Construction method of fiber-reinforced high-performance seawater and sea sand concrete shrinkage prediction model

Abstract

The invention belongs to the technical field of ocean engineering, and discloses a construction method of a fiber-reinforced high-performance seawater sea sand concrete shrinkage prediction model. The construction method comprises the following steps: S1, introducing a seawater concentration correction term to limit shrinkage strain of an existing concrete shrinkage prediction model, and calculating a seawater concentration influence coefficient; s2, an effective humidity correction term is introduced into a humidity function of an existing concrete shrinkage prediction model, and a humidity sensing coefficient is calculated; s3, constructing a fiber constraint function and introducing a fiber inhibition coefficient; and S4, outputting a shrinkage prediction model of the fiber-reinforced high-performance seawater sea sand concrete by utilizing a time development function and combining the seawater concentration correction term, the effective humidity correction term and the fiber inhibition coefficient. A multi-factor coupling theoretical framework is adopted in the established shrinkage prediction model, the interaction influence of the seawater chemical effect, the microscopic physical mechanism and the fiber mechanical constraint is completely considered, and the shrinkage rule of the high-performance seawater sea sand fiber concrete can be accurately represented.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of marine engineering construction materials, and particularly relates to a construction method of a fiber-reinforced high-performance seawater-sea sand concrete shrinkage prediction model. BACKGROUND

[0002] With the continuous expansion of the construction scale of major marine engineering and the severe challenges of water resource scarcity and natural river sand scarcity in coastal and offshore areas, the development and utilization of seawater, sea sand and other marine resources to prepare concrete has become an inevitable choice for the sustainable development of marine engineering construction. However, the soluble salts such as Cl ﹣ , SO4 2－ , Mg 2＋ in seawater have a complex influence on the microstructure and long-term performance of concrete. These ions not only accelerate the early hydration process of cement, promote the generation of Friedel's salt, ettringite and other hydration products, and refine the pore structure, but also crystallize and precipitate in the pore solution to form an internal support system. This complex physical and chemical process significantly changes the shrinkage characteristics of concrete, resulting in essential differences in the drying shrinkage behavior of traditional freshwater concrete.

[0003] At present, the widely used concrete shrinkage prediction models at home and abroad, such as the ACI209 model, the B3 model, the CEB-FIP model and the GL2000 model, are all established for ordinary freshwater concrete. The traditional models lack the mechanism understanding of the influence of seawater ions, and cannot reflect the essence of the changes of micro driving forces such as capillary tension and osmotic pressure caused by salt. Secondly, the model parameter system does not consider the key variable of seawater concentration, and cannot adapt to the actual situation of salinity changes in different sea areas. Thirdly, the existing models cannot characterize the inhibitory effect of fiber reinforcement on shrinkage, and are difficult to guide the optimization design of fiber concrete.

[0004] In summary, it is necessary to design a construction method of a fiber-reinforced high-performance seawater-sea sand concrete shrinkage prediction model to solve the problems in the prior art. SUMMARY

[0005] To solve the above problems in the prior art, the present application provides a construction method of a fiber-reinforced high-performance seawater-sea sand concrete shrinkage prediction model, which solves the problem that the existing concrete shrinkage prediction model cannot accurately predict the shrinkage behavior of fiber-reinforced high-performance seawater-sea sand concrete.

[0006] To achieve the above purpose, the present application adopts the following technical scheme: The construction method of the fiber-reinforced high-performance seawater-sea sand concrete shrinkage prediction model comprises the following steps: S1, introducing a seawater concentration correction term to the limiting shrinkage strain of the existing concrete shrinkage prediction model, and calculating a seawater concentration influence coefficient; S2, introducing an effective humidity correction term to the humidity function of the existing concrete shrinkage prediction model, and calculating a humidity perception coefficient; S3, constructing a fiber constraint function and introducing a fiber inhibition coefficient, and determining a fiber efficiency coefficient through fiber type and dosage tests; S4, outputting a fiber-reinforced high-performance seawater sea sand concrete shrinkage prediction model by using a time development function in combination with the seawater concentration correction term, the effective humidity correction term and the fiber inhibition coefficient.

[0007] In some embodiments of the present application, the calculation formula of the seawater concentration correction term in step S1 is: c =A·c+1; Wherein, η c is the seawater concentration correction term, A is the seawater concentration influence coefficient, and c is the seawater concentration.

[0008] In some embodiments of the present application, the calculation formula of the effective humidity correction term in step S2 is: eff =h·(B·c+1); Wherein, h eff is the effective humidity correction term, h is the environmental relative humidity, B is the humidity perception coefficient, and c is the seawater concentration.

