertical strain field variation of steel fiber MUHPC in one embodiment of this application ( s (Strain); where the volumetric fiber content of (a)-(d) is 0.5%, 1.0%, 1.5%, and 2.0%, respectively.

[0032] Figure 6 shows the vertical strain field variation of hybrid fiber MUHPC in one embodiment of this application (including...). Figure 6-1 to 6-4 , s(Strain); where, (a)-(d) 0.5%SF+(0.15-0.60)CF, (e)-(h) 1.0%SF+(0.15-0.60)CF, (i)-(l) 1.5%SF+(0.15-0.60)CF, (m)-(p) 2.0%SF+(0.15-0.60)CF.

[0033] Figure 7 The stress-strain curve of a single-fiber-doped MUHPC in one embodiment of this application is shown below. s : Response, e : stress); where (a) is single-doped carbon fiber, and (b) is single-doped steel fiber.

[0034] Figure 8 The MUHPC stress-strain curve of hybrid fibers in one embodiment of this application is shown below. s : Response, e (Stress); where, (a) 0.5%SF+CF, (b) 1.0%SF+CF, (c) 1.5%SF+CF, (d) 2.0%SF+CF.

[0035] Figure 9 shows the experimental data and fitted stress of MUHPC specimens with different fiber contents in one embodiment of this application. e )-strain( s Curve comparison chart (including) Figure 9-1 to 9-3 ); among them, (a)-(d) 0.5%, 1.0%, 1.5%, 2.0% SF, (e)-(h) 0.15%, 0.30%, 0.45%, 0.60% CF, (i)-(l) 0.5%SF+(0.15-0.60)CF, (m)-(p) 1.0%SF+(0.15-0.60)CF, (q)-(t) 1.5%SF+(0.15-0.60)CF, (u)-(x) 2.0%SF+(0.15-0.60)CF. Detailed Implementation

[0036] The following examples illustrate specific implementations of the present invention. However, these examples are merely for illustrative purposes and do not limit the scope of the invention in any way.

[0037] The following are the experimental raw materials and methods involved in the examples: 1. Experimental raw materials (1) Cementitious materials Cement: The P.O 52.5 grade cement used in this experiment was produced by China Tianrui Group Zhengzhou Cement Co., Ltd. (The remaining text appears to be incomplete and possibly contains errors.) Figure 1 A, whose main chemical components and performance indicators are shown in Table 1 and Table 2, respectively.

[0038] Fly ash: Grade I fly ash was used in this experiment, such as... Figure 1 B, provided by Henan Rongsong Construction Engineering Co., Ltd. The density of this fly ash is 2.53 g / m³. 3 Its main chemical components are shown in Table 3. The darker the color, the finer the particle size of the fly ash and the higher the carbon content.

[0039] Silica fume: Also known as microsilica powder, silica fume has a high specific surface area due to its nanoscale particle size and high silicon content, thus acting as a filler and exerting a pozzolanic effect in UHPCs. For example... Figure 1 C, whose main component is silicon dioxide, is gray in color. The microsilica powder used in this experiment is produced by Henan Dingnuo Purification Materials Co., Ltd., and its chemical composition is shown in Table 4.

[0040] Table 1 Chemical composition of P.O 52.5 cement

[0041] Table 2 Performance Indicators of P.O 52.5 Cement

[0042] Table 3 Chemical composition of fly ash

[0043] Table 4 Chemical composition of silica fume

[0044] (2) Fine aggregate Magnetite: To meet the experimental requirements, a jaw crusher was used for crushing and screening, ultimately yielding magnetite with two particle sizes: 0-0.6 mm and 0.6-1.18 mm. Their physical morphologies are as follows: Figure 1 As shown in DE, the main chemical composition of the magnetite used was obtained by X-ray fluorescence (XRF) testing, as shown in Table 5. It can be seen that the main component of magnetite is Fe, followed by Si.

[0045] Table 5 Chemical elements of magnetite

[0046] River sand: The sand used in this experiment was natural river sand, which was obtained by screening by Runzhou District Yilin Internet Sales Department, yielding two types of river sand with particle sizes of 0-0.6mm and 0.6-1.18mm respectively. Their physical morphology is as follows: Figure 1 As shown in FG.

