Construction and application of the force-electric response model for ultra-high performance cement-based composite materials

Abstract

This invention relates to the construction and application of a force-electric response model for ultra-high performance cement-based composite materials, aiming to solve the problem that existing self-sensing ultra-high performance cement-based composite materials lack quantitative force-electric constitutive relationships and are difficult to use for accurate structural health monitoring. By preparing magnetite ultra-high performance concrete specimens with different fiber contents, uniaxial compression tests are conducted to simultaneously collect stress-strain and resistivity change data. A quantitative relationship model between strain and resistivity change rate is constructed based on a Gaussian function, and a material proportioning optimization method and a resistivity-strain monitoring method are established based on the model's goodness of fit. This invention achieves a leap from qualitative description to quantitative characterization of force-electric response and dynamic identification of structural damage states, making concrete itself a sensor. While maintaining its radiation shielding function, it also endows the material with pressure-sensitive sensing capabilities. It features high accuracy, low cost, and strong applicability, and can be applied to structural health monitoring of infrastructure such as nuclear power plants, dams, and bridges.

Description

Technical Field

[0001] This invention relates to the field of building materials technology, specifically to the construction and application of a force-electric response model for ultra-high performance cement-based composite materials. Background Technology

[0002] Structural health monitoring is a key technology for ensuring the long-term safe operation of critical infrastructure, with accurate stress and strain monitoring being particularly important. Traditional strain monitoring mainly relies on embedded sensors such as fiber optic sensors, piezoelectric ceramics, and resistance strain gauges. However, these sensors face challenges in practical engineering applications, including insufficient sensitivity, poor compatibility with concrete substrates, limited durability, and high cost, which restricts their large-scale adoption in large and complex civil structures.

[0003] To address the aforementioned issues, existing technologies have proposed utilizing the piezoresistive effect of conductive fillers to prepare self-sensing cement-based composite materials, i.e., smart concrete. By incorporating conductive phases such as carbon fibers, steel fibers, or carbon nanotubes into the concrete, it is made capable of sensing its own strain and damage. In recent years, ultra-high performance concrete has been widely used in major engineering projects due to its superior mechanical properties and durability, making the endowment of it with self-sensing capabilities a research hotspot.

[0004] However, current research on self-sensing ultra-high performance concrete mainly focuses on exploring material formulations, lacking a deep understanding and quantitative description of its mechanical-electrical response behavior. Specifically, existing technologies still have the following shortcomings: First, there is a lack of quantitative force-electric constitutive relations: existing research mostly focuses on qualitative descriptions of the pressure-sensitive phenomenon, that is, it remains at the level of "load causing a change in resistance," and has failed to establish a constitutive model that can accurately characterize the quantitative relationship between strain and the rate of change of resistivity. This makes it difficult for self-sensing concrete to directly provide accurate strain monitoring data for actual engineering projects, and it is impossible to achieve a quantitative assessment of the structural state.

[0005] Secondly, the model construction method is imperfect: the data processing of the electrical response of self-sensing concrete in the existing technology mostly adopts linear fitting or simple polynomial fitting, which makes it difficult to accurately describe the complex resistance change law of the material in the whole process of loading (from the elastic stage to crack propagation and failure). The fitting accuracy is low and the model has poor universality.

[0006] Third, the monitoring methods are disconnected from the model: most existing monitoring methods are isolated resistance measurements, which fail to couple the real-time collected electrical data with the pre-established force-electric model, and cannot realize the inversion mapping from "electrical signal" to "mechanical state". The monitoring results lack the support of theoretical models.

[0007] Fourth, there is a lack of reverse application of models: existing materials research and development relies heavily on trial and error, making it difficult to use the force-electric response characteristics as an evaluation index to guide the optimization of the conductive phase doping ratio, resulting in low efficiency in materials research and development and difficulty in synergistic optimization of performance.

[0008] Given the above challenges, there is an urgent need to develop and construct a constitutive model that can accurately describe the mechanical-electrical response behavior of self-sensing ultra-high performance cement-based composite materials, and to realize quantitative assessment of structural health monitoring and intelligent optimization of material proportions based on this model.

[0009] 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

[0010] This invention addresses the technical problem that existing self-sensing ultra-high performance cement-based composite materials lack quantitative force-electric constitutive relationships and are difficult to achieve accurate structural health monitoring. It adopts a key technical means based on Gaussian functions to construct a quantitative relationship model between strain and resistivity change rate, realizing the inversion monitoring from electrical signals to mechanical states and damage stage diagnosis, and achieving the technical effect of improving the material's self-sensing ability from qualitative description to quantitative assessment.

