Design method of artificial reef of solid waste based marine concrete with FRP bars

Abstract

The application discloses a design method of a solid waste-based marine concrete artificial fish reef based on FRP bars, and comprises the following steps: determining an optimal cementing material ratio set, obtaining an optimal design set, performing artificial fish reef CFD simulation and topological optimization of the size of the artificial fish reef to obtain a first size, determining a biological adaptation pH value according to biological species in a to-be-dumped area and performing specification correction and hole distribution on the first size to obtain a second size, determining a first predicted strength of the to-be-designed artificial fish reef, correcting the first predicted strength to obtain a second predicted strength, matching design parameters by matching the second predicted strength and the biological adaptation pH value to obtain target performance, and matching the design performance to obtain the matching design parameters, and taking the matching design parameters and hole parameters as an artificial fish reef design scheme for the to-be-dumped area. The application effectively improves the durability, structural stability and ecological adaptability of the artificial fish reef by performing strength simulation, size topological optimization, specification correction and hole distribution on the artificial fish reef.

Description

Technical Field

[0001] This invention relates to the field of dimensional design, and more particularly to a design method for artificial reefs based on FRP-reinforced solid waste marine concrete. Background Technology

[0002] In the field of marine engineering construction and ecological restoration, artificial reef technology has received widespread attention and rapid development in recent years as an important means to improve the marine ecological environment and enhance fishery resources. Artificial reefs can not only provide habitats and breeding grounds for marine life, but also optimize the structure of marine ecosystems and promote the sustainable development of marine ecology and economy. Innovation in its design and construction technology is of key significance to the protection and utilization of marine resources.

[0003] However, traditional artificial reef designs often neglect material compatibility and environmental adaptability. In complex marine environments, ordinary concrete reefs are susceptible to erosion due to insufficient durability, leading to structural damage and making it difficult to function effectively in the long term. Furthermore, their design process lacks comprehensive consideration of factors such as the needs of marine life and ocean currents, resulting in suboptimal ecological function and stability. Emerging materials such as FRP-reinforced concrete and solid waste-based marine concrete offer new directions for the development of artificial reefs. This invention proposes a design method for artificial reefs based on FRP-reinforced solid waste-based marine concrete. By conducting tensile tests on FRP-reinforced concrete specimens and hydration thermodynamic simulations of solid waste-based marine concrete, the cementitious material ratio is accurately determined. Simultaneously, combining geotechnical tests under seawater aging, finite element simulation, and CFD simulation, and comprehensively considering factors such as ocean currents and biological species, the method performs strength simulation, dimensional topology optimization, specification correction, and void allocation for the artificial reef. This technical solution effectively improves the durability, structural stability, and ecological adaptability of the artificial reef, achieving an organic combination of material properties and marine environment and biological needs. It has significant practical implications for advancing artificial reef design technology and promoting marine ecological protection and sustainable development of fishery resources. Summary of the Invention

[0004] The purpose of this invention is to provide a design method for marine concrete artificial reefs based on FRP-reinforced solid waste foundations.

[0005] To achieve the above objectives, the present invention is implemented according to the following technical solution:

[0006] This invention includes the following steps:

[0007] Tensile tests were conducted on FRP-reinforced concrete specimens to determine the applicable alkalinity range of FRP reinforcement. Hydration thermodynamics simulation of solid waste-based marine concrete was performed. Based on the hydration thermodynamics simulation results and the applicable alkalinity range of FRP reinforcement, an optimal cementitious material mix ratio was determined. The hydration thermodynamics simulation results included the pH value of the concrete pore solution and the pH value of the concrete surface.

[0008] Geotechnical tests and finite element simulations were conducted on FRP-reinforced solid waste-based marine concrete beams under seawater aging. Based on the results of the geotechnical tests and finite element simulations, strength simulations of artificial reefs of different shapes were carried out to obtain an optimal design set. The optimal design set includes design parameters and design performance.

[0009] Historical extreme ocean current data of the area to be deployed are obtained to perform CFD simulation of the artificial reef. Based on the CFD simulation results, the topology of the artificial reef is optimized to obtain the first size.

[0010] The first size is modified and the holes are allocated according to the species of organisms in the area to be introduced to obtain the second size. The pH value for biological adaptation is determined according to the species of organisms in the area to be introduced. The second size includes the second specification and hole parameters.

[0011] The first predicted intensity of the artificial reef to be designed is determined based on the species of organisms in the area to be deployed and the deployment strategy. The second predicted intensity is obtained by correcting the first predicted intensity based on the environment of the area to be deployed.

[0012] The second predicted intensity and the biologically adapted pH value are combined to form the target performance. The target performance is matched with the design performance to obtain matching design parameters. The matching design parameters and the pore parameters are used as the design scheme for the artificial reef in the area to be deployed.

[0013] Furthermore, the method for determining the preferred set of cementitious material proportions includes:

[0014] FRP-reinforced concrete tensile specimens were prepared, and tensile tests were conducted after immersion in different solution alkalinity conditions to obtain tensile strength. The strength loss rate was calculated based on the tensile strength of the control specimens. The alkalinity of the solution corresponding to the FRP-reinforced concrete tensile specimens with a strength loss rate less than the strength loss rate threshold was selected as the applicable range of FRP reinforcement alkalinity.

[0015] A standard marine environment was set up, and hydration thermodynamics simulation was performed on solid waste-based marine concrete with different cementitious material ratios to obtain the pH value of the concrete pore solution and the pH value of the concrete surface. The cementitious material ratios corresponding to the solid waste-based marine concrete with the concrete pore solution pH value within the applicable range of FRP reinforcement alkalinity were selected as the preferred cementitious material ratios. The preferred cementitious material ratios and the corresponding concrete pore solution pH values ​​and concrete surface pH values ​​were combined to form the preferred cementitious material ratio set.

[0016] Furthermore, the method for obtaining the preferred design set includes:

[0017] Solid waste-based marine concrete test blocks and FRP-reinforced solid waste-based marine concrete beams with different reinforcement ratios were prepared according to the preferred cementitious material ratio and subjected to seawater aging treatment. Material property tests and strength tests were conducted to obtain the strength of the test blocks and the strength of the test beams. The strength of the test beams included yield strength, static load strength and impact strength.

[0018] A test block model of solid waste-based marine concrete was established, and the strength of the simulated test block was obtained by multiphysics coupling simulation. The test block model was adjusted according to the deviation between the strength of the test block and the strength of the simulated test block to obtain an optimal test block model. The multiphysics coupling simulation includes a seawater diffusion module, a chemical damage module, and a structural mechanics module.

