A method for predicting durability of fiber reinforced concrete based on environment-fiber coupling effect

Abstract

This invention discloses a method for predicting the durability of fiber-reinforced concrete based on environment-fiber coupling, belonging to the field of building materials. The method first constructs an environmental impact factor based on temperature and humidity conditions, and a fiber reinforcement factor based on fiber type and dosage. Then, a cumulative damage model is established based on the environmental impact factor, fiber reinforcement factor, and cycle number. A relative dynamic elastic modulus prediction model is then constructed based on the cumulative damage model to obtain the predicted relative dynamic elastic modulus retention rate. This invention enables quantitative prediction of the durability performance of fiber-reinforced concrete under wet-dry and freeze-thaw cycles, and has advantages such as fewer model parameters, high prediction efficiency, and wide applicability. It can be applied to the durability evaluation and service life analysis of hydraulic structures and concrete engineering in cold regions.

Description

Technical Field

[0001] This invention belongs to the field of building materials, and particularly relates to a method for predicting the durability of fiber-reinforced concrete based on the interaction between the environment and the fiber. Background Technology

[0002] Fiber-reinforced concrete, with its ability to inhibit crack development, significantly improves the mechanical and durability properties of the matrix, making it an important material in the construction engineering field under complex service environments. However, most existing durability studies focus on the impact of single environmental factors on fiber-reinforced concrete, such as the performance degradation patterns under individual freeze-thaw cycles, wet-dry cycles, or salt corrosion scenarios, failing to fully reflect the multi-factor coupled service environment in actual engineering projects. Especially in infrastructure construction in cold regions, low-temperature freeze-thaw cycles and wet-dry cycles often overlap and synergistically degrade with factors such as saline soil corrosion. Existing research lacks quantitative characterization methods for the synergistic effects of environmental factors and fiber reinforcement factors, making it difficult to accurately predict the durability performance of fiber-reinforced concrete under wet-dry and freeze-thaw cycles.

[0003] Regarding testing methods for the freeze-thaw and wet-dry cycle durability of fiber-reinforced concrete, existing technologies mainly fall into two categories: one is to conduct the tests in stages, i.e., completing a specified number of wet-dry cycles before conducting freeze-thaw cycle tests; the other is to combine wet-dry and freeze-thaw cycles into a large cycle unit and repeat them sequentially. Neither of these methods can achieve the synchronous coupling of wet-dry and freeze-thaw cycles, and they are disconnected from the short-cycle alternating processes caused by rapid changes in diurnal temperature and humidity in real-world environments. This results in significant discrepancies between the durability data obtained from the tests and the actual material performance degradation observed in engineering projects.

[0004] Therefore, it is urgent to establish a durability prediction model that can comprehensively consider the synergistic effect of environmental factors and fiber reinforcement factors, and to develop a test method that can achieve simultaneous coupling of wet-dry and freeze-thaw cycles, so as to accurately simulate the damage evolution process of fiber-reinforced concrete under complex environments and provide technical support for the durability evaluation and service life analysis of concrete engineering such as hydraulic structures and water conveyance tunnel linings in cold regions. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method for predicting the durability of fiber-reinforced concrete based on environment-fiber coupling, comprising: Environmental factors were constructed based on temperature and humidity conditions. Fiber reinforcing factors are constructed based on fiber type and fiber content; A cumulative damage model is established based on the environmental factors, the fiber reinforcement factors, and the number of cycles. Based on the cumulative damage model, a relative dynamic elastic modulus prediction model is constructed. Based on the relative dynamic elastic modulus prediction model, the predicted relative dynamic elastic modulus retention rate is obtained.

[0006] Optionally, the method further includes a step of verifying the predicted relative dynamic modulus retention rate: Obtain the measured relative dynamic elastic modulus retention rate of fiber-reinforced concrete under wet-dry-freeze-thaw cycle test; The predicted relative dynamic elastic modulus retention rate is compared with the measured relative dynamic elastic modulus retention rate to obtain the error value.