[0011] To achieve the above objectives, this invention, through systematic experimental research, reveals the force-electric response characteristics of magnetite ultra-high performance concrete under different fiber dosages. Based on a modified Andreasen and Andersen continuous packing model, mix design was conducted to prepare single-component and mixed-component specimens with carbon fiber volume content of 0.15%–0.6% and steel fiber volume content of 0.5%–2.0%. Stress-strain data and resistivity change data were simultaneously collected through uniaxial compression tests, and stress-strain curves and resistivity change rate-strain curves were plotted. According to the effective medium theory, compressive load leads to a decrease in fiber spacing, causing electrons to jump between adjacent fibers, forming local conductive paths, thereby causing resistivity changes. Experimental results show that different fiber types and dosages... ε-FCR The curve shows a high correlation with the Gaussian function model, and the coefficient of determination is high. R 2 All values ​​are above 0.9, indicating that the Gaussian function can describe the signal well. FCR The law governing strain variation was investigated. Based on these findings, a strain monitoring method was further developed to realize real-time strain retrieval of structures based on resistivity changes.

[0012] The first aspect disclosed in this application provides a method for constructing a force-electric response model of an ultra-high performance cement-based composite material, comprising the following steps: (1) Preparation of ultra-high performance cement-based composite material specimens containing conductive functional phases; (2) Apply monotonic or cyclic loads to the specimen and simultaneously collect the mechanical and electrical parameters under the loads. The mechanical parameters include at least compressive strain. ε The electrical parameters include at least resistivity; (3) Calculate the rate of change of resistivity at different strain times based on the electrical parameters. FCR ; (4) With the aforementioned compressive strain ε As the independent variable, the rate of change of resistivity FCR Using Gaussian function as the dependent variable, a constitutive model as shown in equation (I) is established through curve fitting, and the model parameters are determined such that the correlation coefficient between the model curve and the experimental data is greater than a preset threshold. (I) Where A, B, and C are the fitting parameters.

[0013] In some embodiments of this disclosure, the conductive functional phase includes a hybrid system of carbon fiber and steel fiber, and magnetite, steel slag, or conductive minerals with a semiconductor oxide layer on their surface as fine aggregates.

[0014] In some embodiments of this disclosure, the carbon fiber content accounts for 0.15% to 0.6% of the total volume of the cement-based composite material, and the steel fiber content accounts for 0.5% to 2.0% of the total volume of the cement-based composite material.

[0015] The second aspect of this application discloses a method for health monitoring of ultra-high performance cement-based composite material structures, comprising: S1: Electrodes are set on the structure under test, and the electrical parameters of the structure are collected in real time during service. The real-time resistivity change rate is then calculated. FCR real ; S2: Obtain a pre-constructed force-electric response model, as shown in Equation (I), which characterizes the mapping relationship between strain and resistivity change rate of the material used in the structure; S3: The real-time resistivity change rate FCR real The force-electric response model is input, and the real-time strain value of the structural component is obtained through model inversion. ε real ; S4: Based on the real-time strain value ε real The damage status of the structural components is assessed by observing their changes and trends.

[0016] In some embodiments of this disclosure, step S3, the model inversion further includes: According to the real-time resistivity change rate FCR real The stress stage of the structural component is determined by the segment in the force-electric response model curve. The stress stage includes: a linear decreasing stage corresponding to the lossless elastic period, a stable stage corresponding to the stable microcrack propagation period, and an increasing stage corresponding to the unstable crack propagation period.

[0017] The third aspect disclosed in this application provides a structural health monitoring system for ultra-high performance cement-based composite materials, comprising: Electrode modules, mounted on ultra-high performance cement-based composite material structural components, are used to collect electrical signals; A data acquisition module, connected to the electrode module, is used to acquire the electrical parameters of the structural component in real time and calculate the real-time resistivity change rate based on the electrical parameters. FCR real ; The storage module stores the constructed force-electric response model. The processing module is communicatively connected to both the data acquisition module and the storage module, and is configured as follows: Receive the real-time resistivity change rate FCR real ; Call the force-electric response model in the storage module; The FCR real Substituting the values ​​into the model, the corresponding real-time strain values ​​are obtained through inversion calculation. ε real ; Output the real-time strain value ε real Or based on the damage assessment results generated by it.

[0018] In some embodiments of this disclosure, the electrode module is a four-electrode system, including two external current electrodes and two internal voltage electrodes, and the data acquisition module includes a DC regulated power supply and a multi-channel data acquisition instrument for realizing DC four-electrode measurement.

[0019] The fourth aspect disclosed in this application provides a method for optimizing the mix proportion of ultra-high performance cement-based composite materials, comprising: Multiple sets of force-electric response models under different fiber doping amounts were constructed according to the method described above; Compare the fitting parameters A, B, C and the fitting correlation coefficient of each model group. R 2 ; Based on the fitted correlation coefficient R 2By maximizing and modeling the curve characteristics, the optimal fiber content ratio that combines mechanical and pressure-sensitive properties is determined.

[0020] The fifth aspect disclosed in this application provides an ultra-high performance cement-based composite material with self-sensing properties, whose compressive strain under uniaxial compressive load is... ε With resistivity change rate FCR The relationship between them conforms to the following equation: ,

[0021] Where A, B, and C are the fitting parameters; The cement-based composite material includes cementitious materials, magnetite aggregate, and hybrid fibers, wherein the hybrid fibers include carbon fibers and steel fibers.