[0009] In some embodiments of the present application, the calculation steps of the seawater concentration influence coefficient A and the humidity perception coefficient B are: Assuming that the influence of seawater concentration on the corrected ultimate shrinkage strain is positively correlated and that seawater concentration affects effective humidity by changing the pore solution chemical potential, the following theoretical relationship is obtained: ; Wherein, ε shu is the corrected ultimate shrinkage strain; The actual shrinkage strain of concrete under different seawater concentrations and different environmental humidities is measured through tests to obtain corresponding test data; Based on the test data, multiple nonlinear regression analysis is performed on the theoretical relationship to simultaneously fit the seawater concentration influence coefficient A and the humidity perception coefficient B.

[0010] In some embodiments of the present application, the determination step of the fiber efficiency coefficient in step S3 includes: The fiber constraint function expression is constructed to obtain a theoretical calculation formula of the fiber inhibition coefficient: ; Wherein, k fiber is the fiber inhibition coefficient, ɑ is the fiber efficiency coefficient, V f is the volume dosage of the fiber, and l f / df the length-diameter ratio of the fiber; The actual shrinkage strain of the concrete with different fiber types, different volume contents V f and different length-diameter ratios l f / d f is measured by the test system, and test data is obtained; According to the test data, the measured values of the fiber inhibition coefficients under each working condition are calculated, and the fiber efficiency coefficients of different fiber types are obtained through inversion analysis fitting.

[0011] In some embodiments of the present application, the fiber types at least include basalt fiber, polypropylene fiber and steel fiber.

[0012] In some embodiments of the present application, the formula of the fiber-reinforced high-performance seawater sea sand concrete shrinkage prediction model in the step S4 is: ; Wherein, ε cs (t) is the shrinkage strain of the fiber-reinforced high-performance seawater sea sand concrete at the age t days, ε shu is the corrected ultimate shrinkage strain, β(h) is the corrected humidity function, β(t) is the time function describing the development of shrinkage with time; kfiber is the fiber inhibition coefficient.

[0013] In some embodiments of the present application, a fiber-reinforced high-performance seawater sea sand concrete shrinkage prediction model is obtained by using the construction method described above, and is used to predict the long-term shrinkage deformation behavior of the high-performance seawater sea sand concrete mixed with fibers in the marine environment.

[0014] In some embodiments of the present application, an electronic device is provided, comprising: a processor, and a memory and a transceiver connected with the processor in communication; The memory stores computer execution instructions; and the transceiver is used to transceive data. The processor executes the computer execution instructions stored in the memory to realize the construction method described above.

[0015] In some embodiments of the present application, a computer readable storage medium is provided, characterized in that, The computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to realize the construction method described above.

[0016] The technical solution of the present application has the following technical effects compared with the prior art: The shrinkage prediction model established by the application can accurately represent the shrinkage law of high-performance seawater sea sand fiber concrete by introducing seawater concentration correction, effective humidity mechanism and fiber inhibition coefficient, and the prediction accuracy is significantly better than that of traditional models.

[0017] Meanwhile, the interactive influence of seawater chemical effect, micro physical mechanism and fiber mechanical constraint is fully considered by adopting the theoretical framework of multi-factor coupling, and a systematic prediction system is formed, which provides an innovative solution for the prediction of concrete shrinkage behavior in marine environment.

[0018] The shrinkage prediction model of fiber reinforced high-performance seawater sea sand concrete constructed by the application has clear physical meaning and strong engineering applicability, can accurately predict the shrinkage deformation of concrete under different working conditions, provides reliable theoretical support for the durability design and long-term performance evaluation of marine engineering structures, and has important engineering application value. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical scheme of the embodiments of the application, the drawings needed in the embodiment description will be briefly introduced as follows, and obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0020] Figure 1 The construction method flow chart of the fiber reinforced high-performance seawater sea sand concrete shrinkage prediction model provided by the application.

[0021] Figure 2 The comparison chart of the prediction results of the model in the present embodiment 1 and the measured values and the calculation results of the traditional prediction model.

[0022] Figure 3 The comparison chart of the shrinkage measured results of the concrete when the seawater concentration is 0% and the calculation results of the present embodiment 2 and the traditional prediction model.

[0023] Figure 4 The comparison chart of the shrinkage measured results of the concrete when the seawater concentration is 50% and the calculation results of the present embodiment 2 and the traditional prediction model.