[0019] Based on the load-displacement curves of FRP-reinforced concrete tensile specimens corresponding to the optimized test block model and the optimized cementitious material ratio, an FRP-reinforced solid waste-based marine concrete beam model was constructed. Multiphysics coupling simulation was performed to obtain the simulated beam strength. The beam model was adjusted according to the deviation between the experimental beam strength and the simulated beam strength to obtain the optimized beam model. The load-displacement curves of the FRP-reinforced concrete tensile specimens were determined based on the pH value of the concrete pore solution corresponding to the cementitious material ratio.

[0020] Based on the preferred beam model and artificial reef parameters, an artificial reef frame model is constructed, and a multiphysics coupling simulation is performed to obtain the reference artificial reef strength. The reference artificial reef strength includes the static load strength and impact resistance of the artificial reef. The artificial reef parameters include the shape and specifications of the artificial reef.

[0021] An optimal design set is constructed based on the multiphysics coupling simulation results and simulation conditions of the artificial reef frame model; the optimal design set includes design parameters and design performance; the design parameters include the shape of the artificial reef, the specifications of the artificial reef, the reinforcement ratio of the FRP-reinforced solid waste-based marine concrete beam, and the cementitious material ratio of the solid waste-based marine concrete; the design performance includes the strength of the reference artificial reef and the pH value of the concrete surface.

[0022] Furthermore, the method for obtaining the first dimension includes:

[0023] Historical extreme ocean current data of the area to be deployed are obtained to determine ocean current simulation parameters. ANSYS Fluent transient model is used to perform CFD simulation on the artificial reef. Based on the CFD simulation results, optimization objectives are determined, and constraints are determined based on stability evaluation indicators. The ocean current simulation parameters include inlet velocity, reef flow field, and vorticity contour map.

[0024] The optimization objective is specifically expressed as follows:

[0025]

[0026] in The drag coefficient, The resistance encountered by artificial reefs For fluid density, For the velocity of the fluid, This refers to the windward area of ​​the artificial reef. For vorticity volume, This is the integration region of the flow field. The vorticity of the fluid;

[0027] The constraints are specifically expressed as follows:

[0028]

[0029] in This represents the maximum stress that an artificial reef may generate under the influence of a flow field. The yield strength of the artificial reef. The overturning resistance coefficient, To resist overturning moment, For overturning moment, The vortex-induced vibration suppression rate, This represents the actual amplitude of the vortex-induced vibration force. For reference, the amplitude of vortex-induced vibration force, The area of ​​the region where the flow velocity is less than the rated flow velocity. The total flow field area;

[0030] Based on the optimization objective and constraints, topology optimization is performed on the artificial reef size to obtain the first size and the first predicted minimum yield strength corresponding to the artificial reef; the first size includes the optimal shape, optimal porosity and first specification.

[0031] Furthermore, the method for obtaining the second dimension includes:

[0032] The second dimension includes a second specification and pore parameters; the pore parameters include the optimal tertiary pore diameter and the corresponding porosity;

[0033] Based on the biological species in the area to be deployed, we obtained the biological volume and pH value of each species by consulting a biological knowledge graph. We then selected species other than whales and sharks to determine their maximum biological volume. For the first specification Make corrections to obtain the second specification ;

[0034] A predator-prey relationship matrix is ​​constructed based on a species database. The target protected species category is input into a biological knowledge graph to obtain the sizes of natural enemies and protected species. A biological feature matrix is ​​generated based on the corresponding size, local density, and protection priority of the protected species and natural enemy categories, and constraints on hole allocation are determined.

[0035]

[0036] in This is the first aperture size. This is the second aperture size. This is the third aperture size. for Minimum size of natural enemies for The largest size of natural enemies, for Maximum size of protected organisms for Minimum size of protected organisms for Porosity at the size level The total porosity of the artificial reef;

[0037] Three aperture sizes are randomly generated as the initial population. Based on the biomarker matrix and aperture allocation constraints, the NSGA-III algorithm is used to optimize the tertiary aperture to obtain the optimal tertiary aperture. The specific steps are as follows:

[0038] The reference point is dynamically generated using the hypersphere algorithm, expressed as:

[0039]

[0040] in For the first The orientation parameters of each reference point are used to determine the position of the reference point on the hypersphere. To optimize the number of objectives in the problem, For the first The objective function at the th ... individual The function value at that point, For vectors The model field, , This represents the current iteration number. This represents the maximum number of iterations.

[0041] Hybrid evolution of operators is performed, specifically including: using fusion differential evolution to process 70% of operators, using covariance matrix adaptive processing to process 30% of operators, and performing polynomial crossover to obtain evolutionary operators;

[0042] Based on the hole allocation constraints, the hole size that violates the constraints is subjected to constraint layering processing. The Kriging surrogate model is used to screen the candidate solutions to obtain the preferred candidate solutions. Based on the preferred candidate solutions, the high potential solutions are repeatedly iterated and output as the optimal third-level hole size.

[0043] Based on the porosity allocation constraints, the optimal third-order pore size, and the biomarker matrix, the porosity allocation is performed to obtain the porosity corresponding to the optimal third-order pore size. The specific steps are as follows:

[0044] Calculate the biodensity weights for each protected species, and use a Gaussian mapping to probabilistically match the optimal tertiary pore size with the body width distribution of the protected species to obtain the porosity corresponding to the optimal tertiary pore size. The expression is:

[0045]

[0046]

[0047] in for Porosity of pore size To protect species The average body width, To protect species The standard deviation of body width For organisms Local density, For organisms Biological density weight, For the sample size, For bandwidth, For organisms The location coordinates of the area where it is located. For the first The location coordinates of each sample This is the Epanechnikov kernel function.

[0048] Furthermore, the method for obtaining the second predicted intensity includes:

[0049] The first predicted strength includes the first predicted impact strength, the first predicted static load strength, and the first predicted minimum yield strength;

[0050] The first predicted impact resistance strength is determined by obtaining the attack power of the organisms in the area to be deployed and the design safety factor based on the knowledge graph;

[0051] Based on the bioattachment status of the area to be deployed using a knowledge graph, the bioattachment load is determined. The stacking load is determined based on the deployment strategy. Finally, the first predicted static load strength is determined based on the bioattachment load, stacking load, and design safety factor, expressed as:

[0052]

[0053] in For the first predicted static load strength, For maximum bioattachment density, The effective surface area of ​​artificial islands and reefs. The maximum number of stacking layers is determined by the delivery strategy. For the density of artificial islands and reefs, The effective volume of a single island or reef. It is the acceleration due to gravity. To design a safety factor;

[0054] The environmental impact factor will be obtained by inputting an environmental function based on the environment of the area to be treated, and the expression is:

[0055]

[0056] in As environmental impact factors, , These are seawater acid ions. Ion weight and ion concentration sensitivity, Seawater acidic ions ion concentration, Seawater acidic ions The critical value of ion concentration. As for ocean current weight, For pressure weight, , The average ocean current velocity and critical current value for the area to be deployed. , The values ​​represent the average seabed pressure and critical pressure in the area to be deployed. , The average temperature and critical temperature of the area to be deployed. for Influence function;

[0057] The second predicted strength is obtained by modifying the first predicted strength according to the environmental impact factor; the second predicted strength includes the second predicted impact strength, the second predicted static load strength, and the minimum value of the second predicted yield strength.