[0022] In some embodiments of this disclosure, the volume replacement rate of the magnetite aggregate is 40% to 80%; the volume content of the carbon fiber is 0.15% to 0.6%; and the volume content of the steel fiber is 0.5% to 2.0%.

[0023] 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 unified mechanical-electrical response model for ultra-high performance cement-based composite materials was constructed, achieving a leap from qualitative description to quantitative characterization: For the first time, Gaussian functions were introduced into the field of self-sensing ultra-high performance cement-based composite materials, and a strain model as shown in Equation (I) was established. ε With resistivity change rate FCR A quantitative constitutive relationship model between them. This model can not only accurately fit experimental data (fitting correlation coefficient) R 2 With optimized proportions, the ratio can reach above 0.9, even approaching 1. More importantly, it can fully describe the three-stage response characteristics of the material during the entire process of uniaxial compressive loading: the linear descent stage corresponds to the lossless elastic period, the steady stage corresponds to the stable propagation period of microcracks, and the rising stage corresponds to the unstable propagation period of cracks. The establishment of this quantitative model fills the gap in the existing technology of lacking accurate force-electric constitutive relations, and lays the theoretical foundation for self-sensing concrete to move from laboratory research to engineering applications.

[0024] 2. A material ratio optimization method based on model fit goodness of fit is provided: the correlation coefficient of the model fit is used as the basis for the optimization. R 2Maximizing the fiber content as an evaluation metric, combined with model curve characteristics, guides the optimization of fiber content ratios. This method changes the traditional material development model that relies on trial and error, establishing a closed-loop feedback mechanism of "performance evaluation - ratio optimization". For example, based on the model construction method of this invention, hybrid fiber ratios with both excellent mechanical and pressure-sensitive properties can be quantitatively screened, significantly improving the efficiency and scientific rigor of material development.

[0025] 3. A resistivity-based strain monitoring method was established: using a force-electric model as the calibration curve, the structural strain was inverted by real-time acquisition of resistivity data, making the concrete itself a sensor, thus avoiding the defects of poor compatibility and insufficient durability of traditional embedded sensors with the substrate.

[0026] 4. Dynamic identification of structural damage state was achieved: utilizing... FCR-ε The model curve exhibits a three-stage characteristic of "decline-stable-rise," which can identify the damage evolution process of a structure from elastic operation and microcrack initiation to macrocrack propagation in real time, providing an intuitive criterion for engineering safety early warning.

[0027] 5. The model possesses broad applicability and scalability, providing a unified framework for performance evaluation of different types of conductive phase materials: the constructed Gaussian function force-electric model is not only applicable to carbon fiber-steel fiber hybrid systems, but can also be extended to other types of conductive phases (such as single fibers, nano-carbon materials, etc.) and functional aggregates (such as magnetite, steel slag, etc.). This unified analytical framework provides a standardized tool for the performance comparison, evaluation, and optimization of self-sensing concrete with different formulations, possessing significant academic value and promising engineering application prospects. Attached Figure Description

[0028] 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.

[0029] Figure 2 This is a pressure-sensitive performance testing device in one embodiment of this application.

[0030] Figure 3 Stress-strain of MUHPC with different steel fiber content in one embodiment of this application (…) σ-ε ), strain-resistivity ( ε-FCR(a) curves; where the volumetric steel fiber content in (a)-(d) is 0.5%, 1.0%, 1.5%, and 2.0%, respectively.

[0031] Figure 4 MUHPC strain with different steel fiber content in one embodiment of this application ( ε -Resistivity FCR Experimental data and fitting curves of the relationship; where the volumetric steel fiber content in (a)-(d) is 0.5%, 1.0%, 1.5%, and 2.0%, respectively.

[0032] Figure 5 Stress-strain of MUHPC with different carbon fiber content in one embodiment of this application (…) σ-ε ), strain-resistivity ( ε-FCR The curves are shown; where the carbon fiber volume content of (a)-(d) is 0.15%, 0.30%, 0.45%, and 0.60%, respectively.

[0033] Figure 6 MUHPC strain with different carbon fiber content in one embodiment of this application ( ε -Resistivity FCR Experimental data and fitting curves of the relationship between (a) and (d) carbon fiber volume fractions are 0.15%, 0.30%, 0.45%, and 0.60%, respectively.

[0034] Figure 7 shows the stress-strain relationship of hybrid fiber MUHPC in one embodiment of this application. σ-ε ), strain-resistivity ( ε-FCR ) curves (including Figure 7-1 , 7-2 ); among them, (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.

[0035] Figure 8 shows the strain of hybrid fiber MUHPC in one embodiment of this application. ε -Resistivity FCR Experimental data and fitted curves of the relationship (including) Figure 8-1 , 8-2 ); among them, (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.