[0007] Optionally, the construction of environmental factors based on temperature and humidity conditions includes: Determine the temperature influence parameters based on the freezing temperature range; Determine the parameters affecting humidity based on the moisture content of the concrete; The environmental impact factor is obtained by adding the temperature impact parameter and the humidity impact parameter.

[0008] Optionally, the construction of the fiber reinforcing factor based on fiber type and fiber content includes: The fiber type coefficient is determined based on the elastic modulus, tensile strength, and interfacial bonding properties of the fiber material. The fiber volume fraction is determined based on the ratio of fiber volume to the total concrete volume. The fiber content influence coefficient is determined based on the distribution of fiber content. The fiber reinforcement factor is obtained based on the fiber type coefficient, the fiber content influence coefficient, and the fiber volume fraction, and is expressed as follows: ; in This is the fiber type coefficient. The coefficient representing the influence of fiber content. This represents the fiber volume fraction.

[0009] Optionally, establishing the cumulative damage model includes: Based on the environmental damage coefficient, environmental action factor, fiber reinforcement coefficient, and fiber reinforcement factor, a correlation is established between the cumulative damage parameter and the number of cycles. The cumulative damage parameter is expressed as follows: ; in, For cumulative damage parameters, The environmental damage coefficient, As an environmental factor, The fiber reinforcement coefficient, As a fiber reinforcing agent, This represents the number of iterations.

[0010] Optionally, constructing a relative dynamic elastic modulus prediction model includes: Based on the cumulative damage parameters, a correlation is established between the predicted relative dynamic elastic modulus retention rate and the cumulative damage parameters. The predicted relative dynamic elastic modulus retention rate is expressed as: ; in, To predict the relative dynamic modulus retention rate, This represents the cumulative damage parameter.

[0011] Optionally, the raw materials of the fiber concrete include polyoxymethylene fiber, cellulose fiber, fly ash, water-reducing agent, air-entraining agent, sand, stone, cement and water, wherein the mass fractions of each component are related as follows: cement: fly ash: water: sand: medium stone: small stone: water-reducing agent: air-entraining agent: crack-resistant expansion agent: fiber = 210~220: 70~75: 100~110: 580~600: 700~710: 700~710: 1~2: 0.09~0.10: 15~17: 0.6~0.9.

[0012] Optionally, the polyoxymethylene fiber has a diameter of 15-30 μm and a length of 5-10 mm; the cellulose fiber has a diameter of 14-16 μm and a length of 10-15 mm.

[0013] Compared with the prior art, the present invention has the following advantages and technical effects: First, by constructing environmental impact factors and fiber reinforcement factors, and establishing a cumulative damage model and a relative dynamic elastic modulus prediction model, quantitative prediction of the durability performance of fiber-reinforced concrete under wet-dry and freeze-thaw cycles is achieved, avoiding the time consumption of traditional methods that rely on long-term durability tests and improving prediction efficiency. Second, by incorporating environmental damage effects and fiber reinforcement effects into the same analytical framework, the accumulation and development laws of internal damage under different fiber types and fiber dosages can be characterized, providing a theoretical basis for the optimization of fiber-reinforced concrete mix proportions and durability design. Third, by verifying the error between the predicted relative dynamic elastic modulus retention rate and the measured value, quantitative verification of the prediction results is achieved. Finally, the model of this invention has few parameters and a wide range of applications, and can be applied to the durability evaluation and service life analysis of hydraulic structures, water conveyance tunnel linings, and other concrete engineering projects in cold regions. Attached Figure Description

[0014] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a schematic diagram of the prediction method flow according to an embodiment of the present invention; Figure 2 This is a process flow diagram of the fiber-reinforced concrete preparation method resistant to wet-dry and freeze-thaw cycles in complex environments, according to an embodiment of the present invention. Figure 3 This is a process flow diagram of the testing method according to an embodiment of the present invention. Detailed Implementation