[0058] Furthermore, the method for obtaining matching design parameters includes:

[0059] The target performance is composed of the second predicted intensity and the biologically adapted pH value. The closeness between the target performance and the performance of the preferred design pool is calculated. The specific steps are as follows:

[0060] calculate The entropy value of the performance item, according to Determining the entropy value of the performance item The weight of a performance item is expressed as:

[0061]

[0062]

[0063] in for The entropy value of the performance item. for The weight of the performance item, To optimize design and improve performance Quantity, To optimize the design set Design performance The value, for The control constants for this performance;

[0064] The positive and negative ideal solutions of the optimized design ensemble are determined based on the design performance weights, and the expression is as follows:

[0065]

[0066]

[0067] in For design performance The negative ideal solution, For design performance The ideal solution;

[0068] The closeness between the target performance and the performance of the optimized design lumped-design is calculated based on the positive and negative ideal solutions of the optimized design lumped-design performance. The expression is as follows:

[0069]

[0070] in For target performance and optimal design set No. The closeness of the group's design performance. For the first Project performance;

[0071] The design parameters corresponding to the design performance of the highest proximity group are taken as the matching design parameters. The matching design parameters and the hole parameters are used as the design scheme for the artificial reef in the area to be deployed.

[0072] Furthermore, the formulation of the solid waste-based marine concrete includes: gel material, water base, sea sand and biomimetic steel fiber; the gel material includes phosphogypsum, steel slag tailings, water-quenched blast furnace slag and alkaline admixtures; the alkaline admixtures are a mixture of red mud and carbide slag; the water base includes seawater and water-reducing agent; the biomimetic steel fiber is obtained by biomimetic treatment of steel fiber with tannic acid.

[0073] The beneficial effects of this invention are:

[0074] This invention relates to a design method for FRP-reinforced solid waste-based marine concrete artificial reefs. Compared with existing technologies, this invention has the following technical advantages:

[0075] This invention improves the accuracy of FRP-reinforced solid waste-based marine concrete artificial reef design by determining the preferred cementitious material ratio set, obtaining the preferred design set, size prediction, strength prediction, and parameter matching steps. This enhances the efficiency and precision of FRP-reinforced solid waste-based marine concrete artificial reef design, and makes the artificial reef parameter design intelligent, which can greatly save resources. It can realize the size design of artificial reefs in the area to be deployed, and achieve the organic combination of material performance with marine environment and biological needs. This has important practical significance for promoting the advancement of artificial reef design technology and promoting the sustainable development of marine ecological protection and fishery resources.

[0076] The solid waste-based marine concrete provided by this invention uses FRP bars instead of steel bars, which can effectively avoid the problem of steel corrosion and improve the structural durability and service life. At the same time, the solid waste-based marine concrete provided by this invention uses gel materials to effectively resist sulfate erosion in the marine environment. The biomimetic treatment of the steel fiber surface with tannic acid improves the corrosion resistance of the steel fiber, thereby improving the crack resistance of the supersulfur cement concrete. The use of tannic acid can reduce the alkalinity inside the cementing system, which is conducive to the epiphytic growth of algae and fish when it is made into artificial reefs. Attached Figure Description

[0077] Figure 1 This is a flowchart illustrating the steps of the design method for marine concrete artificial reefs based on FRP-reinforced solid waste foundations according to the present invention. Detailed Implementation

[0078] The present invention will be further described below through specific embodiments. The illustrative embodiments and descriptions herein are used to explain the present invention, but are not intended to limit the present invention.

[0079] The present invention includes the following steps in the design method of FRP-reinforced solid waste-based marine concrete artificial reef:

[0080] like Figure 1 As shown in this embodiment, the design method for FRP-reinforced solid waste-based marine concrete artificial reefs includes:

[0081] Tensile tests were conducted on FRP-reinforced concrete specimens to determine the applicable alkalinity range of FRP reinforcement. Hydration thermodynamics simulation of solid waste-based marine concrete was performed. Based on the hydration thermodynamics simulation results and the applicable alkalinity range of FRP reinforcement, an optimal cementitious material mix ratio was determined. The hydration thermodynamics simulation results included the pH value of the concrete pore solution and the pH value of the concrete surface.

[0082] Geotechnical tests and finite element simulations were conducted on FRP-reinforced solid waste-based marine concrete beams under seawater aging. Based on the results of the geotechnical tests and finite element simulations, strength simulations of artificial reefs of different shapes were carried out to obtain an optimal design set. The optimal design set includes design parameters and design performance.

[0083] Historical extreme ocean current data of the area to be deployed are obtained to perform CFD simulation of the artificial reef. Based on the CFD simulation results, the topology of the artificial reef is optimized to obtain the first size.

[0084] The first size is modified and the holes are allocated according to the species of organisms in the area to be introduced to obtain the second size. The pH value for biological adaptation is determined according to the species of organisms in the area to be introduced. The second size includes the second specification and hole parameters.

[0085] The first predicted intensity of the artificial reef to be designed is determined based on the species of organisms in the area to be deployed and the deployment strategy. The second predicted intensity is obtained by correcting the first predicted intensity based on the environment of the area to be deployed.

[0086] The second predicted intensity and the biologically adapted pH value are combined to form the target performance. The target performance is matched with the design performance to obtain matching design parameters. The matching design parameters and the pore parameters are used as the design scheme for the artificial reef in the area to be deployed.

[0087] In this embodiment, the method for determining the preferred set of cementitious material proportions includes:

[0088] FRP-reinforced concrete tensile specimens were prepared, and tensile tests were conducted after immersion in different solution alkalinity conditions to obtain tensile strength. The strength loss rate was calculated based on the tensile strength of the control specimens. The alkalinity of the solution corresponding to the FRP-reinforced concrete tensile specimens with a strength loss rate less than the strength loss rate threshold was selected as the applicable range of FRP reinforcement alkalinity.