[0024] Figure 5 The comparison chart of the shrinkage measured results of the concrete when the seawater concentration is 100% and the calculation results of the present embodiment 2 and the traditional prediction model.

[0025] Figure 6 The comparison chart of the shrinkage measured results of the concrete when the seawater concentration is 200% and the calculation results of the present embodiment 2 and the traditional prediction model.

[0026] Figure 7A comparison chart of the shrinkage measured results of the concrete with a seawater concentration of 100% under an environmental humidity of 50% and the calculation results of the embodiment 2 and the conventional prediction model.

[0027] Figure 8 A comparison chart of the shrinkage measured results of the concrete with a seawater concentration of 100% under an environmental humidity of 65% and the calculation results of the embodiment 2 and the conventional prediction model.

[0028] Figure 9 A comparison chart of the shrinkage measured results of the concrete with a seawater concentration of 100% under an environmental humidity of 80% and the calculation results of the embodiment 2 and the conventional prediction model.

[0029] Figure 10 A comparison chart of the shrinkage measured results of the concrete with a seawater concentration of 100% under a polypropylene fiber content of 0% and the calculation results of the embodiment 2 and the conventional prediction model.

[0030] Figure 11 A comparison chart of the shrinkage measured results of the concrete with a seawater concentration of 100% under a polypropylene fiber content of 0.1% and the calculation results of the embodiment 2 and the conventional prediction model.

[0031] Figure 12 A comparison chart of the shrinkage measured results of the concrete with a seawater concentration of 100% under a polypropylene fiber content of 0.2% and the calculation results of the embodiment 2 and the conventional prediction model.

[0032] Figure 13 A comparison chart of the shrinkage measured results of the concrete with a seawater concentration of 100% under a polypropylene fiber content of 0.3% and the calculation results of the embodiment 2 and the conventional prediction model. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present application will be clearly and completely described in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present application.

[0034] In the description of the present application, it should be noted that, unless otherwise explicitly specified and limited, the terms “mounting”, “connection”, “connecting” should be understood in a broad sense, for example, can be fixed connection, can also be detachable connection, or integrally connected. For those skilled in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0035] In order to solve the technical problem that the existing concrete shrinkage prediction model cannot accurately predict the shrinkage behavior of fiber reinforced high performance seawater sea sand concrete, the present application establishes a multi-factor coupled shrinkage prediction model by in-depth study of the physical and chemical effects of seawater ions in concrete and the mesoscopic mechanics effect of fibers. On the basis of inheriting the classical theoretical framework, the prediction accuracy and engineering applicability are significantly improved through a series of innovative modifications. The specific construction method of the shrinkage prediction model is as follows: Embodiment 1, reference Figure 1 As shown in the figure, the construction method of the fiber reinforced high performance seawater sea sand concrete shrinkage prediction model comprises the following steps: S1, introduce a seawater concentration correction term to the limiting shrinkage strain of the existing concrete shrinkage prediction model, and calculate the seawater concentration influence coefficient; Because the Cl - , SO4 2- and other ions in seawater can accelerate cement hydration, promote the generation of Friedel's salt, ettringite and other products, and refine the pore structure, thereby significantly increasing the shrinkage potential of the material.

[0036] Therefore, a seawater concentration correction term η c is introduced to the limiting shrinkage strain of the existing concrete shrinkage prediction model. c The calculation formula of the seawater concentration correction term η is as follows: c η =A·c+1; Wherein, A is the seawater concentration influence coefficient, and c is the seawater concentration.

[0037] The seawater concentration influence coefficient A can be fitted and calculated by measuring the actual shrinkage value of the concrete through experiment, and the specific calculation process is described below.

[0038] S2, introduce an effective humidity correction term to the humidity function of the existing concrete shrinkage prediction model, and calculate the humidity perception coefficient; Through the introduced effective humidity correction term, the influence of seawater ions on significantly reducing the pore solution chemical potential can be effectively quantified, and an additional osmotic pressure difference is established between the pore solution and the environmental humidity, thereby enhancing the influence of the shrinkage driving force.

[0039] Specifically, the calculation formula of the effective humidity correction term is: h eff =h·(B·c+1); Wherein, h eff is the effective humidity correction term, h is the environmental relative humidity, B is the humidity perception coefficient, and c is the seawater concentration.