[0015] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0016] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0017] Example 1 like Figure 1 As shown, this embodiment provides a method for predicting the durability of fiber-reinforced concrete based on environment-fiber coupling, including: Environmental factors were constructed based on temperature and humidity conditions. Fiber reinforcing factors are constructed based on fiber type and fiber content; A cumulative damage model is established based on the environmental factors, the fiber reinforcement factors, and the number of cycles. Based on the cumulative damage model, a relative dynamic elastic modulus prediction model is constructed. Based on the relative dynamic elastic modulus prediction model, the predicted relative dynamic elastic modulus retention rate is obtained.

[0018] Specifically, environmental factors are first constructed based on temperature and humidity conditions. Its expression is: ;in: Parameters affected by temperature; This is a parameter related to the effect of humidity.

[0019] Furthermore, temperature affects parameters Determined based on freezing temperature range: ; Among them, when the freezing temperature decreases, the temperature effect... The parameters increase accordingly.

[0020] Furthermore, humidity affects parameters The sections are determined based on the water content of the concrete: ; in, The parameter represents the effect of humidity on the moisture content of concrete as the moisture content increases. The corresponding increase.

[0021] Furthermore, based on fiber type and fiber content, fiber reinforcing factors are constructed, including: The fiber type coefficient is determined based on the elastic modulus, tensile strength, and interfacial bonding properties of the fiber material. The fiber volume fraction is determined based on the ratio of fiber volume to the total concrete volume. The fiber content influence coefficient is determined based on the distribution of fiber content. The fiber reinforcement factor is obtained based on the fiber type coefficient, the fiber content influence coefficient, and the fiber volume fraction, and is expressed as follows: ; in This is the fiber type coefficient. The coefficient representing the influence of fiber content. This represents the fiber volume fraction.

[0022] Furthermore, This reflects the differences in crack propagation inhibition capabilities of different fiber materials. It is determined based on the fiber material's elastic modulus, tensile strength, and interfacial bonding properties; obtained by fitting the durability test results of different fiber specimens: 1.00 ≤ ≤1.05.

[0023] Furthermore, the fiber content coefficient For the effect of fiber volume fraction on structural stability, take 0.1≤ ≤0.2, as the fiber content increases, the constraint effect of the fiber on the internal structure of the concrete is enhanced, and the fiber content coefficient increases. The corresponding increase.

[0024] Furthermore, the fiber volume fraction The ratio of fiber volume to total concrete volume is expressed as follows: ;in: This refers to the total volume of the fibers. Total volume of concrete; fiber volume fraction Determined based on the actual fiber content.

[0025] Furthermore, considering that the internal damage of concrete under wet-dry-freeze-thaw cycles has the characteristic of rapid initial development followed by a gradual slowdown in the later stages, this invention uses a logarithmic function to characterize the influence of the number of cycles on damage accumulation, thereby establishing a damage evolution model for fiber-reinforced concrete under wet-dry-freeze-thaw cycles: ;in: This refers to the cumulative damage parameter; Environmental factors; It is a fiber reinforcing agent; This represents the number of loop iterations. Environmental damage coefficient; denoted as the fiber reinforcement coefficient. The environmental damage coefficient 'a' and the fiber reinforcement coefficient 'b' were obtained by fitting experimental data.

[0026] Furthermore, a relative dynamic elastic modulus prediction model is established based on the cumulative damage parameter Dn: ;in: To predict the retention rate of relative dynamic elastic modulus.

[0027] Further, the error verification is as follows: .

[0028] The above methods are used to establish a quantitative relationship between fiber type, fiber content, environmental conditions and relative dynamic elastic modulus retention rate, so as to realize the predictive analysis of the durability performance of fiber-reinforced concrete under different dry-wet-freeze-thaw cycles.