[0089] A standard marine environment was set up, and hydration thermodynamics simulation was performed on solid waste-based marine concrete with different cementitious material ratios to obtain the pH value of the concrete pore solution and the pH value of the concrete surface. The cementitious material ratios corresponding to the solid waste-based marine concrete with the concrete pore solution pH value within the applicable range of FRP reinforcement alkalinity were selected as the preferred cementitious material ratios. The preferred cementitious material ratios and the corresponding concrete pore solution pH values ​​and concrete surface pH values ​​were combined to form the preferred cementitious material ratio set.

[0090] In the actual assessment, an artificial island reef in a certain sea area was designed, and 20 sets of FRP reinforced concrete tensile specimens (3 specimens in each set) were made. After being immersed in a solution with pH ∈ [9, 13.5] for 180 days, tensile strength tests were conducted to obtain the tensile strength of the FRP reinforced concrete tensile specimens after immersion under different solution alkalinity conditions (the average tensile strength of 3 specimens in each set was taken). Based on the tensile strength of the FRP reinforced concrete tensile specimens under standard curing conditions, the strength loss rate of each tensile specimen was calculated. The solution alkalinity corresponding to the tensile specimen with a strength loss rate less than 15% of the loss rate threshold was taken as the applicable range of FRP reinforcement alkalinity: pH < 12.3.

[0091] Multiple cementitious material ratios were configured based on the following mass fractions: 20%-30% phosphogypsum, 20%-30% steel slag tailings, 40%-60% water-quenched blast furnace slag, and 10%-20% alkaline admixtures. Hydration thermodynamics simulations were conducted in a simulated standard marine environment (salinity 3.5%, temperature 20℃) to obtain the pH values ​​of the concrete pore solution and concrete surface for different cementitious material ratios. The cementitious material ratio with a concrete pore solution pH value within the applicable alkalinity range of FRP reinforcement (pH < 12.3) was selected as the preferred cementitious material ratio. The preferred cementitious material ratios and their corresponding concrete pore solution pH values ​​and concrete surface pH values ​​were combined to form the preferred cementitious material ratio set.

[0092] In this embodiment, the method for obtaining the preferred design set includes:

[0093] Solid waste-based marine concrete test blocks and FRP-reinforced solid waste-based marine concrete beams with different reinforcement ratios were prepared according to the preferred cementitious material ratio and subjected to seawater aging treatment. Material property tests and strength tests were conducted to obtain the strength of the test blocks and the strength of the test beams. The strength of the test beams included yield strength, static load strength and impact strength.

[0094] A test block model of solid waste-based marine concrete was established, and the strength of the simulated test block was obtained by multiphysics coupling simulation. The test block model was adjusted according to the deviation between the strength of the test block and the strength of the simulated test block to obtain an optimal test block model. The multiphysics coupling simulation includes a seawater diffusion module, a chemical damage module, and a structural mechanics module.

[0095] Based on the load-displacement curves of FRP-reinforced concrete tensile specimens corresponding to the optimized test block model and the optimized cementitious material ratio, an FRP-reinforced solid waste-based marine concrete beam model was constructed. Multiphysics coupling simulation was performed to obtain the simulated beam strength. The beam model was adjusted according to the deviation between the experimental beam strength and the simulated beam strength to obtain the optimized beam model. The load-displacement curves of the FRP-reinforced concrete tensile specimens were determined based on the pH value of the concrete pore solution corresponding to the cementitious material ratio.

[0096] Based on the preferred beam model and artificial reef parameters, an artificial reef frame model is constructed, and a multiphysics coupling simulation is performed to obtain the reference artificial reef strength. The reference artificial reef strength includes the static load strength and impact resistance of the artificial reef. The artificial reef parameters include the shape and specifications of the artificial reef.

[0097] An optimal design set is constructed based on the multiphysics coupling simulation results and simulation conditions of the artificial reef frame model; the optimal design set includes design parameters and design performance; the design parameters include the shape of the artificial reef, the specifications of the artificial reef, the reinforcement ratio of the FRP-reinforced solid waste-based marine concrete beam, and the cementitious material ratio of the solid waste-based marine concrete; the design performance includes the reference artificial reef strength and the pH value of the concrete surface.

[0098] In the actual evaluation, solid waste-based marine concrete test blocks made with different preferred cementitious material ratios and FRP-reinforced solid waste-based marine concrete beams with different reinforcement ratios were subjected to 90 days of seawater aging treatment, and the static load strength and impact strength were tested to obtain the corresponding strength data.

[0099] A solid waste-based marine concrete test block model was established. Seawater aging simulation was performed by setting parameters for the seawater diffusion module and the chemical damage module. Static load and impact simulations were conducted to obtain the strength of the marine concrete simulated test block. The parameters of the seawater diffusion module and the chemical damage module were adjusted according to the deviation between the strength of the test block and the strength of the simulated test block to obtain the optimal test block model (when the deviation is <5%).

[0100] Using the preferred test block model as the material constitutive model and the load-displacement curve of the FRP-reinforced concrete tensile specimen corresponding to the pH value of the concrete pore solution with the preferred cementitious material ratio as the bond-slip constitutive model, an FRP-reinforced solid waste-based marine concrete beam model was constructed. Multiphysics coupling simulation was performed to obtain the simulated beam strength. The bond-slip constitutive model and boundary conditions were adjusted according to the deviation between the test beam strength and the simulated beam strength to obtain the preferred beam model (when the deviation is <5%).

[0101] Based on the optimal beam models with different cementitious material ratios and different reinforcement ratios, artificial reef frame models of different specifications and shapes (including triangular prisms, cubes and cuboids) were built. Multiphysics coupling simulation was performed to augment the data and obtain multiple sets of reference artificial reef strengths. The pH value of the concrete surface of artificial reefs with different cementitious material ratios was determined through the above hydration thermodynamic simulation. The reference artificial reef strength and the concrete surface pH value were combined to form the design performance.

[0102] The design parameters include the shape and specifications of the artificial reef, the reinforcement ratio of the beam, and the proportion of cementitious materials.

[0103] In this embodiment, the method for obtaining the first size includes:

[0104] Historical extreme ocean current data of the area to be deployed are obtained to determine ocean current simulation parameters. ANSYS Fluent transient model is used to perform CFD simulation on the artificial reef. Based on the CFD simulation results, optimization objectives are determined, and constraints are determined based on stability evaluation indicators. The ocean current simulation parameters include inlet velocity, reef flow field, and vorticity contour map.