[0047] (3) Fiber Steel fibers: The UHPC matrix itself is insulating, and steel fibers are an ideal conductive medium. When incorporated into the matrix, they form a conductive network. Steel fibers not only effectively improve the conductivity of UHPC but also enhance its mechanical properties, significantly improving compressive strength, toughness, flexural strength, and impact resistance. This experiment used copper-plated micro-steel fibers produced by Zhitai Steel Fiber Manufacturing Co., Ltd. in Yutian County. The fibers have hooked ends, such as... Figure 1 As shown in H, Table 6 gives the performance indicators of steel fibers.

[0048] Table 6 Performance Indicators of Steel Fibers

[0049] Carbon fiber: Carbon fiber possesses superior properties such as high strength (3-7 GPa), high modulus (200-400 GPa), corrosion resistance, electromagnetic shielding, electrical conductivity, and thermal conductivity. However, fiber content, length, and dispersibility are key factors affecting the mechanical properties of concrete. Too low a content has little impact on the strengthening effect of the matrix, while too high a content easily leads to agglomeration, introducing pores and thus affecting its mechanical properties. Therefore, carbon fiber is usually added to concrete in short-cut form, with a length of 3-6 mm being preferable. Too long a fiber is prone to agglomeration and is difficult to disperse. The carbon fiber used in the experiment was produced by Suqian Nakaite New Material Technology Co., Ltd., mainly using 6 mm short-cut carbon fibers. Its physical morphology and... Figure 1 As shown in Figure I, the main performance indicators are shown in Table 7.

[0050] Table 7 Performance Indicators of Carbon Fiber

[0051] (4) Water-reducing agent Low water consumption in UHPC leads to poor flowability of the mixture. Polycarboxylate superplasticizers, with water reduction rates of 25%-45%, maintain good flowability even with low water consumption and exhibit good compatibility with cementitious materials. This experiment used a high-efficiency polycarboxylate superplasticizer produced by Jiangsu Subote New Material Co., Ltd. This superplasticizer is a colorless, transparent, viscous liquid, such as... Figure 1 As shown in JK, the water-reducing agent has a water reduction rate of 30% and a solid content of 30%, and is used to adjust the fluidity of the UHPC mixture.

[0052] (5) Dispersant Methylcellulose, as a surfactant, is an important way to improve the hydrophobicity of carbon fiber surfaces and can promote fiber dispersion in cement paste. It can also reduce the surface tension of conductive materials and the surface energy of the cement matrix. The dispersant used in this experiment is... Figure 1 As shown in LM, the main performance indicators are shown in Table 8.

[0053] Table 8 Performance Indicators of Methylcellulose

[0054] (6) Mixing ratio The mix design in this study adopted the modified Andreasen and Andersen (A&A) model as a continuous packing model. Specimens were prepared by replacing 60% of river sand with magnetite. In this experiment, carbon fiber with a volume fraction of 0.15%, 0.3%, 0.45%, and 0.6%, and steel fiber with a volume fraction of 0.5%, 1.0%, 1.5%, and 2.0% were incorporated into the concrete matrix as conductive fibers, resulting in 24 different proportions of carbon fiber, steel fiber, and magnetite ultra-high performance concrete. The mix proportions are shown in Table 9.

[0055] Table 9. Mix proportions of magnetite ultra-high performance concrete (kg / m³) 3 )

[0056] Note: (1) The water-cement ratio is uniformly 0.19, the water-reducing agent content is 1% of the mass of cementitious materials, and the dispersant dosage is 0.3% of the cement weight. (2) Magnetite 1 is 0.0-0.6mm magnetite, and magnetite 2 is 0.6-1.18mm magnetite; river sand 1 is 0.0-0.6mm river sand, and river sand 2 is 0.6-1.18mm river sand.