[0029] The fiber-reinforced concrete raw materials in this embodiment include polyoxymethylene fiber, cellulose fiber, fly ash, water-reducing agent, air-entraining agent, sand, stone, cement, and water; wherein the mass fractions of each component are related as follows: cement: fly ash: water: sand: medium stone: small stone: water-reducing agent: air-entraining agent: crack-resistant expansion agent: fiber = 210~220: 70~75: 100~110: 580~600: 700~710: 700~710: 1~2: 0.09~0.10: 15~17: 0.6~0.9. Further, the polyoxymethylene fiber of the present invention has a diameter of 15-30μm and a length of 5-10mm.

[0030] Furthermore, the cellulose fibers described in this invention have a diameter of 14-16 μm and a length of 10-15 mm. Furthermore, the cement described in this invention is P·MH42.5 cement.

[0031] Furthermore, the fineness modulus of the sand described in this invention is 2.5-3.

[0032] Furthermore, the medium-sized stone particles in this invention have a particle size of 20-40 mm, and the small-sized stone particles have a particle size of 5-20 mm.

[0033] Furthermore, the water-reducing agent described in this invention is HTPC-Ⅰ standard high-performance water-reducing agent, the air-entraining agent is HTAE type air-entraining agent, and the structural crack-resistant expansion agent is NSAC-Ⅱ type thin-walled concrete structural crack-resistant expansion agent.

[0034] like Figure 2 As shown, the preparation method of fiber-reinforced concrete is as follows: (1) Pre-set the mass ratio of each raw material used to prepare fiber concrete; before preparation, pour the dry material into the mixer for trial mixing according to the mix ratio, and decide whether to adjust the mix ratio before proceeding with the formal preparation based on the trial mixing situation.

[0035] (2) According to the mix proportion determined in step (1), pour the coarse aggregate and cementitious material into the mixer according to the volume ratio of the mixer, then pour in the sand, and after mixing, pour in the liquid and continue mixing for 3 minutes to make the concrete fully mixed. After mixing, pour it into the mold and place it on the vibrating table for full vibration.

[0036] (3) After the specimen is molded, it is kept at a temperature of 20±2℃. The specimens were cured in a standard curing room with a relative humidity of approximately 95% for 24 hours. After that, the specimens were demolded and continued to be cured in the standard curing room until the planned age.

[0037] The curing temperature is 18-22 degrees Celsius as described in step (3). The relative humidity is ≥95%, and the curing time is 24 hours.

[0038] like Figure 3 As shown, the test method in this embodiment is as follows: the wet-dry cycle is disassembled and sequentially placed into the freeze-thaw cycle. The test specimen undergoes the sequence of "wet-freeze-thaw-wet-dry-wet" in sequence, which is considered as one large cycle. This test method allows the test specimen to undergo wet-dry and freeze-thaw coupled cycles simultaneously in a short period of time. Compared with separate wet-dry and freeze-thaw cycles, the damage to the test specimen is closer to the actual situation, and the analysis of material degradation will be clearer. The specific operation method is as follows: (1) Place the cured specimen into a plastic basket or plastic bucket, then fill the plastic bucket with water to submerge the specimen. Soak the specimen for 12 hours, then take the specimen out of the plastic bucket.

[0039] (2) Place the soaked specimens into the specimen box, add water to cover the top surface of the specimens; place them neatly in the quick-freezing test chamber, connect the temperature probe, and control the temperature at -18°C during the test. Up to 5 The time should be controlled within 4 hours. Take out the test block and rinse the surface of the test block with clean water to remove ice and debris.

[0040] (3) The specimen was soaked at room temperature for 6 hours to thaw initially, and then placed in a blower box to dry at about 60 degrees Celsius for 8 hours.

[0041] After removing it, let it cool at room temperature for 4 hours before starting the next cycle.