[0040] The calculation of the humidity perception coefficient B can be synchronized with the calculation of the seawater concentration influence coefficient A, and the following calculation steps are adopted: I. Assuming that the influence of seawater concentration on the corrected ultimate shrinkage strain ε shu is positively correlated, and at the same time assuming that the seawater concentration affects the effective humidity h by changing the chemical potential of the pore solution eff , the following theoretical relationship is obtained: ; II. The actual shrinkage strain of concrete under different seawater concentrations and different environmental humidities is measured by experiment to obtain the corresponding experimental data; in this embodiment, different seawater concentrations include 0%, 50%, 100%, 200%, and 300%; different environmental humidities include 40%, 60%, and 80%; III. Based on the experimental data, a multiple nonlinear regression analysis is performed on the theoretical relationship in step I to simultaneously fit the seawater concentration influence coefficient A and the humidity perception coefficient B.

[0041] Specifically, the seawater concentration influence coefficient A has a value of 0.055, and the humidity perception coefficient B has a value of -0.02.

[0042] In this embodiment, the existing concrete shrinkage prediction model uses the GL2000 model; the corresponding corrected ultimate shrinkage strain and the corrected humidity function are calculated according to the seawater concentration influence coefficient A and the humidity perception coefficient B.

[0043] Among them, for the corrected ultimate shrinkage strain, the expression is:

[0044] In the formula: K is the cement type coefficient, for ordinary portland cement, K takes 1.00; for slag cement and fly ash cement, K takes 0.70-0.85; for early strength cement, K takes 1.10-1.15; c is the seawater concentration, expressed in percentage cu f

[0045] For the corrected humidity function, the expression is: ;

[0046] In the formula: h is the environmental relative humidity, and B is the influence coefficient of seawater ions on humidity perception obtained by fitting the experimental data.

[0047] S3, construct a fiber constraint function and introduce a fiber inhibition coefficient, and determine a fiber efficiency coefficient through fiber type and dosage test; Step S31, based on the micromechanics of composite materials and the fiber bridging theory, combining the interface bonding mechanics and the stress transfer mechanism, the expression of the fiber constraint function is constructed to obtain the theoretical calculation formula of the fiber inhibition coefficient: ; wherein k fiber is the fiber inhibition coefficient, a is the fiber efficiency coefficient, V f is the volume fraction of the fiber, l f / d f is the aspect ratio of the fiber; Step S32, the actual shrinkage strain of the concrete with different fiber types, different volume fractions V f and different aspect ratios l f / d f is measured by the test system, and test data is obtained; the fiber types used in this step include basalt fiber, polypropylene fiber and steel fiber; in other embodiments, the fiber types can also be selected from glass fiber, PVA fiber, etc.

[0048] Step S33, the measured values of the fiber inhibition coefficient under each working condition are calculated according to the test data , and the fiber efficiency coefficients of different fiber types are obtained by inverse analysis fitting.

[0049] Specifically, the value ranges of the fiber efficiency coefficients a of different fiber types are as follows: basalt fiber: ; polypropylene fiber: ; and steel fiber: .

[0050] S4, a fiber-reinforced high-performance seawater sea sand concrete shrinkage prediction model is output by using a time development function, combining the seawater concentration correction term, the effective humidity correction term and the fiber inhibition coefficient.

[0051] Step S41, the time development function of the embodiment uses the time development function of the classic GL2000 model, and the expression is as follows: =

[0052] wherein t is the age of the concrete; t c is the age of the concrete when the curing ends, i.e., the age when the drying begins; V and S respectively represent the volume and the surface area of the test piece.

[0053] Step S42, the correction terms of steps S1 and S2 are combined with the fiber inhibition coefficient of step S3, and the classic time development function of step 41 is combined to obtain a shrinkage prediction model of the fiber-reinforced high-performance seawater sea sand concrete: ;

[0054] wherein ε cs(t) is the shrinkage strain of fiber reinforced high performance seawater and sea sand concrete at age t days, ε shu is the modified ultimate shrinkage strain, β(h) is the modified humidity function, β(t) is the time function describing the development of shrinkage with time; k fiber is the fiber inhibition coefficient.

[0055] Specifically, to prove the beneficial effects of the model, a strength of 80 MPa is designed, and natural seawater and sea sand are used to cast concrete, and 0.2% volume of polypropylene fiber (aspect ratio =335) is added. The shrinkage prediction under the condition of ambient humidity of 65% is taken as an example to specifically illustrate the present embodiment.

[0056] The concrete mix proportion is shown in Table 1. The cement is PⅡ52.5R grade Portland cement, the fly ash is first grade fly ash, the silica ash is microsilica powder with SiO2 content of more than 97%, the coarse aggregate is crushed granite aggregate, and the water reducing agent is polycarboxylic acid high performance water reducing agent. The standard shrinkage test specimens with a size of 100mm×100mm×515mm are prepared, and the test environment temperature is 20±2℃.