[0036] Figure 9 This is a schematic diagram of the pressure-sensitive performance mechanism of fiber-reinforced MUHPC in one embodiment of this application. Detailed Implementation

[0037] 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.

[0038] 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. (e.g., ...) Figure 1 A, whose main chemical components and performance indicators are shown in Table 1 and Table 2, respectively.

[0039] 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.

[0040] 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.

[0041] Table 1 Chemical composition of P.O 52.5 cement

[0042] Table 2 Performance Indicators of P.O 52.5 Cement

[0043] Table 3 Chemical composition of fly ash

[0044] Table 4 Chemical composition of silica fume

[0045] (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. The main component of magnetite is Fe, followed by Si.

[0046] Table 5 Chemical elements of magnetite

[0047] 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.

[0048] (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.

[0049] Table 6 Performance Indicators of Steel Fibers

[0050] 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 porosity 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.

[0051] Table 7 Performance Indicators of Carbon Fiber

[0052] (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.

[0053] (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.

[0054] Table 8 Performance Indicators of Methylcellulose

[0055] (6) Mixing ratio In this example, the modified Andreasen and Andersen (A&A) model was used as the continuous packing model for mix design. Specimens were prepared by replacing 60% of the river sand with magnetite. In this experiment, carbon fiber with a volumetric content of 0.15%, 0.3%, 0.45%, and 0.6%, and steel fiber with a volumetric content 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.

[0056] Table 9. Mix proportions of magnetite ultra-high performance concrete (kg / m³) 3 )

[0057] 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.

[0058] 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.

[0059] (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.

[0060] 3. Pressure sensitivity test and testing methods (1) Sample preparation Following the above-mentioned method for preparing fibrous magnetite ultra-high performance concrete, 24 mix proportions were designed, and 6 specimens were made for each mix proportion. The specimen size was 40mm×40mm×160mm, which were used to test the pressure-sensitive properties of MUHPC composite materials incorporating steel fibers and carbon fibers.

[0061] (2) Experimental process Once the sample reaches the curing age, it is removed from the curing room, dried, and immediately tested. The resistance and performance of the intelligent MUHPC are evaluated using the four-electrode DC electrode method. Figure 2This diagram illustrates a device for measuring resistance during uniaxial compression. In this device, four wires are connected to conductive tape at corresponding locations, and a direct current (DC) power supply is used to measure resistance. Outer electrodes A and D are connected to a high-precision DC regulated power supply, while inner electrodes B and C and their corresponding voltage values ​​are acquired by a KeysightDigit Multimeter multichannel automatic data acquisition and processing system. The resistance tends to stabilize when the electrode spacing reaches a certain threshold, and decreases as the electrode spacing increases. Using four probes with DC power supplies provides higher accuracy than using two probes with AC power supplies. The four-probe DC method also helps eliminate contact resistance during measurement.

[0062] A microcomputer-controlled universal testing machine with a maximum loading range of 600kN was used for compression loading. Before the test, the casting surface and the top and bottom ends of the specimen were ground with an angle grinder to improve flatness, and the thickness deviation at different locations of the specimen was controlled within ±0.2mm. Markings were made on the specimen with a marker. Considering that strain gauges are only effective before specimen failure, and the data becomes invalid after specimen failure due to damage, displacement gauges were used to calculate displacement changes. Fixtures and displacement gauges were installed 10mm from the top and bottom edges of the specimen longitudinally, ensuring a relatively uniform compression state at the middle 140mm. Strain data was automatically acquired using a dynamic signal analysis system (DHDAS-3821), and load data was acquired via a force sensor connected to computer software. The computer system can simultaneously acquire pressure and displacement data, ensuring synchronization of pressure and displacement acquisition. Simultaneously, current and voltage were measured using two digital multimeters. When applying uniaxial loading to the specimen, the loading rate was fixed at 0.05kN / s. The piezoresistive testing device is as follows: Figure 2 As shown. Resistivity change rate ( FCR The calculation formula is derived from (a): (a) in ρ Resistivity under applied load, ρ 0 represents the initial resistivity under no load. Since resistance tends to decrease under compression, FCR Typically, these values ​​are negative. Therefore, this study uses... FCR The absolute value is used to quantify the change in resistivity of the intelligent MUHPC under load.

[0063] To more intuitively analyze the resistivity change characteristics of concrete during uniaxial compression, relative resistivity is introduced, which can be calculated by equation (b).

[0064] (b) In the formula: ρ r Relative resistivity; ρ 0 represents the resistivity (Ω·mm) at the initial moment; ρ Let be the resistivity (Ω·mm) at any given time.

[0065] In addition, in order to determine the sensitivity of resistivity changes to external strain, the strain sensitivity coefficient SSC is calculated using equation (c).

[0066] (c) In the formula, ε This represents the strain of the material. This coefficient helps in understanding how the electrical properties of concrete change with mechanical strength.