[0042] Furthermore, the wet-dry-freeze-thaw cycle test method controls the overall cycle time to about 36 hours to simulate the wet-dry-freeze-thaw cycle that concrete equipment experiences in a complex environment within a day under real conditions, so as to have a clearer understanding of the deterioration process of the specimen under wet-dry-freeze-thaw cycle.

[0043] Furthermore, the relative dynamic elastic modulus of the material was tested after undergoing wet-dry and freeze-thaw cycles.

[0044] The natural frequencies of the specimen before and after cycling were determined using a relative dynamic modulus of elasticity tester, and the retention rate of the relative dynamic modulus of elasticity was calculated. The expression for this retention rate is as follows: ;in: The relative dynamic elastic modulus before cyclic action; This is the relative dynamic elastic modulus after the nth cycle; This is the dynamic elastic modulus retention rate. The larger the value, the better the integrity of the internal structure.

[0045] Example 2 This invention provides a method for predicting the durability of fiber-reinforced concrete based on environment-fiber coupling, the specific steps of which are as follows: (1) Pre-set the mass proportions of each raw material used to prepare different types and dosages of fiber-reinforced concrete; the mix proportions are as follows: Group 1: Cement: Fly ash: Water: Sand: Medium stone: Small stone: Water-reducing agent: Air-entraining agent: Crack-resistant expansion agent: Cellulose fiber = 218:74:105:590:708:701:1.57:0.095:16:0.6; Group 2: Cement: Fly ash: Water: Sand: Medium stone: Small stone: Water-reducing agent: Air-entraining agent: Crack-resistant expansion agent: Cellulose fiber = 218:74:105:590:708:701:1.57:0.095:16:0.9; Group 3: Cement: Fly ash: Water: Sand: Medium stone: Small stone: Water-reducing agent: Air-entraining agent: Crack-resistant expansion agent: Polyoxymethylene fiber = 218:74:105:590:708:701:1.57:0.095:16:0.6; Group 4: Cement: Fly ash: Water: Sand: Medium stone: Small stone: Water-reducing agent: Air-entraining agent: Crack-resistant expansion agent: Polyoxymethylene fiber = 218:74:105:590:708:701:1.57:0.095:16:0.9.

[0046] As described in step (1), after the specimen is formed, it is kept at a temperature of 20±2℃. The specimens were cured in a standard curing room with a relative humidity of approximately 95% for 24 hours. After that, the specimens were demolded and continued to be cured in the standard curing room until the planned age.

[0047] The curing temperature is 18-22 degrees Celsius as described in step (1). The relative humidity is ≥95%, and the curing time is 24 hours.

[0048] (2) The specimens were subjected to single wet-dry cycle followed by single freeze-thaw cycle and wet-dry-freeze-thaw coupled cycle tests. Experimental method for wet-dry / freeze-thaw coupling test: Place the cured specimen in a plastic basket or bucket, then fill the bucket with water to submerge the specimen, and immerse the specimen for 12 hours; then place the specimen in a rapid freezing test chamber, connect a temperature probe, and control the temperature at -18°C during the test. Up to 5 The freezing time should be controlled within 4 hours. After the rapid freezing test, remove the test block and rinse off the ice and debris with clean water. Thaw the test block by immersing it at room temperature for about 6 hours, then place it in a blower at 60°C. Dry for 8 hours on both sides; after removing, cool at room temperature for 4 hours before starting the next cycle.

[0049] As described in step (2), both the single wet-dry test and the single freeze-thaw test were conducted in accordance with the standard test method of the "Test Procedure for Hydraulic Concrete" (SL 352-2020).

[0050] (3) The dynamic elastic modulus of the four groups of experiments were tested respectively, and the data obtained are shown in Tables 1-2: Table 1 Table 2 According to the test data in step (3), it can be observed that compared with the test method of first a single wet-dry cycle and then a single freeze-thaw cycle, the wet-dry-freeze-thaw cycle test method has a significantly greater impact on the performance of concrete specimens. During the wetting process, the air inside the concrete specimen mixes with water, which will exacerbate the formation of cracks due to the freezing expansion effect of water immediately after the freeze-thaw test, resulting in a significant decrease in the durability of the specimen.