[0057] 2. Specimen preparation and curing (1) Specimen preparation The test procedure for carbon-doped steel fiber MUHPC is as follows: Step 1: Accurately measure the amount of each material in the experimental mix design using an electronic scale; Step 2: First, dissolve the dispersant in half of the test water volume while stirring. The solution will gradually become thicker. Continue to add carbon fiber while stirring. Finally, put it into a mixer to prepare a mixture of (water + dispersant + carbon fiber). Step 3: Add the remaining test water and water-reducing agent to the beaker, and use a glass rod to quickly prepare a (water + water-reducing agent) mixture for 30 seconds; Step 4: Pour the river sand and magnetite into the mixer and dry mix at low speed for 60 seconds; Step 5: Add silica fume, cement, and fly ash to the mixture of river sand and magnetite, and dry mix at low speed for 60 seconds; Step 6: Once the mixture is thoroughly stirred, slowly add the liquid mixture (Step 2 + Step 3) and continue stirring for 60-120 seconds; Step 7: Finally, add the steel fiber, stir at low speed for 30 seconds, then stir at high speed for 30 seconds; Step 8: Pour the freshly mixed UHPC slurry into a 40mm×40mm×160mm mold, vibrate it on a vibrating table for 10-15 seconds, and finally use a spatula to scrape off the excess mixture on the surface of the mold and smooth the surface of the test block.

[0058] (2) Specimen curing It mainly includes the following steps: Step 1: Cover each prepared test block with plastic wrap to reduce moisture evaporation, affix the corresponding group label, and place it in a normal indoor environment for 24 hours to cure. Step 2: After molding for 24 hours, remove the molded specimen and demold it. Be careful during demolding to avoid damaging the specimen. Mark each specimen with the prepared waterproof wax pen to ensure that the marks will not disappear after 28 days of curing. Step 3: Place the marked test blocks in water and continue curing until the required curing age is reached.

[0059] This study uniformly used prism specimens with dimensions of 40mm×40mm×160mm and employed a microcomputer universal testing machine with a maximum load range of 600kN. (Test equipment and loading devices are as follows...) Figure 2 As shown, uniaxial compression tests were conducted on specimens cured for 28 days. Due to the high strength of UHPC, the descent segment of the uniaxial compressive stress-strain curve of concrete was difficult to capture, and sudden brittle failure easily occurred after reaching the peak value, leading to test failure. Therefore, force-controlled and displacement-controlled loading were adopted. The loading rate before the peak load was 0.1 kN / s, and the loading rate was reduced to 0.05 mm / min when the loading reached near the peak value until the specimen's bearing capacity was completely failed. The displacement value synchronized with the stress was taken as the average value of the displacement measurement results before and after the stress.

[0060] Load data is acquired using tension and compression sensors, and displacement data is acquired using displacement sensors. The sampling frequency is 2Hz, and DIC non-contact measurement technology is used simultaneously. An inverse combined Gauss-Newton algorithm is employed in the digital image. In each step of the inverse algorithm's iterative process, a reference region is used to approximate the deformation zone, and the deformation zone is continuously changed in reverse, ultimately achieving sub-region registration. This is a method for measuring surface strain and deformation of an object. Initially, the specimen needs to undergo speckle processing. This method tracks the deformation process of the speckle pattern on the object's surface, calculates the change in the grayscale value of the speckle threshold, and thus obtains real-time load and deformation displacement information of the specimen.

[0061] DIC (Displacement and Strain Measurement) is a non-contact, full-field displacement and strain measurement technology based on computer vision. Its core principle is to reconstruct the three-dimensional deformation field of an object's surface by tracking the deformation of random speckle patterns on the surface, combined with image processing and numerical algorithms, to obtain full-field displacement and strain data. The system equipment includes a high-resolution camera and a light source. The camera is used to capture images of the analysis area of ​​the specimen during loading, and the light source provides uniform illumination.

[0062] DIC can perform deformation measurement through the following steps, the specific process is as follows: (1) Preparation of speckled patterns; (2) Set the region of interest (ROI) and perform system calibration; (3) Image acquisition, extracting the gray values ​​of pixel (x, y) in the reference sub-region and the target sub-region; (4) Image analysis, calculating the residuals between the reference sub-region and the deformed sub-region; (5) Calculate the deformation increment of p in each iteration, and apply the increment back to the parameters of the reference subregion; (6) Terminate when the residual change reaches the maximum number of iterations.