[0105] The optimization objective is specifically expressed as follows:

[0106]

[0107] in The drag coefficient, The resistance encountered by artificial reefs For fluid density, For the velocity of the fluid, This refers to the windward area of ​​the artificial reef. For vorticity volume, This is the integration region of the flow field. The vorticity of the fluid;

[0108] The constraints are specifically expressed as follows:

[0109]

[0110] in This represents the maximum stress that an artificial reef may generate under the influence of a flow field. The yield strength of the artificial reef. The overturning resistance coefficient, To resist overturning moment, For overturning moment, The vortex-induced vibration suppression rate, This represents the actual amplitude of the vortex-induced vibration force. For reference, the amplitude of vortex-induced vibration force, The area of ​​the region where the flow velocity is less than the rated flow velocity. The total flow field area;

[0111] Based on the optimization objective and constraints, topology optimization is performed on the artificial reef size to obtain a first size and the corresponding first predicted minimum yield strength of the artificial reef; the first size includes the optimal shape, optimal porosity, and first specification;

[0112] In the actual assessment, based on historical extreme ocean current data of the area to be deployed, the inlet velocity and fluid velocity were both set to 2.5 m / s, and the initial dimensions were set as: a 2m×2m×3m cuboid with a porosity of 35%.

[0113] Take seawater fluid density Reference vortex-induced vibration force amplitude The topology of the artificial reef is optimized according to the constraints, and CFD simulation is performed until the optimization objective is met. The first size (2.2m×2.2m×2.2m cube, porosity 40%) and the minimum predicted yield strength of the artificial reef (35MPa) are output. The minimum value is determined by the maximum stress of 28MPa that the artificial reef may generate under the action of the flow field. At this time, the drag coefficient is the minimum, the vortex volume is the maximum, and the constraints are met: overturning coefficient 3.1>2.5, vortex-induced vibration suppression rate 75%>60%, and low velocity region proportion 50%>40%.

[0114] In this embodiment, the method for obtaining the second size includes:

[0115] The second dimension includes a second specification and pore parameters; the pore parameters include the optimal tertiary pore diameter and the corresponding porosity;

[0116] Based on the biological species in the area to be deployed, we obtained the biological volume and pH value of each species by consulting a biological knowledge graph. We then selected species other than whales and sharks to determine their maximum biological volume. For the first specification Make corrections to obtain the second specification ;

[0117] A predator-prey relationship matrix is ​​constructed based on a species database. The target protected species category is input into a biological knowledge graph to obtain the sizes of natural enemies and protected species. A biological feature matrix is ​​generated based on the corresponding size, local density, and protection priority of the protected species and natural enemy categories, and constraints on hole allocation are determined.

[0118]

[0119] in This is the first aperture size. This is the second aperture size. This is the third aperture size. for Minimum size of natural enemies for The largest size of natural enemies, for Maximum size of protected organisms for Minimum size of protected organisms for Porosity at the size level The total porosity of the artificial reef;

[0120] Three aperture sizes are randomly generated as the initial population. Based on the biomarker matrix and aperture allocation constraints, the NSGA-III algorithm is used to optimize the tertiary aperture to obtain the optimal tertiary aperture. The specific steps are as follows:

[0121] The reference point is dynamically generated using the hypersphere algorithm, expressed as:

[0122]

[0123] in For the first The orientation parameters of each reference point are used to determine the position of the reference point on the hypersphere. To optimize the number of objectives in the problem, For the first The objective function at the th ... individual The function value at that point, For vectors The model field, , This represents the current iteration number. This represents the maximum number of iterations.

[0124] Hybrid evolution of operators is performed, specifically including: using fusion differential evolution to process 70% of operators, using covariance matrix adaptive processing to process 30% of operators, and performing polynomial crossover to obtain evolutionary operators;

[0125] Based on the hole allocation constraints, the hole size that violates the constraints is subjected to constraint layering processing. The Kriging surrogate model is used to screen the candidate solutions to obtain the preferred candidate solutions. Based on the preferred candidate solutions, the high potential solutions are repeatedly iterated and output as the optimal third-level hole size.

[0126] Based on the porosity allocation constraints, the optimal third-order pore size, and the biomarker matrix, the porosity allocation is performed to obtain the porosity corresponding to the optimal third-order pore size. The specific steps are as follows:

[0127] Calculate the biodensity weights for each protected species, and use a Gaussian mapping to probabilistically match the optimal tertiary pore size with the body width distribution of the protected species to obtain the porosity corresponding to the optimal tertiary pore size. The expression is:

[0128]

[0129]

[0130] in for Porosity of pore size To protect species The average body width, To protect species The standard deviation of body width For organisms Local density, For organisms Biological density weight, For the sample size, For bandwidth, For organisms The location coordinates of the area where it is located. For the first The location coordinates of each sample For the Epanechnikov kernel function;

[0131] In the actual assessment, based on the biological knowledge graph of the area to be released, the largest biological volume (leatherback turtle 4.5m³) of the area, excluding whales and sharks, was obtained. The first specification was then modified to obtain the second specification. m;

[0132] Based on the biological volume and pH values ​​adapted to the target protected organisms (bream / 8-12cm / 7.8-8.5, scallop / 2-10cm / 7.6-8.3, shrimp / 5-7cm / 7.5-8.2) and the pH values ​​adapted to the attached organisms (barnacles / algae 7.2-8.8), the pH range of the artificial reef surface is determined to be 7.8-8.2.

[0133] The constraint hierarchical processing is defined as assigning a violation level to the constraint violation of different aperture sizes. When the constraints corresponding to the first aperture size, the second aperture size, and the third aperture size are violated, the violation levels are 1, 2, and 3, respectively. When optimizing the aperture size, the higher level constraint is satisfied first.

[0134] Based on the predator-prey relationship matrix and biological knowledge graph, the natural enemies and sizes of the target protected species were determined (grouper / 20-150cm, starfish / 15cm, swimming crab / 10cm), and the constraints for hole allocation were determined. , , Take the maximum number of iterations. Target number The polynomial crossover probability is 0.9. Optimizing the three-stage aperture yields the optimal three-stage aperture: , , 20cm;

[0135] The biological density weights for sea bream, scallops, and shrimp were calculated as 1.0, 0.8, and 0.5, respectively. Based on the local densities of each protected organism in the area to be released (0.5 ind. / m³, 2.0 ind. / m³, and 5.0 ind. / m³), and the mean / standard deviation of the body width of sea bream, scallops, and shrimp (9cm / 2cm, 5cm / 1cm, and 5.5cm / 0.5cm), the porosity corresponding to the optimal tertiary pore size was calculated to be 12%, 26%, and 34%, respectively. (12+26+34) = 72% > the total porosity of 40%. The porosity corresponding to the optimal tertiary pore size was then scaled proportionally. , , .