[0067] Example: The effect of fibers on the pressure sensitivity of magnetite ultra-high performance concrete When a specimen is subjected to an external load, the conductive fibers exhibit pull-out and push-in phenomena as the crack closes, affecting the change in resistivity. Fiber-reinforced cementitious composites possess the ability to sense their own strain. This electrical phenomenon is called the piezoresistive effect (i.e., resistivity changes with strain). Different fiber types and fiber content have different effects on the piezoresistive properties of concrete.

[0068] Based on the existing tensile / compressive resistance model of self-sensing concrete, this example introduces different amounts of carbon fiber and steel fiber to endow MUHPC with the ability to sense its own strain, explores the influence of different amounts of carbon fiber and steel fiber on the resistivity change rate of MUHPC under loading and the sensitivity of the corresponding MUHPC specimen's pressure sensitivity, and finally establishes its strain and resistivity change rate force-electric model.

[0069] 1. Test results and analysis of the pressure sensitivity of MUHPC with single steel fiber doping (1) MUHPC with single steel fiber doping σ-ε and ε-FCR Curve characteristics During the uniaxial compression test, the load, axial displacement, and resistance were recorded in real time throughout the entire loading process, and later plotted as a stress-strain-resistivity change rate curve. Figure 3 The stress-strain relationship of single-doped SF (volume doping levels of 0.5%, 1.0%, 1.5%, and 2.0%) MUHPCs is presented. FCR The relationship between them. Each subgraph represents a MUHPC with different SF doping levels. σ-ε and ε-FCR The curve. This is visually reflected in the graph. FCR How does it change with the stress / strain of steel fiber MUHPC?

[0070] Furthermore, sensitivity is an important factor in evaluating the electrical conductivity of MUHPCs, and can be characterized by parameters such as the maximum magnitude of the resistivity change rate. Table 10 provides information on key parameters related to the intrinsic stress sensing characteristics of these MUHPCs. This table includes the maximum resistivity change rate (… FCR max The corresponding stress sensitivity coefficient, strain sensitivity coefficient, and stress / strain sensitivity coefficient of the linear elastic segment pressure sensitivity (for specific calculations, please refer to equation (c) in Chapter 2).

[0071] Under uniaxial compressive load FCR The trend of change can be divided into three stages. In the first stage (section AB), when the compressive stress is small, the resistivity decreases with the increase of load (its resistivity decreases with the increase of compressive stress, which is positive piezoresistive). FCR The growth is relatively steep. This is because the sample is under compression, and the cracks and pores inside the MUHPC matrix are compacted. Contact and tunneling effects exist between the fibers, leading to a decrease in the interfacial resistance between the fibers and the matrix. In the second stage (section BC)... FCR The growth of resistance gradually slows down because the overlapping fibers begin to separate as tiny cracks appear, disrupting the local conductive network and causing a slower rate of resistance decrease. In the third stage, as the cracks further extend, fiber separation occurs, increasing resistance and thus... FCR Gradually decrease.

[0072] Depend on Figure 3 It can be seen that with the increase of steel fiber content, the pressure sensitivity of MUHPC first decreases and then increases in the elastic stage, and the specific sensitivity values ​​can be seen in Table 10. MUHPC with a steel fiber content of 1.5% has the highest stress and strain sensitivity coefficients, exhibiting good pressure sensitivity.

[0073] Table 10 Sensitivity coefficients of MUHPC with single steel fiber doping K

[0074] (2) Establishment of the relationship between strain and resistivity change rate Steel fiber MUHPC FCR The curve exhibits a non-linear "U" or "V" shape, which is closely related to the deformation of the specimen and the changes in the conductive network. Firstly, in the non-damaging elastic stage, the compressive deformation of the specimen can compress the fibers, the conductive network of magnetite, and internal defects. This means that a decrease in the spacing between steel fibers can increase the probability of fiber overlap. In this stage... FCR The curve shows a downward trend. Secondly, when the strain continues to increase to the linear elastic deformation limit stage, that is, before the strain corresponding to the peak load, FCRThe curve remains stable. The third stage is the crack propagation stage. As cracks and damage accumulate, internal microcracks interconnect and develop into macroscopic cracks. The load continues to increase until the specimen fails. FCR Corresponding to the growth trend of the curve, SF enhances MUHPC. FCR The curves correspond well with the stress / strain curves.

[0075] Based on the curve characteristics of the resistivity change rate mentioned above, the relationship between strain and resistivity change rate of fiber MUHPC was established, as shown in equation (d). FCR The relationship between them follows an exponential function, and their stress-resistivity change rate curve is basically consistent with the strain-resistivity change rate curve. Therefore, strain- FCR The data was analyzed. Figure 4 For SF-doped MUHPC strain and FCR The experimental data and fitting curves of the relationship between strain and SF-reinforced MUHPC are shown in Table 11. The correlation coefficients of the fitting curves are in the range of 0.6-0.9. FCR The model relationship between them can be used as a calibration curve for pressure sensitivity.