[0051] (4) Taking Group 2 as an example, the durability of the structure is predicted based on the wet-dry-freeze-thaw cycle test: Furthermore, fiber reinforcing factors are constructed based on fiber type and fiber content. Its expression is: ;in: Fiber type coefficient; The coefficient representing the influence of fiber content; This refers to the fiber content.

[0052] Furthermore, This reflects the differences in crack propagation inhibition capabilities of different fiber materials. It is determined based on the fiber material's elastic modulus, tensile strength, and interfacial bonding properties; for cellulose fibers: 1.00 ≤ ≤1.05; preferably cellulose fiber. ; Fiber content =0.9 kg / m³; the fiber content coefficient is determined based on the fiber content distribution. .

[0053] Determined based on fiber type coefficient, fiber content influence coefficient, and fiber content. , Calculated 1.18.

[0054] Based on the freeze-thaw cycle experiment with an experimental temperature range of -18℃ to 20℃, below -15℃, it can be concluded that... =1.2; while the specimen was saturated with water before freeze-thaw cycles and remained in a high-moisture state for a long time during wet-dry cycles, with a moisture content >80%, it can be concluded that... .

[0055] Environmental factors can be derived from the parameters affecting temperature and humidity. Calculated .

[0056] Based on the relative dynamic elastic modulus test results of four groups of specimens under different cycle numbers, the least squares method was used to fit the results, yielding: a = 0.09; fiber reinforcement coefficient b = 0.07. Therefore, the formula can be used... The cumulative damage parameters were obtained. Calculations were performed after 150 wet-dry freeze-thaw cycles. 0.290.

[0057] pass According to the formula The predicted relative dynamic modulus retention rate is obtained. Calculations show that Right now .

[0058] According to the dynamic elastic modulus experiment, the formula can be used... Calculations show that =74.82%.

[0059] Error verification is as follows: Calculated .

[0060] The data above shows that the method of the present invention can accurately predict the durability of fiber-reinforced concrete.

[0061] Compared with the prior art, the present invention has the following advantages: (1) This invention constructs a method for predicting the durability of fiber-reinforced concrete based on fiber type, fiber content, and environmental conditions. It combines environmental factors such as temperature, humidity, and number of cycles with the fiber reinforcement effect, and establishes a damage evolution model based on the synergistic effect of environmental factors and fiber reinforcement factors. This enables quantitative prediction of the durability performance of fiber-reinforced concrete under wet-dry and freeze-thaw cycles. Compared with traditional methods that rely on long-term durability tests, this invention can quickly predict the performance changes of concrete at different cycle stages based on material composition and environmental parameters, thereby improving the efficiency of durability evaluation.

[0062] (2) This invention establishes a relative dynamic elastic modulus prediction model based on damage accumulation theory by constructing the correlation between the environmental action factor Qi, the fiber reinforcement factor Ri, and the cumulative damage parameter Dn, thus unifying the environmental degradation effect and the fiber toughening effect into the same analytical framework. This model can characterize the accumulation and development law of internal damage in fiber-reinforced concrete during cyclic loading, and realize the dynamic analysis of the durability performance change trend under different fiber types and fiber dosages, providing a theoretical basis for the mix design optimization and durability design of fiber-reinforced concrete.

[0063] (3) This invention uses the relative dynamic elastic modulus as the durability performance characterization index. By comparing the predicted value with the experimentally measured value, the quantitative verification of the durability prediction results is achieved. The established model parameters can be calibrated and modified according to different regional environmental conditions and engineering needs, and have good applicability and scalability.