[0063] This article describes the creation of speckled patterns on the test specimen surface using a manual spray painting method. The procedure is as follows: Select a relatively smooth side of the specimen. First, apply a uniform coat of white matte paint to ensure even and complete coverage. After allowing the surface to solidify, apply a misting spray of black matte paint, allowing the sprayed liquid to drip naturally onto the specimen surface, ensuring even distribution of the black speckled spots. Continue to allow the surface to cure completely. Figure 3 As shown.

[0064] When loading begins, a high-speed camera is simultaneously activated to acquire images at a rate of 2 frames per second (2 images per second). This process is used to acquire calibration images, speckle images, and record the entire loading process. The images are then stored in the computer. When loading ends, both the universal testing machine and the DIC acquisition device stop simultaneously.

[0065] Based on real-time monitoring data of the uniaxial compression failure process of MUHPC using DIC digital image correlation technology, and combined with the evolution characteristics of the surface displacement field of the specimen, the entire compression process can be divided into three typical evolution stages: The first stage is the linear elastic response stage: when the stress level is below the proportional limit, the displacement gradient distribution across the entire specimen is uniform, the material is in the linear elastic region, the displacement contour plot shows a continuous gradual change, and basically no macroscopic crack initiation is observed. The second stage is the stable crack propagation stage, that is, when the load reaches the critical threshold (about 75%-85% of the peak load), a local distortion region appears in the displacement field, indicating that microcracks focus and propagate directionally at the fine aggregate-matrix interface. At this time, the stress-strain curve shows nonlinear hardening characteristics. The third stage is the unstable crack propagation stage, that is, after the peak load, the displacement contour plot shows the formation of the main crack zone. At this time, the crack develops rapidly and is unstable, accompanied by severe strain localization. The crack propagates along the direction of the maximum shear stress, eventually leading to specimen failure and a significant reduction in bearing capacity.

[0066] From a micromechanical perspective, the failure mechanism of MUHPC can be explained as follows: under initial loading, micropore compaction and interface debonding occur within the matrix; as damage accumulates, microdefects expand through fractal structures to form penetrating damage channels; when the accumulated damage reaches the critical energy release rate, the structure becomes unstable, manifested as a sharp drop in macroscopic mechanical parameters. This process conforms to the typical damage evolution law of quasi-brittle materials.

[0067] Example: Study on the uniaxial compressive mechanical properties of fiber-reinforced magnetite ultra-high performance concrete 1. Uniaxial compressive failure state and analysis process Based on the experimental phenomena observed during the uniaxial compression failure process of MUHPC, and combined with the analysis of the real-time monitoring screen of DIC, the vertical displacement contour map of the specimen was obtained, such as... Figure 4 As shown in -6.

[0068] MUHPC prisms exhibit two typical failure modes during uniaxial compression tests. Carbon fiber-infused UHPC shows burst failure, with cracks penetrating the entire specimen, such as... Figure 4 As shown, MUHPC with added steel fibers and with mixed carbon-steel fibers developed vertical cracks near the center of the specimen. Multiple fine micro-cracks were observed at the crack sites. Because the steel fibers hindered crack propagation, the entire specimen remained relatively intact upon failure. Figure 5 And 6.

[0069] During uniaxial compression tests on MUHPC with single carbon fiber doping, the elastic modulus increased during the load rise phase due to the high modulus properties of carbon fiber. Its failure mode is as follows: Figure 4 (a)-(d) The peak strain is maximized when the doping concentration is 0.30%-0.45%. Carbon fiber significantly improves stiffness, but the peak strain is generally low, reflecting the brittle characteristics of carbon fiber reinforced materials.

[0070] During uniaxial compression tests on MUHPC with single steel fiber doping, the uniaxial compressive failure mode of the steel fiber-doped MUHPC was ductile failure, and its failure mode was as follows: Figure 5 (a)-(d) The specimens went through three stages: matrix cracking, fiber bridging, and fiber breakage / pull-out. Therefore, they were still able to withstand a certain load before final failure and did not experience sudden collapse. This phenomenon became more pronounced with the increase of steel fiber content. The incorporation of steel fibers can significantly improve the toughness and crack resistance of MUHPC, ensuring the integrity of the specimens during the compression process.