[0136] In this embodiment, the method for obtaining the second predicted intensity includes:

[0137] The first predicted strength includes the first predicted impact strength, the first predicted static load strength, and the first predicted minimum yield strength;

[0138] The first predicted impact resistance strength is determined by obtaining the attack power of the organisms in the area to be deployed and the design safety factor based on the knowledge graph;

[0139] Based on the bioattachment status of the area to be deployed using a knowledge graph, the bioattachment load is determined. The stacking load is determined based on the deployment strategy. Finally, the first predicted static load strength is determined based on the bioattachment load, stacking load, and design safety factor, expressed as:

[0140]

[0141] in For the first predicted static load strength, For maximum bioattachment density, The effective surface area of ​​artificial islands and reefs. The maximum number of stacking layers is determined by the delivery strategy. For the density of artificial islands and reefs, The effective volume of a single island or reef. It is the acceleration due to gravity. To design a safety factor;

[0142] The environmental impact factor will be obtained by inputting an environmental function based on the environment of the area to be treated, and the expression is:

[0143]

[0144] in As environmental impact factors, , These are seawater acid ions. Ion weight and ion concentration sensitivity, Seawater acidic ions ion concentration, Seawater acidic ions The critical value of ion concentration. As for ocean current weight, For pressure weight, , The average ocean current velocity and critical current value for the area to be deployed. , The values ​​represent the average seabed pressure and critical pressure in the area to be deployed. , The average temperature and critical temperature of the area to be deployed. for Influence function;

[0145] The second predicted strength is obtained by modifying the first predicted strength according to the environmental impact factors; the second predicted strength includes the second predicted impact strength, the second predicted static load strength, and the minimum value of the second predicted yield strength.

[0146] In the actual assessment, the attack power of the strongest organism in the area to be deployed (the impact kinetic energy of the giant grouper is 675J) and the design safety factor of 0.7 were used to determine the first predicted impact resistance strength as 675 / 0.7 = 965J.

[0147] The maximum biofilm density is taken as 15 kg / m² for barnacles and algae, the maximum number of stacked layers is taken as 3, the effective surface area of ​​the artificial reef is taken as 6 * 2.2 * 2.2 * 1.5 = 43.56 m² (taking the area of ​​3 surfaces multiplied by the projection coefficient 1.5), the density of the artificial reef is taken as 2500 kg / m³, and the effective volume of a single reef is 2.2 * 2.2 * 2.2 * 0.1 = 2662 m³ (the artificial reef frame and perforated plate account for 1 / 5 of the total volume). The first predicted static load strength is calculated to be 83.68 kN.

[0148] When pH < 8 When pH ≥ 8, Take ocean current weight Pressure weight Average ocean current velocity Critical value of ocean current velocity Average seabed pressure Critical pressure Average temperature Critical temperature The environmental impact factor is calculated to be 1.115 based on the seawater ion concentration in the area to be treated.

[0149] The second predicted strength is obtained by modifying the first predicted strength based on the environmental impact factor of 1.115 (the minimum value of the second predicted yield strength is 35*1.115=39.025MPa, the second predicted impact strength is 965*1.115=1076J, and the second predicted static load strength is 83.68*1.115=93.3kN).

[0150] In this embodiment, the method for obtaining matching design parameters includes:

[0151] The target performance is composed of the second predicted intensity and the biologically adapted pH value. The closeness between the target performance and the performance of the preferred design pool is calculated. The specific steps are as follows:

[0152] calculate The entropy value of the performance item, according to Determining the entropy value of the performance item The weight of a performance item is expressed as:

[0153]

[0154]

[0155] in for The entropy value of the performance item. for The weight of the performance item, To optimize design and improve performance Quantity, To optimize the design set Design performance The value, for The control constants for this performance;

[0156] The positive and negative ideal solutions of the optimized design ensemble are determined based on the design performance weights, and the expression is as follows:

[0157]

[0158]

[0159] in For design performance The negative ideal solution, For design performance The ideal solution;

[0160] The closeness between the target performance and the performance of the optimized design lumped-design is calculated based on the positive and negative ideal solutions of the optimized design lumped-design performance. The expression is as follows:

[0161]

[0162] in For target performance and optimal design set No. The closeness of the group's design performance. For the first Project performance;

[0163] The design parameters corresponding to the design performance of the highest proximity group are taken as the matching design parameters, and the matching design parameters and the hole parameters are used as the artificial reef design scheme for the area to be deployed.

[0164] In the actual evaluation, the second predicted strength and the biologically adapted pH value were used as the target performance (39.025 MPa, 1076 J, 93.3 kN, 7.8-8.2). Based on 200 sets of design performance data from the preferred design set, the performance weights for yield strength, impact resistance, static load strength, and pH range were calculated to be 0.1, 0.033, 0.833, and 0.033, respectively. The positive and negative ideal solutions for the design performance in the preferred design set were determined, and the closeness between the target performance and the design performance in the preferred design set was calculated. The design parameters corresponding to the highest closeness of 0.78 were taken as the matching design parameters. The matching design parameters and the pore parameters were used as the design scheme for the artificial reef in the area to be deployed.

[0165] A cube with a side length of 2.2m, a reinforcement ratio of 1.21%, cementitious material mix scheme C, a porosity of 40%, and porosities corresponding to three pore sizes (10cm / 6.67%, 14cm / 14.44%, 20cm / 18.89%).

[0166] In this embodiment, the formulation of the solid waste-based marine concrete includes: gel material, water base, sea sand, and biomimetic steel fiber; the gel material includes phosphogypsum, steel slag tailings, water-quenched blast furnace slag, and alkaline admixtures; the alkaline admixtures are a mixture of red mud and carbide slag; the water base includes seawater and a water-reducing agent; the biomimetic steel fiber is obtained by biomimetic treatment of steel fiber with tannic acid;

[0167] Meanwhile, the present invention also provides a method for preparing an artificial reef based on FRP-reinforced solid waste marine concrete, comprising the following steps:

[0168] Select the FRP reinforcement specifications according to the beam reinforcement ratio matching the design parameters and tie them to form an FRP reinforcement cage;

[0169] Artificial reef molds are made according to the shape, specifications and hole parameters of the artificial reef matching the design parameters, and the FRP reinforcement cages are then inserted into the artificial reef molds.

[0170] Solid waste-based marine concrete is prepared according to the material ratio matching the design parameters, and the solid waste-based marine concrete is poured into the mold. After hardening and molding, artificial reefs are obtained.

[0171] In actual preparation, the cementitious material is first prepared according to the cementitious material ratio. The steel slag tailings are the tailings with a particle size ≤3mm and a moisture content of 10-15wt% selected from the steel slag discharged from the steelmaking of the steel plant after conventional crushing, screening, magnetic separation and water washing processes. The water-quenched blast furnace slag is the slag obtained from the ironmaking of the blast furnace after water quenching and granulation, and the selected slag with a particle size ≤5mm and a moisture content of 10-15wt%.