[0057] Table 1 Concrete mix proportion of Example 1 (kg / m³) Component Natural seawater Cement Silica fume Fly ash Sea sand Coarse aggregate Water reducing agent Content 128.33 401.04 80.21 52.64 651.68 1127.91 7.52 The model parameter values and calculation process of the present embodiment are as follows: Step 1, calculation of the ultimate shrinkage strain considering the influence of seawater concentration. Wherein, K=1.15, =80.0MPa, c=1, A=0.055.

[0058]

[0059] Step 2, humidity function calculation considering effective humidity. Wherein, h=65%, c=1, B=-0.02.

[0060]

[0061]

[0062] Step 3, fiber inhibition coefficient calculation. Wherein, =0.2%, =335, α=0.36 (polypropylene fiber).

[0063]

[0064] Step 4, time function calculation (take t=365 days, t c =7 days, V / S=22mm as an example):

[0065] .

[0066] Step 5, calculate the final shrinkage prediction value at the age t = 365 days.

[0067] .

[0068] The comparison results of the test measured value and the model predicted value of the test of the embodiment are shown in Table 2 and Figure 2 .

[0069] Table 2 Comparison of model prediction accuracy of Example 1 (shrinkage strain at 365 days, x 10-4) 6 ) Example 1 Relative error Example measured value 410.75 x 10 -6 ]]> Traditional GL2000 model 463.91 x 10 -6 ]]> +12.94% Invention model 402.4 x 10 -6 ]]> -2.03% From the above results, it can be seen that the shrinkage prediction model proposed in the embodiment can well fit the long-term shrinkage curve of concrete with different seawater concentrations and different fiber contents. For complex fiber-reinforced high-performance seawater sea sand concrete, the prediction error of the model of the application is significantly lower than that of the traditional GL2000 model, and the long-term shrinkage behavior can be accurately predicted, providing a reliable tool for the design and durability assessment of marine engineering structures.

[0070] Example 2, a shrinkage prediction model for fiber-reinforced high-performance seawater sea sand concrete, obtained by the construction method of Example 1, is used to predict the long-term shrinkage deformation behavior of high-performance seawater sea sand concrete mixed with fibers in a marine environment.

[0071] The beneficial effects of Example 1 and Example 2 are: 1. The shrinkage prediction model established by the application can accurately characterize the shrinkage law of high-performance seawater sea sand fiber concrete by introducing seawater concentration correction, effective humidity mechanism and fiber inhibition coefficient, and the prediction accuracy is significantly better than that of the traditional model.

[0072] 2. A multi-factor coupled theoretical framework is used to consider the interactive effects of seawater chemical effects, microphysical mechanisms and fiber mechanical constraints, forming a systematic prediction system, which provides an innovative solution for concrete shrinkage behavior prediction in marine environment.

[0073] 3. The model has clear physical meaning and strong engineering applicability, and can accurately predict the shrinkage deformation of concrete under different working conditions, providing reliable theoretical support for the durability design and long-term performance evaluation of marine engineering structures, and has important engineering application value.

[0074] Test Example 1, used to verify the prediction accuracy of the model of Example 2 under different seawater concentrations.

[0075] The concrete mix proportions are shown in Table 3, with a water-cement ratio of 0.24. Fresh water, a mixture of 50% fresh water and 50% natural seawater, natural seawater, and 200% artificial seawater were used for mixing. P.O52.5 ordinary Portland cement was used, with a silica content exceeding 97% in the silica fume. Grade I fly ash was used. The fineness modulus of the sea sand was 2.3–2.6, and the mud content was less than 1.0%. Granite crushed stone with a particle size of 5–20 mm was used as coarse aggregate. The polycarboxylate superplasticizer used had a water reduction rate of 28%. The specimen size was 100 mm × 100 mm × 515 mm. After standard curing, drying shrinkage tests were conducted in an environment with a temperature of 20 ± 2℃ and a relative humidity of 65 ± 5%. The 28-day cubic compressive strengths of the concrete were 111.4 MPa, 108.3 MPa, 109.8 MPa, and 106.2 MPa, respectively. Shrinkage values ​​were recorded after 7 days of standard curing following pouring.