[0071] MUHPC incorporating hybrid fibers exhibits a synergistic reinforcement effect during uniaxial compression failure. The failure mode is also ductile failure, as shown in Figures 6(a)-(p). In the initial loading stage, i.e. s / s max When the modulus of elasticity is less than 0.8, the concrete matrix is ​​in an elastic deformation state, and the carbon fiber, due to its high modulus of elasticity, bears the load first and inhibits the initiation of microcracks; as the external load increases, i.e., 0.8 < s / s max When the load is less than 0.9, longitudinal cracks gradually form in the matrix. At this point, the steel fibers slow down crack propagation through the bridging effect, while the carbon fibers limit crack width growth through interfacial bonding, forming a densely distributed microcrack network. MUHPC exhibits nonlinear properties. When the load approaches its peak value, i.e. s / s max When the value is greater than 0.9, the steel fiber undergoes plastic deformation and is partially broken, while the carbon fiber gradually breaks due to its brittle properties. However, the combined effect of the two causes the crack propagation path to be tortuous, significantly improving the energy absorption capacity. The main surface crack is blocked by the fiber into multiple micro cracks, and the damaged surface is rough with traces of fiber pull-out and breakage.

[0072] The two types of fibers, through multi-stage inhibition of crack propagation, transform MUHPC from brittle fracture to ductile failure, thereby improving its compressive toughness. The final failure mode of MUHPC is significantly correlated with the steel fiber content; the higher the steel fiber content, the more microcracks there are and the smaller the crack width.

[0073] 2. Analysis of uniaxial compressive stress-strain curves The stress-strain curve of MUHPC with single carbon fiber doping under uniaxial compression exhibits a steep drop characteristic, such as... Figure 7 As shown in (a), during the initial loading stage, due to its high elastic modulus and its collaborative load-bearing with the concrete matrix, the slope of the elastic stage is significantly increased compared to ordinary concrete, effectively suppressing microcrack initiation and resulting in an extended linear deformation stage. The effect of single-component steel fiber on the stress and deformation development of MUHPC is minimal in the ascending stage, as shown in (a). Figure 7 As shown in (b), the peak stress increases linearly with increasing steel fiber content, but the elastic modulus gradually decreases, possibly due to uneven fiber distribution caused by the random distribution of steel fibers or weakened interfacial bonding. With the continuous increase of external load, steel fibers effectively constrain the displacement development of the material shear interface through energy dissipation mechanisms, playing a bridging role in microcrack propagation.

[0074] Figure 8 (a)-(d) show the stress-strain curves of each carbon-steel fiber-modified MUHPC specimen obtained from the uniaxial compression test. It can be clearly seen that when a fixed CF dosage is maintained, all hybrid fiber MUHPC specimens exhibit similar curve characteristics before the peak stress, regardless of the CF dosage. After the peak load, the slope (absolute value) of the descending segment decreases with increasing CF dosage. This indicates that the addition of CF can delay specimen failure. Furthermore, it is noted that... Figure 8 In (c), the slope of MUHPC with 0.6% CF doping is very similar to that of MUHPC with 0.45% CF doping, and is even greater than the slope of MUHPC with 0.45% CF doping. This means that excessive CF doping will affect the performance of MUHPC. When the CF doping is fixed, MUHPC with SF doping varying from 0.5%, 1.0%, 1.5%, to 2.0% will, except... V cf When the SF content is 0.15%, the peak stress decreases from 112.99 MPa to 108.43 MPa when the SF content increases from 1% to 1.5%. The peak stress of the other groups of specimens increases with the increase of SF content.