[0172] Seawater and a water-reducing agent are added to a cementitious material and stirred to obtain solid waste-based marine cement, wherein the water-cement ratio of the water-based cement to the cementitious material is 0.15, and the water-reducing agent content is 0.6% of the mass of the cementitious material.

[0173] Add sea sand with a fineness modulus of 1.6-2.2 and an average particle size of 0.5-0.7 mm, along with steel fibers treated with tannic acid, to the prepared solid waste-based marine cement. After mixing evenly, solid waste-based marine concrete is obtained.

[0174] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A design method for marine concrete artificial reefs based on FRP-reinforced solid waste foundations, characterized in that, Includes the following steps: S1. Conduct tensile tests on FRP-reinforced concrete specimens to determine the applicable range of FRP reinforcement alkalinity, perform hydration thermodynamic simulation of solid waste-based marine concrete, and determine the preferred cementitious material mix ratio based on the hydration thermodynamic simulation results and the applicable range of FRP reinforcement alkalinity; the hydration thermodynamic simulation results include the pH value of the concrete pore solution and the pH value of the concrete surface. S2. Conduct geotechnical tests and finite element simulations of FRP-reinforced solid waste-based marine concrete beams under seawater aging. Based on the geotechnical test results and finite element simulation results, conduct strength simulations of artificial reefs of different shapes to obtain an optimal design set. The optimal design set includes design parameters and design performance. S3. Obtain historical extreme ocean current data of the area to be deployed and perform CFD simulation of the artificial reef. Based on the CFD simulation results of the artificial reef, perform topology optimization of the artificial reef size to obtain the first size. S4. Based on the species of organisms in the area to be introduced, the first size is modified in terms of specifications and the holes are allocated to obtain the second size. The biological adaptation pH value is determined based on the species of organisms in the area to be introduced. The second size includes the second specification and hole parameters. S5. Determine the first predicted intensity of the artificial reef to be designed based on the species of organisms in the area to be deployed and the deployment strategy, and correct the first predicted intensity based on the environment of the area to be deployed to obtain the second predicted intensity. S6. The second predicted intensity and the biologically adapted pH value are combined to form the target performance. The target performance is matched with the design performance to obtain the matching design parameters. The matching design parameters and the hole parameters are used as the design scheme for the artificial reef in the area to be deployed.

2. The design method for marine concrete artificial reefs based on FRP-reinforced solid waste foundations according to claim 1, characterized in that, The method for determining the preferred set of cementitious material proportions includes: FRP-reinforced concrete tensile specimens were prepared, and tensile tests were conducted after immersion in different solution alkalinity conditions to obtain tensile strength. The strength loss rate was calculated based on the tensile strength of the control specimens. The alkalinity of the solution corresponding to the FRP-reinforced concrete tensile specimens with a strength loss rate less than the strength loss rate threshold was selected as the applicable range of FRP reinforcement alkalinity. A standard marine environment was set up, and hydration thermodynamics simulation was performed on solid waste-based marine concrete with different cementitious material ratios to obtain the pH value of the concrete pore solution and the pH value of the concrete surface. The cementitious material ratios corresponding to the solid waste-based marine concrete with the concrete pore solution pH value within the applicable range of FRP reinforcement alkalinity were selected as the preferred cementitious material ratios. The preferred cementitious material ratios and the corresponding concrete pore solution pH values ​​and concrete surface pH values ​​were combined to form the preferred cementitious material ratio set.

3. The design method for marine concrete artificial reefs based on FRP-reinforced solid waste foundations according to claim 1, characterized in that, The method for obtaining the preferred design set includes: Solid waste-based marine concrete test blocks and FRP-reinforced solid waste-based marine concrete beams with different reinforcement ratios were prepared according to the preferred cementitious material ratio and subjected to seawater aging treatment. Material property tests and strength tests were conducted to obtain the strength of the test blocks and the strength of the test beams. The strength of the test beams included yield strength, static load strength and impact strength. A test block model of solid waste-based marine concrete was established, and the strength of the simulated test block was obtained by multiphysics coupling simulation. The test block model was adjusted according to the deviation between the strength of the test block and the strength of the simulated test block to obtain an optimal test block model. The multiphysics coupling simulation includes a seawater diffusion module, a chemical damage module, and a structural mechanics module. Based on the load-displacement curves of FRP-reinforced concrete tensile specimens corresponding to the optimized test block model and the optimized cementitious material ratio, an FRP-reinforced solid waste-based marine concrete beam model was constructed. Multiphysics coupling simulation was performed to obtain the simulated beam strength. The beam model was adjusted according to the deviation between the experimental beam strength and the simulated beam strength to obtain the optimized beam model. The load-displacement curves of the FRP-reinforced concrete tensile specimens were determined based on the pH value of the concrete pore solution corresponding to the cementitious material ratio. Based on the preferred beam model and artificial reef parameters, an artificial reef frame model is constructed, and a multiphysics coupling simulation is performed to obtain the reference artificial reef strength. The reference artificial reef strength includes the static load strength and impact resistance of the artificial reef. The artificial reef parameters include the shape and specifications of the artificial reef. An optimal design set is constructed based on the multiphysics coupling simulation results and simulation conditions of the artificial reef frame model; the optimal design set includes design parameters and design performance; the design parameters include the shape of the artificial reef, the specifications of the artificial reef, the reinforcement ratio of the FRP-reinforced solid waste-based marine concrete beam, and the cementitious material ratio of the solid waste-based marine concrete; the design performance includes the strength of the reference artificial reef and the pH value of the concrete surface.

4. The design method for marine concrete artificial reefs based on FRP-reinforced solid waste foundations according to claim 1, characterized in that, The method for obtaining the first dimension includes: Historical extreme ocean current data of the area to be deployed are obtained to determine ocean current simulation parameters. ANSYS Fluent transient model is used to perform CFD simulation on the artificial reef. Based on the CFD simulation results, optimization objectives are determined, and constraints are determined based on stability evaluation indicators. The ocean current simulation parameters include inlet velocity, reef flow field, and vorticity contour map. The optimization objective is specifically expressed as follows: in The drag coefficient, The resistance encountered by artificial reefs For fluid density, For the velocity of the fluid, This refers to the windward area of ​​the artificial reef. For vorticity volume, This is the integration region of the flow field. The vorticity of the fluid; The constraints are specifically expressed as follows: in This represents the maximum stress that an artificial reef may generate under the influence of a flow field. The yield strength of the artificial reef. The overturning resistance coefficient, To resist overturning moment, For overturning moment, The vortex-induced vibration suppression rate, This represents the actual amplitude of the vortex-induced vibration force. For reference, the amplitude of vortex-induced vibration force, The area of ​​the region where the flow velocity is less than the rated flow velocity. The total flow field area; Based on the optimization objective and constraints, topology optimization is performed on the artificial reef size to obtain the first size and the first predicted minimum yield strength corresponding to the artificial reef; the first size includes the optimal shape, optimal porosity and first specification.