[0076] Table 3 Concrete mix proportions for Experiment 1 (kg / m³) Number Water Water type Cement Silica fume Fly ash Sea sand Coarse aggregate Water reducing agent 0%SWC 145.6 Fresh water 455 91 60.6 739.3 1274 12.1 50%SWC 145.6 50% fresh water + 50% natural seawater 455 91 60.6 739.3 1274 12.1 100%SWC 145.6 Natural seawater 455 91 60.6 739.3 1274 12.1 200%SWC 145.6 200% concentration artificial seawater 455 91 60.6 739.3 1274 12.1 In the model prediction of this experimental example, the parameters were set as follows: cement type coefficient K = 1.15, 28-day compressive strength... Fiber content was measured at pressures of 111.4 MPa, 108.3 MPa, 109.8 MPa, and 106.2 MPa, respectively. =0, the time function is taken as t=365 days. =7 days, V / S=20mm. Seawater concentration influence coefficient A=0.055, humidity influence coefficient B=-0.02, ambient humidity h=65%.

[0077] The comparison results of the 365-day shrinkage measured values ​​of concrete with different seawater concentrations, the model prediction curve of Example 2, the prediction curve of the traditional GL2000 model, the prediction curve of the traditional ACI209 model, the prediction curve of the traditional B3 model, the prediction curve of the traditional CABR model, and the prediction curve of the traditional MC2010 model are shown in [the original text]. Figure 3-Figure 6 The results show that the traditional ACI209, B3, CABR, and MC2010 models significantly underestimate the shrinkage value of high-strength concrete. The traditional GL2000 model, due to its failure to consider the chemical effects of seawater, also predicts a lower value and fails to reflect the influence of concentration gradients. In contrast, the model of this invention, by introducing a seawater concentration correction coefficient and an effective humidity function, achieves a prediction curve that closely matches the measured data at different seawater concentrations, accurately predicting the shrinkage value of concrete at various seawater concentrations.

[0078] Experiment 2 was used to verify the predictive accuracy of the model in Example 2 under different environmental humidity conditions.

[0079] The concrete mix proportion is shown in Table 4, and the water-binder ratio is 0.24. Natural seawater is used for mixing, P.O 52.5 ordinary portland cement is used, the silicon content of silica fume is more than 97%, the fly ash is first-class fly ash, the fineness modulus of sea sand is 2.3-2.6, the clay content is less than 1.0%, the coarse aggregate is granite gravel with a particle size of 5-20 mm, and the polycarboxylate superplasticizer has a water-reducing rate of 28%. The specimen size is 100 mm x 100 mm x 515 mm, and after standard curing, the drying shrinkage test is carried out in an environment with a temperature of 20±2℃, a relative humidity of 50±5%, a relative humidity of 65±5% and a relative humidity of 50±5%. The 28-day cubic compressive strength of the concrete is 109.8 MPa, and the shrinkage value is recorded after starting to test after 7 days of standard curing after pouring.

[0080] Table 4 Concrete mix proportion of test example 2 (kg / m³) Number Water Water type Cement Silica fume Fly ash Sea sand Coarse aggregate Water reducing agent 100%SWC 145.6 Natural seawater 455 91 60.6 739.3 1274 12.1 In the model prediction of this test example, the values of each parameter are as follows: the cement type coefficient K=1.15, the 28-day compressive strength =109.8 MPa, the fiber content =0, the time function takes t=365 days, =7 days, and V / S=20 mm. The seawater concentration influence coefficient A=0.055, the humidity influence coefficient B=-0.02, and the environmental humidity is taken as 0.50, 0.65 and 0.80, respectively.

[0081] The comparison results of the 365-day shrinkage measured value of the concrete under different relative humidities, the model prediction curve of this embodiment 2, the traditional GL2000 model prediction curve, the traditional ACI209 model prediction curve, the traditional B3 model prediction curve, the traditional CABR model prediction curve and the traditional MC2010 model prediction curve are shown in Figure 7-Figure 9 . The results show that the traditional ACI209 model, B3 model, CABR model and MC2010 model still underestimate the shrinkage value of high-strength concrete, and although the traditional GL2000 model can reflect the trend of increased shrinkage caused by reduced humidity, it does not consider the additional osmotic pressure difference caused by seawater ions, so its humidity sensitivity is lower than the measured value. The model of this embodiment 2 accurately captures the shrinkage development behavior of seawater concrete under different humidity environments by introducing effective humidity correction, and the prediction accuracy is significantly better than that of the traditional model.

[0082] Test example 3 is used to verify the prediction accuracy of the model of embodiment 2 under the condition of adding different amounts of fiber (taking PP fiber as an example).