[0075] The elastic modulus is an important indicator for evaluating the deformation capacity of materials in structural design. Among them, the initial modulus... E 0 is 0.5 MPa - 1 / 3 f cr Elastic modulus at time, secant modulus E c 0.5 MPa - 40% f cr The elastic modulus at stress can be calculated using equations (a) and (b), which determine the shape characteristics of the rising segment of the stress-strain curve of concrete. The peak stress, peak strain, and elastic modulus of each specimen are shown in Table 10. Table 10 shows that the elastic modulus of MUHPC increases with the increase of carbon fiber and steel fiber content.

[0076] (a) in s 1 = 0.5 MPa s 2 = 1 / 3 f cr , e1 、e 2 are respectively the corresponding s 1、 s The strain value of 2.

[0077] (b) In the formula s 1 = 0.4 MPa s 2 = 0.4 f cr , e 1. e 2 are respectively the corresponding s 1. s The strain value of 2.

[0078] Table 10 Uniaxial compressive properties of MUHPC specimens

[0079] Peak stress reflects the strength of concrete and is one of the important mechanical parameters for determining the stress-strain constitutive model. The peak stress of MUHPC (… f cr The compressive strength of concrete increases with increasing steel fiber content, consistent with the previously measured variation in compressive strength of each group of concrete. f cr It shows an upward trend, with S2.0C0.60 being higher than S0.0C0.60. f cr It increased by 36.57%; carbon fiber can slightly reinforce the specimens. f cr， However, when the dosage is 6%, agglomeration is prone to occur, reducing the quality of the specimen. f cr For example, S0.0C0.45 f cr It can reach 115.23 MPa, while S0.0C0.60 f cr It is only 93.75 MPa.

[0080] Furthermore, the shape and envelope area of ​​the uniaxial compressive stress-strain curve of concrete can reflect the material's plastic deformation capacity and toughness. Hybrid fibers significantly improve the compressive toughness of concrete through complementary multi-scale reinforcement and energy dissipation pathways. Figure 7 (a) In the single-fiber-doped system, the effect of the fiber on the elastic modulus is not significant. However, when the carbon fiber content is 0.30% and 0.45%, the stress and strain increase, and the envelope area increases somewhat. Figure 7(b) In the single-fiber-doped system, the envelope area increases with increasing fiber content, reaching a peak at 2% steel fiber content. In the hybrid fiber system, steel fibers dominate macroscopic crack bridging, while carbon fibers suppress microcracks. Due to the enhanced synergistic effect of the two fibers, the envelope area is significantly increased.

[0081] 3. Establishment of constitutive relations for uniaxial compression The stress-strain curve relationship is a key parameter of structural mechanical performance. A complete stress-strain curve can reflect the macroscopic response of a series of changes in the structure at various loading stages, such as deformation, microcrack development, ultimate strength, residual stress after peak stress, surface damage, and final failure mode.

[0082] (1) MUHPC Uniaxial Compression Constitutive Model Ordinary concrete exhibits brittle failure after reaching peak load under uniaxial compression, with rapid propagation of macroscopic cracks. The loading rate is difficult to control after the specimen reaches its ultimate load. Displacement loading using a universal testing machine can obtain a complete stress-strain curve, including the descending segment. After adding fiber (CF) and fiber styrene (SF), the specimens showed varying degrees of ductile failure, and the stress-strain propagation rate in the descending segment was controlled. Experiments show that the stress-strain curve of MUHPC is similar in shape to that of ordinary concrete. Therefore, this paper introduces a fiber factor based on a typical compression constitutive model. F =1.2 Vl / d When hybrid fibers are incorporated, the fiber factor can be added together with the fiber factors of carbon fiber and steel fiber, i.e. F = F sf + F cf The parameters of the rising and falling segments are obtained by fitting using equation (c). α and β， Substituting this into the typical constitutive equation under pressure (d), we can further predict the stress-strain curve using equation (e).

[0083] (c) (d) in, y = s / s cr , x = y / y cr For dimensionless stress and strain, s , e and e cr These represent the stress, strain, and peak strain of the concrete, respectively.