[0076] (d) In the formula, FCR The rate of change of resistivity ε Let represent the compressive strain of MUHPC under uniaxial compression, and A, B, and C be fitting parameters.

[0077] Table 11 MUHPC with single steel fiber doping ε-FCR Relationship Fitting Parameters

[0078] 2. Test results and analysis of the pressure sensitivity of carbon fiber-doped MUHPC (1) Single-doped carbon fiber MUHPC σ-ε and ε-FCR Curve characteristics The effect of carbon fiber incorporation on MUHPC FCR The curve variation trend has a significant impact, and the curve variation pattern is the same as that of steel fiber MUHPC. FCR Similar forms of change, such as Figure 5As shown, the process can be divided into three stages: the descending stage, the equilibrium stage, and the ascending stage. These correspond to compaction under compressive load, new crack initiation, and crack propagation, respectively. Compressive stress causes the conductive fillers to move closer together, improving the conductive channels within the MUHPC matrix. The resulting cracks lead to the destruction and reconstruction of the conductive network, and further crack propagation results in the complete destruction of the conductive network. Unlike steel fiber MUHPC, carbon fiber has limited crack bridging ability. Once a crack forms, it propagates rapidly and penetrates the entire matrix. The descending stage of MUHPC with only carbon fiber is very steep, making it difficult to capture. After the peak stress, the stress drops rapidly, indicating brittle failure with weak bonding properties. Therefore, when the stress in MUHPC reaches its peak, the resistance rises rapidly.

[0079] In summary, carbon fibers achieve piezoresistive properties by forming a conductive network. As the doping concentration increases, the fiber spacing decreases, and the strain causes a more significant change in contact resistance. As shown in Table 12, when the doping concentration exceeds the threshold (0.30%-0.45%), the sensitivity decreases. This may be due to excessive and uneven fiber dispersion, which leads to short circuits in the local conductive network, thus reducing the sensitivity.

[0080] Table 12 Sensitivity coefficients of carbon fiber-doped MUHPC K

[0081] (2) Establishment of the relationship between strain and resistivity change rate Figure 6 The strain of carbon fiber MUHPC is shown. FCR The relationship curve between the fibers is based on the effective medium theory. Compressive loading reduces the distance between fibers. When fibers are sufficiently close, electrons jump between adjacent fibers, forming local conductive paths. To further understand the piezoresistive mechanism of carbon fiber MUHPC, an exponential function was used to fit the experimental data to obtain the strain of the composite material under monotonic loading. FCR The relationship can be expressed in the form of equation (d).

[0082] Table 13 MUHPC with single carbon fiber doping ε–FCR Relationship Fitting Parameters

[0083] Table 13 shows that different carbon fiber content ε–FCR The curve fitting correlations are high, both above 0.9, indicating excellent compatibility between the proposed model and the experimental data. Under monotonic loading, the Gaussian function can effectively describe... FCR The law governing stress variation. Therefore, the established strain- FCRThe relationship between them can serve as a calibration curve for the MUHPC piezoresistive properties, laying the foundation for stress-strain monitoring.

[0084] 3. Test results and analysis of pressure sensitivity of hybrid fiber MUHPC (1) Hybrid fiber MUHPC σ-ε and ε-FCR Curve characteristics The resistivity change rate curve of MUHPC incorporating both carbon fiber and steel fiber is similar in shape to that of MUHPC incorporating only steel fiber. In the linear elastic stage, the sensitivity of the piezoresistive performance increases with increasing stress / strain. However, when the specimen approaches its peak load, cracks begin to appear, disrupting the conductive network structure and leading to… FCR Gradually decreasing. Due to the synergistic effect of carbon fiber and steel fiber, the hybrid fiber MUHPC... FCR It is larger than that of single-doped carbon fiber or single-doped steel fiber. For example, when the volume fraction of steel fiber is 2.0% and the volume fraction of carbon fiber is 0.15%, 0.3%, 0.45%, or 0.6%, its... FCR The range of variation remained between 58.26% and 64.32%.

[0085] In summary, with the incorporation of hybrid fibers, the pressure sensitivity of MUHPC is higher than that of single-doped carbon fiber or single-doped steel fiber. Since SF plays a role in hindering crack propagation during the crack growth stage, the amount of SF in MUHPC with less than 1% steel fiber content is insufficient to bridge cracks, resulting in a sudden drop in stress. The formation and propagation of microcracks hinder electron tunneling conduction within the MUHPC matrix. Pull-out of SF and CF directly affects the already formed contact conductive network. When the steel fiber content is greater than 1%, a large amount of SF can bridge microcracks and delay their initial propagation. Therefore, during the stable crack propagation stage, MUHPC with high SF content, under compressive deformation... FCR It continues to decrease slowly. Furthermore, as can be observed from Figure 7, when the steel fiber content is constant, its [result] decreases with increasing carbon fiber content. FCR The relatively fewer jump points in the curve indicate that the fiber content has reached the permeation threshold, the conductive network has been basically formed, and it has good piezoresistive properties.