5. The design method for marine concrete artificial reefs based on FRP-reinforced solid waste foundations according to claim 1, characterized in that, The method for obtaining the second dimension includes: The second dimension includes a second specification and pore parameters; the pore parameters include the optimal tertiary pore diameter and the corresponding porosity; Based on the biological species in the area to be deployed, we obtained the biological volume and pH value of each species by consulting a biological knowledge graph. We then selected species other than whales and sharks to determine their maximum biological volume. For the first specification Make corrections to obtain the second specification ; A predator-prey relationship matrix is ​​constructed based on a species database. The target protected species category is input into a biological knowledge graph to obtain the sizes of natural enemies and protected species. A biological feature matrix is ​​generated based on the corresponding size, local density, and protection priority of the protected species and natural enemy categories, and constraints on hole allocation are determined. in This is the first aperture size. This is the second aperture size. This is the third aperture size. for Minimum size of natural enemies for The largest size of natural enemies, for Maximum size of protected organisms for Minimum size of protected organisms for Porosity at the size level The total porosity of the artificial reef; Three aperture sizes are randomly generated as the initial population. Based on the biomarker matrix and aperture allocation constraints, the NSGA-III algorithm is used to optimize the tertiary aperture to obtain the optimal tertiary aperture. The specific steps are as follows: The reference point is dynamically generated using the hypersphere algorithm, expressed as: in For the first The orientation parameters of each reference point are used to determine the position of the reference point on the hypersphere. To optimize the number of objectives in the problem, For the first The objective function is in the individual. The function value at that point, For vectors The model field, , This represents the current iteration number. This represents the maximum number of iterations. Hybrid evolution of operators is performed, specifically including: using fusion differential evolution to process 70% of operators, using covariance matrix adaptive processing to process 30% of operators, and performing polynomial crossover to obtain evolutionary operators; Based on the hole allocation constraints, the hole size that violates the constraints is subjected to constraint layering processing. The Kriging surrogate model is used to screen the candidate solutions to obtain the preferred candidate solutions. Based on the preferred candidate solutions, the high potential solutions are repeatedly iterated and output as the optimal third-level hole size. Based on the porosity allocation constraints, the optimal third-order pore size, and the biomarker matrix, the porosity allocation is performed to obtain the porosity corresponding to the optimal third-order pore size. The specific steps are as follows: Calculate the biodensity weights for each protected species, and use a Gaussian mapping to probabilistically match the optimal tertiary pore size with the body width distribution of the protected species to obtain the porosity corresponding to the optimal tertiary pore size. The expression is: in for Porosity of pore size To protect species The average body width, To protect species The standard deviation of body width For organisms Local density, For organisms Biological density weight, For the sample size, For bandwidth, For organisms The location coordinates of the area where it is located. For the first The location coordinates of each sample This is the Epanechnikov kernel function.

6. The design method for marine concrete artificial reefs based on FRP-reinforced solid waste foundations according to claim 1, characterized in that, The method for obtaining the second predicted intensity includes: The first predicted strength includes the first predicted impact strength, the first predicted static load strength, and the first predicted minimum yield strength; The first predicted impact resistance strength is determined by obtaining the attack power of the organisms in the area to be deployed and the design safety factor based on the knowledge graph; Based on the bioattachment status of the area to be deployed using a knowledge graph, the bioattachment load is determined. The stacking load is determined based on the deployment strategy. Finally, the first predicted static load strength is determined based on the bioattachment load, stacking load, and design safety factor, expressed as: in For the first predicted static load strength, For maximum bioattachment density, The effective surface area of ​​artificial islands and reefs. The maximum number of stacking layers is determined by the delivery strategy. For the density of artificial islands and reefs, The effective volume of a single island or reef. It is the acceleration due to gravity. To design a safety factor; The environmental impact factor will be obtained by inputting an environmental function based on the environment of the area to be treated, and the expression is: in As environmental impact factors, , These are seawater acid ions. Ion weight and ion concentration sensitivity, Seawater acidic ions ion concentration, Seawater acidic ions The critical value of ion concentration. As for ocean current weight, For pressure weight, , The average ocean current velocity and critical current value for the area to be deployed. , The values ​​represent the average seabed pressure and critical pressure in the area to be deployed. , The average temperature and critical temperature of the area to be deployed. for Influence function; The second predicted strength is obtained by modifying the first predicted strength according to the environmental impact factor; the second predicted strength includes the second predicted impact strength, the second predicted static load strength, and the minimum value of the second predicted yield strength.

7. The design method for marine concrete artificial reefs based on FRP-reinforced solid waste foundations according to claim 1, characterized in that, The method for obtaining matching design parameters includes: The target performance is composed of the second predicted intensity and the biologically adapted pH value. The closeness between the target performance and the performance of the preferred design pool is calculated. The specific steps are as follows: calculate The entropy value of the performance item, according to Determining the entropy value of the performance item The weight of a performance item is expressed as: in for The entropy value of the performance item. for The weight of the performance item, To optimize design and improve performance Quantity, To optimize the design set Design performance The value, for The control constants for this performance; The positive and negative ideal solutions of the optimized design ensemble are determined based on the design performance weights, and the expression is as follows: in For design performance The negative ideal solution, For design performance The ideal solution; The closeness between the target performance and the performance of the optimized design lumped-design is calculated based on the positive and negative ideal solutions of the optimized design lumped-design performance. The expression is as follows: in For target performance and optimal design set No. The closeness of the group's design performance. For the first Project performance; The design parameters corresponding to the design performance of the highest proximity group are taken as the matching design parameters. The matching design parameters and the hole parameters are used as the design scheme for the artificial reef in the area to be deployed.

8. The design method for marine concrete artificial reefs based on FRP-reinforced solid waste foundations according to claim 1, characterized in that, The formulation of the solid waste-based marine concrete includes: gel material, water base, sea sand and biomimetic steel fiber; the gel material includes phosphogypsum, steel slag tailings, water-quenched blast furnace slag and alkaline admixtures; the alkaline admixtures are a mixture of red mud and carbide slag; the water base includes seawater and water-reducing agent; the biomimetic steel fiber is obtained by biomimetic treatment of steel fiber with tannic acid.

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