[0084] Introducing fiber factors F Then, the constitutive model can be expressed as: (e) (2) Parameter fitting of MUHPC uniaxial compressive stress-strain curve Once the parameters of the rising and falling segments of the MUHPC uniaxial compression constitutive model are determined... α and β Its stress-strain constitutive model can be determined by equation (e). Parameters corresponding to MUHPC with different fiber content. α and β See Table 11. The constitutive model matches the rising segment of the stress-strain curves of each group of concrete well. e < e cr As the fiber content increases, the softening segment of the stress-strain curve ( e > e cr The measured data and the model calculation results show slight deviations, as shown in Figure 9. The error increases with the increase of fiber content, the linear elastic deformation stage of the stress-strain curve increases, and the stress-strain curve becomes flatter. The deformation capacity of MUHPC is significantly enhanced with the increase of fiber content.

[0085] Table 11 Constitutive Parameters α、β、F

[0086] With the parameters of each segment now defined, the MUHPC uniaxial compression constitutive model, which considers fiber content and fiber parameters, was compared with the stress-strain curves obtained from experiments, as shown in Figure 9. The model exhibits a high degree of agreement, indicating its good rationality.

[0087] Given that the properties and mix proportions of MUHPC materials are known, but the peak strength and elastic modulus are unknown, the mechanical properties and mechanical state of the proposed, researched, and existing MUHPC materials can be predicted according to Equation (e).

[0088] Although some preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0089] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from the spirit and scope of its inventive concept. Therefore, if these modifications and variations of the invention fall within the scope of the claims of this application and their equivalents, the invention is also intended to include these modifications and variations.

Claims

1. A method for constructing a predictive model for the mechanical properties of hybrid carbon-steel fiber magnetite ultra-high performance concrete, comprising the following steps: S1: preparing hybrid carbon-steel fiber magnetite super high performance concrete test pieces with different fiber contents in multiple groups; wherein, The matrix of the ultra-high performance concrete includes cement, silica fume, fly ash, river sand, magnetite aggregate, mixing water, water-reducing agent and dispersant; the fibers include carbon fiber and steel fiber, and the volume content of carbon fiber and steel fiber in each group of specimens is different. S2: Perform uniaxial compression tests on each group of specimens, collect stress and strain data of each group of specimens throughout the entire loading process to failure, and plot the stress-strain curves of each group of specimens based on the stress and strain data. S3: Determine the peak stress of each group of specimens based on the complete stress-strain curves. σ cr and the corresponding peak strain ε cr ; S4: Introducing fiber factors to characterize the combined effects of carbon fiber and steel fiber content and geometric characteristics on the mechanical properties of concrete. F ; S5: Based on the typical constitutive model under pressure, utilizing the aforementioned fiber factor F For the rising segment parameters of the constitutive model α and descent parameters β Make corrections and establish a dimensionless stress. y = σ / σ cr and dimensionless strain x = ε / ε cr The constitutive equation for variables is as follows: ； in, α and β All of them are the fiber factors F The function; S6: Based on the stress-strain curve data of each group of specimens, determine the parameters by fitting. α and β With fiber factors F The functional relationship between them is used to construct a predictive model for the mechanical properties of the hybrid carbon-steel fiber magnetite ultra-high performance concrete.

2. The construction method according to claim 1, characterized in that, In step S4, the fiber factor F Determined by the following formula: F=F sf +F cf ； in, F sf The fiber component of steel fiber, F cf The fiber factor of carbon fiber; the fiber factor of a single fiber is calculated according to the formula. F i = kV i l i / d i The calculation determines that, among which V i This refers to the volumetric content of the fiber. l i For the length of the fiber, d i The diameter of the fiber. k This is a correction factor related to fiber type.

3. The construction method according to claim 2, characterized in that, In step S5, the ascending segment of the constitutive equation is in the form of: f 1 ( x , α ) = αx + (3-2 α ) x 2 + ( α -2) x 3 The descent segment function is in the form of f 2 ( x , β ) = x / [ β ( x -1) 2 + x ].