[0086] Hybrid fibers incorporated into MUHPC in the elastic stage and FCR The sensitivity coefficient at the maximum moment is shown in Table 14. The table shows the stress-strain ratio corresponding to the elastic stage. FCR Sensitivity coefficient ratio FCR The high sensitivity coefficient at maximum is due to the fact that in the elastic stage, the micro-cracks or pores inside the specimen are compacted by the compressive load, the fiber spacing decreases, and they overlap, resulting in a good pressure sensitivity response. FCRAt the maximum stage, the formation of microcracks inside the specimen disrupts the conductive network, reducing the stress and strain sensitivity coefficients.

[0087] Table 14 Sensitivity coefficients of hybrid fiber MUHPC K

[0088] (2) Establishment of the relationship between strain and resistivity change rate Hybrid fiber MUHPC FCR The curve is shown in Figure 8, and its MUHPC is FCR Curve and single-stranded steel fiber FCR The curves are consistent, all exhibiting a "U" or "V" shape. The figure shows the strain-resistivity change rate curves and fitting curves of MUHPC with hybrid fiber (CF+SF) doping. FCR The relationship between strain and elasticity follows an exponential function. The correlation coefficients of the fitted curves are shown in Table 15. R 2 All values ​​are greater than 0.9, indicating that the established hybrid fiber MUHPC has a high efficiency. FCR The relationship model between pressure and strain can be used as a calibration curve for pressure sensitivity.

[0089] Table 15. Mixed Fiber MUHPC ε–FCR Relationship Fitting Parameters

[0090] like Figure 9 As shown, the pressure-sensitive mechanism of hybrid fiber-reinforced MUHPC is achieved by linking toughening and conductivity mechanisms. This can be attributed to the overlapping and extensive distribution of SF / CF bridging cracks within the concrete matrix, forming a conductive network. Simultaneously, the interfacial bonding between the SF / CF and the MUHPC matrix reduces crack initiation. Secondly, compressive loading leads to the compaction of the SF / CF lap network and microcracks within the matrix, promoting the formation of new conductive channels and enhancing the composite material's... FCR The curve shows a rapid decline during the elastic stage, and during the stable crack propagation stage, FCR The downward trend of the curve is still mainly influenced by the deformation of the sample. Subsequently, as compressive damage begins to accumulate, the rate of resistivity decrease slows down, reflecting the key role of fibers in bridging cracks and delaying initial crack initiation. Finally, during the crack propagation stage, numerous microcracks grow and form the main crack, leading to fiber breakage / pull-out and disrupting the conductive network. FCR The curve shows an upward trend.

[0091] By conducting pressure-sensitive tests on MUHPCs incorporating different amounts of carbon fiber, steel fiber, and carbon-steel hybrid fibers, the following main conclusions can be drawn from the test results: (1) The pressure-sensitive properties of MUHPC under uniaxial compression were studied, and the MUHPCs with different CF and SF doping contents... FCR The curve can be divided into three stages. The first stage is the linear descent stage. In this stage, because the sample is in the non-destructive elastic stage, compression reduces the fiber spacing in the matrix, compacts the pores, and leads to a decrease in resistivity. FCR The curve declines, followed by a plateau phase. During this phase, overlapping fibers begin to separate due to the appearance of microcracks, disrupting the local conductive network and slowing the rate of decrease in electrical resistance. The third phase is a sudden rise; as stress continues to increase, cracks propagate further, leading to fiber separation. For CF-doped MUHPC specimens, the third phase exhibits the following characteristics: FCR The curve increases sharply, while the MUHPC resistance of single-doped SF and mixed-doped SF and CF gradually increases. FCR Gradually rising.

[0092] (2) The pressure sensitivity coefficient of SF-doped MUHPC in the elastic stage increases with increasing SF content, reaching its maximum value when the SF content is 1.5%. The pressure sensitivity coefficient of CF-doped MUHPC increases with increasing fiber content, with the increase initially increasing and then decreasing. The pressure sensitivity coefficient of carbon-steel fiber-doped MUHPC in the elastic stage increases with increasing carbon fiber and steel fiber content. With a fixed steel fiber content, the sensitivity coefficient increases with increasing carbon fiber content, and with a fixed carbon fiber content, the sensitivity coefficient increases with increasing steel fiber content, with the increase initially increasing and then decreasing.

[0093] (3) Based on the MUHPC specimen under uniaxial compression FCR The curve characteristics were used to establish the strain and... FCR Relationships, relationships can be expressed by equations FCR =Ae -((ε-B) / C)2 This indicates that the fitted curve has a high degree of fit with the experimental data.