[0083] The concrete mix proportion is shown in Table 5, and the water-binder ratio is 0.24. The natural seawater is used for mixing, the cement is P.O 52.5 ordinary portland cement, the silica content of silica fume is more than 97%, the fly ash is first-class fly ash, the fineness modulus of sea sand is 2.3-2.6, the clay content is less than 1.0%, the coarse aggregate is granite gravel with a particle size of 5-20 mm, and the polycarboxylate superplasticizer has a water-reducing rate of 28%. By changing the dosage of PP fiber (length 12 mm, diameter 30 μm), concrete specimens with fiber volume contents of 0%, 0.1%, 0.2% and 0.3% are prepared. The specimen size is 100 mm x 100 mm x 515 mm, and after standard curing, the specimens are placed in an environment with a temperature of 20±2℃ and a relative humidity of 65±5% for drying shrinkage test. The 28-day cubic compressive strength of the concrete is 109.8 MPa, 107.2 MPa, 111.3 MPa and 105.1 MPa, respectively, and the shrinkage value is recorded after starting the test after 7 days of standard curing after pouring.

[0084] Table 5 Concrete mix proportion of Example 3 (kg / m³) Number Water Water type Cement Silica fume Fly ash Sea sand Coarse aggregate Water reducing agent Fiber content 0%PP 145.6 Natural seawater 455 91 60.6 739.3 1274 12.1 0 0%PP 145.6 Natural seawater 455 91 60.6 739.3 1274 12.1 0.1% 0%PP 145.6 Natural seawater 455 91 60.6 739.3 1274 12.1 0.2% 0%PP 145.6 Natural seawater 455 91 60.6 739.3 1274 12.1 0.3% In the model prediction of this test, the values of each parameter are as follows: the cement type coefficient K = 1.15, the 28-day compressive strength is 109.8 MPa, 107.2 MPa, 111.3 MPa and 105.1 MPa, respectively, the fiber content is 0, 0.001, 0.002 and 0.003, respectively, the time function takes t = 365 days, 7 days, and V / S = 20 mm. The seawater concentration influence coefficient A = 0.055, the humidity influence coefficient B = -0.02, and the environmental humidity is 0.65. The fiber inhibition coefficient in the fiber efficiency coefficient α, according to the fitting results of the previous system test, for the polypropylene fiber used in this test example, α = 0.036.

[0085] The comparison results of the measured shrinkage values of seawater concrete with different PP fiber contents, the model prediction curves of Example 2, the prediction curves of the traditional GL2000 model, the prediction curves of the traditional ACI209 model, the prediction curves of the traditional B3 model, the prediction curves of the traditional CABR model and the prediction curves of the traditional MC2010 model are shown in Figure 10-Figure 13The results show that the traditional ACI209 model, B3 model, CABR model and MC2010 model still underestimate the shrinkage value of high-strength concrete, and the traditional model cannot consider the constraint effect of fibers, and the predicted value is only the shrinkage curve of plain concrete. The model of embodiment 2 clearly quantifies the constraint effect of fibers on shrinkage strain by introducing the fiber inhibition coefficient derived based on the meso-mechanical theory, and the predicted curve is highly consistent with the measured data of different fiber contents, fully proving the applicability of the model in fiber reinforced high-performance seawater sea sand concrete.

[0086] From the above three test examples, it can be seen that the shrinkage prediction model of fiber reinforced high-performance seawater sea sand concrete proposed by the present application can accurately reflect the complex influence of seawater concentration, environmental humidity and fiber content on the long-term shrinkage behavior of concrete, and the prediction accuracy is significantly higher than that of the traditional model, providing an effective technical tool for accurate prediction of concrete shrinkage and deformation in marine engineering construction.

[0087] Embodiment 3 provides an electronic device, comprising: a processor, and a memory and a transceiver connected in communication with the processor; the memory stores computer execution instructions; and the transceiver is used for transmitting and receiving data; the processor executes the computer execution instructions stored in the memory to realize the construction method in embodiment 1.

[0088] It should be understood that the electronic device can be used to execute the corresponding steps and / or processes in the above-mentioned method embodiments. Alternatively, the memory can include read-only memory and random access memory, and provide instructions and data to the processor. A part of the memory can also include non-volatile random access memory. For example, the memory can also store device type information. The processor can be used to execute the instructions stored in the memory, and when the processor executes the instructions, the processor 210 can execute the corresponding steps and / or processes in the above-mentioned method embodiments.

[0089] It should be understood that in the embodiments of the present application, the processor can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0090] In the implementation process, each step of the above method can be completed by integrated logic circuits of hardware in the processor or instructions in the form of software. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as execution completed by a hardware processor, or executed by a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the art such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, register, etc. The storage medium is located in the memory, and the processor executes the instructions in the memory to complete the steps of the above method in combination with the hardware thereof. To avoid repetition, it will not be described in detail here.