4. The construction method according to claim 3, characterized in that, The carbon fiber is a short-cut carbon fiber with a length of 3 mm and a diameter of 7 μm, and its volumetric content is 0.15%~0.6%; the steel fiber is a copper-plated micro-steel fiber with a length of 13 mm and a diameter of 0.2 mm, and its volumetric content is 0.5%~2.0%; then the parameters are obtained by fitting. α and β With fiber factors F The functional relationship between them is as follows: 。 5. The construction method according to claim 4, characterized in that, Introducing fiber factors F Then, the constitutive model can be expressed as: ； in, y = σ / σ cr , x = ε / ε cr For dimensionless stress and strain, σ , ε and ε cr These represent the stress, strain, and peak strain of the concrete, respectively.

6. A method for predicting the mechanical properties of hybrid carbon-steel fiber magnetite ultra-high performance concrete, characterized in that, Includes the following steps: P1: Obtain the material mix proportion parameters of the carbon-steel fiber magnetite ultra-high performance concrete to be predicted, including at least the volume content of carbon fiber, the geometric parameters of carbon fiber, the volume content of steel fiber, and the geometric parameters of steel fiber. P2: Calculate the fiber factor based on the parameters obtained in step P1. F ; P3: Calculate the fiber factor obtained in step P2. F Substitute the parameters determined by the construction method according to any one of claims 1 to 5 α and β With fiber factors F In the functional relationship, the corresponding calculation is obtained. α and β value; P4: The result obtained in step P3 α and β Substituting the values ​​into the constitutive equation according to any one of claims 1 to 5, the dimensionless stress-strain relationship of the concrete to be predicted is obtained; P5: Obtain the peak stress of the concrete to be predicted σ cr and peak strain ε cr By combining the dimensionless stress-strain relationship obtained in step P4, the full stress-strain curve of the concrete to be predicted is obtained, thereby realizing the prediction of the mechanical properties of the concrete.

7. The prediction method according to claim 6, characterized in that, In step P5, the peak stress σ cr and peak strain ε cr The method is determined through material testing or estimated using empirical formulas based on the mix proportion parameters of the concrete to be predicted.

8. A method for monitoring damage in hybrid carbon-steel fiber magnetite ultra-high performance concrete structures, characterized in that, Includes the following steps: M1: A mechanical property prediction model for the hybrid carbon-steel fiber magnetite ultra-high performance concrete of the target structure is constructed, and the prediction model is obtained by the construction method according to any one of claims 1 to 5; M2: During the service life of the target structure, the resistivity data of the concrete is collected in real time or periodically; M3: Based on the resistivity data collected in step M2, and combined with the pre-generated correspondence between resistivity change rate and stress / strain, determine the actual stress / strain state of the target structure at the current moment; M4: Substitute the actual stress / strain state determined in step M3 into the mechanical performance prediction model constructed in step M1 to predict the damage evolution trend and remaining bearing capacity of the target structure under the current stress / strain state. M5: Based on the prediction results of step M4, assess the safety status of the target structure and issue an early warning signal when the predicted damage level exceeds a preset threshold.

9. The prediction method according to claim 8, characterized in that, In step M2, the resistivity data is collected by electrodes embedded in the concrete or by surface contact electrodes; in step M3, the relationship between the resistivity change rate and stress / strain is determined in advance by calibration tests or estimated by empirical formulas based on the amount of carbon fiber and steel fiber in the concrete.

10. A method for determining the mix proportion of hybrid carbon-steel fiber magnetite ultra-high performance concrete, characterized in that, Includes the following steps: D1: Set the target mechanical performance indicators of the concrete, including at least the target peak stress and the target peak strain; D2: Constructing with fiber factors F A mechanical performance prediction model with independent variables, wherein the prediction model is obtained by the construction method according to any one of claims 1 to 5; D3: Based on the target mechanical performance index set in step D1, calculate the required fiber factor. F The range of values ​​for ; D4: Fiber factor determined in step D3 F Within the range of values, various combinations of carbon fiber and steel fiber dosages are determined, wherein the dosage combinations satisfy the constraints of carbon fiber volume dosage of 0.1% to 0.8% and steel fiber volume dosage of 0.3% to 2.5%. D5: From the various admixture combinations determined in step D4, select the optimal admixture combination that meets the preset workability and / or economic requirements as the mix proportion of the target concrete.

Images