[0064] (4) This invention can be applied to the prediction of durability and service life analysis of fiber concrete under wet-dry cycle, freeze-thaw cycle and wet-dry-freeze-thaw coupling conditions. It is applicable to hydraulic structures in cold regions, water conveyance tunnel lining structures, water conservancy and hydropower projects, transportation infrastructure and other concrete structures that are subjected to complex environments for a long time. It provides technical support for the durability design, maintenance decision and service performance evaluation of engineering structures.

[0065] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for predicting durability of fiber reinforced concrete based on environmental-fiber coupling effect, characterized by, include: Environmental factors were constructed based on temperature and humidity conditions. Fiber reinforcing factors are constructed based on fiber type and fiber content; A cumulative damage model is established based on the environmental factors, the fiber reinforcement factors, and the number of cycles. Based on the cumulative damage model, a relative dynamic elastic modulus prediction model is constructed. Based on the relative dynamic elastic modulus prediction model, the predicted relative dynamic elastic modulus retention rate is obtained.

2. The method of claim 1, wherein, It also includes the step of verifying the predicted relative dynamic modulus retention rate: Obtain the measured relative dynamic elastic modulus retention rate of fiber-reinforced concrete under wet-dry-freeze-thaw cycle test; The predicted relative dynamic elastic modulus retention rate is compared with the measured relative dynamic elastic modulus retention rate to obtain the error value.

3. The method of claim 1, wherein, The environmental factors constructed based on temperature and humidity conditions include: Determine the temperature influence parameters based on the freezing temperature range; Determine the parameters affecting humidity based on the moisture content of the concrete; The environmental impact factor is obtained by adding the temperature impact parameter and the humidity impact parameter.

4. The method of claim 1, wherein, The fiber reinforcing factor is constructed based on fiber type and fiber content, including: The fiber type coefficient is determined based on the elastic modulus, tensile strength, and interfacial bonding properties of the fiber material. The fiber volume fraction is determined based on the ratio of fiber volume to the total concrete volume. The fiber content influence coefficient is determined based on the distribution of fiber content. The fiber reinforcement factor is obtained based on the fiber type coefficient, the fiber content influence coefficient, and the fiber volume fraction. The fiber reinforcement factor is expressed as follows: ； wherein is the fiber type coefficient, is the fiber content influence coefficient, is the fiber volume fraction.

5. The method of claim 1, wherein, The establishment of the cumulative damage model includes: Based on the environmental damage coefficient, environmental action factor, fiber reinforcement coefficient, and fiber reinforcement factor, a correlation is established between the cumulative damage parameter and the number of cycles. The cumulative damage parameter is expressed as follows: ； in, For cumulative damage parameters, The environmental damage coefficient, As an environmental factor, The fiber reinforcement coefficient, As a fiber reinforcing agent, This represents the number of iterations.

6. The method of claim 5, wherein, Constructing a relative dynamic elastic modulus prediction model includes: Based on the cumulative damage parameters, a correlation is established between the predicted relative dynamic elastic modulus retention rate and the cumulative damage parameters. The predicted relative dynamic elastic modulus retention rate is expressed as: ； in, To predict the relative dynamic modulus retention rate, This represents the cumulative damage parameter.

7. The method according to claim 1, characterized in that, The raw materials of the fiber concrete include polyoxymethylene fiber, cellulose fiber, fly ash, water-reducing agent, air-entraining agent, sand, stone, cement and water, wherein the mass fractions of each component are related as follows: cement: fly ash: water: sand: medium stone: small stone: water-reducing agent: air-entraining agent: crack-resistant expansion agent: fiber = 210~220: 70~75: 100~110: 580~600: 700~710: 700~710: 1~2: 0.09~0.10: 15~17: 0.6~0.

9.

8. The method according to claim 7, characterized in that, The polyoxymethylene fiber has a diameter of 15-30 μm and a length of 5-10 mm; the cellulose fiber has a diameter of 14-16 μm and a length of 10-15 mm.

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