[0094] (4) For MUHPC with single steel fiber doping, when the steel fiber doping content is 1.0%, the linear correlation coefficient of the fitted strain-resistivity change rate is ( R 2 The value is close to 1. For single-fiber MUHPC, when the carbon fiber content ranges from 0.30% to 0.6%, its... R 2 All reached above 0.9. For MUHPC with carbon-steel fiber blend, when the steel fiber content was greater than 1%, its [value] increased with the increase of carbon fiber content. R 2All values ​​remained above 0.91-0.98, consistent with the variation of the sensitivity coefficient. The overall results indicate that the piezoresistive performance of the carbon-steel fiber-mixed MUHPC is better.

[0095] 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.

[0096] 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 this invention fall within the scope of the claims of this application and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for constructing a force-electric response model for ultra-high performance cement-based composite materials, characterized in that, Includes the following steps: (1) Preparation of ultra-high performance cement-based composite material specimens containing conductive functional phases; (2) Apply monotonic or cyclic loads to the specimen and simultaneously collect the mechanical and electrical parameters under the loads. The mechanical parameters include at least compressive strain. ε The electrical parameters include at least resistivity; (3) Calculate the rate of change of resistivity at different strain times based on the electrical parameters. FCR ; (4) With the aforementioned compressive strain ε As the independent variable, the rate of change of resistivity FCR Using Gaussian function as the dependent variable, a constitutive model as shown in equation (I) is established through curve fitting, and the model parameters are determined such that the correlation coefficient between the model curve and the experimental data is greater than a preset threshold. （I） Where A, B, and C are the fitting parameters.

2. The construction method according to claim 1, characterized in that, The conductive functional phase includes a hybrid system of carbon fiber and steel fiber, as well as magnetite, steel slag, or conductive minerals with a semiconductor oxide layer on their surface as fine aggregates.

3. The construction method according to claim 2, characterized in that, The volumetric content of the carbon fiber is 0.15% to 0.6%, and the volumetric content of the steel fiber is 0.5% to 2.0%.

4. A health monitoring method for ultra-high performance cement-based composite material structures, characterized in that, include: S1: Electrodes are set on the structure under test, and the electrical parameters of the structure are collected in real time during service. The real-time resistivity change rate is then calculated. FCR real ; S2: Obtain a pre-constructed force-electric response model, as shown in Equation (I), which characterizes the mapping relationship between strain and resistivity change rate of the material used in the structure; S3: The real-time resistivity change rate FCR real The force-electric response model is input, and the real-time strain value of the structural component is obtained through model inversion. ε real ; S4: Based on the real-time strain value ε real The damage status of the structural components is assessed by observing their changes and trends.

5. The health monitoring method according to claim 4, characterized in that, In step S3, the model inversion further includes: According to the real-time resistivity change rate FCR real The stress stage of the structural component is determined by the segment in the force-electric response model curve. The stress stage includes: the linear decreasing stage corresponding to the lossless elastic period, the steady stage corresponding to the stable microcrack propagation period, and the rising stage corresponding to the unstable crack propagation period.

6. A structural health monitoring system for ultra-high performance cement-based composite materials, characterized in that, include: Electrode modules, mounted on ultra-high performance cement-based composite material structural components, are used to collect electrical signals; A data acquisition module, connected to the electrode module, is used to acquire the electrical parameters of the structural component in real time and calculate the real-time resistivity change rate based on the electrical parameters. FCR real ; Storage module, storing the force-electric response model constructed by claim 1: The processing module is communicatively connected to both the data acquisition module and the storage module, and is configured as follows: Receive the real-time resistivity change rate FCR real ; Call the force-electric response model in the storage module; The FCR real Substituting the values ​​into the model, the corresponding real-time strain values ​​are obtained through inversion calculation. ε real ; Output the real-time strain value ε real Or based on the damage assessment results generated by it.

7. The structural health monitoring system according to claim 6, characterized in that, The electrode module is a four-electrode system, including two external current electrodes and two internal voltage electrodes. The data acquisition module includes a DC regulated power supply and a multi-channel data acquisition instrument, used to realize DC four-electrode measurement.

8. A method for optimizing the mix proportion of ultra-high performance cement-based composite materials, characterized in that, include: Construct multiple sets of force-electric response models under different fiber doping amounts according to the method described in claim 1; Compare the fitting parameters A, B, C and the correlation coefficient of each model group. R 2 ; Based on the fitted correlation coefficient R 2 By maximizing and modeling the curve characteristics, the optimal fiber content ratio that combines mechanical and pressure-sensitive properties is determined.

9. A high-performance cement-based composite material with self-sensing properties, characterized in that, Its compressive strain under uniaxial compressive load ε With resistivity change rate FCR The relationship between them conforms to the following equation: ， Where A, B, and C are the fitting parameters; The cement-based composite material includes cementitious materials, magnetite aggregate, and hybrid fibers, wherein the hybrid fibers include carbon fibers and steel fibers.

10. The ultra-high performance cement-based composite material according to claim 9, characterized in that, The volume replacement rate of the magnetite aggregate is 40% to 80%; the volume content of the carbon fiber is 0.15% to 0.6%; and the volume content of the steel fiber is 0.5% to 2.0%.

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