[0091] In this embodiment, a computer readable storage medium is provided, and the computer readable storage medium stores computer execution instructions. The computer execution instructions are executed by a processor to implement the construction method in embodiment 1.

[0092] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. In actual implementation, another division mode can be adopted, for example, a plurality of units or components can be combined or integrated into another system, or some features can be omitted or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, device or unit, and can be electrical, mechanical or other forms.

[0093] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. According to actual needs, part or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0094] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0095] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0096] In the description of the above-described embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0097] The above is merely specific implementation of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for constructing a shrinkage prediction model of fiber reinforced high-performance seawater-sea sand concrete, characterized by, The method comprises the following steps: S1, introducing a seawater concentration correction term to the limit shrinkage strain of an existing concrete shrinkage prediction model, and calculating a seawater concentration influence coefficient; S2, introducing an effective humidity correction term to the humidity function of the existing concrete shrinkage prediction model, and calculating a humidity perception coefficient; S3, constructing a fiber constraint function and introducing a fiber inhibition coefficient, and determining a fiber efficiency coefficient through fiber type and dosage tests; S4, outputting a fiber-reinforced high-performance seawater sea sand concrete shrinkage prediction model by using a time development function in combination with the seawater concentration correction term, the effective humidity correction term and the fiber inhibition coefficient.

2. The construction method of claim 1, wherein, The calculation formula of the seawater concentration correction term in the step S1 is: η c =A·c+1; wherein η c is a seawater concentration correction term, A is a seawater concentration influence coefficient, and c is a seawater concentration.

3. The construction method of claim 2, wherein, The calculation formula of the effective humidity correction term in the step S2 is: h eff = h · (B · c + 1); where h eff is the effective humidity correction term, h is the ambient relative humidity, B is the humidity perception coefficient, and c is the seawater concentration.

4. The construction method according to claim 3, characterized in that, The calculation steps of the seawater concentration influence coefficient A and the humidity perception coefficient B are as follows: It is assumed that the influence of seawater concentration on the corrected limit shrinkage strain is positively correlated, and that seawater concentration affects effective humidity by changing the pore solution chemical potential, and the following theoretical relationship is obtained: ； where ε shu is the modified ultimate shrinkage strain; the actual shrinkage strain of concrete under different seawater concentrations and different ambient humidity is measured by experiment to obtain the corresponding test data; Based on the test data, the theoretical relationship is subjected to multivariate nonlinear regression analysis, and the seawater concentration influence coefficient A and the humidity perception coefficient B are simultaneously fitted.

5. The construction method of claim 1, wherein, The determination step of the fiber efficiency coefficient in the step S3 comprises: The fiber constraint function expression is constructed to obtain a theoretical calculation formula of the fiber inhibition coefficient: ； wherein k fiber is the fiber inhibition coefficient, a is the fiber efficiency coefficient, V f is the volume fraction of the fiber, l f / d f is the aspect ratio of the fiber; The actual shrinkage strain of concrete with different fiber types, different volume contents V f and different aspect ratios l f / d f is measured by a test system to obtain test data. According to the test data, the measured values of the fiber inhibition coefficient under each working condition are calculated, and the fiber efficiency coefficients of different fiber types are fitted through inversion analysis.

6. The construction method of claim 1, wherein, The fiber types at least include basalt fiber, polypropylene fiber and steel fiber.

7. The construction method of claim 1, wherein, The formula of the fiber-reinforced high-performance seawater sea sand concrete shrinkage prediction model in the step S4 is as follows: ； where ε cs (t) is the shrinkage strain of fiber reinforced high performance seawater-sea sand concrete at age t days, ε shu is the modified ultimate shrinkage strain, β(h) is the modified humidity function, β(t) is the time function describing the development of shrinkage with time; k fiber is the fiber inhibition coefficient.

8. A fiber reinforced high performance seawater sea sand concrete shrinkage prediction model characterized by, The construction method of any one of claims 1-7 is adopted to predict the long-term shrinkage deformation behavior of high-performance seawater sea sand concrete mixed with fibers in a marine environment.

9. An electronic device, comprising: It comprises: a processor, a memory and a transceiver connected in communication with the processor; the memory stores computer execution instructions; the transceiver is used for transmitting and receiving data; the processor executes the computer execution instructions stored in the memory to realize the construction method of any one of claims 1-7.

10. A computer readable storage medium, characterized in that, the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by a processor to realize the construction method of any one of claims 1-7.

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